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The Impact of Human Resource Accounting on thePersonnel Selection Process: an Empirical Study.Hilary Charles ZaunbrecherLouisiana State University and Agricultural & Mechanical College

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ZAUNBRECHER, Hilary Charles, 1939- THE IMPACT OF HUMAN RESOURCE ACCOUNTING ON THE PERSONNEL SELECTION PROCESS: AN EMPIRICAL STUDY.The Louisiana State University and Agricultural and Mechanical College, Ph.D., 1974 Accounting

University Microfilms, A XEROX Com pany, Ann Arbor, Michigan

© 1974

HILARY CHARLES ZAUNBRECHER

ALL RIGHTS RESERVED

THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED.

THE IMPACT OF HUMAN RESOURCE ACCOUNTING ON THE PERSONNEL SELECTION PROCESS:

AN EMPIRICAL STUDY

A Dissertation

Submitted to the Graduate Faculty of the Louisiana State University and

Agricultural and Mechanical College in partial fulfillment of the

requirements for the degree of Doctor of Philosophy

inThe Department of Accounting

byHilary Charles Zaunbrecher

•S., University of Southwestern Louisiana, I960 M.Sc, Louisiana State University, 1971

May 17, 1974

EXAMINATION AND THESIS REPORT

Candidate:

Major Field:

Title of Thesis:

Hilary Charles Zaunbrecher

Accounting

The Impact of Human Resource Accounting on the Personnel Selection Process: An Empirical Study

Approved:

Major Professor and Chairman

C>-rrUl-kDean of the Graduate School

EXAMINING COMMITTEE:

Jjt CcrO-Jb&r'

Date of Examination:

March 11, 197 -

ACKNOWLEDGMENTS

The writer wishes to express his appreciation to the Chairman of his Doctoral Committee, Dr. S. Kerry Cooper, Department of Accounting, and to Dr. Kenneth Koonce, Department of Experimental Statistics, Louisiana State University, Baton Rouge, Louisiana for their valuable suggestions and assistance in the preparation of this monograph.

Acknowledgment is also made to Mr. L. E. Streeter, Chairman, Cooperative Research Committee, American Society for Personnel Administration. Without his support the experiment could not have been under­taken.

TABLE OF CONTENTS

PageLIST OF TABLES.................................. viLIST OF F I G U R E S ................................. viii

ChapterI. INTRODUCTION ........................... 1

Current Accounting Treatment ofHuman Resource Expenditures . . . . 1

Effect of Current Treatment onDecision M a k i n g ................ . . 2

Definition of Human ResourceAccounting ......................... 4

Purpose of the Study................. 5General Considerations . . . £Experimental Design ................. 10Statement of the Hypotheses........ 11Experimental Information Inputs . . . 12Variables Considered ................. 12Population, Questionnaire,

and Statistical Techniques ........ 14Limitations of the Scope

of the S t u d y....................... 16II. HUMAN RESOURCES: ECONOMICS

AND ACCOUNTING....................... 19Human Capital in Early

Economic Thought ........... 20iii

ivChapter Page

Method of Valuing Human Resources . . . 22Early Contributions to

Human Asset Valuation................. 23Human Investments as

Consumption Expenditures ........... 26Relationship between Accounting

and Economic Theory................... 27Human Investment as Current Expense . . 28

Impact on the Human Organizationof the F i r m ......................... 30

Renewed Interest in HumanCapital by Economists ............... 32

The Beginning of HumanResource Accounting ................. 34

Objectives of Human ResourceAccounting........................... 35

Definition of Human Resources ........ 36Characteristics of Human Assets . . . . 3#Human Resource Historical Cost . . . . 40Human Resource Replacement Cost . . . . 42Opportunity Cost of Human Assets . . . 44Human Resource V a l u e ................... 46

III. THE EXPERIMENT........................... 56Information..............................58Verity Assumed ....................... 60Relevance Considered ................. 62The D e c i s i o n ........................... 63The Decision M o d e l .................. 68

Chapter PageThe Experimental M o d e l ............... 71Validity of Information Items . . . . 75Demographic and Background

V ar i a b l e s......................... 7#D a t a ................................. 82

IV. THE EXPERIMENTAL RESULTS............. 8k

Rate of Response.................... 86

Statistical Techniques ............... 93The Results of the Experiment . . . . 100Experimental Results of First

Group of Hypotheses . ............. 103Experimental Results of Second

Group of Hypotheses................. 145Respondents' Comments ............... 171

V. SUMMARY, CONCLUSIONS, ANDRECOMMENDATIONS ..................... 176Prospective of the Problem............. 176Experimental Methodology ............ 179Response Rate and Statistical

T ech n i q u e ............. ............ 182

Summary of Results ............. 1&3Recommendations ..................... 1&5

BIBLIOGRAPHY ................................... 136APPENDICES........................................ 200VITA

LIST OF TABLES

Table Page1. Summary of Rate of Response by Group . . SB2. Distribution of Potential Data

by GrOUp e » o o e . o . 0 . . « 0 .« 943. Experimental Results Pertaining

to Hypothesis H-j_ (Group vs Ql) * . . . 1074. Experimental Results Pertaining

to Hypothesis H? (Importance Rating Scale, Group i n vs Q 1 ) ............ 116

5. Experimental Results Pertainingto Hypothesis H3 (Importance Rating of Conventional Employment Items,K 1 - K 14 vs Q 1 ) ..................................................... 129

6. Experimental Results Pertainingto Hypothesis H4 (Importance Rating of Human Resource Items,L 1 - L 14 vs Q 1 ) ................... 1335-1. Chi Squares and Contingency

Coefficients Ranked in Order of Descending Value (K Variables by Group) . . . . 140

6-1. Chi Squares and ContingencyCoefficients Ranked in Order of Descending Value (L Variables by Group) . . . . 143

7. Experimental Results Pertaining to Hypothesis H5 (Managerial Philosophy of Respondents by Groups, Q 1 vs Q 4). 147

S. Experimental Results Pertaining to Hypothesis H6 (Respondent Level Q 1 vs Q 9, Q 10)..................... 14^

vi

viiTable

9.

10.

PageExperimental Results Pertaining

to Hypothesis H7, Respondents Attitudes Toward Human Assets by Groups (Q 1 vs Q 11, Q 12,Q 13, Q 1 4 ) ......................... 152

Experimental Results Pertaining to Hypothesis Hg, Type of Industry, and Size of Company;Level, Field, and Recency of Education of Respondent ( Q 1 vs Q 2, Q 3, Q 5. Q 6a,Q 6b, Q 7a, Q 7b, Q 3 ) ............. 155

LIST OF FIGURES

Figure Page1. Model of the Decision Process for

Experiment in Personnel Selection . . . 702. Summary of Variables by Source

of V a r i a t i o n ........................... 74p3. Xjjr and C , Ranked in DescendingOrder for Group III .............. . 122

4. Composite Importance Rating ofConventional Employment Information Items by Group I and Group III Respondents.............................12$

5. Composite Importance Rating of HumanResource Information Items byGroup II and Group III Respondents . . 126

vii i

ABSTRACT

The increasingly complex business environment requires increased investments by firms in human re­sources, In response to this requirement, the accounting profession has undertaken a reexamination of the treatment accorded investments in human re­sources. Present treatment requires the expensing of the cost of human resource investments in the period incurred rather than in the period expired. This violation of the matching principle, along with the considered change to current value accounting, has prompted accounting researchers to development models for the purpose of determining the cost and value of human resources.

The human resource accounting models developed to date are alleged to provide information useful for internal decision making. The primary purpose of this study is to determine the impact of human resource accounting information on the personnel selection decision.

The experiment utilized a randomly selected sample of the membership of the American Society for Personnel Administration. This organization of pro­fessionals, which endorsed the study through its

ix

X

Cooperative Research Committee, is composed of 11,000+ practicing personnel administrators.

The dependent variable of the experiment is the recorded selection of either Applicant A or Appli­cant B for the position of Assembly Line Foreman. The independent variables considered in the test of the hypotheses are divided into two groups.

The first group consists of that variation resulting from the provision of three different sets of employment information to three subsamples of the original sample. Additionally, the variation in the importance rating of each item of information provided are considered independent variables of the first group. The three sets of employment information pro­vided are as follows; Set I, Conventional Employment Information; Set II, Human Resource Accounting Infor­mation; and Set III, a combination of Set I and Set II.

The second group of independent variables con­sidered resulted from variation in the background or demographic characteristics of the respondents. These variables included the type of industry and size of company of the respondents employment; the major and minor field of study, the level attained and the recency of respondents education; the level of respon­dents business and personnel experience, and the respondents attitude toward the concept of human

xiresources. The nonparametric chi square (x ) and contingency coefficient (C) statistic were utilized to test the existence and strength between the dependent variable and the various independent variables con­sidered.

On the basis of the statistical measurements obtained, sufficient evidence was developed to reject the null hypotheses utilizing the first group of independent variables. Specifically, results demon­strated a significant nexus between the type of infor­mation provided the decision-maker and the applicant selected. The tested hypotheses utilizing the vari­ation in importance rating of information provided are also rejected. The statistical evidence did not indi­cate as strong a causal relationship between applicant selected and importance rating as was indicated between applicant selected and variation in information items provided.

The test involving demographic or background variables revealed no significant causal relationships with the exception of the type of industry of respon­dents employment, major field of study and level of business and personnel experience. In general there is very little evidence of causal relationship between demographic variables and applicant selected.

xiiThese findings indicate that the accounting

profession, specifically that segment concerned with provision of information to internal users, should proceed with the reevaluation of the treatment accorded expenditures for human resources. In record­ing such expenditures as assets rather than expenses, the information provided decision-makers is thereby ameliorated. Further, the findings indicate that human resource accounting can be successfully used to augment information used in the personnel selection process»

CHAPTER I

INTRODUCTION

Human skills and abilities have long been con­sidered assets by economists. Similarly, business executives recognize the value of the people they employ. This recognition is often enunciated by executives in phrases such as "people are our most important asset.In spite of this consideration by economists and recog­nition by businessmen, the concept is not formally employed by either.

Current Accounting Treatment of Human Resource Expenditures

on the way in which human resource expenditures are recorded in accounting. Instead of recording the cost of recruiting, hiring, training, familiarizing, and develop­ment of employees as investments in assets, these expendi­tures are treated as current expense. This treatment assigns a zero value to the asset and all the expenditures of the current period to the expense category, thus presenting an expense that is equally unverifiable as

This exclusion by businessmen has a direct effect

, "People - Assets Tha (July/August 1969), 33

Ted J. Krein The Internal Auditor

That Talk Back,”

1

2deserving expense status. Since the total cost of acquiring employees is written off in the period incurred rather than in the period expired, no attempt is made to match expense with revenue generated by these assets in the current or subsequent accounting periods.

Effect of Current Treatment on Decision MakingThis violation of the matching principle has a

detrimental effect on the accuracy of accounting infor­mation. However, measurement of the accuracy of con­ventionally reported accounting information and concomitant user problems is outside the central purpose of this research.

The focal point of this research is the infor­mation deficiency which is inherent in the current treat­ment of human resource expenditures. The deficiency poses serious problems for both internal and external decision­makers. Stated otherwise, the information problem applies to managers as well as investors and creditors; however, the focus of this research is the internal user of mana­gerial information.

Current treatment has so imbued internal infor­mation users with the concept of human resource expendi­tures as a current expense that the investment aspect of

2American Accounting Association, A Statement of Basic Accounting Theory (Evanston, Illinois! American Accounting Association, 1966), p. 35.

these expenditures is completely ignored. Therefore, users make decisions without the aid of relevant invest­ment information.

The loss of potentially relevant investmentinformation becomes apparent when the results of currenttreatment of human resource cost is compared with therequirements of the decision making process. Decisionmaking can be informally described as a judgementalprocess unique to each individual. Study of this complexfield of human endeavor is subsumed under the titledecision theory. Decision theory has been defined asbeing partly a logical theory, and concerned with decidingactions on the basis of various premises, and with the

3determination of such premises. The determination of premises and deciding of actions is partly dependent on information currently received. Premises and decisions based on premises are also dependent on subjective judge­mental criteria. Invariably, this criteria is linked to information previously received by the decision maker. Since no two individuals perceive information alike, the judgemental criteria thus formed is unique to each indi­vidual. Further discussion of decision theory and con­comitant information requirements appears in Chapter III.

• D. J. White, Decision Theory (Chicago: AldinePublishing Company), p • 113•

4However, based on the foregoing, the implication

of current accounting treatment of human resource expendi­tures is apparent. Since executives are unaccustomed to using human resource information, their judgemental criteria is complete without its inclusion. Furthermore, executives do not receive human resource information as current input in the determination of their decision premises; therefore, their premises are complete without such information. Consequently, managerial decisions are made oblivious to a significant segment of relevant infor­mation.

Definition of Human Resource AccountingThe inaccuracy and deficiency of information caused

by current treatment of human resource expenditures has prompted accountants to suggest alternate treatments. Research into alternate treatments has expanded beyond the initial concern of accounting for human resource expendi­tures. Researchers are not only concerned with the acqui­sition cost of human resources, but also with their value to the organization. This expanded view is demonstrated in an accepted definition of human resource accounting as follows:

Human resource accounting is the process of identifying, measuring, and communicating information about human resources to facilitate effective manage­ment with an organization. In a particular organi­zation, it involves measurements of the acquisition

5cost, replacement cost, and economic value of human resources, and their changes through time.**-

The definition makes it apparent that current interest in human resource accounting is primarily- directed to the development of accounting systems to generate internal managerial information. For manage­ment, such systems would provide a means of putting decisions involving the acquisition, development, allo­cation, compensation, and replacement of human resources

5on a "cost-value" basis.

Purpose of the StudyThe increasingly complex technology of the present

day business environment requires employees possessing special skills and abilities. These requirements have accelerated the rate of investment in employees. Invest­ments in employees by a firm takes the form of recruiting, hiring, training, familiarizing, and development cost.The success or failure of human investments can be deter­mined only if sufficient relevant cost and benefit infor­mation is available. Human investments are profitable

^R. Lee Brummet, William C. Pyle, and Eric G. Flamholtz, "Accounting for Human Resources,” Michigan Business Review, Vol. XX, No. 2 (March 196B), 20.

5Eric Flamholtz, Human Resource Accounting; A Review of Theory and Research (Minneapolis, Minnesota: Presented at the Thirty-Second Annual Meeting of the Academy of Management, August 15, 1972), p. 3.

only when funds are expended on employees capable of sustained and enhanced service to the firm. Such employees are obtained in the labor market only when personnel administrators make the correct employment decision.

Currently, employment decisions are made on the basis of information provided by the prospective employee on the employment application. Further information is developed from applicant testing, credit reporting services, and references. Writers have suggested that cost and value information provided by human resource accounting systems could be useful to internal decision­makers. To date, however, this suggestion is based on the assumed usefulness of human resource information in the decision-making process. No data is available in the literature to verify the actual usefulness of human resource information to internal decision-makers. There­fore, the purpose of this research is to evaluate the actual usefulness of human resource accounting infor­mation to internal decision-makers.

Because it is assumed that human resource infor­mation is useful to internal decision-makers, it can logically be assumed that this information can be used in making decisions affecting human resources. This follows because human resource decisions are made by internal decision-makers, i.e., personnel administrators.

7Specifically, the purpose of this research is to deter­mine if human resource information can be utilized by personnel administrators to ameliorate their personnel decisions.

The purpose of this research is in accord with the basic premise of Brummet et al. as reflected in the following:

A basic premise of our research is that decisions will be made differently and human assets will be managed more effectively with the addition of infor­mation provided by a human resource accounting system. This, however, can be viewed as a testable hypothesis rather than as an arbitrary assumption.We intend, therefore, to simulate decisions involving human resources to determine whether the addition of data provided makes a difference.®

Research to date includes a study of the impact on investors of the inclusion of human resource infor­mation in the income statement and balance sheet. Other studies pertaining to human resource accounting in spe­cific firms is underway. However, no report of research into the impact of human resource accounting on the de­cision-making process of personnel administrators is found in the literature.

Accountants and information users have recognized the deficiency and inaccuracy of current accounting

R. Lee Brummet, Eric G. Flamholtz, and William C. Pyle, "Human Resource Accounting: A Tool to IncreaseManagerial Effectiveness," Management Accounting, Vol. 51, No. 15 (August 1969), 15.

practices pertaining to human resources. The importance of relevant information to proper personnel decisions is apparent. The absence of research on the impact of human resource accounting on internal decision-makers and current trends in accounting research has been cited. Growing out of these observations, this dissertation takes two objectives: (1) to report the results of asurvey, involving experimental conditions, of a random sample of members of the American Society of Personnel Administrators, and (2) to determine the impact of human resource accounting on the personnel selection process. These objectives are pursued within the framework of the design of a field experiment.

General ConsiderationsObjectives, and the conditions under which the

objectives must be attained, determine in general the design of an experimental study. This experiment requires a design to study the impact of certain types and quanti­ties of information on the decision-making process of the participants. If the decisions made by the participants are changed when the type and quantity of information provided is varied, it can be inferred that the information was used in the decision process. It can be assumed that the information was used by the decision-makers to develop an operational decision premise. The premise thus developed is the basis of impending decision.

9The experimental method of varying information

input and observing the effect on decision output is eminently accepted in accounting research. However,Ijiri et al. have suggested that when accounting alterna­tives are used, it is more important to determine the conditions under which variations in accounting methods produce different decisions than it is to determine whether different accounting methods have any effect upon decisions J

Consistent with this suggestion, the experiment is designed to investigate the conditions under which variations in decisions occur. The variation in con­ditions in this experiment refers to variation in job environment, qualification, and attitudes of the par­ticipant. It is assumed that these variables are deterministic in the development of the subjective judge­mental criteria of the decision-maker.

In the previously stated definition of decision theory, deciding of actions (i.e., decisions) were said to be based on premises. In subsequent discussion it was asserted that premises are based on current information

7Yuji Ijiri, Robert K. Jaedicke, and Kenneth E. Knight, "The Effects of Accounting Alternatives on Management Decisions," in Yuji Ijiri, Robert K. Jaedicke, and Oswald Nielson, Research in Accounting Measurement, Collected Papers (Menaska, Wisconsin: American AccountingAssociation, 1966), p. 1S7.

10input and on subjective judgemental criteria. This criteria is linked to information previously received by the decision-maker. By varying current information input and observing and evaluating decision output, the study seeks to reveal the impact of human resource accounting information on premise development of participants. By studying the job environment and assessing qualifications and attitudes of participants, this study delves into the relationship between the subjective judgemental criteria of the participant and his decision output.

Experimental DesignExperimental design is specifically dependent on

the nature of the problem under study and the environment in which the problem is to be studied. Subsumed under the nature of the problem are specific decisions as to the statistical hypotheses to be tested, experimental information inputs, and casual relationships of variables considered. Environment relates to the population under study, the instrument of data collection, and statistical procedures applicable to the data.

The nature of the problem under study is to determine the impact on the decision output of personnel managers resulting from variations in information inputs. Further determination is to be made of the impact on the decision output resulting from variation in job environ­ment, qualifications and attitudes of personnel managers.

11These determinations will be made by acceptance or rejection of statistical hypotheses*

Statement of the HypothesesThe hypotheses to be tested may be divided into

two groups. The first group deals with variation ininformation provided and variation in the importance ofinformation as determined by respondents. The hypothesesof the first group stated in the null form are as follows:

There are no significant differences in decision output (applicant selected) resulting from variation in information input (Set I, Set II, or Set III information).

H2 There are no significant differences in decision output resulting from variation in relative importance attached by respondents to conventional and human resource information (Set III infor­mation) •

Ho There are no significant differences in decision output resulting from variation in relative importance attached by respondents to conventional information in different environments (Set I and Set III information).

H, There are no significant differences in decision output resulting from variations in relative importance attached to human resource accounting information presented in different environments (Set II and Set III information).The second group of hypotheses to be tested deals

with the job environment, qualifications and attitudes ofparticipants. The hypotheses of the second group statedin the null form are as follows:

Hr There are no significant differences in decision 5 output resulting from variations in managerial

philosophies (autocratic, participative or free- rein) of respondents.

12There are no significant differences in decision output resulting from variation in levels of experience of respondents.

Hy There are no significant differences in decision output resulting from variations in respondent's attitudes toward human assets.

Hg There are no significant relationships between decision output and variations in job environ­ment and qualifications of respondent (size and type of company of respondent's experience; level, field and recency of education) of respondent.

Experimental Information InputsTo test these hypotheses, randomly selected

personnel managers were asked to decide to hire either Applicant A or Applicant B. This decision was to be based solely on information inputs provided in the questionnaire. The sample was partitioned into three subsamples. Each subsample received questionnaires con­taining one of three sets of information. Information types comprising the three sets are as follows:

Set I. Conventional employee selection information items for Applicant A and Applicant B. In this set Applicant A is the expected preferred choice.

Set II. Employee selection information items for Applicant A and Applicant B which can be generated by a human resource accounting system. In this set Applicant B is the expected preferred choice•

Set III. Set I and Set II combined.

Variables ConsideredThe dependent variable of the study is the response

to the question as to the choice of applicant for employment

based on information provided. The choice is considered to be a function of the independent, hypothetically asymmetrical, variables of the study. It is assumed that the choice of applicant for employment will be based on a decision by the personnel administrator. The personnel administrator's decision is assumed to be based on the premises developed from current information and his sub­jective judgemental criteria which is built on infor­mation accumulated over a period of time. This criteria is a function of the personnel administrator's job environment, qualifications, and attitude. Therefore, to implement the experiment the following independent variables are considered:

1. Variation resulting from provision of three different sets of information to the respondents.

2. The importance assigned by the respondents to the items of information provided.

3. The experience level of the respondent.4. The apparent managerial philosophy of the

hiring agent.5. The size and type of company by which the

respondent is employed.6 . Education level, field of study, and recency

of education of respondent.7. The attitude of the respondent toward the

concept of human resources.

14The existence and strength of the casual relation­

ships between the dependent and independent variables is established by accepting or rejecting the null hypotheses. This is decided on the basis of the chi square and con­tingency coefficient computed for each hypotheses.

Population, Questionnaire, and Statistical TechniquesIn consideration of the environment in which the

experiment was carried out, mention must be made of the population sampled, the questionnaire used, and the statistical procedure applied to the data collected.

The population sampled was the entire membership of the American Society for Personnel Administration.The organization is nation-wide with members in every state. The current membership, and therefore the popu­lation for the experiment, is in excess of 11,000. Theprocess of sampling has long been accepted as a legitimateand expeditious method of research. Therefore, to facili­tate the study, a sample of 1,210 members was randomly generated by the organization's computer. The sample was randomly divided into three groups so as to allow variation of information provided between groups. Members within each group received the same information. The distribution of questionnaires by group was as follows:

Group Questionnaires Mailed1 4002 4013 409

15This approximately equal distribution of question­

naires provides for a potentially equal response from each of the three groups.

The questionnaires contained instructions, infor­mation items and questions. The cover letter was addressed to the recipient from the Chairman, Cooperative Research Committee, American Society for Personnel Administrators. The enclosed return envelopes were serially numbered to facilitate follow-up if necessary. A sample of each of the three types of questionnaires used appears in Appendix A.

Measurement of the dependent variable (i.e., choice of applicant) is obtained in response to question #1. The information inputs provided the respondent by each of the three questionnaires coincide with the three sets of employee selection data used to test hypotheses

Data generated by the rating of information items provides the independent variable values to test hypothe­ses Eg* ^3» anc* H^. Responses to the question quantify the remaining independent variables of the study.

The dependent variable of the study is discrete in nature. The independent variables can also be con­sidered discrete. The chi square test, which is an accepted test for discrete data, is used to test the hypotheses. The contingency coefficient, which indicates the degree of association between independent and

16dependent variables, is used to measure the strength of the relationship.

Limitations of the Scope of the StudyIn a study of this nature there are myriad areas

of interest which may be explored. However, academic considerations require strict limitations of scope so as to increase concentration on specific areas.

In theory, human resource accounting involves all information generated by human interaction between managers, employees, customers, suppliers, owners and all other groups in the business environment. This research is restricted to that information generated and utilized by internal users only. Internal users of managerial information comprise, a large group ranging from foreman to company president. This research is restricted to one specific category of user of management information. It is restricted to the informational needs of the personnel administrator. The personnel administrator is involved in a broad range of decision-making. Decisions of personnel administrators concern the hiring, training, promoting, transferring, demoting, and terminating of employees. This research is specifically limited to an inquiry into the use of human resource accounting infor­mation in connection with the hiring decision as it relates to a choice between two applicants.

17The inputs of the experiment are restricted to

those items of information which can be generated by- proposed human resource accounting systems and con­ventional employment procedures. The amount and type of information provided the respondents is circumscribed by the limitations inherent in a field experiment. The experiment is further curtailed by the unfamiliarity of the participants as to concepts and terminology of human resource accounting. Finally, the study specifically excludes an inquiry into the impact on employees when a human resource accounting system is implemented.

The remainder of this dissertation consists of four chapters. Further explanation of the design of the experiment appears in Chapter III. This explanation includes a discussion of decision theory as it relates to the experiment. Also, the basis for selection of the independent variables of the study is discussed in Chapter III. Chapter IV contains a restatement of the hypotheses tested, reports the response to the survey, and discloses the outcome of the statistical techniques applied to the data collected. However, before the expanded explanation and experimental results are pre­sented, Chapter II provides a brief survey of the history of human resources accounting. This information is intended to provide a basis from which the experiment can be viewed in prospective. The survey includes a

discussion of the treatment accorded human resources in economic theory as well as in accounting. First, the discussion is intended to explain current treatment of human resource expenditures by recounting their treat­ment in economic theory. Secondly, the potential uses of human resource accounting information by decision makers will be detailed. Finally, several of the pro­posed human resource accounting concepts will be presented. A summary of the results and conclusions drawn from the experiment and recommendations appears in Chapter V.

CHAPTER II

HUMAN RESOURCES: ECONOMICS AND ACCOUNTING

The concept of human capital has received only- limited coverage in economics and accounting literature. Familiarity with the concept is essential if the experi­ment reported in the subsequent chapters is to be viewed in proper prospective. Therefore, the purpose of this chapter is to provide background information. This infor­mation can be divided into three main categories:(1) development of the concept and measurement techniques by economists, (2) the impact of these developments on accounting, and (3) recent developments in human resource accounting.

Development of the concept and measurement tech­niques will be traced from the early history of economic thought to the present. Where appropriate, similarities between early and recent ideas will be pointed out. The current treatment of human resource expenditures will be examined in light of the relationship between economics and accounting. Alternatives to current treatment of human resource expenditures will be discussed in present­ing several recently proposed human resource accounting concepts. This discussion will include value based con­cepts as well as cost based concepts.

19

20

Human Capital in Early Economic ThoughtRecently, several books and articles have been

published concerning human assets. These publications represent renewed rather than incipient interest, because the concept is deeply rooted in the history of economic thought. Throughout history most economists have been concerned with the concept of human capital.

Economists who considered human beings or their skills as capital include such well-known names in the history of economic thought as Smith* Say, Senior, List, von Thunen, Roscher, Bagehot, Sidgwick, Walras and Fisher.^" Although these men thought of humans as capital, they did not engage in a rigorous analysis of the concept. Their treatment was generally limited to including human beings in their definition of capital. Although most of the well-known economists were not involved, several motives for treating human beings as capital and valuing them in money terms have been found. Among these motives are:

1. To demonstrate the power of a nation.2. To determine the economic effects of edu­

cation, health investments, and migration.

^B. F. Kiker (ed.), The Historical Roots of the Concept of Human Capital, "Investment in Human Capital'1; Columbia, South Carolina: University of South Carolina Press, 1971)> p. 51.

21

3. To propose tax schemes believed to be more equitable than existing ones.

4. To determine the total cost of war.5. To awaken the public to the need for life

and health conservation and the significance of the economic life of an individual to his family and country.

6. To aid the courts and compensation boards inmaking fair decisions in cases dealing with compensation

2for personal injury and death.From these motives one prime motive is apparent.

That motive is the desire to place a monetary value on human beings to serve as a basis for making a decision or to influence the decisions of others. These motives imply an assumption of the usefulness of human asset information.

Prompted by these motives, a small group of relatively unknown economists undertook to develop tech­niques for human capital measurement. This group includes Petty, Ernst Engels, Farr, and Wittstein. With the exception of Petty, these economists sought to place a valuation on individual workers. Petty was concerned with placing an aggregate value on all workers. The methods devised by these men follow two different approaches to the problem of human valuation.

^Ibid., p. 52

22

Method of Valuing Human ResourcesBasically, two methods were used by early econo­

mists to estimate the value of human beings: the cost-3of-production and the capitalized earnings procedure.

With modifications these methods are similar to the approaches proposed by researchers in human resource accounting.

In the cost-of-production approach, the modifi­cation involves a variation in prospective. Instead of estimating the cost incurred in "producing" a human being, human resource accounting attempts to estimate the cost of acquiring an employee.

The capitalized earnings procedure consists of estimating the present value of an individual's future income stream. The method is subjective as it requires an estimate of the future earnings of an individual and an estimate of the rate at which the earnings are to be discounted. This method is the theoretical basis for value approaches to human resource accounting. However, in human resource accounting the prospective is slightly different. Instead of estimating the present value of the future earnings of the individual worker, an estimate is made of the future benefit derived from the individual worker by the firm. This estimate is considered to be the value of the employee to the firm.

•^Ibid., p. 51

23Early Contributions to Human Asset Valuation

The purpose of presenting a survey of the methods employed by early economists to value human assets is twofold: (1) to demonstrate the degree of analysisaccorded the concept, and (2) to provide the basis for a comparison of measurement approaches employed by early economists and current researchers.

Variations of the capitalized earnings method were proposed by Petty and Farr. Ernst Engels favored the cost-of-production method. Wittstein devised a formula which combined the two approaches.

One of the first attempts to estimate the money value of human beings was made around l691’by Sir William Petty. To him labor was the "father of wealth" and therefore must be included in any estimate of national wealth. Petty estimated the value of the stock of human capital by capitalizing the wage bill in perpetuity, at the market interest rate; the wage bill determined by deducting property income from national income.

The first truly scientific procedure for finding the money value of human beings was devised in 1853 by William Farr. He advocated the substitution for the existing English income tax system of a property tax that would include property consisting of the capitalized value of earning capacity. His procedure for estimating capitalized earning capacity was to calculate the present

24value of an individual's net future earnings. In his formula, personal living expenses were deducted from earnings and allowances were made for deaths in accordance with life tables.

Ernst Engel in his writings around 1S83 preferred a cost-of-production procedure for estimating the mone­tary value of human beings. He reasoned that expenditures of rearing children were costs to their parents, this cost might be estimated and taken as a measure of their mone­tary value. This monetary value at Age X may be deter­mined from a formula:

Cx = cQ 1 + x + k [x(x + l)/2]

where C is the total cost of producing a human being through age x» c0 denotes costs incurred up to the point of birth, and k is the annual percentage increase in cost.

Theodor Wittstein in his writings in I&67 employed a variation of both Farr's capitalized earnings and Engel's cost-of-production approaches to value human capi­tal. He assumed that an individual's lifetime earnings are equal to his lifetime maintenance cost plus education, the approaches yield the same estimates — which inevitably come out to be zero at birth. His procedure may be summa­rized in the following formulas:

25

°(n) - aR(o) h ° 2 rn - aE( .L(n) (n>’

c (n) - x r (n ) i i a i pR-" - aRL(n)

(n).

Where a is annual consumption expenditures including education for an average male in a particular occupation,R = (1 + i), where i. is the market interest rate;P = 1/r; is the number of men living at age n in alife table; is the value at age of a $1.00 annunity(for a given r and purchased at birth); x is the value of the future output of an average man in a particular occu­pation; N is the age at which this man enters the laborforce. The basic problem with Wittstein*s approach is that his assumption that lifetime earnings and lifetime maintenance cost are equal is unjustified. There is also a possibility of duplication of values in a combination of capitalized-earnings and cost-of-production methods.^"

In the enumeration of early economists who con­sidered humans as capital and developed formulas for its evaluation, one name is conspicuous by its absence. This is the name of Alfred Marshall. This special treatment accorded Marshall coincides with the special place he

^Ibid., pp. 52-56

occupies in the development of the concept of human resources.

