Scientific Research- Deductive Inductive

8/13/2019 Scientific Research- Deductive Inductive

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SCIENTIFICINVESTIGATION


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The hallmarks of science

. Purposivness

. Rigor

. Testability

. Replicability

. Objectivity

. Generalizability

. Parsimony

Limitation to scientific research in management

The building blocks of Science and the hypothetico-deductive method of research


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The seven steps of the hypothetico-deductive method

of research

1- Observation

2- Preliminary information gathering3- Theory Formulation

4- Hypothesizing

5- Further scientific data collection

6- Data analysis

7- Deduction


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Other types of research

. Case studies

. Action research


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Scientific Research focuses on solving problems

and pursues a step-by-step logical, organized,

and rigorous method to identify the problems,gather data, analyze them and draw valid

c o n c l u s i o n s t h e r e f o r e .


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Scientific research is not based on hunches,experience and intuition (though these may play apart in final decision making).

It is purposive and rigorous.

Similar studies done using same methodologyshould give same results.

Universal applicability - This helps various otherorganizations to apply those solutions when they

encounter similar problems. Findings are accurate and confident.

It is more objective.


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Highlights the most critical factors at the work place

that need specific attention.

Scientific Investigation and Managerial Decision

Making are integral part of effective problem solving.

It applies to both basic and applied research.

Applied research may or may not be generalizable to

other organizations.


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1.Purposiveness

2.Rigor

3.Testability

4.Replicability

5.Precision and Confidence

6.Objectivity

7.Generalizability

8.Parsimony

The hallmarks or main distinguishing characteristics of scientificresearch may be listed as follows:

Let us consider the case of a manager who is interested ininvestigating how employees commitment to the organizationcan be increased examining the eight hallmarks of science.


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1. Purposiveness It has to start with a definite aim or purpose. The focus is on increasing employees

commitment.

Increased employee commitment will translateinto more turnover, less absenteeism andincreased performance levels.

Thus it has a purposive focus.


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A good theoretical base and sound methodological

design would add rigor to the purposive study.

Rigor adds carefulness, scrupulousness and the

degree of exactitude in research.

In the case of our example:

Let us say the manager asks 10-12 employees how to

increase the level of commitment.

Solely on the basis of this enquiry the manager reachesseveral conclusions on employee commitment

The study is unscientific and lacks rigor


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1. Opinions of few employees may not be

representative of the entire workforce2. framing and addressing the questionsno basis

3. There might be other important influences oncommitment which were ignored

Thus, Rigorous research involves a good theoreticalbase and a carefully thought-out methodology.

an appropriate sample selected at random withthe minimum degree of bias,

Suitable analysis of the data gathered.


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The researcher might hypothesize thatthose employees who perceive greater

opportunities for participation in decision

making would have a higher level of commitment.

After review of literature,

Interview of employees of the organization, researcherdevelops certain hypothesis howemployee commitment can

be enhanced

Hypothesis can be tested by applying

certain statistical tests to the datacollected.


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Let us suppose that themanager/researcher, based on the results ofthe study,concludes that part ic ipat ion indecis ion m aking is one of the most impo rtantfactors that inf luences the comm itment o femployees to the organization.

Repl icable - i f s im i lar f ind ing emerge on thebasis of data col lected by other

organizat ions employ ing the same methods.


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Studying the universe of items or population we are interested inis impossible ,

We base our findings on a sample that we draw from thepopulation.

However, our findings should be as close to reality as possible, sothat we can place reliance or confidence in the results. .

Precision Precision refers to the closeness of the findings to reality

based on a sample. It reflects the degree of accuracy and exactitude of the

results of the sample.

Example: If a researcher estimated the number of production days

lost during the year due to absenteeism at between 32 and 38, asagainst the actual of 35, this is more precise than

The the estimation of mean between 25 to 45

This would remind us of confidence interval

5. Precision and

Confidence


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Confidence refers to theprobability that ourestimations are correct.

That is, it is not merelyenough to be precise,

but it is also importantthat we can confidentlyclaim that 95% of thetime our results wouldbe true and there is

only a 5% chance of ourbeing wrong. This is also known as

confidence level.


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The conclusions drawn through the interpretation of theresults should be objective; that is, they should be

based on the facts of the findings derived from actual

data,Not on our subjective or emotional values. For instance:

A hypothesis Greater participation in decision making will

increase organizational commitment

The H is not supported by the results, the statement is notbased on data, facts or findings and hence is not objective

The more objective in the interpretation of the data, the more

scientific the research investigation becomes.