Human Investments as Consumption ExpendituresOn the theoretical level, Marshall was perhaps

the most forceful proponent of the concept of humanassets. In 1$9& he wrote, "Capital consists in a greatpart of knowledge and organization; and of this some part

5is private property and the other part is not." His work contains a clear discussion of the capitalized-net- earning approach to human capital evaluation. However, while holding that human beings are incontestably capital from an abstract and mathematical point of view, he held it would be out of touch with the market place to treat them as capital in practical analysis. Therefore, Marshall disregarded the notion of human capital as "unrealistic" because human beings are not marketable.

Writing in I960, Theodore W. Schultz credits this assessment by Marshall for the lack of interest in the concept of human resources from the beginning of the twentieth century to the recent renewal of interest. He contends that Marshall's views were generally accepted by

CAlfred Marshall, Principles of Economics (London: MacMillian & Company, Limited, 1898), p. 13&.

6Ibid., pp. 7S7-7SS.

27his fellow economists because of his great prestige.Since Marshall considered the concept "unrealistic" themain stream of economic thought held it was neitherappropriate nor practical to apply the concept of capital

7to human beings.Besides Marshall's assessment, various other

reasons have been advanced to explain the exclusion of humans from the concept of economic capital. Generally, the mere thought of investments in humans was offensive to most people. Also, it has been all too convenient in marginal productivity analysis for economists to treat labor as if it were a unique bundle of innate abilities that are wholly free of capital.

The above-mentioned reasons were sufficient to generally exclude human capital from the main stream of economic thought. Therefore, expenditures for humans were viewed as consumption rather than investments. This treatment had a significant impact upon the way in which human resource expenditures are recorded in accounting.

Relationship between Accounting and Economic TheoryTo a significant degree economics and accounting

are concerned with the generation of information relevant

7'Theodore W. Schultz, Investment in Human Capital (New York: The Free Press, 1^71), p. 2?.

^Ibid., p. 26.

to the decision-making process of intended users. To a larger degree, both disciplines utilize economic data as information. These common bonds provide the foundation for most of the theoretical considerations of accounting theory. Many of the underlying structural concepts of modern accounting theory were derived directly from classical economic theory. These accounting concepts were developed during the period in which human capital was excluded from practical consideration by economists. Because of the close conceptional relationship between accounting and economics, accounting theorists ignored human assets as the concept was simultaneously ignored in economic analysis. Consequently, the theoretical treat­ment of human investment expenditures carried over into accounting. Just as economists treat investments in humans as "consumption’' rather than "capital" expendituresaccountants record these investments as "expense" rather

othan "assets."

Human Investment as Current ExpenseIn accounting, the concept of assets has been,

traditionally limited to tangible things. Investments in human skills seem more tenuous than investments in

oR. Lee Brummet, W. C. Pyle, and Eric G.Flamholtz, "Accounting for Human Resources," Michigan Business Review, Vol. XX, No. 2 (March 196$), 2l.

29physical assets. Human skills are intangible, only the product of human skills is tangible. Humans do not fit intuitive notions of the nature of assets. "Assets” are "things" of value owned, according to conventional accounting and our culture has placed constraints on willingness to imply ownership or place a monetary value

i 10on people.Another impediment to recognition of humans as

assets in accounting lies in the primal purpose of account­ing. The basic purpose of accounting is to provide quanti­tative information about business enterprises that is useful in making economic decisions. Quantitative infor­mation implies quantification of economic events necessi­tating measurement of the impact of the events on the performance of the entity. Herein lies a difficulty not only for accounting; but for all disciplines dependent in varying degrees upon the validity of measurement tech­niques employed. The term "measurement" is defined and used both between disciplines and within disciplines in a variety of strikingly different ways. Anyone attempting to find a single, well-established, definition of measure­ment is due for a disappointment.^^

10Ibid.■^Robert R. Sterling, Theory of the Measurement

of Enterprise Income (Lawrence, Kansas: The UniversityPress of Kansas, l9?0), p. 66.

30With respect to accounting for human resources,

the measurement problem is reflected in the difficulty of estimating the initial investment in humans by an enter­prise. Further difficulty is encountered when an attempt is made to distinguish between the part of the investment currently expired and that part which will expire in later periods.

Recording of human resource expenditures is also affected by the accounting concept of conservatism —that most ancient and probably the most pervasive rule of

12valuation. The practice of writing off the cost of assets in the period incurred rather than in the period expired results in conservative asset valuation. The practice concomitantly understates income in the period of write-off.

Impact on the Human Organization of the FirmThe degree of impact current treatment of human

expenditures has on the human organization is directly related to degree of labor intensity of the firm. In addressing the practical impact of current accounting treatment of human resource expenditures, Pyle identifies three problem areas: (1) budgetary considerations,

12Ibid., p. 256

31(2) maintenance of human capabilities, and (3) return on

13investment.Since humans are not considered resources,

expenditures for their acquisition are not considered capital expenditures and are therefore excluded from the firm's capital budget. This is in contrast to proposed expenditures for physical plant and equipment which are included in the capital budget. Consequently, managers are wont to ignore human resource expenditures in the budget planning stage. Subsequently, human resource expenditures are difficult to justify because they are in effect unplanned.

The level of human capabilities maintained cannot be assessed in financial terms under current accounting procedures. This is because amortization schedules are not prepared for these unrecorded assets. The. result is improper maintenance and non-planned replacement of human resources.

One of the most commonly employed measures of overall efficiency is the return generated on capital employed. In current practice, however, human invest­ments are excluded from the investment base and income is reduced by current write-off of human expenditures.

13•'William C. Pyle, "Monitoring Human Resources — 'On Line,'" Michigan Business Review (July 1970), p. 19.

32Therefore, human investments are not included in return on investment calculations for evaluating current or future projects.

The problems posed by considering human expendi­tures current expense rather than investments are not confined to accounting. The advent of massive govern- mentally supported social programs in the decade of the I960's rekindled the interest of economists in human assets. Particularly, economists sought to influence the direction of the massive investment in these social pro­grams. They sought to evaluate these programs in terms of return on investment. This desire led to the necessity of thinking of such investments as capital rather than consumption expenditures.

Renewed Interest in Human Capital by EconomistsAmong economists who displayed a renewed interest

in the concept were Theodore W. Schultz, Lester C. Thurow, and Simon Kuznets.

Schultz contended "the exclusion of human assets from capital analysis was wrong in the classical period and it is patently wrong now."'*' The impact of the error is compounded by the increasingly massive investments by industry in human assets. The large increases in real

^Theodore W. Schultz, Investment in Human Capital (New York: The Free Press, 1971), p« 28.

33earnings of workers, essentially unexplained by classical analysis, can reasonably be attributed to return on investment in humans.

To measure these investments, Schultz suggested the cost-of-production approach. He described human resources as having a quantitative and qualitative dimension. The number of people, the proportion entering upon useful work, and hours worked are essentially quantitative characteristics. Skill, knowledge, and similar attributes that affect particular human capa­bilities to do productive work are qualitative character­istics. Schultz contends the practice followed in connection with physical goods will suffice to measure the magnitude of human investment. Therefore, to esti­mate the magnitude of capital formation the expenditures

l''made to produce the human capital are considered.Schultz recognizes the allocation problem of accounting for human resource expenditures when he describes as formidable; the problem of how to distinguish between expenditures for current consumption and those for capital formation.

In an analysis of the growth rate of real national income by sources, Kuznets concludes that the percentage of growth contributed by labor is increasing with time

■^Ibid., p. 35

34-

while the percentage contributed by physical capital is, • 16 decreasing.

Thurow's work has substantiated the increase inlabor's marginal product due to training. His findingstend to confirm the existence of human capital resulting

17from investments is training programs. 1

The Beginning of Human Resource AccountingThe revival of interest by economists in human

capital was accompanied by, or perhaps caused, an exami­nation of the concept by accountants. Until then, accountants considered the problem of valuing human resources to be part of the larger problem of valuing goodwill. This view is expressed by Gynther when he argues:

. . • Goodwill exists because assets are present, even though they are not listed with the tangible assets. For example, "special skill and knowledge," "high managerial ability," . . . and "established clientele" are assets in this category.1°

1 AEdward Shapiro, Macroeconomic Analysis (New York: Harcourt, Brace & World, Inc., 1V70), p. 495.

17Lester C. Thurow, Poverty and Discrimination (Washington, D. C.: The Brookings Institution, lyb9j,p. 86.

1 dReg S. Gynther, "Some Conceptualizing on Good­will," Accounting Review, Vol. XLIV, No. 1, p. 247.

35Similarly, Brummet argues "that a major portion

of goodwill recognized in business combinations is, in fact, an economic assessment of human resources.""^

Research is currently underway to distinguish economic values attributable to the human resources of a firm from the values attributable to other components of goodwill. These projects and controlled implementation of research results is subsumed under the title human resource accounting.

Objectives of Human Resource AccountingThe primary objective of human resource accounting

is to remedy the current human resource informationaldeficiencies by developing and integrating financiallyoriented measurement techniques to facilitate the manage-

20ment of an organization's people resources. To accomplish this objective, researchers are attempting to develop methods of measuring human resource cost and value. To obtain value measurements, researchers are attempting to develop a theory explaining the nature and determinants of the value of people to formal organizations. These

19R. Lee Brummet, "Accounting for Human Resources," The New York Certified Public Accountant, Vol. XL, No. 7(juiy 1 9 7 0 ), p. m ' . -------------------------

20William C. Pyle, "Monitoring Human Resources —'On Line,"' Michigan Business Review (July 1970), p. 20.

36measurements of cost and value will permit the monitoring of the effectiveness of management's utilization of human

a. 21assets.In their effort to develop a theory explaining

the nature and determinants of human resource value, researchers have attempted to formulate an operational definition of human resources.

Definition of Human ResourcesIn an early work on human resource valuation,

Hermanson defines assets as:. . . Scarce resources (defined as service but

grouped by and referred to as agents), operating within the entity, capable of being transferred by forces in the economy, and expressible in terms of money; which have been acquired as a result of some current or past transaction, and which have the apparent ability to render future economic benefit.

This definition allows for the inclusion of operationalassets as well as owned assets. Owned assets are allscarce resources, legally or constructively owned by theentity, have a separate determinable market value andtherefore could conceivably be directly used or converted

piEric Flamholtz, Human Resource Accounting: AReview of Theory and Research (,Minneapolis, Minnesota: Presented at the Thirty-Second Annual Meeting of the Academy of Management, August 15, 1972), p. 4.

37for the payment of its debts. Operating assets are all scarce resources operating in the entity that are not owned. Within the operational asset category, human assets are included.

Likert refers to human assets as " . . . the value of the productive capacity of a firm's human organization and to the value of its consumer good­will.”23

Elias defines human assets as "aggregates of service potentials available for or beneficial to expected operations of the firm from its internal or external members, that is, managers, employees, and customers.2 -

These definitions are similar in that they refer to human assets as possessing the ability to render economic benefit, productive capacity, or service potentials beneficial to the firm of their employment.

To further define human assets it is appropriate to examine the differences in the nature of physical and human assets. Comparing several characteristics of human

21-'Rensis Likert, The Human Organization: ItsManagement and Value (New York: McGraw-Hill BookC ompany, I96b), p . 14$.

2^Nabil S. Elias, "The Impact of Accounting for Human Resources on Decision-Making: An ExploratoryStudy" (unpublished doctoral dissertation, Graduate School, The University of Minnesota, 1970), p. 20.

assets with physical assets will demonstrate these differences.

Characteristics of Human AssetsHuman assets are truly scarce. They cannot be

mass produced on short notice. The supply of ’’really good” people is severely limited. This places a premium on the effective use of existing human assets. This is in contrast to physical assets which can normally be mass produced on demand and therefore subject to diminishing value.

Another characteristic of human assets is that they usually appreciate in value through proper utili­zation. With the exception of land, this is the exact opposite of physical assets which inevitably depreciate through use. Human assets are more adaptable than physical assets. They can be trained to perform an infinite number of alternate tasks. Physical assets are usually built to perform only certain tasks.

Another difference is that physical assets are lost only through obsolescence, casualty, or sale. Human assets are easily lost because of the mobile society in which we live. People are free to seek employment almost anywhere they wish. A final difference is that human assets are unique because they talk back. This provides

39for information exchange which is impossible with physical assets.

The character of human assets is at variance with that of physical assets. This variance requires modifi­cation of measurement techniques employed for physical assets when these techniques are employed to measure human assets. There is some agreement as to the nature and character of human assets as noted in the similarity in definitions. This agreement extends only to the nature of the property to be measured — human assets — not to the method of measurement. There is wide disagreement as to the appropriate measurement technique. The remainder of this chapter describes various measurement techniques which have been suggested.

Research in human resource accounting completed to date reflects the bifurcation evidenced in current accounting theory. One segment of the research is directed toward the investigation of concepts for the measurement of human resource costs: original cost, replacement cost,and opportunity cost. Another segment is conducting research to investigate the determinants of the value of human resources. This segment is further divided between efforts to identify the determinants of value of employees as a group and the value of individual employees.

40The purpose of the following survey of the pro­

posed basis for human resource accounting is twofold:(1) to demonstrate the variety of bases suggested, and(2) to provide the information necessary to establish the validity of the information items provided the respondents in the experiment reported in the remaining chapters.

Human Resource Historical CostAttempts to measure human resource cost have

resulted in the development of three different concepts and measurement models. Original cost is the actual, historical outlay incurred as an investment in human resources. Brummet, Flamholtz, and Pyle individually and collectively have developed concepts, models, and tech­niques for measuring the historical cost of human

25resources. A generalized model of their effort is shown at Appendix B, Figure I. This model has been applied at a relatively small, light manufacturing company, the R. G. Barry Corporation. At present no attempt has been made to assess the validity and reliability of the system except on a "face-validity” basis.

The operation of the model involves:1. Identifying the cost of human resources.

R. L. Brummet, E. G. Flamholtz, and W. C. Pyle, ’'Human Resource Measurement - Challenge for Accountants,” The Accounting Review (April 1969), p. 222.

412. Classifying the cost into two basic cate­

gories.3. Classifying the assets by function.4. Reclassifying the functional assets by

individuals. (Groups could also be used as a classifi­cation unit.)

5. Amortizing and write-off of the asset (in a manner analogous to depreciation of plant and equip-

/Iment).

The authors of the model describe some of the uses of their concept of human resource accounting as follows:

Human resource accounting should also be useful in reporting on actions taken and results achieved in relation to objectives and goals. Information about the composition of investments in human resources can be analyzed to determine standard costs or recruiting, hiring, training, and developing individuals in order to bring them up to their present level of technical competence and famili­arity required for a given position. In addition to providing a cost control mechanism, these data should be useful to estimate replacement costs to acquire people for various positions. Replacement costs can be used to budget investments in manpower planning and development. The result is a standard cost accounting system for human resource costs similar to that for manufacturing c o s t s . 27

Implementation of a system based on this model should provide a basis for evaluating a company’s return on its investment in human resources. It should also

a/E. Blaine, C. A. and W. T. Stanbury, "Accounting

for Human Capital,” Canadian Chartered Accountant (January 1971)> p. 7TI

2 7 Brummet, Flamholtz and Pyle, op. cit., p. 220.

42create an awareness of the importance of the human organi­zation by management. However, there are several draw­backs to the use of historical cost measurement. The subjectivity associated with the appreciation and amortization of the investments would surely present aproblem. Also, the real economic value of the investment

2$may be significantly higher or lower than its cost.

Human Resource Replacement CostIn their description of the uses of the cost

concept for human resource accounting, the designers of the model allude to its usefulness in estimating replace­ment cost. This is a measure of the cost to replace a firm’s existing human resources. This estimate would be useful in the solution of a variety of manpower planning and control problems as the principle measure of the cost of replacing people per se. It is also potentially useful in developing a valid and reliable surrogate measure of the value of people to formal organizations. Flamholtz has developed a model for the measurement of human resource replacement cost as shown in Appendix B, Figure 2. This model has been applied in a medium-sized mutual insurance company. As in the case of the..

2$Report of the Committee on Human Resource Accounting (Prepared by The Committee on Human Resource Accounting of the American Accounting Association). The Accounting Review, Supplement to Vol. XLVIII (1973)» p. iy *

43generalized cost model, no attempt has been made to assess the model's validity except on a "face validity" basis.

The end result of the operation of the model is a measure of the cost to replace individuals occupying specified organizational positions (positional replace­ment costs). Operation of the model involves the esti­mation of the cost of recruiting, selecting, hiring, and placement of a replacement to fill the job of the employee whose replacement cost is being estimated. These estimates are termed direct cost of acquisition. Indirect acqui­sition costs are estimates of promotion or transfer of an employee to the position being assessed from another position within the company. Learning costs are estimates of direct formal and on-the-job training and the indirect cost of the trainer's time to bring the replacement up to company performance standards. Separation costs are estimates of the direct separation pay to the departed employee and the indirect cost of loss of efficiency prior to separation and vacancy in position during the search for a new employee. The sum of the estimates of acqui­sition, learning, and separation costs is equal to the positional replacement cost of the employee under con­sideration.

44Opportunity Cost of Human Assets

As a method of asset valuation, replacement cost suffers from two deficiencies:

1. Management may have some particular asset which it is unwilling to replace at current cost, but which it wants to keep using because the asset has a value greater than its scrap value.

2. There may be no similar replacement for a29certain existing asset.

The deficiencies in the replacement cost approachled to the development of the concept of opportunity costto value human resources. This is the value of an assetwhen there is an alternative use for it. Hekimian andJones have suggested a system of competitive bidding toobtain managerial assessments of opportunity cost ofhuman assets. The suggestion has not been tested orapplied in any organization. Elovitz has attacked the

30notion as being too artificial to be effective.In general, the suggestion to value human assets

at historical or original cost is an accounting adap­tation of the cost of production techniques developed by

29 James S. Hekimian and Curtis H. Jones, "Put People on Your Balance Sheet," Harvard Business Review (January/February, 1967), p. 10FI

■^David Elovitz, "From the Thoughtful Business­man," Harvard Business Review (May/June, 1967), p. 59.

45Ernst Engels in 1S83 and suggested by Schultz in I960. Attempts to obtain valid replacement or opportunity cost measures for human resources reflect the current tendency in accounting theory to find an acceptable alternative cost based accounting.

In an attempt to find an acceptable alternative to historical cost, current value has been suggested as an accounting basis. In human resource accounting, researchers are following this suggestion by attempting to develop a theory that explains the nature and determi­nants of the value of people to formal organizations.

The development of human resource value theory is proceeding from two different approaches. Growing out of the studies on organization and leadership at the University of Michigan's Institute for Social Research, Likert et al. have attempted to develop a model of determinants of a group's value to an organization. In the earliest work on human resource valuation for account­ing, Hermanson proposed two possible techniques for the monetary valuation of the total human assets of a firm. Additionally, Brummet, Flamholtz, and Pyle as well as Lev and Schwartz have suggested methods to arrive at the value of employees as a group. In a different approach, Flamholtz has attempted to develop a model of the determinants of an individual's value to a firm.

46

Human Resource ValueDevelopment of techniques to measure the value

of human resources as a group is not restricted to mone­tary measurement. Several authors have suggested that non-monetary behavioral measurements would be useful in human resource accounting. The Committee on Human Resource Accounting of the American Accounting Association did not exclude non-monetary measurements from its deliberation.

Drawing on organization and leadership studies, Likert et al. are investigating the relationship between the system of management used by a firm and the produc­tivity of the organization. They have formulated a model of the variables which determine the effectiveness of the firm's "human organization" and, in turn, the effectiveness of the enterprise as a whole.

The model, which appears in Appendix B, Figure 3> is composed of three classes of variables: "causal,""intervening," and "end-resuit." They are defined as follows:

1. The causal variables are independent variables which can be directly or purposely altered or changed by the organization and its management and which, in turn, determine the course of developments within an organi­zation and the results achieved by the organization. "General business conditions," for example, although an

47independent variable, are not viewed as causal since the management of a particular enterprise can do little about them. Causal variables include the structure of the organization, and management's policies, decisions, business leadership strategies, skills, and behavior.

2. The intervening variables reflect the internal state, health, and performance capabilities of the organization, e.g. the loyalties, attitudes, moti­vations, performance goals, and perceptions of all members and their collective capacity for effective action, interaction, communication, and decision making.

3. The end-result variables are the financialand performance data of the firm. They are the dependentvariables that reflect the results achieved by theorganization, such as its productivity, costs, scrap

31loss, growth, share of the market, and earnings.The operation of the model consists of measuring

the causal, intervening, and end-result variables. The causal variables influence the intervening variables, which in turn, determine the organization's end-result performance. The model's variables are measured as per­ceptions of the organization's members. These measure­ments are taken at periodic intervals with a rating instrument as shown in Appendix B, Figure 4*

31Rensis Likert, "Human Resources— The Hidden Assets of Your Firm," Credit and Financial Management (June 1969), p. 21.

46Likert’s model includes four systems of manage­

ment. System 1 and 2 are generally described as authori­tarian; systems 3 and 4 are described as participative.He contends that management systems of type 1 and 2 yield more favorable attitudes as measured by variation in the intervening variables and therefore produce more favorable end-results.

Findings of reliability and validity studies of the model by Bowers and Taylor have resulted in a recon­ceptualization of the model presented in Appendix B,

32Figure 3* They found that the organizational processes are better classified as causal rather than intervening variables. Similarly, they concluded that satisfaction is more likely to be an intervening rather than an end- result variable. The studies undertaken by Bowers and Taylor were not intended to test the model as a set of determinants of the value of the human organization, but to test the effectiveness of various managerial philosophies.

The results of longitudinal studies undertaken since 1966 seem to confirm a stronger relationship

3 2David G. Bowers and James W. Taylor, The Survey of Organizations (Ann Arbor, Michigan: Institutefor Social Research, 1972).

49between the variables of the Likert model over a longer

33span of time. The model as presently constructed, however, cannot be used to place a value on the human resources of a firm. Its contribution to valuation is the establishment of relationships between variables. Likert contends that human resources can ultimately be measured by predicting a firm’s future earnings based on the current states of causal and intervening variables; and allocating a portion of the present value of future earnings to human resources.^

The first attempt to value human resources for accounting purposes was made in 1964. In it, Hermanson proposed two methods for valuing human capital. The first is analogous to a determination of the unpurchased (and therefore unrecorded) goodwill and is referred to as the Unpurchased Goodwill Method. The second method proposed by Hermanson is an adaptation of the method proposed in 1£$53 by the economist William Farr. Certain adjustments are made in the computation of the present

■^Rensis Likert, David G. Bowers, and Robert M. Norman, ”How to Increase a Firm's Lead Time in Recog­nizing and Dealing with Problems of Managing its Human Organization," Michigan Business Review, Vol. XXI (January, 19o9), pp. lb-17.

• Report of the Committee on Human Resource Accounting (.Prepared by The Committee on Human Resource Accounting of the American Accounting Association), The Accounting Review, Supplement to Vol. XLVIII (1973)>P. 177.

50value of employee wages, therefore it is called the Adjusted Present Value Method.

In his Unpurchased Goodwill Method, Hermanson recognizes the theoretically correct valuation of oper­ational assets is equal to the present value of the future services these resources can provide to the firm. Such valuation would require, however, an estimate of future net income in order to identify that portion attributable to operational assets. This estimate of future income is open to manipulation and to such wide differences of opinion among firms that comparability of financial statements recording operational assets would be lacking. Therefore, in an attempt to provide the best evidence of the current existence of unowned resources, only the current year’s income performance is used in the computation.

To compute the amount of human capital, an average rate of return on owned assets is established for all firms in an industry. If a firm is earning a rate of return superior to the average for the industry, this superior return is attributed to human capital in the particular firm. To establish the evaluation of the human assets, the amount of income in excess of the normal amount is capitalized at the normal rate of return on investment established for the industry. This method is essentially the one used by accountants to estimate

51goodwill. The only difference is that goodwill would be called human resources and reported on the financial statements even though it had not been purchased.

The Adjusted Present Value Method uses a weighted average to modify the present value (discounted at the economy rate of return on owned assets for the latest year) of the expected wage payments over the subsequent five years.

First, the present value of the future wage pay­ments is determined. This is done by estimating the wage payments by year and discounting the payments back to their present value. Next, an efficiency ratio is calculated by the following formula:

Efficiency Ratio = 5/ ^ 0!+ 3/W pll \SWhen:

^Fn = The rate of accounting income on ownedassets for the firm for the current year.

^En = The average rate of accounting income on owned assets for all firms in the economy for the current year.

If a given firm earned exactly the rate of return that the average of all firms in the economy earned each year, it would have an efficiency ratio of 1. Alterna­tively, if the human resources were more efficient than

P T

52the average, its efficiency ratio would be greater than1. If they were less than normally efficient, itsefficiency ratio would be less than 1. The dollaramount of human capital is calculated by multiplying thepresent value of future human resource payments by the

3 cefficiency ratio.Drawing on Likert's model and economic value

theory, Brummet, Flamholtz and Pyle have suggested an approach to measuring a group's value to an organization. As in Likert's suggestion, their approach uses the measurement of changes in the variables of the model to forecast future earnings attributable to human resources. Human resources are considered to be the present value of these future earnings.

In a suggestion similar to that made by Hermanson, Lev and Schwartz have proposed using discounted future compensation as a surrogate measure of human resource value. A person's worth is the present value of his remaining earnings from employment. It is contended

3 5Roger H. Hermanson, Accounting for Human Assets, Occasional Paper No. 14 (East Lansing, Michigan: fiureau of Business and Economic Research, Michigan State University, 1964), pp. 6-17.

R. E. Brummet, Eric G. Flamholtz, and W. C.Pyle, "Human Resource Accounting— A Challenge for Accountants," The Accounting Review (April 1968), p. 218.

53that the values arrived at by this method can be aggre­gated to arrive at the value of a group of individuals.-^

In an effort to measure an individual's value to a firm, Flamholtz has developed a model utilizing non­monetary and monetary methods of valuation. The model, which appears in Appendix B, Figure 5> is conceptualized as a stochastic process with rewards. It is based on the notion that a person is not valuable to an organization in the abstract, but in relation to roles (service states) he is expected to occupy in the organization through time.

Operation of the model involves the following:1. Estimate the time period during which the

person is expected to render services to an organization.2. Identify the service states that the person

may occupy.3. Measure the value derived by the organization

if the individual occupies the state for a specified time period.

4. Estimate the probability that a person will3goccupy each state at specified future times.

-^Baruch Lev and Aba Schwartz, "On the Use of the Economic Concept of Human Capital in Financial State­ments,” The Accounting Review (January 1971)» p« 104.

•^Eric Flamholtz, Human Resource Accounting: AReview of Theory and Research (Minneapolis, Minnesota: Presented at the Thirty-Second Annual Meeting of the Academy of Management, August 15, 1972), p. 18.

54Findings from operationalization of the model in a medium sized mutual insurance company indicate that replacement cost, compensation, and sales revenue each possess con­vergent and discriminant validity as surrogate measures of an individual's value at an ordinal measurement level.

With the exception of Likert's model, the methods proposed for measuring the value of employees or groups of employees to an organization are similar in principle to the proposal of the economist William Farr. At the core of the proposals is the realization that the value of people to an organization is the present worth of the future services they are expected to render.

Likert's model per se is not intended to measure the value of human resources, but the efficiency of various types of management systems. Likert, Flamholtz, Pyle, and Brummet have suggested that measurement of the present state of the causal and intervening variables would provide a basis to forecast future end-result variables. The forecasted end-result variables would serve as a basis to forecast future contributions by employees. This would serve as a basis to value human resources.

Hermanson*s suggested methods attempt to provide protection against manipulation by management. The pro­posals utilize capitalized current excess earnings or modified future employee earnings as a measure of human

55capital. In both proposals the impact of the economic concept of value is apparent.

The proposal of Lev and Schwartz to capitalize future compensation is a direct adaptation of the method of William Farr. Flamholtz’s suggestion for the valuation of an individual utilizes a series of capitali­zations corresponding to the service states the indi­vidual is expected to occupy.

The purpose of this chapter is to provide back­ground information. This information provides a pro­spective from which the experimental results reported in the remaining chapters can be viewed. No attempt was made in this chapter to rank the proposals in terms of validity. No attempt was made to point out the relative weaknesses or strengths of the various proposals. Such attempts require an objective basis from which to judge.The purpose of Chapter III is to set the stage for that basis. In Chapter IV an objective basis from which to judge the validity of the various proposals is established by the empirical findings of the experiment. The objec­tivity of the basis rests on the assessments made by practitioners of the impact the proposed information had on their decision process. With the basis thus established, an attempt is made in Chapter V to indicate the relative merits of the various proposals.

CHAPTER III

THE EXPERIMENT

The information contained in Chapter II is but one of two integral parts of the basis by which the results and conclusions reported in Chapters IV and V can be assessed. One objective of this chapter is to provide the second essential part: a thorough understanding of the experiment undertaken. This is accomplished by a rigorous description of the experimental design.

The focus of this research, as stated in Chapter I, is to determine if quantitative human resource account­ing information can be utilized by personnel managers to ameliorate their personnel selection decisions. A con­comittant objective of this chapter is to clearly demon­strate the nexus between the question posed and the experiment undertaken.

The description and demonstration of connection is essential because: (1) the behavioral character ofthe experiment makes control of experimental conditions tenuous, and (2) inferences drawn from the experimental results must be subject to the limitations imposed by the untested, tentative nature of the human resource accounting information items and the impalpable nuances of human decision making.

56

57To carry out these objectives, the components of

the experiment are dissected and examined with the intent of relating each component to the question posed. In the examination the dependent variable and the independent variables considered are reviewed in light of the require­ments of decision theory. Information items in the questionnaire are viewed as to source. The conventional information items provided to respondents are related to current employment practices. The human resource infor­mation items are examined in light of the proposed human resource accounting systems reported in Chapter II. The information items are also viewed as to decision utili­zation. To this end, the question of how the importance of the various items of information provided is related to decision output is examined. Finally, the demo­graphic and background characteristics of the respondents, which are assumed to be deterministic in the respondent’s subjective decision criteria, are examined.

To accomplish the purpose of this chapter, infor­mation and the information requirements of decision-making are discussed. The discussion includes aspects of de­cision theory as they apply to the experiment. With this foundation, the decision model applicable to the experi­ment is developed. Next, the information items contained in the questionnaire and necessary to make the model operational are examined. The chapter concludes with a

discussion of the statistical aspects of the type of data provided in and generated by the questionnaire.

InformationThe terms "communication" and "information" are

sometimes used synonymously in the literature. Sterling differentiates between them by describing the trans­mission of unevaluated data as "communication." "Infor­mation" is restricted to the description of useful messages.'*' White describes information as simply a collection of propositions whose truth value is 0 or 1.Any proposition whose truth value is not known to be 0

2or 1 contains no information.The assertions of White and Sterling can be

reconciled with respect to what constitutes information. In White’s definition, if the truth value of a message is known to be 0, then the message further confirms what is already known to be untrue. White still considers this "information." In Sterling’s definition, if the message does not conform to reality, it is termed misinformation; but it strengthens the receiver's conception of what is not true. It has been argued that even if a message is

■^Robert R. Sterling, Theory of the Measurement of Enterprise Income (Lawrence! The University Press of Kansas, 19?0), p. ifO.

pD. J. White, Decision Theory (Chicago, Illinois: Aldine Publishing Company, 1970), p. 140.

59known to be untrue, its receipt is information in that it has the effect of strengthening the convictions of the receiver.

For a message to be useful two requisites are necessary: (1) verity and (2) relevance.-^ To possessverity a message must be in "conformance with reality."A message is a verbal or symbolic proposition which pur­ports to say something about the "real world." If the message describes the real world, it is "veritable"; and may be termed "information." Verity is judged by agree­ment among qualified observers. In common usage another word for verity is objectivity.

Relevance is the second attribute necessary for a message to be information. In common usage other words for relevance are the value or importance of the message to the receiver. To affix a value or importance to a message, the receiver must have prior knowledge of the problem under consideration. Prior knowledge is a requisite, but it is not sufficient. Additionally, the receiver of information must have a theory or framework from which to view the problem. The functions of a theory or framework are (1) to select the relevant infor­mation from a myriad of complex observations and (2) to arrange the information in a comprehensible combination.^

3Sterling, loc. cit.^Ibid., p. 41•

60From a different approach, White distinguishes

two levels of information: (1) state and (2) relation.^State type information describes the state of affairs in some context (i.e., the state of a person). The "state" is not confined to present conditions and may be made up of observations made over a long period of time. The "state" may contain variables subject to choice or not subject to choice.

Relation type information specifies some con­nection between states. Relational information allows deduction of one set of propositions from another, whereas "state" information contains no deductive element and is purely a means of identification.

Verity AssumedIn this experiment verity or objectivity of both

human resources accounting and conventional information is assumed. Stated otherwise, the information provided respondents in the questionnaires whether it be Set I, conventional employment information, or Set II, human resource accounting information, is considered to reflect the actual situation and is not considered a subject of inquiry. This assumption of verity is justified for several reasons. First, the purpose of this experiment is to determine whether human resource accounting

cWhite, loc. cit., p. 140.

61information can be utilized to ameliorate decision­making; in essence, the thrust of the experiment is to gauge the relevance of human resource accounting infor­mation to the decision process of personnel adminis­trators. To dilute the experiment with an inquiry into the verity of human resource information would be pejorative to the primal purpose of the experiment.This leads to the second reason. Human resource account­ing is still in the incipient stage. It consists mainly of proposals with only scattered attempts at implemen­tation. An inquiry into the verity of the information provided by human resource accounting is premature at this time. The attempts to establish the validity of the proposed human resource accounting models are still being evaluated. Thirdly, the decision as to what types of conventional information items were to be included in the information section of the questionnaire was made after several employment applications were studied. After studying the application blanks used by various organi­zations, the impression received is that ’’when you have

£seen one, you have seen them all." There is a surprising degree of similarity between employment application blanks used by different organizations. This is because

^Edwin B. Flippo, Principles of Personnel Management (New York: McGraw-Hill book Company, 1966),pTiSr:—

62the information requested is basic and all organizations agree on its importance. As far as types of conventional information is concerned, there is no need to question its verity.

The actual quantities or qualities entered under Applicant A and Applicant B might be subject to question. Justification for the quantities and qualities presented is contained later in this chapter.

Relevance ConsideredTo ascertain the relevance or value of infor­

mation currently received, the receiver must possess prior knowledge. Stated differently, the "state” of the recipient must contain some bits of information which can be utilized to identify the relevance of the new infor­mation. Additionally, the receiver must have some theory or framework from which to view the problem. In Chapter I, this framework or theory was referred to as the receiver's subjective judgemental criteria. In this experiment, the demographic and background information is assumed to be deterministic of the decision theory posed by the decision maker. With this state, decision theory, framework, or subjective judgemental criteria, the decision maker is capable of determining the relevance, to use Sterling's word, or the relational content to use White's word, of information currently received. In this experi­ment, the information currently received is the information

63embodied in the independent information variables of the study. The information variables include conventional employment information variables (K1 - K14) and human resource accounting information variables (LI - L14).The relationship between information currently received and information previously received is of paramount sig­nificance in the decision process. According to decision theory, the information currently received interacts with information previously received (i.e., the decision maker's decision theory) and forms a decision premise.The decision is the logical consequence of the decision premise. The action taken is a manifestation of the decision made.

The DecisionAn essential pre-requisite of an occurrence of

decision is the existence of a motivating state of ambi-7guity. The decision is resolution of the ambiguity.'

Choice of one of several alternatives is the manifest enactment of a decision. Indeed, choice is the end point of a selection process, and preference results in choice. In decision theory, choice and selection are inter­changeable words. Therefore, it can be said that the actual selection of an alternative comes at the end of

'White, op. cit., p. 1.

64the selection process and is not directly involved in the making of a decision.

The definition of a preferred choice is a choice enacting a decision. However, in some cases it cannot necessarily be inferred from observing a person's choice that it is a "preferred" choice. This is true in the case of random selection. In such instances, a choice is made; but it is not preceded by a decision. In random selection the choice is made on a basis other than decid­ing between alternatives. Dunlop summarizes the relation­ship between choice or selection and decision with thefollowing words: "there can be choice without decision;

9but there cannot be decision without choice."In this experiment the selection of Applicant A

or Applicant B is assumed to rest on a decision made on the basis of information provided. The basis for this assumption is the instructions for filling out the questionnaire. In the instruction section of the question­naire, respondents are informed that they must decide to hire either Applicant A or Applicant B. The word decide is used instead of choose to guide the respondents away

^Ibid., p. 6.9W. Dunlop, "The Representation of Choice,"

Terminology Review, Quarterly Bulletin No. 3» Sept., 1951, quoted in D. J. White, Decision Theory (Chicago, Illinois: Aldine Publishing Company, 19t>9), p. 2.

65from random selection. Stated in terms of the question posed, the respondents could have chosen an applicant without making a decision based on a premise resting on current information received and their subjective judge­mental criteria. Such random choice is not the intent of this experiment. Conversely, if only Applicant A's or only Applicant B ’s credentials had been made known to the respondents, they could not have decided between the two. In decision situations acceptable alternative selections are a prerequisite.

According to Dunlop, there are four phases in decision: hesitancy, knowledge, striving, and willing.^Presumably, hesitancy signals the existence of an am­biguous state. This is the alert mechanism in the decision process.

In this experiment the respondent reached this state when the instructions on the questionnaire indi­cated that two applicants were available for employment and that he must decide between the two. The ambiguity existed in that either of the applicants were feasible employees; but only one could be employed. The fact that the respondent was to make a selection was not ambiguous. The cover letter and the instructions on the questionnaire informed the respondent of the impending decision situation.

^Jbid., p. 11.

' 66The second phase in decision making is knowledge.

In the knowledge phase information is acquired by the decision maker pertaining to the specification of the ambiguity as well as information relevant to the reso­lution of the ambiguity. In this experiment the infor­mation conveyed by the questionnaire is divisable into two parts: (1) the information which informs the respon­dent of his hypothetical decision role, and (2) the infor­mation which is to be used in the formation of the decision premise (i.e., the independent variables,K1 - K14, and LI - L14).

Striving corresponds to an attempt to decide between the alternatives. This stage of the decision process was entered in this experiment when the respon­dents read and weighed the information items. As weights were assigned to the individual items they were recorded on the rating scale of the questionnaire. The inter­action between the weight assigned by a respondent to an information item and the variance in the qualities and quantitative magnitudes assigned to Applicant A and Appli­cant B is intended to provide the matrix for the respon­dents decision. The configuration of the decision matrix is simultaneously dependent upon the antecedent theory, framework, or state of the respondent.

In the fourth phase of decision according to Dunlop, willing is considered to mean the will to use the

alternative chosen. In this experiment this phase corresponds to the hypothetical hiring of the applicant selected by the personnel administrator.

In describing the decision process as a function, Ijiri et al. identify three factors: decision inputs,decision outputs, and decision rule.^ Decision inputs are factors which are considered by the decision-maker in making his decision. This function is analogous to Dunlop's phases of hesitancy and knowledge. The inputs provide the necessity for decision, thus the hesitancy. Inputs also provide the knowledge with which the decision can be made. Decision output are the decisions made by the decision-maker. This function corresponds to Dunlop's willing phase. Decision rule is a rule by which a set of decisions is associated with a set of decision outputs. Striving is the application of the decision rule to the set of current information and arriving at a decision.

Whether classified by phases or functions, the decision is decomposable into specific segments each of which combine to make the decision process an integrated, unique human exercise.

11Yuri Ijiri, Robert K. Jaedicke, and Kenneth E. Knight, "The Effects of Accounting Alternatives on Management Decisions,” in Yuri Ijiri, Robert K. Jaedicke, and Oswald Nielson, Research in Accounting Measurement, Collected Papers (Menaska, Wisconsin: American AccountingAssociation, 1966), p. 137.

The Decision ModelIn practical considerations better decision mak­

ing is synonymous with improved consequences. Indeed, the focus of this experiment is to determine if human resource accounting information can be effectively uti­lized to improve the selection process and thereby provide the firm with productive employees. The decision made by respondents in this experiment is correct if it coincides with the selection based on Set I or Set II information items. The correct selection is assumed to result in improved consequences. That is, hiring the applicant most capable of sustained productive employ­ment. Those characteristics which have been adjudged to indicate such productive capacity have been assigned to Applicant A in Set I, conventional information, and to Applicant B in Set II, human resource accounting infor­mation.

Even though improved decision making is assumed to produce improved employee selection for this experi­ment, in reality chance plays a part in the consequences of a decision. Therefore, chance cannot be ruled out of the decision process. Chance enters the decision process because decision-makers normally receive limited quantities of current information on which to base decisions. There is always the possibility that information relevant to the decision is not received by the decision-maker. In such

69situations the decision is logical; but, because of chance the consequences are not improved.

Because not all ambiguity is eliminated prepara­tory to the act of deciding, judgemental criteria enters the decision process. In fact, if all ambiguity were eliminated the decision would be unnecessary; the selec­tion would be eminently apparent. However, deciding involves weighing the various components of information inputs and assigning a probability as to their verity.It is in the area of assigning probabilities that judge­ment enters the decision model. The function of assigning probabilities is normally carried out by the decision maker in the course of the decision process. However, in the case of Set II, human resource information, variables L9 - Lll, the probabilities of promotion and salary increases are provided.

A model of the decision process as envisioned for this experiment is presented on the following page. The phases or functions of the decision process are indicated across the top of the sketch. The time frame of infor­mation received is indicated in the left margin. Depend­ing on the questionnaire received by the respondent, decision inputs consist of one of three combinations:(1) Set I, conventional employment information and back­ground variables, (2) Set II, human resource information and background variables, or (3) Set III, conventional

FIGURE I

MODEL OF THE DECISION PROCESS FOR EXPERIMENT IN PERSONNEL SELECTION

HESITANCY/KNOWLEDGE INPUT

STRIVING DECISION RULE

WILLINGOUTPUT

and/or

orand

rrcvious IInformation

jIrrelevant iInformation

DecisionRule

ObjectiveComponent

DecisionPremise

SubjectiveComponent

Applicant A

CurrentInformation

HumanResource

Applicant B

ConventionalEmployment

BackgroundVariables

employment information, human resource information, and background variables. The conventional information items and/or human resource information items comprise the objective component of the decision premise. The back­ground variables of the respondent comprise the sub­jective component. The objective component and the subjective component interact to determine the decision premise. The decision premise is formed after truth probabilities are assigned to the information received. This assignment determines the usability or unusability of the information. Information judged not useful in the decision premise is disregarded as irrelevant. The decision rule is applied and the decision is observable in the respondents selection of either Applicant A or Applicant B in response to Question #1 of the question­naire. In this experiment the decision rule requires selection of the applicant best qualified to be Assembly Line Foreman.

The foregoing material is intended to provide the background information necessary to grasp the nature of the decision required in the experiment. The remaining part of this chapter describes the environment in which the experimental decision is made.

The Experimental ModelThe design employed to carry out the experiment

can be presented as a static, deterministic, empirical

model. It is described as static because it is not manipulated through time. One assumption of the useful­ness of accounting information is that given the same information input and the same decision-maker; the identical decision will be made in succeeding time periods. There would be little value in studying decision theory and its relationship to accounting if this assump­tion were not made. This property of the decision process is called decision reliability. However, the design of this experiment does not allow for serial assessments of the decision process of the respondents over time. Such a longitudinal study is far beyond the scope of a doctoral dissertation in both resources and time requirements.

The model is deterministic as opposed to sto­chastic in that the independent variable values are taken from actual measurements. Random variables are not utilized in the operation of the model. The operation of the model involves statistical data collected on the questionnaire; therefore, the model is considered empirical.

Specifically, the design calls for the selection of one of two hypothetical applicants, Applicant A or Applicant B. The selection is considered to be based on a decision of the personnel administrator's responding.The decision is to be based on the quantitative and qualitative credentials of Applicant A and Applicant B.

Precisely, the employment decision is considered to be a function of the independent variables. The first vari­able falls into the current information category. All other variables are considered to be components of the respondent’s subjective judgemental criteria and are therefore in the category of information previously acquired. A schematic summary of the variables con­sidered in this experiment appears on the next page. The variables and source of variation are as follows:

INDEPENDENTVARIABLE

1. Set I, Set II, or Set 1. Ill information

2. Importance of infor- 2.mation items

3. Experience level 3•

4. Managerial philosophy 4.

5. Company experience 5«

6. Educational 6.experience

SOURCE OF VARIATION

Provision of the three different sets of infor­mation to three groups of respondentsVariation in the impor­tance assigned the items of information provided the respondentsVariation in the level of business and employment experience of all respondentsVariation in the ambient management styles of the respondents place of employment: autocratic,participative, or free- reinVariation in size and type of company employing respondentVariation in level, field, and recency of respondent's education

FIGURE II SUMMARY OF VARIABLES BY

SOURCE"OF VARIATION .Independent Variables

r Current Input Subjective Criteria

Set I.Conventional Employment

:rrati:

Set III Conventional Employment I r "i crm g t i onHum. n Resource I f orm ation

Set IIHuman Resource Information

Importance Rating of Conven­tional Items

Importance Rating of Human Resource Items

ExperienceLevelFrom Q9 & Q10*Managerial Philosophy From Q -Company Experience From Q2 & Q3Educational Experience From Q5» Q6A&B Q7A&B, Q8Attitude Toward Human Resources From Qll, Q12,Q13. Ql^

Dependent Variablei----------------- T

Decisioni------------ 1

^Response to Question #1

*Q9 & QIC refers to Question #9 and Question #10 of the Questionnaire. -p-

75INDEPENDENTVARIABLE

SOURCE OF VARIATION(continued) (continued)

7* Attitude toward human 7. Variation in the per-

Validity of Information ItemsTo complete the inquiry into the design of the

experiment, it is essential to examine the validity of the information input items. As stated previously, Set I, conventional employment information items were selected after a study of the similarity of several employment applications. These items are in common usage and further examination is unnecessary.

human resource information, rests on the validity of the models proposed for human resource accounting. The examination of the Set II items is divided into two parts: (1) an enumeration of the models from which the items are drawn, and (2) examination of the validity of the magni­tude of the values assigned to the items for Applicant A and Applicant B. The specific items and the proposed human resource accounting model from which they are drawn are as follows:

resources ceived need for information, the infor­mational propensity, and attitude of the respondent toward the concept of human resources

The validity of the items included in Set II,

76

INFORMATION DRAWNITEM FROM

L 1 Recruiting cost Figure 1. Generalized ModelL 2 Training cost Figure 2. Replacement

ModelCost

L 3 Cost of lost production

Figure 2. ReplacementModel

Cost

L 4 Separation cost Figure 2. ReplacementModel

Cost

L 5 Present value of fringe benefits

Discounted Earnings — Schwartz

Lev &

L 6 Present value of salary

Discounted Earnings — Schwartz

Lev &

L 7 Present value of employee replacement

Figure 2. ReplacementModel

Cost

L 8 Employees' time with company

Figure 5. Stochastic Model

L 9-- K 11 Probability of promotion

Figure 5. Stochastic Model

L12 Present value of in-company training

Figure 2. ReplacementModel

Cost

L13 Value in 2nd most productive capacity

Opportunity Cost — Hekimian & Jones

L14 Value of one additional employee

Figure 5. Stochastic Model

The items were drawn from the proposals as indi­cated. However, in a number of cases the wording appear­ing on the questionnaire is necessary to make the items understandable to respondents who were unfamiliar with the concept of human resource accounting.

To provide information about Applicant A and Applicant B variation in the values assigned was necessary.

This introduced the possibility that the decision would be based on the magnitude of the differences of the quantities assigned. Basing the decision solely on the magnitude of the differences and not considering the importance of the information items is at variance with the stated purpose of the experiment. To overcome this possibility, the relative magnitudes of the differences of quantitative information items are equal. This tech­nique is based on Weber-Fechner’s Law and empirical find-

12ings of Rose, Beaver, Becker, and Sorter. Weber- Fechner1 s Law states that the change in intensity of a stimulus necessary before it can be detected is a con­stant function of the amount of stimuli present. The validity of the law is the subject of continuing contro­versy. Despite extensive criticism, the law has never been clearly invalidated. Neither has it been completely validated.

The empirical researchers concluded that subjects reacting to data behave in a symmetric, regular, and pre­dictive manner consistent with observed response patterns to sensory stimuli. The change in intensity of stimulus needed before it can be detected is essentially a constant — approximately This constant percentage

12J. Rose, W. Beaver, S. Becker, and G. Sorter, ’’Toward an Empirical Measure of Materialty,” Empirical Research in Accounting: Selected Studies, 1970,pp. I3S-I4S.

78

is used as the difference in the quantitative information items provided. By removing variation in assigned quantitative magnitudes between items of a continuous nature, the selection decision should be based on the importance attached by the respondent to the respective information items.

The problem of differences in magnitudes does not exist for items expressed qualitatively. However, a similar problem could have arisen if the qualities were so diverse to exclude one applicant from consideration by the respondents. To preclude this possibility position and duties (i.e., variables L9 and Lll) are the same for Applicant A and Applicant B. Major study and machine skills (i.e., variables K6 and KS) are only slightly varied so as not to preclude consideration of both applicants by the decision-maker.

Demographic and Background VariablesThe demographic and background information

gathered by the questionnaire is designed to evaluate the job environment, qualifications, and attitude toward the concept of human resources. These variables are assumed to be deterministic of the respondents subjective judge­mental criteria as shown in the summary of variables con­sidered. No formal attempt is made in the experiment to test the validity of this assumption. It is required, however, to demonstrate the basis of this assumption.

79The importance attached to each information item

is indicative of the degree of respondent familiarity with the item. As stated previously, prior knowledge and a framework or theory is essential if messages received are to be considered information. If the respondent places a very low rating on an item of infor­mation, it can be inferred that his decision premise is complete without its inclusion. Conversely, a high rating indicates an acceptance of the information item to complete the decision premise.

The level of experience, both in business and in charge of the personnel management functions (Questions #9 and #10), is reflective of two respondent character­istics: decision rigidity and decision validity. Therespondent with many years experience is likely to follow the familiar decision inputs (i.e., conventional employ­ment information) to arrive at a logical decision. Simultaneously, the well seasoned decision-maker is not likely to accept unfamiliar information. For the respon­dent with little experience the situation is just the reverse. He is not as likely to arrive at a logical decision, but he is more likely to be less rigid in se­lection of relevant information.

As stated in Chapter II, the original purpose of Dr. Likert's model was not to value human resources, but to evaluate the efficiency of four systems of management.

soThe rating scale of Question #4 is designed to capture the respondents impression of the dominant leadership style of his immediate work environment. The desig­nation of Question #4 is assumed to reflect the respondent’s own managerial philosophy. This assumption is based on the observation that an autocratic person­ality cannot long survive in a free-rein environment and vice-versa. To do so is dysfunctional. The in­direct question pertaining to the respondents environ­ment rather than the direct question pertaining to the respondent was used to exclude bias. The natural disposition of respondents answering questions about themselves is to adhere to the mean and indicate a participative disposition. The information contained in response to Question #4 will be used to assess the relationship between the managerial philosophies and the acceptance of the concept of human resources by the respondents.

Question #11 through #14 are designed to assess the attitude of the respondent toward the concept of human resources. Question #11 is a filter for Question #12. Question #12 is designed to establish the infor­mational propensity of the respondent. If respondents are quantitatively oriented, it is assumed that human resource information can be easily assimilated into and utilized in their decision process. Likewise, a positive

81answer to Question #13 and an indication that human and physical assets are essentially the same in Question #14; indicates a favorable disposition toward the con­cept of human resources. A favorable disposition is assumed to mean a willingness to consider and use the information in the decision process.

The type of industry, Question #2, and the size of the company, Question #3, is considered to be an indication of the informal familiarity of the respon­dent with the existence of human resources in his firm. Service oriented organizations, including educational and governmental organizations, require the acquisition of a larger percentage of human resources to total resources than do manufacturing organizations. Also, due to the increased managerial complexity, large organizations require the acquisition of relatively more human resources than small firms. It is assumed that the existence of human resources in a firm has an expan­sive effect on the cognition of the personnel adminis­trator. Therefore, the purpose of the information gathered is to assess the relationship between the assumed existence of human resources in the respondents environment and the utilization of information pertain­ing to human resources in the employment function.

Questions #5 through #8 pertain to the respon­dents educational background. The purpose of gathering

this information is to discover the relationship, if any, between the level, recency, and type of education of the respondent and the propensity of the respondent to use human resource information. It is hypothesized that respondents with graduate level education recently completed will be more adept at utilizing human resource information than those of less educational attainment not as recently completed. This assumption is based on the assumed broadening effect of graduate work on the cognitive functions of respondents. Also, respondents with quantitative backgrounds as indicated by their major and minor field of study are assumed to be better able to analyze and use human resource information.This follows from the basically quantitative character of human resource information. Further, respondents with accounting backgrounds should be sufficiently quantitatively oriented to utilize quantitative infor­mation. Respondents with personnel management course work are considered to be qualitatively oriented and less able to assimilate quantitative information.

DataThe data provided the respondents by the

questionnaire are quantitative with the exception of Set I, variables L6, L&, L9, and L10. These variables are qualitative. The quantitative data provided respondents are continuous.

S3The data gathered in response to the importance

rating of the information by the respondents are quantitative. These variables are considered discrete.

Data acquired in response to Questions #1, 2,5, 6, 11, 12, 13, and 14 are qualitative. The response to Question #1 is in binomial form. Additionally, Questions #11 and #14» in effect, result in open-ended qualitative information. The responses to Questions #3, 7> 8, 9i and 10 are quantitative and discrete in form. Only the response to Question #4, the rating scale, could be considered quantitative and continuous. However, to facilitate analysis the continuous data were transformed into discrete data by assigning .5 intervals to the scale. Therefore, a 1.0 rating represents extreme autocratic managerial philosophy while a 6.0 rating represents extreme free-rein management.

The following chapter reports the response to the survey, restates the hypotheses tested, and dis­closes the acceptance or rejection of the hypotheses on the basis of the statistical techniques applied to the data.

CHAPTER IV

THE EXPERIMENTAL RESULTS

The preceding chapters have provided the pro­spective essential to view the experimental results reported in this chapter. Therefore, the content of this chapter is primarily concerned with relating and interpreting the data generated by the experiment. To present clearly the data generated and concomitant interpretation, the chapter is divided into four categories:

(1) A report of the rate of response to thesurvey.

(2) A discussion of the statistical techniques applied to the data.

(3) A restatement of the hypotheses, a report of data bearing on the hypotheses, the acceptance or rejection of the hypotheses and possible influences drawn from the rejection of the hypotheses.

(4) A report and interpretation of the comments made by the respondents. These comments were solicited in Questions #11 and 14 of the questionnaire.

The rate of response by groups is indicative of the willingness of the respondents to use the type of

information provided by the questionnaire. Therefore, the variation in rates of response between groups is considered to be an integral part of the experiment.To be most informative, the response rate is presented by groups.

An understanding of the power and limitations of the statistical techniques applied is essential to draw valid inferences from the statistical results.The discussion details the prerequisites and valid influences applicable to chi square and the contingency coefficient.

The hypotheses are restated to show clearly the relationship between the hypotheses considered and the objective of the experiment. The restatements are intended to show clearly the basis of the hypothesis, the relationship of the hypothesis to human resource account­ing information, and relative importance of the indi­vidual hypotheses to the overall objective of the experiment. To accomplish this, each hypothesis is broken down into its component parts and examined to discover the basis, relationship, and importance to the study. The acceptance or rejection of the hypothesis rests solely on the experimental data gathered for that purpose. The inferences drawn are based on the results of the statistical procedures applied to the data.

36

To round out the report of the experimented results, it is essential to report the open-ended responses solicited from respondents in the comment part of Questions #11 and 13. Open-ended data is exception­ally informative; however, it poses a problem in presentation. To make the problem manageable, the comments will be categorized and the most pervasive responses will be reported.

Rate of ResponseAll questionnaires were mailed on October 1,

1973* Included in the envelope were the questionnaire (see Appendix A), a cover letter from the Chairman, Cooperative Research Committee, American Society for Personnel Administration, and a serially numbered busi­ness reply envelope. The questionnaires were printed on a 25i-" by H 5-" sheet and folded twice so that the page size was &§-" by llir"• Printed on both sides, the pages folded out from the left and right to enable the respon­dent to observe the instructions and information items in Set III questionnaires simultaneously. In Set I and II questionnaires, the respondent could view the instructions, the information items, and the first eight questions simultaneously.

A ninety (90) day period was alloted as response time. A follow-up letter was to be mailed to non­respondents on October l‘)t 1973 • However, the high response

37rate in the first two weeks of October made the follow- up unnecessary.

The relatively high overall response rate of 43*41$ along with the 42.33$ usable response rate received without follow-up is attributable to several causes. First, the membership of the American Society for Personnel Administration, from which the same was drawn is highly professional; therefore, it is interested in expanding the intellectual basis of the profession. Secondly, the study was enclosed and sup­ported by the Cooperative Research Committee of the American Society for Personnel Administration. This endorsement was clearly stated in the cover letter from the chairman of the cooperative committee to the recipi­ents. Thirdly, the members of the sample possess a high level of educational attainment. This is clearly demon­strated in Table VIII C of Appendix C. Significantly, S3.2$ indicated reaching the Bachelor level in their education. Even more significant 21.4$ reached the Master's level while 2.4$ indicated receipt of the Ph. D.

The rate of response is presented by groups in Table I on the following page.

The approximately equal number of questionnaires sent to each of the three groups provided for a poten­tially equal number of responses from each group. After

TABLE I SUMMARY OF RATE OF RESPONSE

BY GROUP

Questionnaires MailedQuestionnaires Returned by Post OfficeQuestionnaires Returned by Other Than Intended RespondentNet Potential ResponseDefectively Printed Questionnaires ReturnedQuestionnaires Returned by Intended Respondent (Participation Declined)Received After Cut-Off DateUnuseable Questionnaires ReceivedUseable Questionnaires ReceivedTotal ResponseTotal Response RateUseable Response Rate

Jroup #1 Group #2 Group #3 Total400 401 409 1210

0 0 1 1

0 2 0 2400 399 408 120?

0 1 0 1

1 8 0 90 3 0 31 12 0 13

190 152 169 511191 164 169 524

47.75% 41.10# 41.42# 43.41#47.50# 38.10# 41.42# 42.33#

39reducing Group #3 by the questionnaires returned by the post office and Group #2 by the two questionnaires returned incomplete by persons other than the intended respondent, the Net Potential Response varies a maximum of 2.2% between Group #2 and Group #3. This variation is statistically insignificant.

The three groups are subsets of a randomly generated sample of potential respondents. The only known variable between groups is the difference in the type of information items provided by the question­naires to each group. Members of Group #1 received only conventional employment information; Group #2 members received only human resource information items; while Group #3 members received both conventional and human resource information items. All other group characteristics are assumed constant between groups. Therefore, variation in group response rates could be attributed to the variation in the type of information provided the respondent in the questionnaire. Since respondents are familiar with conventional employment information and unfamiliar with human resource account­ing information, apriori reasoning indicates a high response by the groups receiving conventional infor­mation items and low responses by the groups receiving human resource accounting information items.

90The pervasive use of and familiarity with con­

ventional employment information and the general un­familiarity with human resource accounting information is indicated by the variation in response rate of the groups. This fact can be demonstrated by considering(1) the usable response rate and (2) the overall response rate.

Since Group #1 respondents could use only con­ventional employee selection information, their rate of response was the highest of the three groups. The 47.50$ usable response rate shows the willingness of the participants to respond when asked to utilize infor­mation with which they are familiar. To further confirm the contention of the positive relationship between the rate of response and familiarity with information items provided, the next highest rate of response was for Group #3. This is expected since Group #3 contained conventional information items along with human resource information items. The 41.42$ usable response rate for Group #3 fall between the high usable response rate of Group #1 and the 3$*10$ usable response rate of Group #2. Since Group #2 respondents received only human resource information, it follows that their response rate would be the lowest of all three groups.

The overall response rate by groups monitored the pattern set by the groups in the usable response

91rate. Group #1 was the highest with 47.75$ followed by Group #3 and Group #2 with 41.42$ and 41.10$ respec­tively.

A comparison between the overall response rate and the usable response rate by groups provides further evidence in support of the positive correlation between usable responses and type of information provided the respondent. The difference between overall and usable response rate for Group #1 is negligible. There is no difference in the rates of Group #3. However, there is a significant difference of 3*0$ in Group #3. The one defective questionnaire should be eliminated; but, the eight declining to respond and the three received after cut-off date should be considered.

The eight respondents declining participation offered various reasons for their actions. Generally, the reason centered around the fact that they were not involved in the selection of Assembly Line Foreman in their present employment. Six indicated they were in­volved in the employment or placement of professional employees. Two were University professors; therefore, they were not involved in any employee selection function.

As stated previously, the only variation between groups was the difference in information items provided. The groups are subsets of the original random sample

92partitioned on a random basis. Therefore, sampling theory indicates an equal distribution between groups with respect to group members actually involved in personnel selection in their jobs. It is significant, therefore, that eight potential respondents pointed to the fact that they are not involved in the selection of manufacturing personnel in declining to participate.It can be validly assumed that an equal number of the members of Groups #1 and #3 are not involved in the selection of manufacturing employees; yet, only one in Group #1 and none in Group #3 declined participation.This situation lends support to the assertion that the declined participation was prompted largely by the un­familiarity with the information provided in the question­naire. The reasons offered were methods for rationaliz­ing the potential respondent's position.

Throughout the ninety (90) day alloted response time, response from Group #2 was not only the lowest in percentage, it was also the slowest. The response for Group #2 did not build up until approximately thirty days prior to the cut-off date. Indeed, the three type #3 questionnaires received after the cut-off date is indi­cative of the slow response rate. This relatively slow response rate corroborates the assertion of unfamiliarity and non-use of human resource accounting information.Being unfamiliar with the information items, Group #2

93respondents postponed answering the questionnaire to a greater extent than did Group #1 and #3 respondents.

In spite of the low and slow response rate of Group #2, those that did respond were able to utilize the information provided very effectively. This finding is further developed in the discussion of the statisti­cal results associated with Hypothesis H- later in this chapter.

Statistical TechniquesThe amount of data generated by the 511 usable

questionnaires received is quite formidable. The distribution of the potential bits of data by groups appears in Table II on the next page.

To deal effectively with the 17,696 potential bits of data, it was necessary to employ the computer.To facilitate compilation and analysis information from each questionnaire was transferred to a computer input card. Summaries of frequency distributions of responses and percentages appear in Appendix C.

The problem arose as to how to treat question­naires not completely filled out. All questionnaires were substantially complete; but some were returned with one or two bits of information not entered. To dis­regard a questionnaire not entirely filled out would have resulted in a waste of valuable information. To

TABLE II

DESCRIPTION OP VARIABLEQuestionnaire #Group #Importance Rating (Conventional K1 ... K14)Importance Rating (Human Resource LI ...L14)Responses to Questions #1 - 14Total Variables Per QuestionnaireUseable QuestionnairesTotal Potential Data

DISTRIBUTION OF POTENTIAL DATA BY GROUP

GROUP I GROUP II GROUP III TOTAL1 1 1 31 1 1 3

14 0 14 28

0 14 14 28

14 14 14 42

30 30 44120 152 162 ill5700 4560 7436 17696

MD•e-

95solve the problem, the computer program utilized all applicable responses in specific compilations and analysis. This was accomplished by considering all 511 inputs as part of a data set. Then, if a specific compilation analysis required, for example, the presence of Group number and response to Question #1, all inputs not having either a group number or a response to Question #1 were deleted. Consequently, the resultant set was composed of usable data items.