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Generalizabilityrefers to the scope of applicabilityof the research findings in one organization settingto other settingsuniversal applicability

Obviously, the wider the range of applicability of thesolutions generated by research, the more useful the

research is to the users.For instance: If a researchers findings thatparticipation in decision making enhancesorganizational commitment are found to be true in avariety of manufacturing, industrial, and serviceorganizations, then there is generalizability

The more generalizable the research, the greater itsusefulness and value.


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Simplicity in explaining the phenomena or problemsthat occur, and in generating solutions for theproblems, is always preferred to complex researchframeworks that consider an unmanageable numberof factors.

For instance, if 2-3 specific variables in the worksituation are identified, which when changed wouldraise the organizational commitment of theemployees by 45%,

Therefore, the achievement of a meaningful andparsimonious, rather than an elaborate andcumbersome, model for problem solution becomes acritical issue in research.


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Management research isnot

exact

100% scientific research isnot possible

Difficulties encountered inthe

measurement and collectionof

data in the subjective areasof

feelings, emotions, attitudes,

and


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One of the primary methods of scientificinvestigation is the hypothetico-deductive method.

Deduction and InductionsAnswers to issues can be found either bythe process of deduction or the process ofinduction, or by a combination of the two.


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Deduction is the process by which we arrive at

a reasoned conclusion by logical generalization

of a known fact.

Example: we know that all high performers are highly

proficient in their jobs.

If John is a high performer, we then conclude that he

is highly proficient in his job


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Induction is a process where we observe certain

phenomena and on this basis arrive at

conclusions.

In other words, in induction we logically

establish a general proposition based on

observed facts.


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Observation of trends, changes in behaviour pattern

Managers are always sensitive to and aware of what ishappening in and around the workplace.

Preliminary information gathering Changes in attitudes, behaviors, communication patterns

and styles can be picked up by managers who aresensitive to the various differences.

Unstructured interviews followed by structured interviews

seeking of information in depth, of what is observed. Followed by survey of literature

This information would give additional insight of possiblefactors that could be operating in particular situation-


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Theory information, the next step is an attempt tointegrate all the information in a logical manners, sothat the factors responsible for the problem can beconceptualized and tested.

The theoretical framework formulated is often guided

by experience and intuition. In this step the critical variables are examined as to

their contribution or influence in explaining why theproblem occurs and how it can be solved. Thenetwork of associations identified among the variables

would then be theoretically woven together withjustification as to why they might influence the

problem.


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It is the next logical step after theory formulation.

From the theorized network of associations among the variables,certain testable hypotheses or educated conjectures can be

generated. For instance, one might hypothesize that if a sufficient

number of items are stocked on shelves, customer

dissatisfaction will be considerably reduced.

This is a hypothesis that can be tested to determine if the

statement would be supported.

Hypothesis testing is called deductive research.

Sometimes, hypotheses that were not originally formulated do

get generated through the process of induction. That is after data

are obtained.

Generally, in research, hypotheses testing through deductive

research and hypotheses generation through induction are both

common.


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After the development of the hypotheses,data with respect to each variable in thehypotheses need to be obtained.

In other words, further scientific data

collection is needed to test the hypothesesthat are generated in the study. These data then form the basis for further

data analysis.


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In this step, data gathered are statisticallyanalyzed to see if the hypotheses that weregenerated have been supported.

For instance, to see if stock levels influencecustomer satisfaction, one might want to do acorrelational analysis and determine therelation ship between the two factors.

Analysis of both quantitative and qualitative

data can be done to determine if certainconjectures are substantiated.


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Deduction is the process of arriving atconclusions by interpreting the meaning of theresults of the data analysis.

For instance, if it was found from the data analysis

that increasing the stocks was positivelycorrelated to (increased) customer satisfaction(say 0.5), then one can deduce that if customersatisfaction is to be increased, the shelves haveto be better stocked.

Another inference from this data analysis is thatstocking of shelves account for (or explains) 25%of the variance in customer satisfaction.

Based on these deductions, the researcher wouldmake the recommendations on how thecustomer dissatisfaction problem could be

5.@


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1. Case Studies

2. Action ResearchThey are used sometimes to study certain types ofissues.


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Case studies involve in-depth, contextual analyses of similar situationsin other organizations, where the nature and definition of the problem

happen to be the same as experienced in the current situation.

Case study, as a problem-solving technique, is not often undertaken in

organizations because such studies dealing with problems similar to

the one experienced by a particular organization of a particular sizeand in a particular type of setting are difficult to come by.

Moreover authentic case studies are difficult to find because many

companies prefer to guard them as proprietary data.

It should be noted that case studies usually provide qualitative rather

quantitative data for analysis and interpretation. However, the

application of case study analysis to certain organizational issues is

relatively easy.

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Scientific Research- Deductive Inductive