As reported in Chapter III, responses to. Questions #3, It &t 9i and 10 are quantitative and discrete. Re­sponses to Question #4, the rating scale, was converted from continuous to discrete form. To facilitate compi­lation and computation the qualitative data generated in response to Questions #1, 2, 5, 6, 11, 12, 13, and 14 was assigned numerical values to give it the appearance of quantitative discrete data. However, the qualitative character of this data is maintained. Only the data generated in response to the comment sections of Questions #11 and #14 was not converted to quantitative data. These comments will be reported by category with­out application of statistical procedure.

In testing null hypotheses, two types of errors may enter the process. Type I errors (level of signifi­cance) result when a true hypothesis is rejected. Type II errors result when a false hypothesis is not rejected.

For a fixed sample size to decrease the risk of one type of error is to increase the risk of the other.In the tables of experimental results, the exact probability of Type I error is denoted by P.

The statistical methods employed require no particular assumptions about the form of the population sampled. Consequently, the methods employed are non- parametric and distribution free. Statistical pro­cedures applied to the data include the computation of

pchi square (x ), and the contingency coefficient (C).Chi square or the Goodness of Fit test is

applied to determine whether frequencies in the classes of a sample distribution differ sufficiently from theoretical normal frequencies to discredit the assump­tion of normality in the sampled population.^ The chi

psquare statistic (x ) is used in the computation of the contingency coefficient (C). Specifically, C is com­puted utilizing the following formula:

2when x is the computed chi square and N = total obser­vation in the table.

"hvierle W. Tate, Nonparametric and Shortcut Statistics (Danville, Illinois: Interstate Printersand Publishers, Inc., 1957), p» 5#.

97The contingency coefficient is based on the idea

that the amount of correlation between valuables classi­fied in a contingency table depends upon the divergence of observed frequencies in cells from the frequencies expected if there were no relationship. The contingency coefficient, or test of independence is a versatile statistical tool. It may be used when the variables are continuous, discrete, or quantitative, or when one variable is of one kind and the other of another kind. Therefore, chi contingency coefficient is especially suited to the data generated in this experiment.

In effect, the contingency coefficient is a measure of the strength of the relationships between two or more than two variables. The lower limit of (C) is zero; the upper limit depends on the number of cells in the contingency table. It is always less than one. In a 2 x 2 table (C) cannot exceed .707; for a 3 x 3 table (C) is limited to .$16. In a 4 x 4 table the upper limit of (C) is .£70.^ Therefore, C's computed for tables of different sizes are not entirely comparable. Further, C possesses ordinal rather than interval or ratio measurement qualities. Consequently, inferences

^Ibid., p. 19.^Sidney Siegel, Nonparametric Statistics for

Behavioral Sciences (New York: McGraw-Hill Book Co.,1956')"," p.' 2UT.-----

based on C cannot be assumed proportional to the differ­ences in the magnitude of C for tables of different sizes. For example, a C value of .800 cannot be inter­preted to indicate a relationship twice as strong as a C of .400 even if both C's are computed from comparable contingency tables. All that can be inferred is that the higher C value indicates a stronger relationship than the lower, but how much stronger cannot be deter­mined. The answer to the question of what magnitude of C constitutes a significant relationship between the independent and dependent variables is a subjective matter. The strength of C computed for a particular contingency table size can be judged by comparison to the limit of C for that table size. It can also be judged by reference to the other values of C computed insimilar circumstances. Further, the magnitude of the

2computed x is an indication of the strength of C com­puted for the same set of data.

2In addition to providing the x and C value full disclosure requires the reporting of the Exact Probabil­ity (P) and the Degrees of Freedom (DF) for each contin­gency table. The exact probability has reference to the level of significance or degree of risk assumed with respect to Type I error. In effect, the value P pro­vides information as to the likelihood of the corre-

2sponding x be attributed to chance variation. A P

99value of .001 indicates that a value as high or higher than the indicated x will occur due the random factors in 1 of 1000 such computations made.

The Degrees of Freedom (DF) is significant in the determination of P. As the DF increase the risk of Type I error also increases. The formula for computing DF is as follows;

DF = (K-l) (h-1),

when K is the number of columns and h is the number of rows. Therefore, a 2 x 2 table has IDF, while a 3 x 3 table has 4DF.

To draw proper inferences from the computed data shown in the results section of the tables reportingexperimental results, the relationship between chi square

2(x ), contingency coefficient (C), Degrees of Freedom DF,and Probability (P) must be understood.

2As indicated previously, x is used in the compu­tation of C. Therefore, there is a direct relationship

2between x and C. That is, high C values are computed2from high x values. However, the total number of obser­

vations (N) is also included in the computation of C. As N increased from sample to sample the value of G decreases. Therefore, there exists an inverse relationship between C and N. The Degrees of Freedom is dependent upon the size of the contingency table considered. As the number

100of cells of contingency tables increase so does the DF. Probability of Type I error (P) is dependent upon x2 and DF. Specifically, as x increases, concomitant P values decrease. As DF are increased P values increase. These enumerated relationships between x , C, N, DF, and P will be referred to in interpreting the experimental results.

This concludes the report of response rate and statistical techniques applied to the experimental data. The remainder of this chapter is devoted to restating the hypotheses tested, reporting the data collected relevant to the different hypotheses, and drawing inferences from the statistical analysis of the data.In effect, the information contained in the remainder of this chapter is the core of the experiment undertaken.

The Results of the ExperimentAs stated in Chapter I, the statistical hypoth­

eses to be tested are divided into two groups. The hypotheses of the first group are tested to disclose the existence or non-existence of a causal relationship between the dependent variable, the selection of an applicant for employment, and the independent variables considered in the test. Referring to Figure I, Chapter II, of this study, the independent variables considered in the test of the first group of hypotheses are shown

101to be the objective components of the decision model.That is, the variables considered are derived from information currently received by the respondent. Succinctly, the independent variables in testing the hypotheses of the first group emanate from variation in the type of personnel selection information provided the different groups of respondents. Further, inde­pendent variables germane to the first group of hypoth­eses include the variation in importance attached to the items of information provided the decision-maker(i.e., K1 - K14, LI - L14).

It is observed that the importance rating pro­cess as shown in Figure II, Chapter III for Human Resource and conventional informative items occurs in the striving segment. That is, when the decision premise is being formulated as also shown in Figure I, Chapter III. Even though the rating process is classed as part of the subjective criteria in Figure II, Chapter III, it results from an interaction of subjective criteria, decision theory of the respondent, and the receipt of current information. Therefore, in reality the importance rating variable is neither entirely current input nor subject criteria. However, to make the analysis manageable in the test of hypotheses in the first group, the background factors are considered constant. Therefore, variation in types of data provided

102the respondent and variation in the environment in which data is provided are the only variables considered in testing hypotheses H- through H^. By virtue of this assumption, variation in the importance of assigned information items is assumed to emanate solely from current input.

Independent variation to test the Second group of hypotheses is taken as measurements of the demo­graphic or background variables of the respondents.Again in testing the second group of hypotheses, the goal is to determine the existence or non-existence of a causal relationship between the dependent variable, selection of applicant, and the specific independent variables considered.

In the decision model shown in Table I, Chapter III, the background variables comprise the subjective component of the decision process. The subjective com­ponent is dependent on information previously received by the respondent. In Figure II, Chapter III, these variables fall under the heading of subjective criteria. This classification is based on the assumption that the variables listed are deterministic in the decision theory of the respondent.

103Experimental Results of First Group of Hypotheses

Presented in order of importance Hypothesis is primal to the experiment herein reported. Hypoth­esis H- stated in null form is as follows:

H- There are no significant differences indecision output (applicant selected) resulting from variation in information input (Set I,Set II, or Set III information).

The test of this hypothesis is intended to show the causal relationship between the type of information items provided the decision-maker and the decision made. If the decision varies from group to group as the infor­mation provided each group is varied, it can be concluded that the information was used in the decision process. Further, the percentage of correct decisions made by respondents of the three groups is indicative of the degree of efficiency associated with the use of infor­mation provided. Correct decisions are defined as those consonant with expected selection.

The information provided respondents is expected to cause Group I and Group II to select Applicant A and Applicant B respectively. Since Group III respondents received both sets of information input, it is assumed the decisions of the group will be evenly divided between Applicant A and Applicant B.

In the absence of a high percentage of correct decisions by group members, any or all of the following situations are assumed to have occurred:

104(1) The respondent did not properly understand

the instructions. However, of the 524 questionnaires returned only two complained of ambiguity in the instructions to the respondent. It is safely assumed that if the instructions were not understood, the questionnaire was not returned.

(2) The decision could have been based on the magnitude of the differences of the informative item between Applicant A and Applicant B. However, as indi­cated in Chapter III, Fuchner's-Weber's law and equal variation in magnitudes of information items tends to make this situation unlikely.

(3) Group II respondents did not understand the terminology used (i.e., present value, opportunity cost) to relate the human resource information; there­fore, either ignored or misconstrued the information. This is a real possibility since in Chapter III the dis­cussion of the decision model indicated the necessity of prior knowledge and a decision theory to make message evaluation possible. The occurrence or non-occurrence of this situation can be determined by interpreting the experimental results.

(4) Group III respondents were overwhelmed by the amount and opposite indications of the conventional and human resource information. This volume of infor­mation at cross-indication could have caused a breakdown

105in the decision process of the respondents. Therefore, the selection could have been a random choice and not a decision.

In reporting the results of the statistical techniques applied to the data, the questions posited by the foregoing situations will be answered.

The thrust of this research is to measure the degree of effect human resource accounting information could have on the cognitive process of personnel adminis­trators. The decision made (i.e., the applicant selected) is regarded as the culmination of the decision process. Therefore, variation in applicant selection among groups is evidence of the usefulness of human resource infor­mation. Heretofore, Human Resource Accounting infor­mation was assumed to be useful. The purpose of this study in general and of this hypothesis in particular is to demonstrate actual usefulness.

Of the 511 usable questionnaires returned by respondents, 4&9 indicated a selection of applicant in response to Question #1. The distribution of no answers, selection of Applicant A and Applicant B by groups appears in Table 1C, Appendix C.

The distribution of responses is very interesting. Of Group I respondents 64.3$ made the correct selection. However, $6 .6$ of Group II respondents made the correct selection. In this context, the result:', show that

106Group II respondents were better able to assimilate the information into their decision process than Group I respondents. Further, Group III respondents were approximately equally divided in their selection with 2.6io more respondents selecting Applicant B and Appli­cant A. Taken together, these results tend to indicate a degree of usability associated with human resource information in the personnel selection process.

The distribution of applicants selected by group and the results of the statistical analysis applied to the data is presented in Table III on the next page.

The Frequencies section of Table III indicates the distribution of usable responses by applicant selected by groups. The Results section shows the com- puted total chi square (x^), the total contingency co­efficient (C,p), the applicable Degrees of Freedom (DF), and the exact probabilities of risk of Type I error assumed (P), (i.e., level of significance). The total chi square is computed by considering the interaction between the dependent variable (aggregate selection of applicant by group) and the independent variable (vari­ation of information provided between groups). Stated

2succinctly, the computation x— takes the form: Groupvs. Question #1. Since the selection of applicant was confined to either A or B and all three groups of

App. A

App. BTotal

TABLE III EXPERIMENTAL RESULTS PERTAINING

TO HYPOTHESIS H,(GROUP vs Ql) x

FREQUENCIES RESULTSGROUPn119

66185

GROUP#219

121142

GROUP#379

_81162

TOTAL217

272489

G1 vs G3 x2 X1

8.53DF*1P=.0036

*0^.1545

G2 vs G1+G3

77.89DF*1P=.0001

C2*.3705

TOTAL4

86.36 !DF=2 P=.0001

Cm*.3872

♦Maximium C Value .707 .707 707 < C < .816

O

103respondents are involved in the computation, this analysis results in a 2 x 3 contingency table or matrix with DF = 2.

The total chi square can be partitioned intosingle degrees of freedom according to Lancaster.^ The2 2 x ’s derived by partitioning the total x^ are indicated

in Table III under columns headed vs and2 2^2 vs ^1 + ^3* c°lumns are subtitled x-j and x^,

respectively. In effect, Group I responses were compared against Group III responses and Group II responses were compared against the summed responses of Group I and Group III. This analysis resulted in two, 2 x 2 matrices each with DF = 1. This specific type of par­titioning is referred to as complete, orthogonal, inde-

2 2pendent and additive. Therefore, the sum of x-j- and x-2should equal x^. The Results section of Table III

2 2indicates the value of x-j and x^ to be 3.53 and 77.39respectively. The sum of these values is 36.42. However,

2 2 the computed xrp is 36.36. Therefore, the sum of x^ and2 2 x»y exceeds the computed x r by .06. This difference is

due to the absence of a correction for continuity sub­routine in the computer program used to analyze the

2 ^H. 0. Lancaster, "The Derivation and Partitionof x in Certain Discrete Distributions," Biometrike, Vol. 36, 1949, pp. 117-29.

109Odata. The correction is necessary when computing x

2 2with one degree of freedom. Both xy and x- was computedwith DF = 1. Therefore, in these computations thecorrection should have been used but wasn't. The

2correction always decreases x because the absolute value of the difference between observed and expected cell frequencies is decreased by .5 before squaring. Because the correction factor is small, in this case .06, the decision based on the results is not altered by inclusion of the error. Therefore, no attempt is made to allow for the correction for continuity in the discussion of results. This holds true for all subse­quent discussion.

Hypothesis is designed to test the signifi­cance of the relationship between applicant selected and the type of information received by the decision-maker. The xy of 36.36 suggests a high degree of interaction between the independent variables, information received, and the dependent variables, applicant selected. In fact the P value indicates a xy of 36.36 could only be attributed to chance in 1 in 10,000 computations. There­fore, Hypothesis H- can be rejected with little risk of incurring a Type I, level of significance, error. Therejection of the Hypothesis H- is corroborated by the

2 2values of xy and x y These are the orthogonal, theo-2 2retically additive partitions of Xy. The Xy value of

110p

8.53 and x^ value of 77-89 suggests a firm basis for the rejection of Hypothesis H- . It is noted, however, that the interaction between Group I and III indepen­dent variables and Question #1 is not as significant as the interaction between Group II and the combined frequencies of Group I and III and Question #1. How- ever, the applicable values of x and P are sufficient to reject Hypothesis H^ emphatically in total and in partition.

In research a significance level of .01 isoften used. Therefore, accepting a risk factor of .01,

2the computed x s indicate the hypotheses can be safely2rejected with margin to spare. In all three x s, the

risks involved are less than .01.As stated previously, the assessment of the

significance of C values is a subjective matter. How­ever, some guidance as to the significance of C can be obtained by comparing the computed C to the limit of C for a particular matrix size. Maximum obtainable values for G^ vs G^ and G2 vs G- + G^ computations is .707. The maximum C computed for all Groups vs Question #1 is between .707 and .316, Therefore, the computed C's of .1545 and .3705 should be compared against a maximum of .707 and the .3$72 should be compared against a maximum of .707 C .$16.

IllTherefore C's computed for Table I can be

interpreted as follows: The total C of .3872 and theG2 vs G- + G^ of .3705 indicates a significant inter­action between information received and decision made.That is, Group II respondents varied their decisions in response to receipt of human resource information which indicated a correct selection to be Applicant B.This is borne out from the percentages from Table 1C and Appendix C. The percentages indicate Group I respondents did not make the correct selection as often as Group II respondents (i.e., 64.3% Group I vs 86.6%Group II). Further Group III respondents split their responses between Applicant A and Applicant B almost evenly (i.e., Applicant A 46.7% and Applicant B 49.1%).It can be considered on the basis of the C computed for G2 v s G-j_ + G2 and total C that there is a strong relation­ship between information received and decision made.This is because the decision varied significantly in consonance with the variation in information provided between groups.

This significant relationship is not indicated in the C of .1545 computed for G- vs G^. This is because the variation in selection was not as pronounced in Group I as in Group II and Group III responses were almost evenly divided indicating almost no variation. There­fore, the comparatively low C of .1545 buttresses the

112argument for rejection of Hypothesis H- . All of the statistical evidence taken together indicates Hypothesis H^ can be emphatically rejected. Alluding to the hypo­thetical situations posited in earlier discussion in this chapter, on the basis of Hypothesis H^'s rejection, the following is concluded: Group II respondents didunderstand the terminology used in providing human resource information. Further, they did not ignore the information but utilized it very effectively. Group III respondents were not overwhelmed by the amount and opposite indications of the information provided. In fact, the almost even division of responses is indi­cative of the ability of all respondents to absorb and utilize equally human resource and conventional employ­ment information. This conclusion rests on the fact that the Group III respondents were confronted with two sets of data indicating two different correct selections. Since favorable information was evenly divided between Applicant A and Applicant B when the two sets of infor­mation provided is combined, the even division of responses is indicative of effective use of the infor­mation provided.

Included in the first group of hypotheses are those to be tested utilizing variation in information type and variation in importance attached by respondent to information items. Hypothesis H| was rejected on the

113basis of the decisive interaction discovered between applicant selection and type of information provided. Hypotheses H2> and are considered jointly as they all utilize the variation in importance assigned by respondents to information items as the independent variable. Statistical summaries of importance ratings by variable by group appear in Tables IIC, IIIC,IVC-1 and IVC-2 of Appendix C.

The hypotheses remaining to be considered from the first group of hypotheses stated in null form are as follows:

H2 There are no significant differences indecision output resulting from variation in relative importance attached by respondents to conventional and human resource information (Set III information).

Ho There are no significant differences indecision output resulting from variation in relative importance attached by respondents to conventional information in different environments (Set I and Set III information).

H, There are no significant differences in ^ decision output resulting from variations

in relative importance attached to human resource accounting information presented in different environments (Set II and Set III information).The purpose in testing these hypotheses is to

examine the causal relationship between the importance assigned to an item of information used in the decision process of the respondents and the validity of the decision made. Validity in this instance refers to

114

degree of adherence of the decision outcome (i.e., applicant selected) to the correct selection for a given set of information. The correct decision for Group I respondents is to select Applicant A, for Group II respondents Applicant B, and an equal division of selections between Applicant A and B for Group III respondents. The degree of correctness of responses taken by groups is indicative of the message power of conventional and human resource. An equal distribution of Group III responses between Applicant A and Applicant B is indicative of co-equal message power of the two types of information items.

In terms of importance to the study Hypotheses H2> and are ranked second to the primal importance of Hypothesis H- . This ranking follows from the propo­sition that it is first necessary to determine if the information provided by human resource accounting is useful in the personnel selection process. Rejection of Hypothesis H- , assured the actual usefulness of human resource information. Secondly, it is essential to assess the message power of human resource information items. That is, the degree to which the individual information items can transmit information must be determined.

Acceptance or rejection of Hypothesis H2 must rest on data generated by respondent of Group #3 only.

115This is because only Group #3 respondents received both human resource and conventional employment information.

The fact that the two different sets of infor­mation items are utilized as variables in Group III questionnaires introduces a statistical problem. The problem is further complicated by the fact that each set contains 14 items. The solution to the problem lies in the computation of two different sets of chi square (x ) and contingency coefficients (C) one for each set of variables. Since each set contains four different information items, chi squares and C's arecomputed in total and in partition for each item. The

2partitioned x and C are computed for the sum of notapplicable and below average importance ratings vs the

2sum of average and above-average ratings. The two x and C's for each of the four items of the two sets of data (i.e., K1 - K14 and LI - L14) results in the reporting of 56 x 's and C's pertaining to Hypothesis

The observed frequencies and the results of thestatistical procedures applied to the data appear inTable IV on the next four pages.

2Although x 's are* not additive when computed from different variables in a strict statistical con­text, it is interesting to observe the following. The total of all xjr computed for human resource variable

TABLE IV EXPERIMENTAL RESULTS

PERTAINING TO HYPOTHESIS H2 (IMPORTANCE RATING SCALE, GROUP III vs Q 1)

CONVENTIONAL ITEMS (K1-K14) HUMAN RESOURCE ITEMS (L1-L14)FREQUENCIES RESULTS FREQUENCIES RESULTSAPP APP APP APP

A B TOT 1+2vs3+4 TOT A B TOT 1+2vs3+4 TOT

K1 i LI *1 T 4*1 16 18 34 1.30 5.59 16 10 26 .02 2.69**2 25 33 58 DF=3 DF*3 21 29 50 DF»1 DF»3*#**5 29 30 59 Pa.252 P®.132 30 34 64 Pa.862 Pa.443*♦**4 JL

7718?

8159

C^.090 Ct*.185 1077 14

83 iio c^.010 CTa.l28

K2 t L21 3 3 6 1.16 4.72 12 4 16 4.71 7.662 10 6 16 DF«1 DF»3 22 19 41 BF»1 DF®33 54 92 P*.281 P*.192 31 38 64 Pa.028 P=.0534 26 12 C,«.085 cT».170 l£ 21 c,=.169 C m® • 214

77 82 159 JL 77 83 160 X 1

K3 * L31 13 22 9.63 12.23 10 1 11 5.5 4 10.382 15 28 43 DF*1 DF«3 19 16 35 DF®1 DF®33 28 24 52 Pa.002 Pa,007 30 37 67 Pa.017 Pa.0164 21 8 -22 C,a.239 c«*.267 11 11 46 C,a.l83 CT«.247

77 82 159 X 77 82 159 X A

HHOn

TABLE IV(continued)

K 6

CONVENTIONAL ITEMS (K1-K14) FREQUENCIES RESULTS

APP APPA B TOT l+2vs3+4

4

L41 31 34 65 1.292 22 29 51 DF»33 22 16 38 P®.2554 2 C.a.090

77 82 159 1

K5 * L5

TOT

2.09 DF=3

P®.557 Ct«.113

2.72DF®3

P®.439Ct=.130

3.27 DF®3 P®.352

CT=.142

K7 i L71 5 1 6 1,22 3.482 17 16 33 DF=1 DF®3

44 49 93 P®.268 P®.32311 U _2£ C.a.087 CTa.l4777 tl 15§ 1 T

1 2 0 2 1.412 8 6 14 DF=13 46 53 99 P®.2334 21 22 44 C,a.093

77 82 159 1

L61 2 0 2 1.762 11 8 19 DF=13 32 40 72 Pa.1814 32 34 66 C^a,104

77 82 159 X

HUMAN RESOURCE ITEMS (L1-L14) FREQUENCIES RESULTSkpp APPA B TOT 1+2V83+4 TOT

*1 xT

15 14 29 .94 1.2528 26 54 DFal DF®330 36 66 P®.335 P®.745477 JL

83 iJoc^.076 CTa.088

12 13 25 .41 .5024 30 54 DF»1 DF®336 35 71 P®.530 Pa.917JL 10 C.=.050 Cm®.05577 83 Ifo X i

13 12 25 .44 1.3321 29 50 DFal DF«333 34 67 Pa.514 P®.7251077

Jl83 lio

C^.052 CTa.090

12 14 26 .34 1.7817 21 38 DF®1 DF®339 34 73 Pa.568 P®.623Jl77 it

23160

Cl®.046 CTa.l05

117

TABLE IV(continued)

K8 i

K9 »

K10

Kll

CONVENTIONAL ITEMS (K1-K14) FREQUENCIES RESULTS

APP APPA B TOT 1+2vs3+4 TOT

2 2*1

L81 3 4 7 .11 7.042 8 6 14 DF**1 DF=33 33 20 53 P=.739 Ps=.0694 21 50 -S3 C,=,026 Cm=.207

77 80 157 X

L91 5 1 6 3.04 3.072 - - - DF*1 DF=23 16 19 35 P=.077 P*.2134 16 62 118 C., = .137 Cm=.137

77 82 159 1

LIO1 3 1 4 1.23 1.462 3 2 5 DF=1 DF=33 29 33 62 P=.267 P*.6954 42 45 87 C^.088 Ct=.095Lll1 4 1 5 2.06 2.212 20 20 40 DF*1 DF=23 - - - P*. 147 Ps.,3324 21 61 114 C,=.113 Cm*.117

77 52 159 X i.

HUMAN RESOURCE ITEMS (L1-L14) FREQUENCIES RESULTS

APP APPA B TOT 1+2vs3+4 TOT

2 2*1 *T

4 3 7 .18 .296 6 12 DF**1 DF=328 30 58 Ps.678 P=.9572177

4483 ifo C^.040 CT=.04l

4 4 8 4.28 8.9413 cJ 18 DF*1 DF*337 37 74 P*.036 P*s.03016 21 C,*.168 CT*.23870 79 159 X 1

5 3 8 0.00 14.6014 4 18 DF-l DF*342 48 90 P*.917 P*,0029 27 36 C^.000 cT=.296

6 3 9 2.57 8.9317 14 31 DF*1 DF®338 37 75 P*.105 P*.03070

26So -35150

C^.130 Ct*.237

TABLE IV(continued)

CONVENTIONAL ITEMS (K1-K14) FREQUENCIES RESULTS

APP APPA B TOT 1+2v s 3+4 TOT2 2

*1K12 i L121 - - - .02 .652 11 11 22 DF-1 DFa2

3 48 55 103 Pc.86? Pa.7284 18 15 33 Cje.010 CTa.063

K13 * LI31 6 3 9 4.91 6.292 21 13 34 DF=1 DFa33 40 47 87 Pa.025 P=.0974 9 18 27 C^.173 CTa.l96

K14 « L141 20 10 30 1.46 6.15- 2 24 29 53 DF=1 DF=33 26 29 55 P=.224 Pa.103k 14 21 Cis.095 Ct=.193

77 82 159 A A

Important Rating Scale* Does not apply** Below Average

*** Average**** Above Average

HUMAN RESOURCE ITEMS (L1-L14)FREQUENCIES tf>P APP

RESULTSA B TOT 1+2vs3+4

*1TOTx§

13 7 20 .28 2.9619 25 44 DF«1 DF=337 43 80 Pa.606 Pa,4006 8 14 C^.041 CTa.l66

11 4 15 1.71 5.3320 22 42 DFal DF«332 37 69 P=.187 Pa.14712 20 32 Cja.103 Ct-.181

14 5 19 4.11 13.1010 10 20 DFal DFa339 36 75 P*.040 P=.0051275

3Z83

44158

Cja.160 CTa.277

h-i-

120

(L variables) is 79.74 for an average of 5.64. This is2in contrast to the x r computed for conventional items

(K variables) of 60.97 for an average of 4.35. On the basis of these observations it can be concluded that the degree of interaction between the importance attached to the human resource items and the applicant selected is greater than the interaction between con­ventional information items and applicant selected.That is, there is a stronger causal relationship between human resource information items and correct application selection than between conventional information items and correct applicant selection.

These conclusions are confirmed when the Cvalues of the two sets of information are considered.

2The caveat issued in respect to the additivity of x also applies to C. However, the total C for all L variables is 2.363 for an average of .169. These values are to be compared against a total C value of 2.163 and an average of .154 for K variables.

Bearing in mind the ordinal level measurement of2x and C, it can be inferred that the causal relation­

ship between L variables (i.e., human resource items) and applicant selection is stronger than the causalrelationship between K variables (conventional items)

2and applicant selection. However, since x and C use ordinal level measurements and not interval or ratio

121level measurements it cannot be inferred that the relationship of human resource items and applicant selected is 3&/° stronger (i.e., 5.64-435/435) than the relationship between conventional items and appli­cant selected.

In addition to determining the overall useful­ness of human resource accounting information, a con­comitant purpose of this research is to determine those specific items of human resource information that can be most effectively utilized in the personnel selection process•

pIn fidelity to the ordinal level of x and Cmeasurements the relative strengths of the causal

2relationships as demonstrated by computed Xtjt and C's are ranked in descending order for Group III in Figure III on the next page.

The ranking in Figure III indicates variables L-10, L-14> L-3, L—9, L-ll and L-2 possess a significant relationship to decision-making when considered in the augmented information environment of Group III. It will be recalled that in Group III questionnaires the con­ventional information input (K variables) was augmented by human resource information items (L variables). In terms of strength of causal relationships established, the results indicate the information provided by the Stochastic Model possesses a high degree of relevance to

O'. y/\

t?9 FIGURE III

AND RANKED IN DESCENDING 1 ORDER FOR GROUP III

SANK

8

' 1< AJk. i1314

X1Arp CT VARIABLE INFORMATION ITEM14.60 .296 L10 Probability of Promotion13.10 .277 L14 Value of additional employee10.38 .247 L3 Cost of Lost Production8.94 .238 L9 Probability of Promotion8.93 .237 Lll Probability of Promotion7.66 .214 L2 Training Cost5.33 .181 LI 3 Value in 2nd most

Productive Capacity2.96 .166 LI 2 Present value of

in-company training cost2.69 .128 LI Recruiting Cost1.78 .105 L7 Present value of Employee

Replacement1.33 .090 L6 Present value of Salary1.25 .088 L4 Separation Cost.50 .055 L5 Present Value of Fringe

Benefits.29 .041 L8 Employees time with company

DRAWN FROMStochastic Model Stochastic Model Replacement Cost Model Stochastic Model Stochastic Model Replacement Cost Model Opportunity Cost

Replacement Cost Model

Generalized Model Replacement Cost Model

Discounted Earnings Replacement Cost Model Discounted Earnings

Stochastic Model

122

123decision-making in personnel selection. Second in importance, the Replacement Cost model seems to provide the most useful information. Therefore, this ranking indicates a direction for human resource accounting research. On this basis research should be directed toward developing the Stochastic Model shown at Figure V, Appendix B. Secondly, research should be directed toward validating the Replacement Cost model shown in Figure II, Appendix B.

2The results of the partition Xy and C computedfor each variable of the two sets tend to confirm the

2finding related in respect to Xijr and total C,p. In2effect the computation of x-j- and C- involved summing of

not applicable and below average responses and thesumming of average and above average responses. Since

2 2 the xy and C- thus computed monitored the x^ and C,p foreach variable, further elaboration is unnecessary.

On the basis of the statistical evidence here­tofore presented, cognizant of the difficulty posed by the treatment of two sets of variables, Hypothesis H£is rejected. This rejection is made on the basis of

2the average and overall difference in x^ and C's com­puted from Group III data for K (conventional) and L (human resource) variables. This rejection is not in accord with normally accepted statistical hypothesis testing; therefore, the inferences drawn from this

124hypothesis are severely limited. However, it can be inferred there does not exist a definite causal relationship between the importance attached to an information item pertaining to an applicant and the selection of an applicant for employment. Further, it is inferred that the causal relationship is stronger when considering human resource information items than when conventional items are considered.

The purpose of testing Hypotheses H^ and H^ is to demonstrate the effect of variation in the mode of presentation on importance rating and applicant selected. The mode of presentation is varied as the environment of presentation is varied for K variables between Set I and Set III questionnaires. Set I questionnaires contained only conventional items whereas Set III questionnaires contained both K vari­ables and L variables. That is, Set III questionnaires contained a combination of convention and human resource items. In this fashion the environment and mode of presentation is varied. Likewise, Set II questionnaires contained only human resource items (L variables) while Set III contained both K and L variables.

To demonstrate the effect on importance attached by respondents to conventional and human resource items in varied invironments and the effect on the applicant selected, Figures IV and V are presented on the next two pages.

125FIGURE IV

COMPOSITE IMPORTANCE RATING OF CONVENTIONAL EMPOLOYMENT INFORMATION ITEMS

BY GROUP I AND GROUP III RESPONDENTS

K1K2K3YLk

K5

INFORMATION ITEMSi+->s>>art

Time lived at current residence

IMPORTANCE

Minimum wage acceptable Height/Weight Number of dependents Years of education completed

K6 Major Study K? Grade average (A=4)

K8 Machine or equipment Skills

Work experiencei (Most recent) K9 PositionK10 Time in positionKll Duties KI2 PayK13 Score on validated Personnel

Test (Normal Range 90 - 110)K14 Estimates by applicant of

their annual salary ten years from now.

GROUP I Responses

- - - GROUP III Responses

126

LIL2

L3iA

L5

L6

L7

L8

L9 LIO Lll LI 3

Llk

FIGURE VCOMPOSITE IMPORTANCE RATING OF HUMAN RESOURCE INFORMATION ITEMS

BY GROUP II AND GROUP III RESPONDENTS

II#ORMA®20rr, ITEMS i IMPORTANCE

Recruiting costTraining cost (Salary during training and trainers salary)Cost of loss production during trainingSeparation cost (Separation pay* accrued vacation* vested retirement)Present value of fringe benefitsPresent value of salary for total period of employmentPresent value of cost of replacing current applicant when terminatedTime employee will remain with companyProbability of number of pro­motions with salary increases

At least oneAt least twoAt least three

Present value of cost of in­company development trainingTheoretical value of employee to company if employed in 2nd most productive capacityTheoretical increase in profit by adding one additional employee of equal productivity

+»w

i i

» !ObH CO 0) >

127The composite Importance Rating is a weighted

average of the responses for each variable by all respondents for the group indicated. The composite rating is shown for conventional items, Group I and Group III, in Figure IV. Figure V details the compos­ite rating of human resource items Group II and Group III.

Figure IV reveals a relatively similar importance rating assigned by respondents of the two groups with the exception of variable K-6 and K-7- Group III respondents considered these variables relatively more important than did Group I respondents. It is interest­ing to note that ratings by Group I and III for variables K-9 and K-10 actually coincide.

The importance ratings of Figure V reveal little variation except in the case of variables L-6 and L-9.In both instances Group II respondents considered these variables more important than did Group III respondents. This is attributed to the esoteric nature of the vari­ables. Since Group III respondents have twice the number of variables to consider the importance of each variable was diluted. Therefore, if the respondent was unfamiliar with the concept or terminology of an infor­mation item, the variable could safely be assigned a low importance rating. The multitude of other variables were sufficient to provide decision information. Again,

128as in Figure IV, the ratings accorded L-12 and L-13 by- respondents of Group II and III actually coincide.

The results of statistical test applied to data generated pertaining to Hypotheses and is presented in Tables V and VI respectively. These tables are presented on the following eight pages.

The purpose of testing Hypothesis H^ is to demonstrate the relationship, if any, between the environment in which information items are presented, the importance attached to conventional employment items, and the decision made. In effect the variation in environment results from the fact that Group I respondents received only conventional information items while Group III respondents received both human resource and conventional items. Therefore, if there is a variation in the strength of the causal relationship between Group I and Group III, then it can be asserted that a significant difference in decision output did occur. Hence, the Hypothesis H^ can be rejected.

The decision rule for Hypothesis H^ acceptance/rejection is troublesome to employ because of the myriadx fs computed for the purpose. Table V contains 56 sets

oof x 's and C's. Bearing in mind the non-additivity of2 2 x and C, the total and average of x 's and C's is pre­

sented by group for informational purposes only. It is presented for informational purposes, because the

TABLE yEXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS H3

(IMPORTANCE RATING OF CONVENTIONAL EMPLOYMENT ITEMS, Kl-Kl4vsQl)

GROUP I GROUP III

APP APPA B

Kl*1 31 18**z 26 19***3 50 25

n §K21 k 22 8 13 67 384 -31 Z1

117 62K31 17 102 21 263 46 224

i 86

34

FREQUENCIES TOT

RESULTS

49457512

181

69

105_52179

274768

—38180

1+2vs3+44

1.01DF=1

P=.3l6C^.074

1.55 DF=1 P*.211

Cn=.092 Cm*

9.40DF=1

FREQUENCIES APP APP

RESULTSTOT A B TOT 1+2vs3+4 TOT*T xj x|

1.63 16 18 34 1.30 5.59DF=3 25 33 58 DFal DF»3

P=.657 29 30 59 Pa,252 Pa.132!t=.094 J I 1 8 C,a.090 CTa.i84

77 82 159 X

2.34 3 3 6 1.16 4.72DF=3 10 6 16 DF«1 DF=3Pa,508 38 54 92 P®.281 Pa.192

114 2k 1 2 - 4 5 C,».085 Cfn* . 1701 77 82 159 X 1

14.82 13 22 35 9.63 12.23DF*3 15 28 43 DFal DF«3'a. 002 28 24 52 P=.002 Pa.007,= .276 21 8 _22 C,a,239 Cm*.267

77 82 159 X X 129

TABLE V(continued)

GROUP IFREQUENCIES RESULTS

APP APPA B TOT 1+2V63+4

A

TOTx §

K41 39 31 70 1.42 4,022 31 14 45 DF*1 DF»33 42 17 59 P=.231 P=.2584

n t i— 2181

C^s.088 Ct=.14?

K51 3 1 4 .17 3.892 12 6 18 DF=1 DF®33 51 38 89 P=.686 P=.2724 -51117

2035 1S 2 C^.030 Ct=*.145

K61 5 1 6 .16 1.312 8 5 13 DF=1 DF»33 50 31 81 P*.693 P*.7314 _54

1172855 i f f C^.028 CT*,084

K71 1 2 3 .77 9.562 21 7 28 DF=1 DF*33 67 50 117 P*.385 P*.0234

i f ?6

*5-21181 Cj-,065 Ct*.224

GROUP IIIFREQUENCIES RESULTS

APP APPA B TOT 1+2vs 3+4 TOT

*1 x§

31 34 65 1.29 2.0922 29 51 DF*1 DF=322 16 38 P*.255 P*.J57-1 Jk __S C1».089 CT*.ll477 82 159

2 2 1.41 2.728 6 14 DF*1 DF=346 53 99 P*.233 pa,440

21 n Jfc4 C^.093 CT».13077 82 159

2 « 2 1.76 3.2711 8 19 DF*1 DF»332 40 72 P*.181 P*.35221 £ 66 C,«,104 Cm*.14277 82 159 X 1

5 1 6 1.22 3.4817 16 33 DF=1 DF®344 49 93 pa.268 P*.323U ii J £6 C,a.087 CT*.14777 81 158 X 1

130

TABLE V(continued)

GROUP IFREQUENCIES RESULTS

APP APP A B TOT 1+2vs3+4 TOT

2 2*1 *T

1 3 4 1.8916 2 18 DF=151 18 69 P=.l6548

11542*5 i S

C^.101

14.88 DF=3

P®,002 Ct*.275

2 - 2 4 2 6

28 15 4382 48 130115 £5 181

.43 1.22DF=1 DF«3

P=.518 P=.753 C1*=.048 CT*.08l

3 - 3 .05 5.497 5 12 DFal DF*337 30 67 Pa.811 P-.137

iff S -22181C^a.014 Ct».171

2 0 2 .17 4.073 2 5 DF«1 DF=318 17 35 Pa.682 P®.253

GROUP IIIFREQUENCIES RESULTS

APP APPA B TOT 1+2vs3+4 TOT

3 4 7 .11 7.048 6 14 DF=1 DF=333 20 53 P=.739 Pa.07021 10 _82 C,a.026 Cm®,20777 80 157 X X

5 1 6 3.04 3.07- - - DFal DF®216 19 35 P*.077 Pa.21356 62 118 Cis.137 Cm®.13777 82 159 X 1

3 1 4 1.23 1.463 2 5 DF«1 DF®3

29 33 62 P=.267 Pa.69542 HI _82 C.a.088 CTa.09577 81 158 X Jl

4 1 5 2.06 2.21- - - DFal DF®220 20 40 Pa.147 F®.33311 61 114 C -1 a , 113 Cm®.11777 82 159 X

131

TABLE V(continued)

K121234

K13123

Kl41234

APPA

GROUP I FREQUENCIES RESULTS

21270

_ 2 i115

31776^20

153953

Ilf

APPB

07

*5

264116*5

9202410

TOT

21?44 114

14 4jI§0

523

117i l l

245977

*3 179Important Rating Scale

* Does not apply ** Below Average

*** Average **** Above average

1+2v s 3+4 TOT4

*2

.08 1.93DF*1 DF=*3P-.770 P-.591^=.020 CT=.103

.78 2.18DF*1 DF=3

P=.383 P=.540x=.065 CT*.109

.00 3.18DF=1 DF»3

P=.903 P«.365C,=.000 Cma.132

GROUP III FREQUENCIES RESULTS

APP APP A B TOT l+2vs3+4 TOT

- - - .02 .6411 11 22 DF*1 DFs*248 55 103 P».867 P*.72818 11 -12 C,=.010 CT=.06377 81 158 1

6 3 9 4.91 6.2921 13 34 DF*1 DF®340 47 87 P*.025 P*.0977§

1881 -22

157C^.173 Ct=.196

20 10 30 1.46 6.1524 29 53 DF*1 DF=326 29 55 P».224 P«.103_Z 14 -21 C,«.095 Ct*.19377 82 159 X X

132

LI*1*2*3*4

L21234

L3123

TABLE VIEXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS

(IMPORTANCE RATING OF HUMAN RESOURCE ITEMS, Ll-Ll4vsQl)

GROUP IIFREQUENCIES

APP APP A B TOT 1+2vs3+4

*1

RESULTSTOT

GROUP IIIFREQUENCIES

APPA

APPB

RESULTSTOT 1+2vs3+4 TOT

X T

582

__218

323641

37444312 15

121 139

1.65DF=1

P*.195C^, 108

4.37 DF=*3 Pa,223

Ct«.175

1621301077

10 26 29 5034 64iO _2& 83 160

.02 DFal

P».862 3,«.010

2.69 DF*3

Pa.443 ^*.128

357

_i18

102857

133364

26 29121 139

1.20 DFal

P=.272 C^.092

1.73DF*3

P=.635c t=.iio

1222311277

4 1619 4138 69

4.71DFal Pa.028

C.=.169

7.66 DF=3

Pa.053 Ct=.214

246

71846

92252

1.40 DFal

Pa.2341.51 DF=3

Pa.685101930

11637

113567

5.54 DFal

Pa.01810.38 DF«3

pa.016

TABLE VI(continued)

GROUP IIFREQUENCIES RESULTS

APP APPA B TOT 1+2v s 3+4 TOT

2 2Xy x|

L41 2 22 34 .322 8 43 51 DFal3 5 37 42 P*.5?94

I?8

12011

I3I 0 H1 1 • O 00

L51 1 21 22 2.812 3 31 34 DFal3 10 49 59 Pa.0904 4

1820

12124

139C *.140

L61 1 7 8 .022 4 24 28 DFal3 7 59 66 P*.8504 6

18 -22119 -32137C^.010

L71 4 20 24 .442 4 24 28 DFal3 5 46 51 P*.5164 -3L121

-J6139

C^.057

3.86DF=3

P=.276CT«.l65

3.02 DF*3

P*.389 Ct*.1^6

.90 DF=3 P».828

Ct«.081

.81 DF*3 Pa.847

GROUP IIIFREQUENCIES RESULTS

APP APPA B TOT l+2vs3+4 TOT

2 2xy xy

15 14 29 .94 1.2528 26 54 DF*1 DF*330 36 66 P=» 335 P*.745477 si 160 C^a.076 Cj*. 088

12 13 25 .41 .5024 30 54 DF*1 DF*336 35 71 P*.530 Pa.917— 577

-583C^.050 V ’055

13 12 25 .44 1.3321 29 2° DFal DF*333 34 67 P*.514 Pa.72510 8 18 c,».052 C^a.09077 S3 ISO 1

12 14 26 .34 1.7817 21 38 DF*1 DF*339 34 73 P*.568 P*.623_277 lit83 ifo

C^*,046 CTa.l05

134

TABLE VI(continued)

GROUP IIFREQUENCIES

APP APPA B TOT

2 4 64 18 222 36 3810 J&2 JL218 121 139

L91 1 4 52 5 20 253 6 37 43

lS 112 128LIO1 - 2 2 2 2 11 133 12 58 704 _3 41 46

17 H 4 131Lll1 2 7 92 2 20 223 8 38 464 6 49 55

RESULTS1+2vs3+4 TOT

2.24 4.77DF=1 DF=3

pa.131 Pa.187 C^.126 Ct=.182

2.02 3.00DF«l DF=3Pa.152 Pa,393

C^.124 Ct«.151

0.00 3.14DFal DF*3Pa.917 Pa.372

C^.000 CTa.l53

.02 1.85DFal DF=3pa.862 P=.609

C^.010 CTa.l87

GROUP IIIFREQUENCIES RESULTS

APP APPA B TOT 1+2vs3+4 TOT

x2 J,X1 *T

* 3 7 .18 .296 6 12 DP*1 DFa328 30 58 Pa.678 Pa.95722 & 83 C *.040 C.a.04177 83 Ho 1 1

4 4 8 4.28 8.9413 5 18 DF*1 DF*337 37 74 Pa.036 P«.03015 22 Jt2 Cj-,168 CTa.23870 79 149 1

5 3 8 9.22 14.6014 4 18 DF*1 DF«342 48 90 P*.003 Pa.002_2 _2Z Cj-,239 Ct*.29670 82 152

6 3 9 2.57 8.9317 14 31 DF*1 DF=338 37 75 Pa.105 Pa.0309 26 35 Cj-,130 Ct*.237

135

TABLE VI(continued)

GROUP IIFREQUENCIES

APP APPRESULTS

A B TOT 1+2vs3+44

TOT4

L121 1 13 14 .64 1.832 4 32 36 DF=*1 DF=33 12 61 73 Pa.429 P=.6134 1

T5 33$Cj®.068 Ct=.114

LI 31 3 15 18 .56 1.512 5 27 32 DF*1 DF*33 8 49 57 P*.459 P».6844 JL18

28119

_20137

C^.063 Ct=.104

L141 2 12 14 .11 .882 3 17 20 DF®1 DF*33 8 44 52 P=.737 P*.8324

18 J*Z120-52138

C^.028 CTa.079

rtant Rating Scale** Below Average

*** Average **** Above Average

GROUP IIIFREQUENCIES RESULTS

APP APPA B TOS l+2vs3+4 TOT

413 7 20 .28 2.9619 25 44 DF»1 DF=337 43 80 P».606 Pa.4006 8 JLk Cia.04l Cma•166

75 83 158 1

11 4 15 1.71 5.3320 22 42 DF*1 DF*332 37 69 pa.187 Pa.1471Z75 « l i

Oja.103 CT=.181

14 5 19 4.11 13.1010 10 20 DFal DF=339 36 75 Pa.040 Pa.00512 32 44 C,«=.l60 Cma.27775 83 158 X X

VjOOn

137specific data design for the test of Hypothesis pro-

2vides x 's and C's computed from comparable data ofGroup I and Group III. Therefore, direct comparisons

2can be made between x 's and C's for each K variable and acceptance or rejection can be based on this com­parison. By contrast, this direct comparison was impossible in considering Hypothesis H^ because the variables considered were K variables and L variables. (See Table IV)

Therefore, for informational purposes only, thetotal of x 's for Group III was 60.97 for an average of

24«35• In contrast Group I x 's summed to 70.52 and averaged to 5.05* On the average this information indicates a stronger causal relationship between Group I variables and correct selection than Group III vari­ables and decision. In contraposition to this indi­cation, Group I C values totaled 21.03 for an average of .150 while Group III C values totaled 21.62 for anaverage of .154» At a first approximation it appears

2that the x and C values contradict each other. How­ever, it will be recalled that the computation of C is

2made by using x and N, the total number of observations. Large N's tend to reduce C values. Therefore, the seem­ing contradictory results are explained in terms of the difference in the value of N. The N used in computing C's for Group I was 110 while the N used in computing C's for Group III was 159.

i3dThe acceptance or rejection of Hypothesis is

pconsidered to rest on the variation in x 's and C's computed for each K variable in Table V shows that notwo values are equal for Group I and Group III. The

2Group I Xjjr values for variables K-3, K-4, K-5, K-7,K-S, K-10, K-ll, and K-12 exceed the comparable values for Group III. For the remaining K variables Group III values exceed those of Group I.

2In a ranking by descending value of x^ Group I2Xjjr’s computed for K-S and K-3 occupy position one and

two respectively. In Group III the rank order is reversed with K-3 first followed by K-&. Under normal hypotheses acceptance/rejection procedure, sufficient causal relationship is demonstrated between information item importance and decision output for only three K variables at a .01 level of significance; and for only four K variables at a .05 level of significance. These variables include K-3, K-3 and K-7 of Group I and only K-3 of Group III.

Given the statistical evidence presented in Table V, the acceptance/rejection of Hypothesis H^ lends itself to a two tiered resultation. Firstly, the hypothesis can be rejected because there is a signifi­cant difference in decision output resulting fromvariation in importance rating. This significant

2difference is demonstrated by the variation in Xjp and

139C,p values between groups for comparable K variables.

oIn no case does the x^ or C,p coincide for a particularK variable for the two groups. Additionally, there isno significant coincidence of position in rank by

2descending value of xjjt and C,p by group. This fact is clearly demonstrated in Table V-l on the next page.The only two positions that do coincide between groups are #1 and #2 for C,p. Variable K-3 is first in both

pgroups and K-S is second. This is not true for x^.This difference in rank position is attributable todifferent values of N.

On the second tier of consideration, attention 2is directed to the x^ and C,p computed for Hypothesis

pH^. Of the 2$ xtjt's and C^'s computed, only four aresufficient to reject the hypothesis at a .05 level ofsignificance. Therefore, even though there is variationin decision output resulting from variation in importancerating, in a vast majority of K variables (i.e., 24 or2&) the causal relationship between the dependent andindependent variable is tenuous. The degree of tenuity

2is apparent in a review of the x?jr and C,p values of TableV-l. Therefore, Hypothesis H^ is rejected in general.The degree of rejection is circumscribed but the weakcausal relationship established for most K variables

2considered. Since the values of x-j- and C- , for each group shown on Table VI generally monitor the movement

TABLE V - l CHI SQUARES AND CONTINGENCY COEFFICIENTS

RANKED IN ORDER OF DESCENDING VALUE ( K VARIABLES BY GROUP)

GROUP IIft An is. XfVariable Value Variable ^ Value

1 K8 14.88 K3 .2762 K3 14.82 K8 .2753 K7 9.56 K7 .2244 Klo 5.49 K10 .1715 Kll 4.07 Kll .1486 K4 4.02 . K4 .1477 K5 3.89 K5 .1458 K14 3.18 K14 .1329 K2 2.3^ K2 .11410 K13 2.18 K13 .10911 K12 1.91 K12 .10312 kl I.63 Kl .09413 K6 1.31 K 6 .08414 K9 1.22 K9 .081

x§Variable

GROUPValue

IIICTVariable Value

K3 12.23 K3 .26?K8 7.04 K8 .207K13 6.29 K3 .196K14 6.15 K14 .193Kl 5.59 Kl .189K2 4.72 K2 .170K7 3.48 K7 .147K6 3.27 K6 .142K9 3.07 K9 .137K5 2.72 K5 .130K4 2.09 Kll .117Kll 2.06 K4 .114K10 1.46 K10 .095K12 .62 K12 .063

140

141pin the values of and CT for the same K variables,

further elaboration is unnecessary.The purpose of testing Hypothesis is compa­

rable to that of testing Hypothesis H^ with the exception that the variables considered are human resource infor­mation variables (L variables) instead of conventional employment information variables (K variables). The variation in environment results from the fact that Group II respondents received only human resource accounting information while Group III respondents received both human resource and conventional employ­ment information items.

As in consideration of Hypothesis H^, the rulefor rejection is complicated by the large number of 2x ' s and C's computed. Therefore, the format of

presentation and application of acceptance/rejectionrule applied for Hypothesis H^ will be utilized forHypothesis H^.

The total of xjp's for Group III, Table VI is79.74 with an average of 5.55. The total of xj 's forGroup II is 33.1^ with an average of 2.3$. This dif-

2ference is 3.17 in average x r is compared with a dif­ference of only .70 for Hypothesis H^.

The relatively low average x^ is attributable to the fact that the importance ratings reported by Group II respondents was. not significantly higher for

142any L variable considered than the ratings by Group III respondents. However, as pointed out previously, GroupII respondents exceeded Group I respondents in correctselection of applicant by 80.9i<> to 62.5$. This 1S.4$excess in the dependent variable juxtaposed with a

2weaker importance rating accounts for the low x^ of Group II.

The average C,p value of Group II is .130 for atotal of values of 18.21. The total of CT fs forGroup III is 23.63 with an average of .169. In this

2instance x f and C , vary in the same direction between groups. This is attributable to the approximate equality of. N's for both groups.

Given the statistical evidence presented in Table VI and following the decision rule put forth in the discussion of Hypothesis H^ the following inferences can be drawn. First, Hypothesis H^ can be rejected because there is a significant difference resulting from the variation in importance rating by Group II and GroupIII respondents of the L variable. This difference in

2decision output is shown by the variation in the xjjt andCrp’s computed from the frequencies of Table VI. Thatis to say, there is no constant, corresponding relation-

2ship resulting in computation of xjjr's and C^’s for any given L variable as shown in Table VI-1 on the next page.

TABLE VI -1 CHI SQUARES AND CONTINGENCY COEFFICIENTS

RANKED IN ORDER OF DESCENDING VALUE ( L VARIABLES BY GROUP)

GROUP IIRANK x| CT

Variable Value Variable Value1 L8 4.7? Lll .1872 LI 4.37 L8 .1823 L4 3.86 LI .1754 L10 3.14 L4 .1655 L5 3.02 L10 .1536 L9 3.00 L9 .1517 Lll 1.85 L5 .1468 L12 1.83 LI 2 .1149 L2 1.73 L2 .11010 L3 1.51 L3 .10411 LI 3 1.51 LI 3 .1641 2 1 6 .90 L6 .08113 Ll4 CD00• L14 .07914 L7 • 00 H

* L7 .0 76

2 GROUP IIICT

Variable Value Variable ValueL10 14.60 L10 .296L14 13.10 L14 .277L3 10.38 1*3 .249L9 8.94 L9 .238Lll 8.93 Lll .237L2 7.66 L2 .214LI 3 5.33 LI 3 .181L12 2.96 LI 2 .166LI 2.69 LI .128L7 1.78 L7 .105L6 1.33 L6 .090L4 1,25 L4 .088L5 .50 L5 .055L8 .29 L14 .041

H-P-V jO

144The table indicates a fairly strong causal

relationship between independent and dependent variablesfor the first six L variables ranked under Group III.These first six could be rejected with a .05 level ofsignificance. No such rejection could be made for any

2L variable of Group II. Rejection of x^ for variablepL-8, the highest xjjt, incurs a risk of .1$7 of chance

variation. Therefore, even though the hypotheses in general is rejected, the causal relationship as demon- strated by x^ and computed with L variables of Group II is shown to be very weak. Chi square and C,p com­puted from the L variables of Group III demonstrate a somewhat stronger relationship; yet, eight of the four­teen could not be rejected without incurring a high

2Type I risk. Since the values computed for x-j- and C-2in general reflect the changes that occur in Xijr and Crp,

further evaluation is unnecessary. The results of statistical techniques applied to data to test hypoth­eses of the first group reveals grounds for rejection of all of the hypotheses of the first group. However, due to difficulties heretofore discussed only Hypotheses H- can be emphatically rejected. Hypotheses H£, H^ and H, are rejected but with limitations previously set forth.

145Experimental Results of Second Group of Hypotheses

The hypotheses of the second group are con­sidered least important to the study as a whole. This consideration emanates from two observations. First, hypotheses of the second group rely upon data collected from respondents dealing with their background. In the model of the decision process, Figure I, Chapter III, these data are shown to be the background variables resulting from information previously acquired. As such, the independent variables considered in testing this group of hypotheses belong to the subjective com­ponent of the decision premise. Because of the time span over which this information has accumulated with the respondent, it is difficult to ascertain the definite relationship between the assumed deterministic impact of the information on the respondent's subjective criteria and his decision. Secondly, and following from the first reason, because of the infinite possibilities of combinations of information received by individual respondents, the cumulative effect of these combinations is impossible to assess. Therefore, to round out this research Hypotheses H^, H^, Hy and Hg are tested, but the test results are considered less important to the study as a whole.

The hypotheses of the second group states in the null form are as follows:

145Experimental Results of Second Group of Hypotheses

The hypotheses of the second group are con­sidered least important to the study as a whole. This consideration emanates from two observations. First, hypotheses of the second group rely upon data collected from respondents dealing with their background. In the model of the decision process, Figure I, Chapter III, these data are shown to be the background variables resulting from information previously acquired. As such, the independent variables considered in testing this group of hypotheses belong to the subjective com­ponent of the decision premise. Because of the time span over which this information has accumulated with the respondent, it is difficult to ascertain the definite relationship between the assumed deterministic impact of the information on the respondent's subjective criteria and his decision. Secondly, and following from the first reason, because of the infinite possibilities of combinations of information received by individual respondents, the cumulative effect of these combinations is impossible to assess. Therefore, to round out this research Hypotheses H^, H^, Hy and Hg are tested, but the test results are considered less important to the study as a whole.

The hypotheses of the second group states in the null form are as follows:

146Hr There are no significant differences in decision

output resulting from variations in managerial philosophies (autocratic, participative or free-rein) of respondents.There are no significant differences in decision output resulting from variation in levels of experience of respondents.

Hr, There are no significant differences in decision output resulting from variations in respondents' attitudes toward human assets.

Hg There are no significant relationships between decision output and variations in job environment and qualifications of respondent (size and type of company of respondent experience; level, field and recency of education) of respondent.

The data generated from Question #2 through Question #14 of the questionnaire appears in summary form in Appendix C, Tables V C through XVII C. The frequencies generated and the results of statistical techniques applied to the data appear in Tables VII through X on the following 1# pages.

Hypothesis H^ is tested to investigate the re­lationship between the variation in managerial philoso­phies of the respondents and the selection of applicant.A total Chi Square for all groups of 4.02 suggest some interaction between philosophy and decision made. How­ever, the N of 4&5 in the computation of Crp causes a value of .091 which indicates a weak causal relation­ship. Therefore, Hypothesis H^ cannot be rejected on

pthe basis of xjp and Crp for the total of all groups. In essence the study did not discover a causal relationship

TABLE VIIEXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS Hy

(MANAGERIAL PHILOSOPHY OF RESPONDENTS BY GROUPS« Q1v sQ4)

FREQUENCIESGROUP I

APP APPA B

*1 35 20**2 68 40

3 iii4Vi

GROUP II1 5 472 9 653 JL 11

19 123GROUP III

1 25 352 3 6 383 -12 -1578 83

TOTAL OF GROUPS1 65 1022 113 1383 -32 _30

215 270* Autocratic

** Participative*** Free-rein

RESULTS

lvs3 2 vs 3 TOTTOT55 *1 *2

1.51 1.82 1.86108 DF«1 DF*1 DF«2

P*.217 P*».173 P-.3960 2182

C1».141 C2».119 CTa.lOO

52 4.57 3.65 5.14DF=1 DF=1 DF=274 P*.031 P=.053 Pa.17516 C^.251 C2=.197 CT«.187XV

152

60 1.10 .01 1.77DF«1 DF=1 DF=274 Pa, 294 P».890 P=.41632

looC^.109 c2*.ooo CTa.l04

lvs3 2V83 TOT167 30.24 1.40 4.02251 DF«1 DF=1 DF=24 2 Ps.065 P».249 P*.110

C^.338 C2a.O66 GT=.091

147

TABLE VIII

EXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS(RESPONDENT LEVEL QlvsQ9»Q10)

Q9 (BUSINESS EXPERIENCE LEVEL OP RESPONDENT)

FREQUENCIES RESULTSGROUP I

APP APPA B TOT 1v b 3

*12vsl+3*2<2

TOTx§

*1 9 **2 20

***3 87Il6

118

2028

132180

3.26DF=*1

P*.067C^.145

.71DP«1

P=.405C2=».062

4.02 DF=2

P=.132 Ct=.148

GROUP II1 32 43 12

19

1922

_sa121

2226

_22140

.01 DF=1

P=.900 C^.000

.09 DF*1

P=.758 C2=.024

.09DF*2P*=.943

Ct*.024

GROUP III1 92 15

3 #

1419

8

2334

ill

1.34 DF=1

P*.246 C^.104

.37DF=*1P*.552

C2=.048

1.71DF*2P=.429Ct*.104

TABLE VIII(continued)

FREQUENCIESTOTAL OF GROUPS

APP APPA B TOT

1 21 44 652 39 49 883 121211 m

323476

* Less than five years** Six - nine years

*** More than ten years

RESULTS

lvs3 2vsl+3 TOT4 4

^.39 .00 5.It?DF=1 DF®1 DF«2

P*.037 P«.000 P«.051C1=.106 C2®.000 C “.106

149

TABLE VIII (continued)

Q10 (PERSONNEL MANAGEMENT EXPERIENCE LEVEL OF RESPONDENT)

FREQUENCIES RESULTSGROUP I

APP APPA B TOT lvs3 2vsl+3 TOT

4 X1X2 x§*1 53 42 95 6.09 .52 6.70

DF=1 DF*1 DF»2**2 27 12 39 P=.013 Pa.478 P«.034

C,=.200 C?*.053 Ct*.187••*3 -22119 8

X C 1

GROUF' II1 11 65 76 .01 .23 .24

DF*1 DF=1 DF=22 4 32 36 P=.890 Pe.636 Pa.882

C,=.000 Co*.040 Cq,a. 0403 4

19 - 2 1122 i f f

i c.

GROUF> III1 37 52 89 2.43 1.07 3.48

DF»1 DF**1 DFa22 18 14 32 p«.115 Pa.302 P*.173

c1a.!37 C,a.081 CTa.i473 21 16 - 2 2

C, X

l l 82 158

150

TABLE VIII(continued)

FREQUENCIESTOTAL OF GROUPS

APP APPA B

1 101 1592 49 583 _52215 270

* Less than five years** Six - nine Years

*** More than ten years

TOTTOT

26010?

RESULTS

lvs3 2vs1*3 TOTyi w£*1 *2 *T8.24 .18 6.91DF=1 DF=1 DF=2P®,004 P®. ?00 P=.027

C-L*.l46 C2=.06l Ct=.119

151

TABLE IXEXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS v RESPONDENTS ATTITUDES TOWARD HUMAN ASSETS BY GROUPS

(QlVSQll,Q12,Q13,Q W

Qll (NEED FOR MORE INFORMATION)FREQUENCIES

GROUP I GROUP II GROUP III TOTAL OF GROUPSYES NO TOT YES NO TOT YES NO TOT

APP A 109 8 117 17 1 18 70 6 76 196 15 211APP B TOTAL

62171

210

64181

112129

1112

123I4i i B -511 J31157

250446 1833

268479

Q13 (SKILL OF WORKERS ASSETS OF THE FIRM)GROUP I GROUP II GROUP III TOTAL OF GROUPS

YES NO TOT YES NO TOT YES NO TOTAPP A 114 2 116 19 - 19 76 1 77 209 3 212APP B TOTAL 179 ~~2

_6i181120139 _33

123142

82158 “l

82159

2674?6 ■i

270482

Q14 (SKILLS SAME AS PHYSICAL ASSETS)GROUP I GROUP II GROUP III TOTAL OF GROUPS

SAME DIFF TOT SAME DIFF TOT SAME DIFF TOTAPP A 20 91 111 4 15 19 17 57 74 41 163 204APP B TOTAL _1237

46137 174

2125

_26111 112136

1431

66123

80154

5293

208371

260464

152

TABLE IX(continued)

QllRESULTS

GROUP I GROUP II GROUP III 2 2 2

*1 *1 *11.09 .23 .18DF=1 DF®1 DF=1

P=.296 P=.636 P=.676C 1=.077 C 2=.040 C 3*.033

Q13

*f *1 *11.13 A7 1.07DF=1 DF=1 DF=1

P=.287 P“ .^99 P=.301C^.079 C1=.057 C^.081

Q14

*r *i *i1.93 .10 .71DF=1 DF=1 DF=1

P=.161 Ps.7^2 P=.402C^.104 Cx=. 026 C^.068

TOTAL OF GROUPS

.03DF*1P^.lOOcT».ooo

.10DF*1

P*.750Ct=.014

.00DF=1

P^.100CT«.000

153

TABLE IX(continued)

Q12 (TYPE OF INFORMATION DESIRED)FREQUENCIES

GROUP I GROUP II GROUP ill TOTAL OF GROl

QUAL QUAN BOTH TOT QUAL QUAN BOTH TOT QUAL QUAN BOTH TOT QUAL QUAN BOTH TOTAPP A 35 55 18 108 8 7 2 17 32 29 7 68 75 91 27 193APP B TOTAL n58 29

841028

62170 a

4855

1215

114131

28Zo 81118 i g

104179

115206 £ m

RESULTSGROUP I GROUP II GROUP III TOTAL

*!2 2

Xl x| X1 AIJI3vsl+2 TOT 3vsl+2 TOT 3vsl+2 TOT 3vsl+2 TOT

.01 .40 .00 .01 .53 1.81 .42 .32DF=1 DF=2 DF=1 DF=2 DF=1 DF=2 DF=1 DF=2P=.889 P=.820 P=.917 P=.988 P=.474 P=.4o6 P=.500 P=.600C-p.000 Ct=.048 C-^.000 cT=.ooo c1=.o6o CT=.lll C^.036 Ct=.026

■*7 ST

TABLE X

EXPERIMENTAL RESULTS PERTAINING TO HYPOTHESIS Hgc TYPE OF INDUSTRY, AND SIZE OF COMPANY|

LEVEL, FIELD, AND RECENCY OF EDUCATION OF RESPONDENT (QlvsQ2#Q3.Q5.Q6a»Q6b,Q7a,Q7b,Q8)

Q2 (TYPE OF INDUSTRY)FREQUENCIES

GROUP I

APP APPA B TOT A B TOT A B TOT A B TOT

GROUP II GROUP III TOTAL OF

APP APP APP APP APP APPTOT A B TOT A B TOT A B74 4 49 53 33 37 70 88 10956 10 36 46 20 23 43 67 7838 4 27 31 21 20 41 49 61

JLZ185-A19

11123

12152

478 83 ISl 2lf

24272

*1 51 23 74 b 49 53 33 37 70 88 109 197#*2 37 ly 56 10 36 46 20 23 43 67 78 145***3 24 14 38 4 27 31 21 20 41 49 61 110

*♦**4 7 10 17 1 11 12 4 3 7 12 24 36TOTAL 119 tE 185 19 123 1^2 78 83 I5l 216 272 $4lT

♦Service Industry ♦♦High Manufacturing

♦♦♦Heavy Manufacturing ♦♦♦♦Other

TABLE X(continued)

RESULTS

*1lvs2+3

.30 DF=1 P=.590 C.=.04l

GROUP I GROUP II GROUP IIIx—

2l+4vs2+3

.03DF=1P=.845C„=.010

*1XTOT4.75DF=3P=.190

Ct=.162

*1lvs2+3

2.98 DF=1 P=.081 c^.150

X2l+4vs2+3

3.35DF=1P=.064C2=.152

*2 *PJITOT4.60 DF=3 P=.202

Ct=.1?7

2 2 2 2*1 *2 X/ji X1

lvs2+3 l+4vs2+3 TOT.04 .01 .45 .48

DF=1 DF=1 DF=3 DF-lP=.819 Pa.886 P=.926 P=.510C^.014 c2=.ooo Ct=.052 C^.031

TOTAL OF GROUPS

*2.03 DF=1 pa.890 C2=.028

6.72 DF=3 P=.091

’m=.121

f—1 V_n On

TABLE X(continued)

Q3 (SIZE OF COMPANY)

FREQUENCIESGROUP I GROUP II GROUP III TOTAL OF GROUPS

APP APP APP APP APP APP APP APPA B TOT A B TOT A B TOT A B TOT*1 6 7 13 1 13 14 4 9 13 11 29 40**2 6 3 37 100 13 68 81 49 49 98 125 154 279#**3 42 15 57 3 33 36 19 21 40 64 69 133**»*4

TOTAL8

1192

19 12311

152 _2794

33 0 221720

272 589* 100 or less

** 100 to 999 *** 1000 to 5000

**** over 5000

Q5 (EDUCATIONAL ATTAINMENT)FREQUENCIES

GROUP I GROUP II GROUP III TOTAL OF GROUPSAPPA

APPB TOT

APPA

APPB TOT

APPA

APPB TOT

APPA

APPB TOT

*1**2***3TOTAL

460

0 5119

233%

693

i§£

1711

1943

_25121

45086

T5o

143#

3405282

483

T?o

6110100215

8116144255

142262444a4

* High school** Attended college and attained Bachelor's degree*** Attended college passed Bachelor's level

157

TABLE X(continued)

Q3 RESULTSGROUP I GROUP II GROUP III TOTAL OF GROUPS„2 2 2 2 2 2 2 2 2 2 2 2

1 2 X/p X1 x2 ’‘I X2 X1 Xg x^lvs2+3+4 1+2vs3+4 TOT lvs2+3+4 1+2vs3+4 TOT lvs2+3+4 1+2v s 3+4 TOT lvs2+3+4 l+2vs3+4 TOT

2.01 1.35 4.91 .52 .46 1.98 1.83 .12 2.74 5.08 1.14 1.69DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3P=.152 P=.250 P=.177 P=.477 P=.505 P=.581 P=.172 P=.780 P=.435 P=.024 P=.621 P=.680V . 1 0 3 C2=.085 Ct=.161 C-p.060 C2=.057 Ct=.036 C1=.105 C2=.027 Ct=.129 ci=.ioi C2=.077 Ct=.058

Q5

GROUP IX1 *§ x| *1

lvs2 2 VS 3 TOT lvs2.01 .00 .01 .36

DF=1 DF=1 DF=2 DF=1P=.880 P=.928 P=.983 P=.559

C^.010 c 2=.ooo cT=.ooo C1=.081

RESULTSGROUP II 2 2 2 GROUP III 2

*2 Xip XI XJ2 vs 3 TOT lvs2 2 vs 3.04 .50 1.10 .43DF=1 DF=2 DF=1 DF=1

P=.822 P=.782 P=.300 P=.522C2=.014 Ct=.060 C^.339 C2=.052

TOTAL OF GROUPS2 2 2 2x ;

TOT *1 Xg x^

1.35 .02 2.80 1.40DF=2 DF=1 DF=1 DF=2

P=.5l^ P=.925 P=.251 P=.500CT=.092 C^.017 C2=.06l C^.053

HUl03.

TABLE X(continued)

Q6a (MAJOR FIELD OF STUDY) FREQUENCIESGROUP I GROUP II GROUP III TOTAL OF GROUPS

APP APP APP APP APP APP APP APPA B TOT A B TOT A B TOT A B TOT

*1 14 9 23 2 23 25 14 15 2f 30 47 77**2 14 6 20 - 3 3 9 1 10 23 10 33***3 13 13 26 2 31 33 10 9 19 25 53 78

•***4TOTAL JZ1112 15

63106175

1117 I H

_Z4135 H 5580 ill

127205 m

27846<5

Q6b (MINOR FIELD OF STUDY)*1 27 13 ^0**2 10 2 12

***3 14 13 2?♦***4 40 21 61TOTAL 91 49 140

2 32 34 24 18 42 53 63 1161 7 8 3 7 10 14 16 304 20 24 10 14 24 28 47 75

iJ -3897 -45111243X E j a127 ill

86212

*1 Ail other**2 Engineering and Science

***3 Phychology and Education »***4 Accounting, Personnel Management-Ind„ Rel. and all other business

159

TABLE X(continued)

Q6a RESULTS

4Ivs2vs4.45DF=2

P=.801V-055

GROUP Ix—2

Ivs2vs31.91 DF=2

P=.388 C„=.164

X1TOT3.03 DF=3 P=.388cT=.i3o

XI1.90 DF=2

P=.380 C^.135

GROUP II4

Ivs2vs4 Ivs2vs3.31 DF=2

P=.855 C2=.071

xlTOT3.85 DF=3 P=.277 Ct=.166

4Ivs2vs47.73 DF=2

P=.021 C^.2 31

GROUP III4Ivs2vs35 >9 DF=2

P=.062 C2=.294

*2TTOT7.86 DF=3 P=.048

:t=.219

xiIvs2vs4

8.92 DF=2 P=.015 C^.15?

[■OTAL OF GROUPS 2 2

x2 XTIvs2vs3 TOT

1 3 . 88 29.09DF=2 DF=3P=.001 P=.001\=.082 Cm=. 242

Q6b

RESULTS

1.47 3.91 3 . 9 4 1.79 1 . 7 6 2 . 1 1 2 . 6 2 3.07 3.11 0 . 1 8 1.46 1 . 6 0DF=2 DF=2 DF=3 DF=2 DF=2 DF=3 DF=2 DF=2 DF=3 DF=2 DF=2 DF=3

P«=.484 P=.140 p= . 267 P=.411 P=.418 P=.554 P= . 269 P=.213 P=.376 P=.960 P= . 5 0 0 P=.650C ^ . 113 C2*.217 Ct=.165 C^.142 C2=.l6l Ct=.136 C^.157 C2=.197 Ct=.153 C^.007 C2=.08l Ct=.064

ONo

TABLE X(continued)

Q7a (COLLEGE CREDIT HOURS - ACCOUNTING)FREQUENCIES

GROUP I GROUP II GROUP III TOTAL OF GROUPSAPP APP APP APP APP APP APP APPA B TOT A B TOT A B TOT A B TOT

*1 23 17 40 1 28 29 18 16 34 42 61 103*»2 55 27 82 13 61 74 40 43 83 108 131 239***3 23 12 35 2 17 19 12 14 26 37 43 80«*•*£}.

TOTAL 15# 518

1^51

176

112 __Z1294

7*1

75 JTtf8

19512

25720

552

Q7b (COLLEGE CREDIT HOURS - PERSONNEL MANAGEMENT)*1 21 9 30 4 16 20 16 12 28 41 37 78**2 28 23 51 4 42 46 27 25 52 59 90 149***3 30 17 47 6 26 32 20 23 43 56 66 122

TOTAL 113 %Jt1175

4IS jn117 -22135

1275 1279 155 20S 258 m

* None** Less than 15 hrs.

*** Less than 30 hrs. **«« over 30 hrs.

161

TABLE X(continued)

RESULTSQ7a

GROUP I GROUP II GROUP III TOTAL OF GROUPS2 2 2 2 2 2 2 2 2 2 2 2XI *2 Xjp X1 X£ ’'l XT 2 XT1vs2+3+4 1+2vs3+4 TOT 1 vs 2+3+^- l+2vs3+4 TOT lvs2+3+ l+2vs3+^ TOT lvs2+3+4 1+2vs3+4 TOT.69 .16 3.^5 3.10 .08 3.77 .15 .Ok 2.18 .59 .Ok .77DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3

P=.*H0 P=. 687 P=.328 P=.075 P=.773 P=.297 P=.698 P=.821 P=.539 P=.750 P=.960 P=.800^=.064 c2=.030 c C1=.153 C2=.02^ CT=.168 c1=.032 c2=.ou CT=.l^ C1=.036 C!2=.028 :t».04i

Q7b.k7 1.10 3.72 .90 .16 2.75

RESULTS

.98 1.70 2.3k 9.89 . .02 3.51DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3P=.502 P=.296 P=.293 P=.Jkk P=.687 Pa.60k P=.325 P=.189 P=.509 P=.002 P=.920 P=.410^=.509 Cp= . 079 c T=.ikk C1=.081 c2=.033 C T=.lkl C^.079 c2=.104 Ct=.122 C ^ . l k l C2=.020 Ct=.086

TABLE X (continued)

Q8 (ACADEMIC STUDIES COMPLETED)FREQUENCIES

GROUP 1 GROUP II

APP APP APP APPA B TOT A B TOT

*1 24 10 34 19 19**2 36 25 61 7 39 46***3 42 11 35 8 44 52*#**4TOTAL 1$ 8

-12177 IN­ -16118 i S

* Before 1951 ** 1951 * I960

* * * 1961 - 1970 **** After 1970

GROUP III TOTAL OF GROUPS

APP APPA B TOT10 11 2127 24 5129 34 638

U80 iffc

APP APPA B TOT34 40 7470 88 15879 89 16825 44 62208 2SI 569

O'VjJ

yo GROUP I GROUP II2 2 2 2 2

*2 XI *21+2v s3+4 2vs3 TOT l+2vs3+4 2 vs 3

.14 5.37 13.14 .66 0.00DF=1 DF=1 DF=3 DF=1 DF=1P=.709 P=.020 P=.005 P=.422 P=.930C1=.026 C2=.212 Ct=.263 Cx=.069 c =.000

TABLE X(continued)

RESULTSGROUP III TOTAL OF GROUPS

2 2 2 2 2 2 2*1 *2 *1 *2 x^

TOT l+2vs3+4 2 vs 3 TOT 1+2vs3+4 2vs3 TOT3.37 .38 .54 .57 .06 2.40 2.41DF=3 DF=1 DF=1 DF=3 DF=1 DF=1 DF=3’=.338 P=.544 P=.470 P=.902 P=.890 P=.125 P=.500,= .155 C^.049 C2=.069 Ct=.060 c 1= . o n CO0II*(\j0 c =.226

HO■F-

165between indicated managerial philosophy and decisionoutput. It is interesting to note that when the largeamount of respondents indicating participative mana-gerial philosophy is dropped out and xj is computed,

2the x values is exceptionally high. This results in a C- of .33$ which indicates relative strong causal relationship.

In testing Hypothesis both respondents' level of business experience, Question #9, and experience level as personnel manager, Question #10, are con­sidered independent variables. With respect to Question #91 the Xpjr for all groups of 5 •kl indicate relatively strong interaction. The P value of .051 indicates the hypothesis could be rejected without significant risk. While the C,p value is rather low, .106, the hypothesisis rejected in consideration of Question #9 variable,

2based on the size of x^ for all groups and the P of .051.In considering the data generated in response to

Question #10, level of personnel administration experi- ence, the x£ and CT for all groups is higher than when business experience level is considered. The x^ of 6.91 and P of .027 suggest grounds for rejecting hypothesis

without undue risk. The Crp of .119 is low compared to a possible maximum between .707 and .#16. However, given the inexact nature of the independent variable considered (i.e., impact of experience level on

subjective criteria) the hypothesis is rejected. There­fore, it can be asserted that for all respondents taken as a group, there is a correlation between years of experience and decision ability. It should be noted, however, the opposite effect of experience on Group II

prespondent selection. Question #9, x^ of .09 and C,p of.024, and Question #10, x^ of .24 and C,p of .040,suggests there is less Group II interaction thanaverage for all groups. This is because the oldermore experienced personnel managers are perhaps lessquantitatively oriented; therefore, they did notassimilate and effectively utilize Set II, human

2resource information. Therefore, the low Xip and C,p for Group II corroborate the observation with reference to decision rigidity and decision validity made in Chapter III of this study. In essence, given the data person­nel administration are accustomed to, experience en­hances decision validity. However, in the face of unfamiliar data, rigidity prevents proper assimilation of the data; therefore, human resource information has an adverse effect on decision validity.

In testing Hypothesis Hy data generated in response to Questions #11, #12, #13 and #14 is utilized. The frequencies are results appear in Table IX. The questions considered were designed to establish the attitude of the respondent towards humans as assets.

167If the respondent answered "Yes" to Question #11, "Quantitative" to Question #12, "Yes" to Question #13 and "Same" to Question #14, he was considered to befavorably disposed to the concept of human resources.

2The extremely low x— 's and C's for groups and vari­ables (i.e., Questions #11 through #14) provides no grounds for rejection of the Hypothesis Hy. Therefore, it can be concluded that there is no relationship between attitude toward the concept of human resources and proper utilization of human resource information in the decision process.

In testing the final hypothesis of this study, Hypothesis Hg, data generated in response to Questions #2, #3> #5, #6a, #6b, #7a, #7b and #8 is considered to be the independent variables. Frequencies and results appear in Table X of this chapter.

The hypothesis is rejected in respect to the relationship between applicant selected, Question #1, and type of industry, Question #2. The 6.72 xjp for all groups and P of .091 indicates rejection is in order at the .10 significance level. In effect, rejection of the hypothesis based on Question #2 variables indicates a definite causal relationship between.type of industry of respondents' employment and ability to utilize human resource information for decision-making.

\i6d

The relationship holds fairly strong for Group I and Group II but is not strong when only Group III responses are considered. The rejection of the hypothe­sis in respect to Question #2 variables indicates a causal relationship between the degree of labor intensity of a firm and the validity of the decision process dependent on human resource information of its personnel directors. Service firms are considered to be most labor-intensive and heavy manufacturing firms are considered to have a small human investments rela­tive to physical plant investment. Therefore, person­nel administrators employed by service firms were better able to utilize human resource information. Rejection of this part of Hypothesis Hg confirms this relationship.

In considering Question #3, size of company, as the dependent variable, Hypothesis Hg cannot be rejected

Oowing to the low Xip and CT for all groups of 1.69 and .056, respectively. In effect, there is no relationship between the size of the firm in which a respondent is employed and his decision output. Therefore, firm size is not a causal factor in the ability of personnel administrators to utilize human resource information.

This same situation seems to hold true for2Question #5 of Hypothesis Hg. The low and C , of

1.40 and .053 does not permit rejection. Therefore,

169this research has not discovered a relationship between education level of respondent and ability to utilize the quantitative data output of human resource accounting.

A very interesting situation developed in the results computed for Question #6a, major field of study, and Question #6b, minor field of study. That part of Hypothesis Hg considering major field of study as the independent variable can definitely be rejected due to the and C,p for all groups of 29*09 and .242, respectively. In effect, there is a relationship between major field of study and ability to utilize human resource data.

This relationship does not hold true when the minor field of study is considered the dependent vari­able. When data generated by Question #6b is con-

2sidered the independent variable, the xijr of 1.60 and C,p of .064 indicate an extremely weak or non-existent causal relationship.

In considering the level of respondents' edu­cation in accounting or personnel management, Question#7a and Question #7b, as independent variables, Hypothe-

2sis Hg cannot be rejected owing to the low x^ and2For Question 7a, x^ equals .77 and C,p equals .041. For

Question #7b, x^ equals 3.51 and equals .0&6. Therefore, this study discovered no discernible re­lationship between respondents' college credit hours

170in the fields of accounting or personnel management- industrial relations and the ability, indicated by response to Question #1, to use human resource data information.

When responses to Question #S, receiving ofeducation, are considered the independent variable

oHypothesis Hg cannot be rejected due to the and CT for all groups of 2.41 and .226, respectively. To do so would incur a .500 risk of Type I error. These findings support the position that when all factors are considered, the time span between conclusion of education and the present is not indicative of the respondents’ ability to make decisions.

In summary, Hypothesis Hg can be rejected when considering data gathered by Questions #2 and #6a only. Considering Questions #3, #5, #6b, #7a, #7b and #& as independent variables does not permit rejection of the hypothesis. On balance, it can be stated that there is very little interaction between decision output and job environment and qualifications of respondents.

In summarizing the test results of hypotheses of the second group, H^ through Hg, the following can be maintained. The only definite causal relationship discovered by this research is between level of business, personnel experience, type of industry of respondents’ employment and decision output. Additionally, some

171evidence of interaction was developed between major field of study of respondent. In general, however, little positive interaction was determined to exist between the background variables considered in this study and ability to select the correct applicant.

Respondents* CommentsOf the 511 usable questionnaires received, 191

comments were recorded either in response to Questions#11, #14 or in general. The distribution of commentsby type and group is as follows:

Comments Received in Response to Question #11, Question #14,

and in General by GroupGroup I Group II Group III Total

Question #11 24 16 11 51Question #14 56 37 37 130General 1 S 1 10

Total 91 61 49 191

Question #11 is a filter for Question #12. Its purpose was to screen out those respondents who did not consider additional information input necessary to the

personnel selection process. A "Yes’* answer is con­sidered favorable since human resource information falls in the category of additional input to the

172

decision process. The comment portion of Question #11 was intended to provide a means of alternative response to the rigid yes/no dichotomy presented.

The 51 comments received in this section fall into two categories: (1) those indicating a surfeitof information available to and government regulation of employment practices, and (2) those indicating a need for more information.

The references to excessive regulations usually inferred that irrespective of the amount and quality of potential information available, federal government regulations of employment practices somewhat subverts the effectiveness of the data. For instance, in some cases employees must be accepted for employment because they are members of certain socio-economic groups rather than on the basis of demonstrable ability.

The second category of responses indicated a need both for more information and different kinds of information depending on the job to be filled. Refer­ence was made to a need for further validation of applicant testing procedures. Also, the need for additional information with respect to prevailing labor market conditions was indicated.

Some respondents indicated a need for additional information relevant to the myriad government regu­lations pertaining to employment. In general, those

173respondents indicating a need for additional infor­mation on which to base employment decisions did recognize the nexus between the relevance and variety of information and the validity of the decision process.

The comment section of Question #14 drew the bulk of the responses. The answer to the question required a differentiation on the part of the respon­dent between human assets and physical assets. Approxi­mately 25$ of the 130 comments did not make this differentiation as the question intended. In the question, physical assets referred to what is commonly called plant assets in accounting. However, 25$ of the respondents indicated they considered physical assets to be the physical skills of workers. To this group, only mental ability was considered human assets. In spite of this frustration of original intent, the responses gave an indication that 25$ of the respon­dents commenting consider only mental abilities to be human assets. The survey of research in human resource accounting included in Chapter II of this study reveals that human assets are considered to be the total pro­ductive capacity of humans: both mental and physical.The disparagement between research and practice is significant.

The 75$ of the 130 respondents who did inter­pret physical assets as plant assets usually referred

to the problems involved in considering human assets the same as physical assets. The question of how to value humans was raised several times. Further, the question of how to depreciate humans and the effect of recording valuation and depreciation of humans was raised. The expressed difficulty of valuation centered on the problem of valuing human assets in different job environments. The respondents indicated a need to approach the valuation of an executive and that of a foreman from different directions. That is, they seemed to recognize the different magnitudes of benefits con­tributed by each to the productivity of the firm.There was also recognition given to the ephemeral nature of human assets: the emotional side of humanbeings. There seems to be a pervasive recognition of the difference between potential human resources and actual human resources. The potential resources can become actual only if properly motivated by the environment provided the employees by the firm.

The comments entered elsewhere on the question­naire were very informative. They ranged from a comment on a Set I questionnaire that this research was hardly "doctor's level" to a comment on a Set II questionnaire that it was excellently designed and well thought out. Other comments were on the configuration of the real world of the employment function: a quick

check and interview; to a page-long analysis of the information provided by human resource accounting in a Set II questionnaire. There were several references to the arcane terminology used such as present value and opportunity cost. In a general sense these comments added significantly to the information gathered by the survey. The difficulty in reporting the comments mentioned earlier, did not detract from the value of the information gathered.

This concludes the report of the experimental results. Chapter V is devoted to a summary of the findings, conclusions drawn from the research, and recommendations based on the conclusions.

CHAPTER V

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

In the main, information generated by human resource accounting can be useful to personnel adminis­trators in their personnel selection process. The pre­ponderance of evidence uncovered in this empirical study demonstrates beyond reasonable doubt a nexus between the utilization of human resource information currently provided the selected decision-makers and the validity of decisions based thereon. This research has established the efficacy of human resource infor­mation. This conclusion emerged from the implemen­tation of an experimental design requiring (1) a survey of a random sample of practicing personnel adminis­trators, and (2) determination of the impact of human resource accounting information on the personnel selection process by inferences drawn from the testing of data gathered in the survey.

Prospective of the ProblemTo provide a prospective from which the infer­

ences drawn from the surveyed statistical results could be viewed, the history of human resources was traced

176

from its inception to the present. The two basic methods for valuing human assets developed by early economists, the cost-of-production and the capitalized earnings procedure, were detailed at length. The exposition of these methods recalled the contributions of Petty, Farr, Ernst Engels, and Wittstein. Recounted, also, was the pervasive impact of Alfred Marshall on the concept of human resources. Because of his dis­position to consider the valuing of humans as un­realistic, the concept of human resources remained dormant for the first sixty years of the 20th century. Because of the intricate relationship between the theoretical structure of accounting and economics, this dormancy has had a pervasive impact on the development of the concept of human resources for accounting purposes. Since most of the underlying concepts of modern accounting developed during the first sixty years of the 20th century, this development was devoid of a consideration of humans as assets of the firm of their employment. Consequently, investments in human assets are considered current expenditures and are written off in the period incurred rather than in the period expired.

In an effort to correct this violation of the matching principle, and in response to renewed interest in the concept of human resources by economists,

accounting research has undertaken a study of the accounting application of the concept of human re­sources. Research to date and models for human resource accounting derived therefrom, has proceeded beyond the concern for the matching of revenue generated with expired human resource cost. Current research is reflective of the bifurcation in the direction of research in accounting in general. While some human resource accounting models are concerned with the de­termination and allocation of human resource cost, others are delving into the approaches to the determination of the economic value of human resources. These trends in research closely monitor developments in accounting theory. Currently, accounting is cost-based. However, due to seminal research undertaken by several organi­zations, the concept of current value accounting is gaining currency. Specifically, the inquiry into the basis of financial accounting by the Research Committee of the Financial Accounting Standards Board is indica­tive of the growing concern for the need to reconsider the basis of financial accounting. The currently per­vasive research environment of the accounting profession makes the consideration of value-based human resource accounting information feasible.

Given this feasibility, this research was undertaken for the purpose of determining the impact

179of the provision of information generated by proposed human resource accounting to personnel administrators. The degree of impact was judged by the ability of respondents to select the "correct" applicant from a selection of two applicants. The "correct" applicant is a function of the set of information received by the respondent.

Experimental MethodologyThe design of the experiment is predicated upon

its objectives and the environment in which the objec­tives must be achieved. To gain a prospective of the information requirements of the personnel selection process, the information concepts of verity and rele­vance are discussed. To provide an understanding of the decision process of personnel selection, a model of the process is presented.

To effectuate the objectives of the experiment, variation is introduced by the provision of three different sets of information to three randomly par­titioned groups of the original sample of prospective participants. One group received questionnaires con­taining conventional employment information items for Applicant A and Applicant B. Another group received questionnaires containing information that can be generated by proposed human resource accounting systems.

A third group received questionnaires containing the combined information items of the other two groups. Further variation was introduced by the varied im­portance rating respondents attached to each item of personnel selection information provided. In a summary of variables considered, the variation in types of information received and variation in importance rating of the information items are considered to be current input. In the decision process this current input is considered the objective component of the decision premise. The variation introduced by current input in the independent variables is considered in the tests of the first group of hypotheses, Hypothesis to H^.The dependent variable is obtained in the response to Question #1. The dependent variable (i.e., applicant selected) is considered to be a function of the indepen­dent variable (i.e., variation in information items provided and variation in importance assigned by respon­dents to information items provided).

A second set of independent variables was intro­duced into the experiment by consideration of the back­ground or demographic characteristics of the respondents. This set of variables is considered to be the subjective component of the decision premise. They are determi­nistic of the subjective judgemental criteria utilized by the respondents in application of the decision rule.

131Variation introduced by the background or demographic characteristics of respondents is utilized to test the hypotheses of the second group, Hypotheses to Hg.In testing this group of hypotheses the independent variables considered are the respondents’ level of experience, managerial philosophy, size of company and type of industry of respondents employment, edu­cational attainment, and attitude toward the concept of human resources. The dependent variable is the selection of either Applicant A or Applicant B in response to Question #1. The dependent variable is considered to be a function of the independent vari­ables considered.

In terms of importance to this research, hypotheses of the second group are ranked third, primed by the second ranked importance of Hypotheses H£ through H^ and the crucial importance of Hypothesis H- . This ranking of the importance of the hypotheses tested emanates from the following rationale. It is first necessary to determine actual usefulness of the broad category of human resource information. Determi­nation of actual usefulness is essential because here­tofore research in human resource accounting has proceeded on the assumed usefulness of information generated by proposed models. The responses of actual

182practitioners in this survey provides the basis for the finding of actual usefulness in this study*

The establishment of the actual usefulness of human resource information is but the first step.Given the myriad of proposed accounting models, each resting on a different theoretical foundation, it is of secondary importance to determine the particular model or models which tend to produce the most efficacious information. The determination of the respondents* subjective judgemental criteria is considered least important in reference to the study as a whole. This ranking emanates from the difficulty in ascertaining the causal relationship between information previously accumulated by the respondent and current decision performance. This tenuity in the relationship causes the variables considered to be moderating. Therefore, hypotheses of the second group, to Hg are considered least important to the study as a whole.

Response Rate and Statistical TechniqueThe high usable response rate of 42.33$ is

attributed to the endorsement of this study by the Cooperative Research Committee of the American Society for Personnel Administration. The response rate is a tribute to the membership of the society. It is indica­tive of the high professional standards associated with membership.

183The statistical techniques applied to the data

included compilation of statistical summaries appearing in Appendix C, and computation of the Chi Square and Contingency Coefficient to test the existence and strength of the causal relationships between the dependent and independent variables considered. The high response rate multiplied by the number of vari­ables from each response produced a mass of usable data. The computer was used to compile the frequenciesand compute the Chi Squares and Contingency Coeffi-

2cients. Since x ' s and C's computed for partitioned variables monitored the results of the variables con­sidered in total, the acceptance/rejection of the null

2hypotheses was made on the basis of total Xrp and C,p.

Summary of ResultsHypothesis H- is rejected with authority. This

rejection indicates the existence of a definite causal relationship between the information provided the respondent and the decision made. According to the data generated, Group II respondents were better able to assimilate the human resource information provided than were Group I respondents who received conventional employment information. The rejection of Hypothesis H- based on data collected from practicing personnel administrators establishes the actual usefulness of

Filmed as received

without page(s) tru

UNIVERSITY MICROFILMS.

RecommendationsOn the basis of the findings of this research,

it is recommended that additional research be under­taken to permit operationalization of the human re­source accounting systems represented in the Stochastic and Replacement Cost models. Implementation to date has been limited and selective. In view of the results reported herein, validation of these models through experimental implementation is warranted.

It is further recommended that research be directed to areas specifically excluded from consider­ation in this research. Specifically, research should be undertaken into the usefulness of human resource information to other decision situations of the person­nel administrator, namely: the promotion, demotion, and termination functions. Further research is recom­mended into the uses of human resource accounting information for other management groups. Finally, research into the impact on employees of the instal­lation of a human resource accounting system is recommended.

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. "On the Use of the Economic Concept of Human Capital in Financial Statements: A Comment,"The Accounting Review, XLIV (January, 1972),148—152.

"Should Your Organization Attempt to Value Its Human Resources?" California Management Review (Winter 1971), pp. kO-VT.

"Toward A Theory of Human Resource Value in Formal Organizations," The Accounting Review,XLIV (October 1972).

Ford, Gordon. "Importance of Human Resources and How They Contribute to the Firm’s Success," Ohio CPA, XXV (Autumn 1966), 145-52.

Francia, Arthur J., and Robert H. Strawser. "Per­ceptions of Financial Reporting Practices by Accounting Educators: An Empirical Study," TheAccounting Review, XLVI, No. 2 (April, 1971),380-84.

Gilbert, Michael M. "The Asset Value of the Human Organization," Management Accounting, July, 1970,pp. 25-28.

192

Graves, Clare W. ’’Levels of Existence: An Open SystemTheory of Values," Journal of Humanistic Psychology. X (Fall, 1970), 131^T5T:--------------- 1-

Gynther, Reg S. "Some Conceptualizing on Goodwill,"The Accounting Review, XLIV (April, 1969), 247-55.

Haire, Mason. "The Management of Human Resources. A Symposium," Industrial Management Review, II (Winter, 1970), l3-2j5.

Hekimian, James S., and Curtis H. Jones. "Put People on Your Balance Sheet," Harvard Business Review,XLV (January-February, 1967), 105-113.

"How Texas Instruments Measures Who’s Worth What," Corporate Financing (January-February, 1971).

Imke, Frank J. "Relationships in Accounting Theory,"The Accounting Review, XLI (April, 1966), 321.

Kelly, Roger T. "Accounting in Personnel Adminis­tration," Personnel Administration, XXX (May-June, 1967), 2 4 - ^ ----------------------

Kiker, B. F. "The Historical Roots of the Concept of Human Capital," The Journal of Political Economy (October 1966), I£-l3.

Krein, Ted J. "People — Assets that Talk Back,"Journal of the Institute of Internal Auditors (July-August, 1969), 33-42.

Lall, R. M. "An Enquiry into the Nature of Assets,"The New York Certified Public Accountant (November,T9SS), 793-797 .--------------------------------------------

2Lancaster, H. 0. "The Derivation and Partition of X in Certain Discrete Distributions," Biometrika,XXXVI (1949), 117-129.

Lawrence, Susanne. "Put People on Your Balance Sheet," Personnel Journal (January 1971), 30-31.

Leavitt, Harold J. "Management According to Task: Organizational Differentiation," Management International, No. 1 (1962), 13-2TI

Lev, Baruch. "On the Use of the Economic Concept of Human Capital in Financial Statements," Accounting Review, XLV1 (January, 1971), 1U3-12.

193Lev, Baruch, and Aba Schwartz. "On the Use of the

Economic Concept of Human Capital in Financial Statements: A Reply," The Accounting Review, XLVII(January, 1972), 153-4.

Likert, Rensis. "Human Organizational Measurement:Key to Financial Success," Michigan Business Review, XXII, May 1971. ----- ------------------

_______. "A Technique for the Measurement of Atti-tudes," Archives of Psychology, 1932, 140, pp. 1-55.

. "A New Twist to People Accounting," Business Week, October 21, 1972, pp. 67-66.

"Human Resource - The Hidden Assets of Your Firm," Credit and Financial Management, June, 1969,pp. 20-22”.

, and S. Seashore. "Making Cost Control Work," Harvard Business Review (November-December, 196S),pp.' 96-108.----- --------

, and David G. Bowers. "Organization Theory and Human Resource Accounting," American Psychologist (September 196S), pp. 565-592.

, and William C. Pyle. "Human Resource Account-ing; A Human Organizational Measurement Approach," Financial Analysts Journal (January-February, 1971).

, David G. Bowers, and Robert M. Norman. "Howto Increase a Firm's Lead Time in Recognizing and Dealing with Problems of Managing Its Human Organi­zation," Michigan Business Review, XXI (January 1969), 177:

, and William C. Pyle. "Human Resource Account-ing: A Human Organizational Measurement Approach,"Financial Analysts Journal, XXVII (January-eTB'ruary', 1971), pp. 7 5 -3 2 .

McGregor, Douglas. "The Human Side of Enterprise," Proceeding on the Fifth Anniversary Convocation of the School of Industrial Management, Cambridge, Massachusetts: Massachusetts Institute ofTechnology, April 9, 1957-

McMurry, R. N. "The Case for Benevolent Autocracy," Harvard Business Review (January-February, 1956), p p . 82-90':-------------

Maslow, A. H. "A Theory of Human Motivation," Psychological Review, C, 1943, pp. 370-396.

Megginson, Leon, and Aubrey Sanford. "A Reevaluation of the Human Resource Philosophy," Personnel Journal (January 1969), pp. 52-57.

Miner, John B. "Bridging the Gulf in Organizational Performance," Harvard Business Review, XLVI (July-August, 196$), pp. 102-110.

Miles, Raymond E. "Human Relations or Human Resources? Harvard Business Review, XLIII (July-August, 1965), pp. 148-163 *

Miller, James R., III. "To Managing Human Resources," Industrial Management Review, II, No. 2 (Winter1970), ppV 24-10.----------

Mills, D. Q. "Industrial Relations and the Theory of Human Resource Management," Sloan Management Review, Fall 1970.

Mincer, Jacob. "On-The-Job Training: Costs, Returns,and Some Implications," J. P. E ., Supplement (October 19o2), pp. 50-79"!

Mullins, Peter L. "The Price Tag on Employee Transfers Personnel 46:34-39 (March-April, 1909).

Myers, M. Scott. "Conditions for Manager Motivation," Harvard Business Review (January-February, 1966), _ CT_

Newell, G. E. "Should Humans be Reported as Assets?" Management Accounting 54:13-16, December 1972.

Norton, H. S., and B. F. Hiker. "Public Utility Concept and Human Capital," Public Utilities Fortnightly (April 11, 19oS), pp. 15-20.

Paine, Frank T. "Human Resource Accounting - The Current State of the Question," The Federal Accountant, XIX, No. 2 (June 1970), pp. 57-66.

Patz, Alan L. "Management," Industrial Management Review, II, No. 2 (Winter 1970), pp. 31-35.

"People Are Capital Investments at R. G. BarryCorporation," Management Accounting (November1971), p. 53. --------------------

195Peterson, Sandra E. "Accounting for Human Resources,"

Management Accounting (June 1972), pp. 19-22."Put Human Resources on the P & L Sheet," Iron Age

205:25 (January 29, 1970). ------"Putting People on the Balance Sheet," Personnel

Management (January 1971).Pyle, William C. "Monitoring Human Resource — 'On

Line'," Michigan Business Review, July, 1970, pp. 19-3^

. "Human Resource Accounting," FinancialAnalysts Journal, September-October, 1970, pp.19-3 2 .

"An Accounting System for Human Resources," Innovation, No. 10, 1970, pp. 46-54.

Report to Management - "Price-Lagging Company's Human Resources," Iron Age (April 25, 1963), p. 25.

Radar, Lawrence A. "A Stock Is a Company in People," Financial Analysts Journal, September-October,T'96'9',’ pp. 105-108.--------

Rayburn, L. G. "Are Accountants Overlooking the Human Aspects of Budgeting?" The Woman CPA,March 1971.

Rose, J., W. Beaver, S. Becker, and G. Sorter."Toward an Empirical Measure of Materiality," Empirical Research in Accounting: SelectedStudies, 1970, pp. 13 V-I48.

Schoonmaker, Alan N. "Why Mergers Don't Jell: TheCritical Human Elements," Personnel, XLVI (September-October, 1969), 39-48.

Schultz, Theodore W. "Reflections on Investment in Man," The Journal of Political Economy, LXX,October 1902.

"Investment in Human Capital," American Economic Review, March, 1961, pp. 1-17.

Singer, Henry A. "The Impact of Human Resources on Business," Business Horizons, April, 1967, pp. 53-53.

196Simpson, Robert R., Jr. ’’Measurement of Human Re­

sources," Journal of Accountancy, September, 1971, p. 42.

Slater, Philip E., and Warren G. Bennis. "Democracy Is Inevitable," Harvard Business Review, XLII (March-April, 1964), pp. 51-59.

Sorter, George H., and Charles T. Horngren. "Asset Recognition and Economic Attributes - The Relevant Casting Approach," The Accounting Review, XXXVII (July, 1962), pp. 391-4'0T.

Stone, Florence. "Investment in Human Resources at1 AT&T," Management Review, October, 1972, pp.23-27.

Waters, James. "Human Resource Investment Evaluation:A Practical Application of Human Resource Account­ing Techniques," Personnel Administration, XXXV (June, 1972), 41-46.

Weiss, Marvin. "Human Resources Accounting - ANeglected Area," CPA Journal, XLII (September,1972), 735-43.

"Where 'Human Resources Accounting' Stands Today," Administrative Management, November,1972, pp. 43-4d.

Weiser, Herbert J. "The Impact of Accounting Control on Performance Motivation," The New York Certified Public Accountant, XXXVIII (March 1968), pp. 19TJ-20I.------

Weisbrod, Burton A. "The Valuation of Human Capital," The Journal of Political Economy, LXIX (October1961), p. 426.-----------------

Woodruff, Robert L. "What Price People," ThePersonnel Administrator, January-February, 1970.

. "Human Resource Accounting," Canadian Chartered Accountant, XCIII (September 1970),pp-.' "155-T6T:-------- '

Wright, F. K. "Measuring Asset Services: A LinearProgramming Approach," Journal of Accounting Research, VI (Autumn 1968), pp. 222-236.

197Wright, Robert. "Managing Man As A Capital Asset,"

Personnel Journal, April, 1970, pp. 290-9S.

C. REPORTS

American Accounting Association. Report of the Committee on Human Resources Accounting.Supplement to Volume XLVIII, 1973> pp. 169-185•

Brummet, R. Lee, Eric G. Flamholtz, and William C.Pyle. "Human Resources Accounting," Development and Implementation in Industry (Ann Arbor: Foundation for Research on Human Behavior, 1969).

Becker, G. S. Human Capital. Columbia University Press, National bureau of Economic Research No.SO, 1961.

Cohn, Theodore. "Introduction to Human ResourceAccounting," Memo to Technical Studies Committee of the AICPA, New York, 1973-

Elias, Nabil S. "The Effects of Human Asset State­ments on the Investment Decision: An Experiment,"Empirical Research in Accounting: SelectedStudies jT97"27•----------------

Flamholtz, Eric G. Human Resource Accounting: AReview of Theory and Research Presented tothe Organization Behavior Division at the 32nd Annual Meeting of the Academy of Management: Minneapolis,Minnesota, 1972.

________ . "Measuring Positional Replacement Cost,"Unpublished Working Papers No. 72-2F, Graduate School of Business, Columbia University, 1972(d).

"The Management of Human Resources; A Symposium,"The Industrial Management Review, Volume II, No. 2, Winter 1WT.------ ------------

Likert, Rensis, and Robert J. Woodruff, Jr. "A Brief History of the Development and Implementation of Industry's First Human Resource Accounting System at the R. G. Barry Corporation Institute of Social Research. University of Michigan, Ann Arbor, Michigan.

193Pyle, William C. "New Perspectives on Managing Human

Resources," A paper delivered to the American Management Association's 42nd Annual Personnel Conference, February 9, 1971> New York.

Sprouse, R. T., and M. Moonitz. "A Tentative Set of Broad Accounting Principles for Business Enter­prise," Accounting Research Study, No. 3> AICA,New York, l9b2.

Telly, Charles S., Wendell L. French, and William G. Scott. The Relationship of Inequity to Turnover Among Hourly Workers" Graduate School of business Administration, University of Washington, reprint No. 29, 1972.

Tomassini, Lawrence. The Impact of Human Resource Accounting on Management Decision-Making. Unpublished Working Paper, June, 1972.

D. MISCELLANEOUS

American Accounting Association. Accounting and Reporting Standards for Corporate Financial"" Statements. Iowa City: American AccountingAssociation, 19 57•

________ . A Statement of Basic Accounting Theory.Chicago^ Illinois: American Accounting Association,1966.

Elias, Nabil S. "The Impact of Accounting for Human Resources on Decision-Making: An ExploratoryStudy." Unpublished Ph. D. dissertation, The University of Minnesota, 1970.

Flanders, Harold. The AT&T Company Manpower Laboratory, Circa, 1971. Report to the Jlst Annual Meeting of the Academy of Management, August, 1971.

Hermanson, R. H. Accounting for Human Assets. East Lansing, Michigan: Michigan State University,Bureau of Business and Economic Research, 1964*

Hyatt, Jim. "R. G. Barry Includes Its Employees Value on Its Balance Sheet," The Wall Street Journal. April 3, 1970.

199Ijiri, Yuji, Robert K. Jaedicke and Kenneth E. Knight.

"The Effects of Accounting Alternatives on Manage­ment Decisions," Research in Accounting Measure­ment . Collected papers. Eds. Yuji Ijiri, Robert K. Jaedicke and Oswald Nelson. Menasha, Wisconsin: American Accounting Association, i960, pp. 1S6-99.

The R. G. Barry Corporation 1969 Annual Report.Columbus, Ohio.

"R. G. Barry Counts the Human Factor in Its Operations," The Wall Street Journal, Thursday, April 1, 1971.

Smith, William H. "Putting People in the FinancialStatement Is the Aim of Human Resource Accounting," The Carolina Financial Times, Monday, June 3,19'7'0,"p. 1 .------------------------------

Sprouse, Robert T., and M. Moonitz. A Tentative Set of Broad Accounting Principles for Business Enter­prises . Accounting Research' Study bio• 3.New York: American Institute of Certified PublicAccountants, 1962.

Statement of the Accounting Principles Board No. 4 .American Institute of Certified Public Accountants, 1970.

Traum, Richard. "The Dollar Value of People."Transcript of 2nd Annual Conference of Human Resource Systems Users. Information Science Incorporated. New City, New York, 1972.

"Transcript of the Second Annual Conference of Human Resource Systems Users." Information Science Incorporated. New York, 1972.

Woodruff, Robert L., Jr., and Robert G. Whitman."The Behavioral Aspects of Accounting Data for Performance Evaluation at the R. G. Barry Corpo­ration (with special reference to human resource accounting)." The Behavioral Aspects of Accounting Data for Performance Evaluation, ed., Thomas J.Burns (Columbus, Ohio: College of AdministrativeScience, The Ohio State University, 1970), pp.1-33.

, , and R. Lee Brummet. "Discussion:ft. G. ftarry Human Resources Accounting," The Behavioral Aspects of Accounting Data forTer- fonuance Evaluation. Ed. Thomas J. Burns,Columbus: College of Administrative Science, TheOhio State University, 1970, pp. 35-47.

APPENDIX A

TYPE I QUESTIONNAIRE

202

FIRST CLASS

PERMIT N O . 188

BATON R O U S E , L

COOSB U S I N E S S R E P L Y M A I L

N o Postage S tam p N ecessary if M a iled in th e U nited S ta les

POSTAG E W ILL BE PAID BY

H. C. ZAUN BREC HER

P. O . BOX 21517

UNIVERSITY STATION

BATON ROUGE, LOUISIANA 70803

AMERICAN SOCIETY FOR. PERSONNEL ADMINISTRATION

N A T I O N A L H E A D Q U A R T E R S10 C H U R C H ST R E ET B E R EA . O H IO 44 0 1 7 T E L E P H O N E <ai«) 3 3 4 3 3 0 0

October 1, 1973

Dear ASPA Member,

You are one of a random sample of our membership selected to participate in this survey. The Cooperative Research Committee believes the survey is timely and valuable in that it introduces the Human Resources concept in to the selection process.

Mr. Zaunbrecher will make the results of the survey and related information available to ASPA. These results and information will be distributed to the entire member­ship in one of the bulletins early in 197^.

We hope you will take the time to complete and return the questionnaire. You are part of a small sample of the membership and your response is necessary to make the study statistically valid.

Thank you,

Leo E. Streeter, Chairman Cooperative Research Committee

204E MP L OY E E S E L E C T I ON I N F OR M A T I ON?

An Empirical Research Questionnaire

Decisions about which applicants to employ and the placement of employees are among the most difficult any company has to make. The increased importance of initial hiring and placement decisions results from increasingly complex technology requiring greater investment in training. What information is necessary to make these increasingly important decisions? Can information now provided be augmented to improve the selection process?I believe only the practicing personnel professional! like yourself, has the answers to these and related questions.

To secure these answers, I am conducting a survey to determine the usefulness of various types of information in the employee selection process. The findings of the survey will improve the quality of information available for personnel selection. Your response is essential to the success of this research.

Pretesting indicates the questionnaire can be completed in 15 minutes. Research is not required as all information necessary to complete the questionnaire is provided. Since the project must be completed shortly, please return the completed questionnaire at your earliest convenience.

The responses of individuals will be held in strict confidence. Only grouped results will be reported. Do not sign the questionnaire or the enclosed envelope. The number on the envelope will be used cnly to facilitate f ollow-up.

The success of this study is dependent on a valid sample of opinions of practicing professional personnel managers. Only through your response can this validity be assured.Thank you,

1 .

Candidate for Ph. D. Louisiana State University

205

YOUR ATTENTION IS DIRECTED TO THIS EMPLOYEE SELECTION SITUATION.....

As the Personnel Manager of a manufacturing concern, you are to decide either to hire Applicant A or Applicant B. One of the two applicants must be hired to fill the job of Assembly Line Foreman with your company.

Base your decision on information provided on the following page(s). The information is intentionally limited to isolate the impact of the variables under study. The applicants are equally qualified with respect to items of information normally included in the selection process but not specifically stated.

With respect to each information item indicate your estimate of the importance of the item by placing an (X) in the appropriate block. The information under columns headed Applicant A and Applicant B is to be used in your selection. Record your choice in response to question #1. Responses to the remaining questions (#2 through #14) will be used to study the background and decision criteria of respondents as a group.

206

EMPLOYEE SELECTION INFORMATION ITEMSt

Time lived at current residenceMinimum wage acceptableHeight/WeightNumber of dependentsYears of education completedMajor StudyGrade average (A=4)

Machine or equipment Skills

Work experiencei (Most recent) PositionTime in positionDutiesPay

Score on validated Personnel Test (Normal Range 90 - 110)Estimates by applicant of their annual salary ten years from now.

IMPORTANCEf*O d) d) 0)(Z M W) M

>3 S cd rt a> nJ to i—i o k > ftd ft H a) a> o a>O f t <D > > 43 >

ZD□ □ czZ3□ □ dZDzd□ 1=ZD□ 0 d=]□ □ dzdn □ czZD□ □ cz

zd□ □ dZD□ □ dZD□ □ dZD□ □ dZ3□ □ d=□□ □ cz

APPLICANTA

36 Mo. $900/Mo.6'1B/l 99 215

Mech. Eng3.0

LatheTypewriterCalculator

Ass'tForeman22 Mo.Supervisor$850/Mo.

94

$1500/Mo.

APPLICANTB

3^ Mo. $960/Mo. 5’8"/213 1

Ind. Eng.2.8

LatheWeldingMachine

Ass’tForeman24 Mo.Supervisor$800/Mo.

101

$1600/Mo .

(CONTINUE ON NEXT PAGE)

Now that you have evaluated each item of information, which applicant would you employ?

Applicant A _______________________Applicant B _______________________

Indicate the type of industry in which you are presently employedt

Service Industry ___________________Light Manufacturing ______________Heavy Manufacturing ______________Other _____________________________

Indicate the total number of employees at your current place of employmenti

100 or Isss ______________________100 to 999 ________________________1,000 to 5,000 ___________________Over 5,000 ________________________

On the scale below indicate with an (X) the dominant leadership style employed by management in your immediate work environmentii_____________ 1______________1______________1______________ 1_____________ iAutocratic Participative Free-reinWhat level of education did you attain? (If no college, go to Question # q )

High School _______________________Attended College___________________Bachelor ____________ __________Graduate WorkMaster ______Ph.D. _______Other

What were your major and minor fields of study?Major _____________________________Minor

How many college credit hours have you earned?In Accountingj In Personnel Management!None____________________ None ___________________Less than 15 ___________ Less than 15 ___________Less than 30 ___________ Less than JO ___________Over 30 ________________ Over 30 ________________

(CONTINUE ON NKXT f'AGb)

2088. Indicate the period in which your academic study

was completed!Before 1951 ______________________1951 - I960 _______________________1961 - 1970 _______________________After 1970 ________________________

9. Indicate the number of years of your full time business experience!

Less than 2 ___________________•2 - 5 _____________________________6 - 9 _____________________________10 - 20 ___________________________More than 20 ______________________

10. Indicate the number of years you have been responsible for the personnel management function of your employer!

Less than 2 _______________________2 - 5 _____________________________6 - 9 _____________________________10 - 20 ___________________________More than 20 ______________________

11. Do you recognize a need for more information input in the personnel decision making process?

Y e s _______________________________No ________________________________Comment ___________________ _______

12. If you feel additional information is needed, shouldit be qualitative (traditional) or quantitative(expressed in dollar amounts and probabilities)?

Qualitative _______________________Quantitative _____________________

13. Do you consider the skills of individual workers asassets of the firm by which they are employed?

Yes _______________________________No ________________________________Ik. In your decision process, if you consider skills of

workers as assets, are these human assets considered basically the same or quite different from physical assets?

Same ______________________________Different _________________________Comment ___________________________

TH A N K YOU

TYPE II QUESTIONNAIRE

210

AMERJCAN SOCIETY FOR PERSONNEL ADMINISTRATION

N A T I O N A L H E A D Q U A R T E R SIB C H U R C H ST R E ET B E R EA . O H IO 44 0 1 7 T E L E P H O N E (BIS) 234-BSO O

October 1, 1973

Dear ASPA Member,

You are one of a random sample of our membership selected to participate in this survey. The Cooperative Research Committee believes the survey is timely and valuable in that it introduces the Human Resources concept in to the selection process.

Mr. Zaunbrecher will make the results of the survey and related information available to ASPA. These results and information will be distributed to the entire member­ship in one of the bulletins early in 197^.

We hope you will take the time to complete and return the questionnaire. You are part of a small sample of the membership and your response is necessary to make the study statistically valid.

Thank you,

Leo E. Streeter, Chairman Cooperative Research Committee

211E M P L O Y E E S E L E C T ION I N F O R MA T I ON?

An Empirical Research Questionnaire

Decisions about which applicants to employ and the placement of employees are among the most difficult any company has to make. The increased importance of initial hiring and placement decisions results from increasingly complex technology requiring greater investment in training, What information is necessary to make these increasingly important decisions? Can information now provided be augmented to improve the selection process?I believe only the practicing personnel professional, like yourself, has the answers to these and related questions.

To secure these answers, I am conducting a survey to determine the usefulness of various types of information in the employee selection process. The findings of the survey will improve the quality of information available for personnel selection. Your response is essential to the success of this research.

Pretesting indicates the questionnaire can be completed in 15 minutes. Research is not required as all information necessary to complete the questionnaire is provided. Since the project must be completed shortly, please return the completed questionnaire at your earliest convenience.

The responses of individuals will be held in strict confidence. Only grouped results will be reported. Do not sign the questionnaire or the enclosed envelope. The number on the envelope will be used only to facilitate follow-up.

The success of this study is dependent on a valid sample of opinions of practicing professional personnel managers. Only through your response can this validity be assured.Thank you,

1 .

Candidate for Ph. D. Louisiana State University

212

YOUR ATTENTION IS DIRECTED TO THIS EMPLOYEE SELECTION SITUATION.....

As the Personnel Manager of a manufacturing concern, you are to decide either to hire Applicant A or Applicant B. One of the two applicants must be hired to fill the job of Assembly Line Foreman with your company.

Base your decision on information provided on the following page(s). The information is intentionally limited to isolate the impact of the variables under study. The applicants are equally qualified with respect to items of information normally included in the selection process but not specifically stated.

With respect to each information item indicate your estimate of the importance of the item by placing an (X) in the appropriate block. The information under columns headed Applicant A and Applicant B is to be used in your selection. Record your choice in response to question #1. Responses to the remaining questions (#2 through #14) will be used to study the background and decision criteria of respondents as a group.

213

EMPLOYEE SELECTIONINFORMATION ITEMSi IMPORTANCE APPLICANTA APPLICANT

BThe following was developed from current and past data

O Q) <U 0),z x> M w>1 i (d «] a> aj fff-i O U f-i > h mft HO) (1) O 0) go, a> > > & >

A

Recruiting cost $905 $845Training cost (Salary during training and trainers salary) m o u n d $3850 $3600Cost of lost production during training o nu m m $9630 $9000Separation cost (Separation pay, accrued vacation, vested retirement) 0 0 0 1 0 $1605 $1500

•Present value of fringe benefits d o o m $4700 $4400Present value of salary for total period of employment d o n u m $33000 $35310Present value of cost of replacing current applicant when terminated o o r n m $5350 $5000

Time employee will remain with company o m m m 36 Mo. 38 Mo.Probability of number of pro­motions with salary increasei

At least one omuom 80$ 85$At least two o o m m 6 5% 70$At least three o m m m 40$ 43$

Present value of cost of in­company development training o m m m $2000 $2140Theoretical value of employee to company if employed in 2nd most productive capacity o m m m $1300 $1390

Theoretical increase in profit by adding one additional o m m m $1500 $1600employee of equal productivity

•Present value is the amount necessary, if currently deposited at interest, from which payments could be made in specific amounts at specific intervals. At the end of the period the principle would be zero.

(CONTINUE ON NEXT PAGE)

Now that you have evaluated each item of information, which applicant would you employ?

Applicant A _______________________Applicant B __________ ____________

Indicate the type of industry in which you are presently employed«

Service Industry _________________Light Manufacturing ______________Heavy Manufacturing ______________Other _____________________________

Indicate the total number of employees at your current place of employmenti

100 or less ____________ .__________100 to 999 ________________________1,000 to 5,000 ___________________Over 5,000 ________________________

On the scale below indicate with an (X) the dominant leadership style employed by management in your immediate work environmenti•.__________i__________i__________i__________ i_________ »Autocratic Participative Free-reinWhat level of education did you attain? (If no college, go to Question #9 )

High School _______________________Attended College_________Bachelor _______________ _ _ _Graduate WorkMaster ______Ph.D. _______Other

What were your major and minor fields of study?Major _____________________________Minor___________________ __ ___

How many college creditIn AccountingiNone________________Less than 15 _______Less than 30 _______Over 30 ____________

hours have you earned?In Personnel Management!

None ___________________ Less than 15 ___________ Less than 30 ___________ Over 30 ________________

(CONTINUE ON NEXT PAGE)

215

8. Indicate the period in which your academic study was completedt

Before 1951 ______________________1951 - I960 _________________ _1961 - 1970 ______________________After 1970 ________________________

9. Indicate the number of years of your full time business experiencet

Less than 2

10 - 20More than 20 _____________________

10. Indicate the number of years you have been responsiblefor the personnel management function of your employer 1

Less than 2 ______________________2 - 5 _____________________________6 - 9 _____________________________10 - 20 __________________________________________________More than 20 _____________________

11. Do you recognize a need for more information inputin the personnel decision making process?

Yes _______________________________N o ________________________________Comment ___________________________

12. If you feel additional information is needed, shouldit be qualitative (traditional) or quantitative(expressed in dollar amounts and probabilities)?

Qualitative ____ „______ __________Quantitative _____ ____ ___________

13. Do you consider the skills of individual workers asassets of the firm by which they are employed?

Yes _______________________________No ________________________________

14. In your decision process, if you consider skills ofworkers as assets, are these human assets considered basically the same or quite different from physical assets?

Same ______________________________Different _________________________Comment ___________________________

THANK YOU

TYPE III QUESTIONNAIRE

AMERICAN SOCIETY FOR, PERSONNEL ADMINISTRATION

N A T I O N A L H E A D Q U A R T E R Sl» C H U R C H S T R E E T B E R E A , O H IO 4 4 0 1 7 T E L E P H O N E (218) 3 3 4 - 2 9 0 0

October 1, 1973

Dear ASPA Member,

You are one of a random sample of our membership selected to participate in this survey. The Cooperative Research Committee believes the survey is timely and valuable in that it introduces the Human Resources concept in to the selection process.

Mr. Zaunbrecher will make the results of the survey and related information available to ASPA. These results and information will be distributed to the entire member­ship in one of the bulletins early in 197^.

We hope you will take the time to complete and return the questionnaire. You are part of a small sample of the membership and your response is necessary to make the study statistically valid.

Thank you,

Leo E. Streeter, Chairman Cooperative Research Committee

218E M P L O Y E E S E L E C T I ON I N F OR M A T ION?

An Empirical Research Questionnaire

Decisions about which applicants to employ and the placement of employees are among the most difficult any company has to make. The increased importance of initial hiring and placement decisions results from increasingly complex technology requiring greater investment in training. What information is necessary to make these increasingly important decisions? Can information now provided be augmented to improve the selection process?I believe only the practicing personnel professional, like yourself, has the answers to these and related questions.

To secure these answers, I am conducting a survey to determine the usefulness of various types of information in the employee selection process. The findings of the survey will improve the quality of information available for personnel selection. Your response is essential to the success of this research.

Pretesting indicates the questionnaire can be completed in 15 minutes. Research is not required as all information necessary to complete the questionnaire is provided. Since the project must be completed shortly, please return the completed questionnaire at your earliest convenience.

The responses of individuals will be held in strict confidence. Only grouped results will be reported. Do not sign the questionnaire or the enclosed envelope. The number on the envelope will be used only to facilitate follow-up.

The success of this study is dependent on a valid sample of opinions of practicing professional personnel managers. Only through your response can this validity be assured.Thank you,

I . .Candidate for Ph. D. Louisiana State University

219

YOUR ATTENTION IS DIRECTED TO THIS EMPLOYEE SELECTION SITUATION.....

As the Personnel Manager of a manufacturing concern, you are to decide either to hire Applicant A or Applicant B. One of the two applicants must be hired to fill the job of Assembly Line Foreman with your company. •

Base your decision on information provided on the following page(s). The information is intentionally limited to isolate the impact of the variables under study. The applicants are equally qualified with respect to items of information normally included in the selection process but not specifically stated.

With respect to each information item indicate your estimate of the importance of the item by placing an (X) in the appropriate block. The information under columns headed Applicant A and Applicant B is to be used in your selection. Record your choice in response to question #1. Responses to the remaining questions (#2 through #14) will be used to study the background and decision criteria of respondents as a group.

220

EMPLOYEE SELECTION INFORMATION ITEMSi

Time lived at current residenceMinimum wage acceptableHeight/WeightNumber of dependentsYears of education completedMajor StudyGrade average (A=4)

Machine or equipment Skills

Work experiencei (Most recent) PositionTime in positionDutiesPay

Score on validated Personnel Test (Normal Range 90 - 110)Estimates by applicant of their annual salary ten years from now.

IMPORTANCE

O Q) 0) <1),z hfl hD h£>5 i cd cd <d cdOH Ok k > km a rid <u outop, o> > >

— ! I— ! I— 11—Vb b m m J Lw b m m I

UEJEJCZ□ □ □ C = □ □ □ [ =

= ] □ □ [ =

U E J E J E Z □ □ □ C U E J E J E I U E H E J C Z

UEJCJCZ= □ □ □ ( = :

(CONTINUE ON NEXT PAGE)

APPLICANTA

36 Mo. $900/Mo. 6'1"/199

2

15Mech. Eng3.0

LatheTypewriterCalculator

Ass't Foreman22 Mo.Supervisor$850/Mo.

94

$1500/Mo.

APPLICANTB

34 Mo. $960/Mo .5* 8"/213 114Ind. Eng.2.8

LatheWeldingMachine

Ass" t Foreman24 Mo.Supervisor$800/Mo.

101

$1600/Mo .

221

EMPLOYEE SELECTION INFORMATION ITEMSiThe following was developed from current and past data

Recruiting costTraining cost (Salary during training and trainers salary)Cost of lost production during trainingSeparation cost (Separation pay, accrued vacation, vested retirement)

♦Present value of fringe benefitsPresent value of salary for total period of employmentPresent value of cost of replacing current applicant when terminatedTime employee will remain with companyProbability of number of pro­motions with salary increase»

At least oneAt least twoAt least three

Present value of cost of in­company development trainingTheoretical value of employee to company if employed in 2nd most productive capacityTheoretical increase in profit by adding one additional employee of equal productivity

♦Present value is the amount necessary, if currently deposited at interest, from which payments could be made in specific amounts at specific intervals. At the end of the period the principle would be zero.

IMPORTANCE+>q o> a) a), 2 n bfl w >> i cti cd a> cdtjH O h b > ti njpH H # Cl) Otl 5P. CD > J> £i > nr< W •*< ■< •<■«<m m m m

APPLICANTA

APPLICjQ

$905 $845

m m m a $3850 $3600

mmi am $ 9 6 3 0 $9000

$1605 $1500

men cuci $4 7 0 0 $4400

m m m m $ 3 3 0 0 0 $35310

m m m m $5350 $5000

m a d i d 36 Mo. 38 Mo

mm mid 80# 85%mmmcd 65% 70#mmmid 40# 43#

ii ii ii $2000 $2140

mmmcd $ 1 3 0 0 $1390

mmmid $ 1 5 0 0 $1600

(CONTINUE ON NEXT PAGE)

2221. Now that you have evaluated each item of information,

which applicant would you employ?Applicant A _______________________Applicant B _______________________

2. Indicate the type of industry in which you are presently employed:

Service Industry _________________Light Manufacturing ______________Heavy Manufacturing ______________Other _____________________________

3. Indicate the total number of employees at your current place of employmenti

100 Or lOFS ________________________100 to 999 ________________________1,000 to 5,000 _______Over 5,000 ________________________

4. On the scale below indicate with an (X) the dominant leadership style employed by management in your immediate work environmenti

5. What level of education did you attain? (If no college, go to Question #9 )

High School _______________________Attended College___________________Bachelor _____________________ ____Graduate Work __________________ __Master ____________________________Ph.D. _____________________________Other ___________________________________

6. What were your major and minor fields of study?

7. How many college credit hours have you earned?

Autocratic Participative Free-rein

MajorMinor

In Accounting: In Personnel Management:None________Less than 15 Less t.han 30 Over 30

None _______Less than 15 Less than 30 Over 30

(CONTINUE ON NEXT PAGE)

2238. Indicate the period in which your academic study

was completed!Before 1951 _______________________1951 - I960 _______________________1961 - 1970 _______ ______________After 1970 ________________________

9. Indicate the number of years of your full time business experience!

Less than 2 _______________________2 - 5 _____________________________6 - 9 _____________ ;_______________10 - 20 _More than 20 ___________ __________

10. Indicate the number of years you have been responsiblefor the personnel management function of your employer!

Less than 2 _______________________2 - 5 ________________6 - 9 ___ .10 - 20 ___________________________More than 20 ______________________

11. Do you recognize a need for more information inputin the personnel decision making process?

Yes _______________________________No ________________________________Comment ___________________________

12. If you feel additional information is needed, should it be qualitative (traditional) or quantitative (expressed in dollar amounts and probabilities)?

Qualitative _______________________Quantitative ______________________

13. Do you consider the skills of individual workers as assets of the firm by which they are employed?

Yes _______________________________No ________________________________

Ik. In your decision process, if you consider skills of workers as assets, are these human assets considered basically the same or quite different from physical assets?

Same ______________________________Different _________________________Comment ___________________________

THANK YOU

APPENDIX B

'225

Figube 1G b n s b a l u s o M odel os H u m a n R isoubce A ccounting System sob

Investments in M anagebs

(Po k UomI A n n AccMwts)

Sourcet R. Lee Brummet, William G. Pyle, and Eric G. Flamholtz, "Accounting for Human Resources," Michigan—Business Review. Vol XX, No. 2, March 1968, p. 25.

I

i

226FIGURE 2

Model for Meastirement of Human Resource Replacement Cost*

Recruitment SelectionHiringPlocenent

Cost ofI’ror.otion orTransferfrom within

Formal Training end OrientationOn-the-Job Training

Dire ct Costs

IndirectCosts

DirectCosts

Cost of Trainer's Tine

IndirectCosts

DirectCosts

SeparationPay . . \✓

Loss of efficiency Prior to Separation V IndirectCost of Vacant Position during

Search i. - . —■ — •■ i -

f Costs

•• •

AcquisitionCosts

Learning✓

SeparationCosts

Positional Replacement Cost

Sourcei .Eric G. Flamholtz, The Theory and Measurement of an Individual8s Value to an Organization. Unpublished Doctoral Dissertation, University of Michigan, 19o9.

227Figure 3 : LIKERT’S MODEL OF DETERMINANTSOF A GROUP'S VALUE TO AN ORGANIZATION: SCHEMATIC RELATIONSHIPS AMONG CAUSAL, INTER- VENING. AND END-RESULT VARIABLES____________

CausalVariables Intervening Variables

End-Resuit Variables

Managerial Behavior •

Perception

Communication.

Subordinate . Peer Behavior

Motivation

Decision Making

Organizational^Structure

Control

Coordination

Health and Satisfaction

Productivity and FinancialPerformance

Feedback Loops

Source: Rensis Likert and David G. Bowers, "Organizational Theory andHuman Resource Accounting," American Psychological Assocation Address, August 30, 1968, p. 7.

Figure

Instructions for completing this questionnaire are as followsi

On the line below each organizational variable (item), please place a check mark ( ) at the point which, in your experience describes your organization at the present time. It is important that you answer each question as thoughtfully and frankly as possible. This is not a test; there are no right or wrong answers. The important thing is that you answer each question the way you see things or the way you feel about them. Treat each item as a continous variable from the extreme at one end to that at the otner.

229

TABLE 1 . PROFILE OF ORGANIZATIONAL CHARACTERISTICS

SYSTEM 1 SYSTEM 2 SYSTEM 3 SYSTEM 4

Organisationalvariable*

I s shown I n s u b o r d i n a t e s ?VI r t u a l 1y n o n e

i i i i

Some

i i i i

S u b s t a n t i a l am o u n t

1 i : i i

A g r e a t d e a l

ii i i , i

♦ e •

2 '*■ * How f r e e d o t h e y f a a l t o t a l k t o s u p e r i o r s a b o u t J o b ?

Not v e r y f r e e

i i i i

Somewhat f r e e

i i i i

Q u i t e f r e e

1 i i i i

V e r y f r e e

i i i i l

j;°4 1 How o f t e n a r c s u b o r d i n a t e ' s I d e a s s o u g h t a n d u s e d

c o n s t r u c t i v e l y ?

S e l d o m

1 i i i i

Some t i mes

1 1 1 !

Of t e n

I I I ! !

V e r y f r e q u e n t l y

i l l ; 1

i < :I s p r e d o m i n a n t u s e ma de o f

1 f e a r , 2 t h r e a t s , 3 p u n i s h m e n t , k r e w a r d s , 5 i n v o l v e m e n t ?

t , 2 , 3 , o c c a s i o n a l l y k

i i i i i

k , sa me )

i i i i

k , so me 3 e n d S

I i i : i

S , k , b a s e d on g r o u p

i i i i i

: t

! *i !

tA ia r e I s r e s p o n s 1 b 11 i t y ‘ f e l t f o r a c h i e v i n g o r g a n i z a t i o n ' s g o a l s ?

M o s t l y a t t o p

1 i i i i

Top e n d m i d d l e

i i i i

Fa i r l y g e n e r a l

I 1 1 1 !

At a l l l e v e l s

i i i i l: t'* : : o • i % • how m uc h c o o p e r a t i v e

t c a n w o r k e x i s t s ?V t r y l l t t l .

1 1 1 1 1

R e l a t i v e l y 1 i t t l e

i I i i

M o d e r a t e amou . t

l l l l l

G r e a t d e a l

i i i i l

What i s t h e u s u a l d i r e c t i o n o f i n f o r m a t i o n f lo w ?

Downward

1 i i i i

M o s t l y do w nw a rd

l i . i

Down a n d up

I i i i i

Oown, u p , a n d s i d e w a y s

i i i i :

; ^ : 3 ^ :• t-i t How I s do w n w a rd

c o e n u n i c a t i o n a c c e p t e d ?W i t h s u s p i c i o n

1 i i i i

P o s s i b l y w i t h s u s p i c i o n

I I I I

Wi t h c a u t i on

I i i i i

W i t h a r e c e p t i v e m in d

i i i i i

; s j •

i * I

How a c c u r a t e i s u p w a r d c o o t n u n l c a t i o n ?

U s u a l l y I n a c c u r a t e

1 i i i i

O f t e n i n a c c u r a t e

i i i i

O f t e n a c c u r a t e

l l l l l

A l m o s t a l w a y s a c c u r a t e

i i i i !

i i• C» ;

How w e l l do s u p e r i o r s know p r o b l e m s f a c e d by s u b o r d i n a t e s ?

Not v e r y w e l t

1 i i i i

R a t h e r we 11

i i i i

Q u i t e w e ) 1

I i i i i

V e r y we 11

i i i i l

: e: <.j 2

At w h a t l e v e l a r e d e c i s i o n s m a d e ?

M o s t l y a t t o p

1 i i i i

P o l i c y a t t o p , s o m d e l e g a t i o n

i i i i

B r o a d p o l i c y a t t o p , m o r e d e l e g e t i o n

I i i i i

T h r o u g h o u t b u t w e l l i n t e g r a t e d

i i i i l: % : : o :

: ♦A r e s u b o r d i n a t e s i n v o l v e d In

d e c i s i o n s r e l a t e d t o t h e i r w o r k ?A l m o s t n e v e r

1 i i i i

O c c a s i o n a l l y c o n s u l t e d

i i i i

G e n e r a l l y c o n s u l t e d

I i i i i

F u l l y i n v o l v e d

i i i i !! ' o ! 2 2 : o : What d o e s d e c i s i o n - m a k i n g p r o c e s s

c o n t r i b u t e t o m o t i v a t i o n ?Not v e r y much

1 i i i i

R e l a t i v e l y l i t t l e

i i i i

Some c o n t r i b u t i o n

I i i i i

S u b s t a n t i a l c o n t r i b u t i on

i i I I J

: fo •How a r e o r g a n i z a t i o n a l

g o a l s e s t a b l i s h e d ?O r d e r s i s s u e d

1 i i i i

O r d e r s , som e c o m m e n t s i n v i t e d

i i i i

A f t e r d i s c u s s i o n , by o r d e r s

I i i i i

By g r o u p a c t i o n ( e x c e p t i n c r i s i s )

i i i i !

1 ^ :2 O 2 t ' 5 : How much c o v e r t r e s i s t a n c e

t o g o a l s I s p r e s e n t ?S t r o n g r e s i s t a n c e

1 i i i i

M o d e r a t e r e s ( s t a n c e

i i i i

Some r e s i s t a n c e a t t i m e s

I i i i i

L i t t l e o r no n e

i i i i I

How c o n c e n t r a t e d a r e r e v i e w a n d c o n t r o l f u n c t i o n s ?

V e r y h i g h l y a t t o p

1 i i i i

Q u i t e h i g h l y a t t o p

i i i i

M o d e r a t e d e l e g a t i o n t o l o w e r l e v e l s

i i i i i

W i d e l y s h a r e d

i i i i l

: ^ •\Q : 2 ^ 2 2 E-. •

I s t h e r e a n I n f o r m a l o r g a n i z a t i o n r e s i s t i n g t h e f o r m a l o n e ?

Y e l

1 1 1 1 1

U s u a l l y

1 1 1 !

S o m e t i m e s

I i i i i

N o - — - s a m e g o a l s a s f o r m a l

i i i i l

2 O 2 2 u 2 What a r e c o s t ,

p r o d u c t i v i t y , a n d o t h e r c o n t r o l d a t e u s e d f o r ?

P o l i c i n g , p u n i s h m e n t

I I 1 1 1

R e w a r d a n d p u n i s h m e n t

l i l t

R e w a r d , som e s e l f - g u i d a n c e

1 1 I - i ......J -------

S e l f - g u i d a n c e ,p r o b l e m - s o l v i n g

l l l l '

C o p y r i g h t © . 5 96 7 b y M c G r a w - H i l l . I n c . I ’ s c d l . y p e r m i s s i o n of M c G r a w - H i l l B o o k C o m p . n i > . M'wl if iv ii i r u m A p p e n d i x I I in “ T h e H u m a n O i g a n i z a t i o n . I t s M a n a g e m e n t a m i V a l u e " b y R c n s i s L i k e r t . \< i f u r r i w r r e p r o d u c t i o n o r d i s t r i b u t i o n a u t h o r i z e d .

IndividualAttributes

InstrumentalIndividualDeterminants

C ognitiveA b ilities

PersonalityTraits

Skills

| Organizational], • Structure ;i— ------------ 1

ftManagement

Style

O rganizationalAttributes

ActivationLevel

Attitudes

Elements of Conditional Value

Promotabllity_±_

Productivity

Transferability

I

Individual'sConditional

Value

Role

r."xn.r! Rewardsj

— ^ ----------:-----------Satisfaction

V' --Probability of

with \ MaintainingOrganization Organizational

Membership

Individual's Expected

Realizable Value to a

Formal Organization

InstrumentalOrganizationalDeterminants

Symbols

>< >

Meaninghypothesized determinants hypothesized interaction a subsetp ossib le determinant

Figure 5 . Revised Model of the Determinants of an Individual's Value to a Formal Organization

Sourcei Eric G. Flamholtz, "Assessing the Validity of a Theory of Hurr.ar.R esource V alue: A F ie ld S tu d y ," E m p ir ica l R esearch in A ccounting -1

S e le c t e d S t u d ie s ., 1972.

230

a p p e n d i x c

SELECTION ♦GROUP #1

TABLE I CAPPLICANTS SELECTED

(QUESTION #1)

•♦GROUP #2 ♦♦•GROUP #3 TOTAL# % § * # % # %

No Answer 5 2.6 10 6.6 7 4.2 22 4.30Applicant A 119 62.6 19 12.5 79 46.7 217 42.46Applicant B 66 34,8 121 80,9 SI *9.1 222 53.?3Total 190 100.0 152 100.0 169 100.0 511% of Grand Total 37.2 29.7 33.1 100.0

♦Group #l-Conventional Employment Information •♦Group #2-Human Resource Employment Information

♦♦♦Group #3"Combination of Group #1 and Group #2

232

TABLE II CIMPORTANCE ASSIENED BY GROUP 1 RESPONDENTS

TO CONVENTIONAL EMPLOYMENT INFORMATION ITEMSNo Does Not

Rating Apply# % # *

K1 4 2.10 50 26.31K2 6 3.16 7 3.68K3 5 2.63 27 14.21K4 4 2.10 73 38.42K5 3 1.58 5 2.63K6 3 1.58 6 3.16K7 4 2.10 5 2.63K8 4 2.10 4 2.10K9 4 2.10 2 1.05K10 4 2.10 4 2.10Kll 4 2.10 2 1.05K12 5 2.63 3 1.58K13 4 2.10 5. 2.63Kl4 6 3.16 26 13.68

TotalNuaber 60 219% ofGrand 2.25 8.23Total

BelowAverage # %

Ave#

ira^e

49 25.79 75 39.4711 5.79 106 55.7948 25.26 71 37.3746 24.21 60 31.5818 9.47 91 47.9013 6.84 82 43.1628 14.73 119 62.6320 10.53 69 36.326 3.16 44 23.16

12 6.31 67 35.265 2.63 36 18.95

19 10.00 118 62.1025 13.16 118 62.1061 32.10 77 ^0.53

>61 1133

13.53 42.59

AboveAverage Total# % # %12 6.31 190 100.0060 31.58 190 100.0039 20.53 190 100.007 3.69 190 100.0073 38.42 190 100.0086 45.26 190 100.0034 17.90 190 100.0093 48.95 190 100.00

134 70.53 190 100.00103 5^.21 190 100.00143 75.26 190 100.00^5 23.68 190 100.0038 20.00 190 100.0020 10.53 190 100.00

887 2660

33.33 100.00

TABLE IIICIMPORTANCE ASSIGNED BY GROUP 2 RESPONDENTS

TO HUMAN RESOURCE INFORMATIVE ITEMS

No Does Not Below AboveRating Apply Average Average Average Total# % # % # 95 # % # % # %

LI 4 2.63 40 26.31 46 30.26 47 30.92 15 9.90 152 100.00L2 4 2.63 14 9.21 37 24,34 68 44.73 29 19.08 152 100.00L3 5 3.29 10 6.58 25 16.45 56 36.84 56 36.84 152 100.00L4 5 3.29 36 23.68 53 34.87 47 30.92 11 7.24 152 100.00L5 4 2.63 24 15.79 36 23.69 63 41.45 25 16.45 152 100.00L6 6 3.95 9 5.92 30 19.74 71 46.71 36 23.69 152 100.00L7 5 3.29 25 16.45 30 19.74 55 36.19 55 36.19 152 100.00L8 4 2.63 7 4.60 24 15.79 42 27.63 75 49.34 152 100.00L9 15 9.87 7 4.60 28 18.42 46 30.26 56 36.84 152 100.00L10 13 8.55 5 3.29 15 9.87 72 47.37 47 30.92 152 100.00Lll 12 7.90 12 7.90 24 15.79 47 30.92 57 37.50 152 100.00LI 2 5 3.29 16 10.53 38 25.00 77 50.66 16 10.53 152 100.00L13 6 3.95 19 12.50 35 23.03 60 39.48 32 21.05 152 100.00114 4 2.63 15 9.87 21 13.82 55 36.18 57 37.50 152 100.00

Totalumber 92 239 442 806 549 2128<£ ofGrand 4.32 11.23 20.77 37.87 25.80 100.00Total 234

TABLE IV C-lIMPORTANCE ASSIGNED BY GROUP 3 RESPONDENTS

TO CONVENTIONAL EMPLOYMENT INFORMATION ITEMS

No Does Not BelowRating Apply Average# % # % § %

K1 3 1.78 36 21.30 62 36.67K2 3 1.78 8 4.73 17 10.06K3 3 1.78 37 21.89 46 27.22K4 3 1.78 69 40.83 53 31.36K5 3 1.78 3 1.78 16 9.4?K6 3 1.78 1.78 20 11.83K7 4 2.37 8 4.73 34 20.19K8 6 3.55 8 4.73 15 8.88K9 4 2.37 7 4.14 - -

K10 5 2.96 4 2.37 6 3.55Kll 4 2.37 6 3.55 - -

K12 4 2.37 - 24 14.20K13 5 2.96 12 7.10 35 20.71K14 4 2.37 32 18.94 55 32.54

AboveAverage Average Total# % # % # *60 35.50 8 4.73 169 100.0095 56.21 46 27.21 169 100.0052 30.77 31 18.3^ 169 100.0039 23.08 5 2.96 169 100.00

102 60.36 45 26.63 169 100.0076 44.97 67 39.65 169 100.0097 57.40 26 15.39 169 100.0054 31.95 86 50.89 169 100.0036 21.30 122 72.19 169 100.0063 37.28 91 53.85 I69 100.0041 24.26 118 69.82 169 100.00

105 62.13 36 21.30 169 100.0090 53.25 27 15.98 I69 100.0057 33.73 21 12.43 169 100.00

TotalNumber 5^ 233 383 967 729 23665 o

Grand 2.28 9.85 16.19 ^0.32 30.81 100.00Total

TABLE IV C-2IMPORTANCE ASSIGNED BY GROUP 3 RESPONDENTS

TO HUMAN RESOURCE INFORMATION ITEMSNo Does Not Below

Rating Apply Average# * # % # %

LI 3 1.78 26 15.39 53 31.36L2 3 1.78 17 10.06 43 25.44L3 4 2.37 12 7.10 36 21.30L4 3 1.78 32 18.94 56 33.14L5 3 1.78 27 15.99 57 33.73L6 3 1.78 26 15.39 53 31.36L? 3 1.78 28 16.57 40 23.67L8 3 1.78 8 4.73 13 7.70L9 14 8.28 9 5.32 20 11.83L10 11 6.51 9 5.32 19 11.24Lll 13 7.70 10 5.92 32 18.94L12 5 2.96 21 17.43 4? 27.81L13 5 2.96 16 9.4? 45 26.63L14 5 2.96 20 11.83 23 13.61

AboveAverage Average Total# % # % # %66 39.05 21 12.42 169 100.0072 47.60 34 20.19 169 100.0071 42.01 46 27.22 169 100.0067 39.65 11 6.51 169. 100.0072 42.60 10 5.92 169 100.0069 40.83 18 10.65 169 100.0075 44.38 23 13.61 169 100.0059 34.91 86 50.89 169 100.0077 45.56 49 28.99 169 100.0094 55.62 36 21.30 169 100.0079 46.75 35 20.71 169 100.0081 47.93 15 8.88 169 100.0071 47.01 32 18.94 169 100.0077 45.56 44 26.04 169 100.00

TotalNumber 78 261 537 1030 460 2366% of"rand 3.30 11.03 22.70 19.44 43.53 100.00T o t a l 10\x>o

TABLE V: C

TYPE OP INDUSTRY OF RESPONDENTS EMPLOYMENT(QUESTION #2)

GROUP #1 GROUP #2 GROUP #3 TOTAL# % # % # 95 # 95

No Answer - - - 2 1.18 2 .004Service Industry- 75 39.4? 58 38.16 71 42.01 204 39.2172Light Manufacturing 58 30.53 ^9 32.24 47 27.81 154 30.1369Heavy Manufacturing 40 21.05 31 20.40 42 24.85 113 22.113Other 12 8,95 14 9,21 _z 4,14 JJi 7,436Total 190 100.00 152 100.00 169 100.00 511 100.00

TABLE VI CSIZE OF COMPANY OF RESPONDENTS EMPLOYMENT

(QUESTION #3)

GROUP #1 GROUP #2 GROUP #3 TOTAL# * # % # * # %

No Answer - - - - 1 .59 1 .001100 or Less 13 6.84 16 10.53 13 7.70 42 8.21100 to 999 101 53.16 87 57.24 101 59.7* 289 56.551000 to 5000 59 31.05 37 24.34 43 25.44 139 27.20Over 5000 .12 8,95 12 7,90 JL1 6,51, 40 7,83

Total 190 100.00 152 100.00 169 100.00 511 100.00

ASSIGNEDVALUE

No Answer

Participative1

Free-Rein

Total

TABLE VII CLEADERSHIP STYLE EMPLOYED IN RESPONDENTS IMMEDIATE

WORK ENVIRONMENT (QUESTION #4)

GROUP #1 GROUP #2# % # %3 1.58 1 .661 . 53 1 .66

12 6.32 7 4.6120 10.53 14 9.2123 12.11 33 21.7123 12.11 18 11.8472 37.90 40 26.3217 8.95 19 12.508 4. 21 15 9.87

11 5.79 4 2.63

100.00 152 100.00

GROUP #3 TOTAL# % 0 %3 1.78 7 1.361 .60 3 .598 4.73 27 5.28

13 7.70 47 9.1939 23.08 95 8.6014 8.28 55 10.7643 25.44 155 30.3313 7.70 49 9.5923 13.61 46 9.002 1.18 2 .39

10 5.92 25 4.90

169 100.00 511 100.00 239

TABLE VIII CRESPONDENTS EDUCATIONAL ATTAINMENT

(QUESTION #5)GROUP #1 GROUP #2 GROUP #3 TOTAL# * # 56 # % # 56

No Answer 1 .53 2 1.31 2 1.18 5 198High School 7 3.68 4 2.63 4 2.37 15 2.94Attended College 28 14.74 12 7.90 30 17.75 70 13* 70Bachelor 66 34.74 42 27.63 57 33.73 165 32. 28Graduate Work 49 25.79 49 37.24 45 26.63 143 27-99Masters 36 18.95 34 22.37 25 14.80 95 18. 60?h. D. 1 .53 6 3.94 5 2.96 12 2-35Other _2 1.05 1.97 __1 _ ,60 6 1.17

Total 190 100.00 152 100.00 104 100.00 511 100.00

240

TABLE IX C-lRESPONDENTS MAJOR FIELD OF STUDY

(QUESTION #6A)

GROUP #1 GROUP #2 GROUP #3 TOTAL# % # % # % # *

No Answer 11 5.79 8 5.26 6 3.55 25 4.89Accounting 5 2.63 4 2.63 3 1.78 12 2.35Per. Mngt.-Ind.Rel 45 23.68 26 17.11 3* 20.12 105 20.55All Other Bus. 60 31.58 51 33.55 66 39.05 17? 34.64Engineering 12 6.32 1 .66 6 3.55 19 3.72Psychology 18 ' 9.47 26 17.11 15 8.88 59 11.55All other fields 23 12.11 26 17.11 30 17.75 79 15.46Education 8 4.21 8 5.26 4 2.37 20 3.91Science 8 *.21 .JL32 5 . _ ,2,^6 7.94Total 190 100.00 152 100.00 169 100.00 511 100.00

241

TABLE IX C-2

RESPONDENTS MINOR FIELD OF STUDY (QUESTION #6B)

OROUP #1 GROUP #2 GROUP #3 TOTAL# % # * # % # *

No Answer 46 24.21 33 21.71 39 23.08 118 23.09Accounting 12 6.32 2 1.32 7 4.14 21 4.11Per.Mngt.-Ind.Rel. 10 5.26 12 7.90 13 7.69 35 6.85All Other Bus. 42 22.11 36 23.68 32 18.93 110 21.53Engineering 4 2.11 2 1.32 2 1.18 8 1.57Psychology 20 10.53 23 15.13 24 14.20 67 13.12All other fields 40 21.05 35 23.03 42 24.85 117 22.89Education 8 4.21 3 1.97 2 1.18 13 2.54Science 8 4.21 6 __a ..4,. 73 22 ..,4*3.;Total 190 100.00 152 100.00 169 100.00 511 100.00

242

TABLE X C-lRESPONDENTS ACCOUNTING CREDIT HOURS

(QUESTION #7A)GROUP #1 GROUP #2 GROUP #3 TOTAL# % # % # % # %

No Answer 21 11.05 13 8.55 15 8.88 49 9.59None 40 21.05 30 19.74 35 20.71 105 20.54Less than 15 85 44.74 77 50.66 8? 51.48 249 48.73Less than 30 36 18.95 23 15.13 27 15.98 86 16.83Over 30 __8 4. 21 __2 5.92 2.9.6 22 . A. 3.1Total 190 100.00 152 100.00 169 100.00 511 100.00

TABLE X C-2RESPONDENTS PERSONNEL MANAGEMENT CREDIT HOURS

(QUESTION #7B)GROUP #1 GROUP #2 GROUP #3 TOTAL# * # % # % # %

No Answer 11 5.79 8 5.26 9 5.33 28 5.4 7None 30 15.79 21 13.82 30 17.75 81 15.85Less them 15 51 26.84 48 31.58 53 31.36 152 29.74Less than 30 47 24.74 34 22.37 45 26.63 126 24.66Over 30 26.84 41 . .26*2.6, — 22 . ;m3,?4 124 3,4J>7Total 190 100.00 152 100.00 169 100.00 511 100.00

TO

TABLE XI C

RESPONDENTS RECENCY OF EDUCATION(QUESTION #8)

GROUP #1 GROUP #2 GROUP #3 TOTAL# % # % # % # %

No Answer 8 4.21 6 3.95 7 4.14 21 4.11Before 1951 35 18.42 22 14.4? 21 12.43 78 15.261951-1960 65 34.21 48 31.57 57 33.73 170 33.271961-1970 53 27.90 52 34.21 63 37.28 168 32.87After 1970 29 15,26 -24 -.1L..Z9 21 . 12 4,3 _Z4 *4*49Total 190 100.00 152 100.00 169 100.00 511 100.00

245

TABLE XII CRESPONDENTS BUSINESS EXPERIENCE

GROUP #1(QUESTION

GROUP #2¥9)

GROUP #3 TOTAL# % # * # % # %

No Answer 5 2.63 2 1.32 7 4.14 14 2.74Less than 2 years 2 1.05 8 5.26 4 2.37 14 2.742 - 5 years 18 9.47 15 9.87 19 11.24 52 10.186 - 9 years 28 1^.74 26 17.10 34 20.12 88 17.22

10 - 20 years 77 40.53 59 38.82 60 35.50 196 38.36Yore than 20 60 11.58. 42 _.2Z,i3 26.61 147 .28,77Total 190 100.00 152 100.00 169 100.00 511 100,00

TABLE XIII CRESPONDENTS PERSONNEL MANAGEMENT EXPERIENCE

(QUESTION #10)GROUP #1 GROUP #2 GROUP #3 TOTAL# * # $ # % # %

No answer - 1 .66 5 2.9 6 6 1.17Less than 2 years 3 6 18.95 36 23.68 44 26.04 116 22.702 - 5 years 59 31.05 45 29.61 48 28.40 152 29.756 - 9 years 41 21.58 38 25.00 35 20.71 114 28.1810 - 20 years 39 20.53 28 18.42 30 17.75 97 18.98More than 20 JLi 7,90 4 2,63 __Z 26 5,88Total 190 100.00 152 100.00 169 100.00 511 100,00

TABLE XIV C

RESPONDENTS NEED FOR ADDITIONAL EMPLOYMENT

GROUP #1# %

No Answer 4 2.11Yes 175 92.11No 11 5,79Total 190 100.00

(QUESTION #11)GROUP #2 :# %

GROUP #3 # *

1 .66 7 4.14139 91.45 150 88.7612 7.90 12 7.10

152 100.00 169 100.00

INFORMATION

TOTAL# *12 2.38

464 90.8035 _ 6.85

511 100.00

TABLE XV C

TYPE OF ADDITIONAL INFORMATION NEEDED (QUESTION #12)

GROUP 01 TOTAL# % # % # * \ # %

No answer 16 8.42 12 7.90 19 11.24 47 9.19Qualitative 62 32.63 65 42.76 64 37.87 191 37.37Quantitative 84 44.21 57 37.50 68 40.23 209 40.90Both Qualitative and Quantitative 28 14.74 18 11.84 18 10,65 64Total 190 100.00 152 100.00 169 100.00 511 100.00

249

1

TABLE XVI C SKILLS AS ASSETS OF THE FIRM

(QUESTION #13)GROUP #1 GROUP #2 GROUP #3 TOTAL# $ # % # % # 96

No answer 4 2.11 - 5 2.96 9 1.76Yes 184 96. 84 148 97.3? 163 96.45 495 96.87No __2 1.0? 4 2.63 1 _ *59 __Z X*J1Total 190 100.00 152 100.00 169 100.00 511 100.00

250

TABLE XVII CHUMAN ASSETS SAME AS PHYSICAL ASSETS

(QUESTION #14)GROUP #1 GROUP #2 GROUP #3 TOTAL# % # % # * # *

No answer 11 5.79 8 5.26 10 5.92 29 5.68Same 38 20.00 26 17.11 35 20.71 99 19.38Different 141 74.21 118 .21,63 124 JLLJZ m .7^,95Total 190 100.00 152 100.00 169 100,00 511 100.00

VITA

Hilary Charles Zaunbrecher was born on a rice farm near Mowata, Louisiana on September 13, 1939. He is the 9th of 10 children of Mr. and Mrs. Joseph A. Zaunbrecher. He attended parochial school in Acadia Parish and graduated from high school in 1957.

That same year he enrolled at Louisiana State University, Baton Rouge, Louisiana. After transferring to University of Southwestern Louisiana he obtained a B.S. in Business Administration with a major in Eco­nomics in I960.

In 1961 he entered the military service (Army) where he attained the rank of SP4. After service in Korea he was honorably separated from the Army in 1963.

He accepted employment with the General Motors Corporation for the period 1963-1966. In 1967, he entered the farming and trucking business until 1969.

In January, 1970 he enrolled in the Graduate School at Louisiana State University, Baton Rouge, majoring in Accounting. In August, 1971 he obtained the M.S. in Accounting Degree. During this period he was admitted to Beta Alpha Psi, the Honorary Accounting Fraternity. From September, 1971 until December, 1972

252

253he completed the course requirements for the Ph. D. while teaching as a graduate assistant at Louisiana State University, Baton Rouge. During the Summer of 1972, he received the Summaer Fellowship in the Account­ing Department.

In January, 1973, he was appointed an Instructor, Department of Accounting, Louisiana State University,New Orleans, Louisiana. He was awarded the Certificate of Certified Public Accountant, Louisiana, in August, 1973* In September, 1973, he was appointed Assistant Professor of Accounting at University of Southwestern Louisiana, Lafayette, Louisiana. On February 2S, 1974, he was appointed to a Summer Residency with Arthur Anderson & Company.