The antecedents and consequents of user perceptions in information technology adoption

Ž .Decision Support Systems 22 1998 15–29

The antecedents and consequents of user perceptions ininformation technology adoption

Ritu Agarwal a,), Jayesh Prasad b

a Information and Management Sciences Department, College of Business, Florida State UniÕersity, Tallahassee, FL 32306-1042, USAb UniÕersity of Dayton, Department of MIS and Decision Sciences, Dayton, OH 45469-2130, USA

Accepted 5 February 1997

Abstract

A common theme underlying various models that explain information technology adoption is the inclusion ofperceptions of an innovation as key independent variables. Although a fairly significant body of research that empiricallytests these models is now in existence, some questions with regard to both the antecedents as well as the consequents ofperceptions remain unanswered. This paper reports the results of a field study examining adoption of an informationtechnology innovation represented by an expert systems application. Two research objectives that have both theoretical andpractical relevance motivated and guided the study. One, the study challenges an assumption which is implicit in technologyacceptance models: that of the non-existence of moderating influences on the relationship between perceptions and adoptiondecisions. Specifically, the study examines the effects of an important moderating influence – personal innovativeness – onthis relationship. Two, the study seeks to shed further light on the determinants of perceptions by examining the relativeefficacy of mass media and interpersonal communication channels in facilitating perception development. Theoretical andpractical implications that follow from the results are discussed. q 1998 Elsevier Science B.V.

Keywords: Information technology adoption; Personal innovativeness; Communication channels; Expert system adoption

1. Introduction

Computing technology and information systemsrepresent substantial investments for organizations;investments on which they hope to realize a return inareas such as efficiency and improved decision mak-ing. Simply acquiring the technology, however, isoften not sufficient; in order to obtain the anticipatedbenefits, it must be used appropriately by its in-tended users. This problem, variously labelled infor-

) Ž .Corresponding author. Tel.: 904 644-7890; e-mail:[email protected]

mation systems implementation, technology accep-tance, and technology adoption, has persisted in theinformation systems literature spanning over two

w x.decades 26,11,15 . In fact, one of the hypothesizedreasons for the productivity paradox is that systemsacquired are never used and therefore, the gains inproductivity realized from investments in informa-tion technology have not been at expected levelsw x35 .

New information technologies have often beentreated as innovations for target users. Althoughusers in recent times have had significantly moreopportunities to be socialized with information tech-

0167-9236r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.Ž .PII S0167-9236 97 00006-7

( )R. Agarwal, J. PrasadrDecision Support Systems 22 1998 15–2916

nologies, the rapid pace of technology developmentusually means that every new technology representsa fairly major change over the previous one. Forexample, for a user who is comfortable with a text-oriented interface like DOS, a direct manipulationinterface represents a major innovation, although itprovides roughly equivalent functionality. This pro-cess of innovation adoption has been studied in a

w xvariety of contexts 27,36 and characterized as acomplex behavioral and social phenomenon.

Writers who have examined the problem of newinformation technology acceptance have drawn ex-tensively from theories developed in innovationadoption and in social psychology; and several mod-els have been proposed to guide inquiry into this

w xphenomenon 11,22,4 . Despite the existence of sev-eral models and despite some divergences in hypoth-esized relationships, a common theme underlyingthese models is the inclusion of perceptions of aninnovation as key independent variables. For in-

w xstance, Rogers’ 36 view of the diffusion of innova-tions regards perceptions as antecedents to the deci-sion to adopt the innovation. The technology accep-

w xtance model 11 , and its precursor, the theory ofw xreasoned action 17,2 , both postulate that percep-

tions or beliefs about the innovation are instrumentalin the development of attitudes that eventually resultin system utilization behavior. Given the persistenceof perceptions in the research literature, the focalconcerns of this study are with the antecedents aswell as the consequents of perceptions.

Although a fairly significant body of research thatempirically tests these alternate models and theories

w xis now in existence 1,13,28,38 , some questions withregard to the role of perceptions in innovation adop-tion remain unanswered. Empirical work in innova-

w xtion diffusion research 29 suggests that perceptionsare directly instrumental to the adoption decision anddoes not acknowledge the existence of moderatinginfluences. There is, however, support for the ideathat perceptions can play differential roles in adop-tion decisions depending on adopter characteristicsw x w x36 . Whereas the theory of reasoned action 17 andits specialization to the domain of information sys-

w xtems, the technology acceptance model 11 bothpostulate the existence of a mediating construct be-tween perceptions and adoption decisions, that of apotential adopter’s attitude, neither one of them ex-

plicitly supports the possibility of any moderatinginfluences on this relationship.

Besides the lack of attention paid to the possiblycontingent relationship between perceptions and theadoption of new information technology, there isconsiderably less work done in examining what leadsto the development of perceptions about an innova-tion. In particular, the relationship between howinformation is obtained and the development of per-ceptions about the innovation has not been exten-sively studied. According to the theory proposed by

w xRogers 36 , communication channels play a domi-nant role in the development of such perceptions.Although the role of different types of communica-tion channels in facilitating information technology

w xadoption has been investigated by others 42,32,4 ,these studies have typically examined the effects ofalternate communication channels on the adoptiondecision without taking the intervening perceptionsinto account. Consequently, little is known about therelative efficacy of different communication chan-nels for the development of perceptions. The pivotalrole played by perceptions in technology acceptancemodels and theories clearly highlights the need formore work.

We report the results of a field study conducted toexamine user adoption of an information systemsapplication. The general motivation underlying thestudy is concern with the broad problem of theadoption of new technologies. The specific motiva-tion is to further examine the issues discussed abovewith regard to the antecedents and consequents ofperceptions about an information technology innova-tion. Two research objectives that have both theoreti-cal and practical relevance motivated and guided thestudy. One, the study challenges an assumption whichis implicit in technology acceptance models: that ofthe non-existence of moderating influences on therelationship between perceptions and adoption deci-sions. Specifically, we examine the effects of a keymoderating influence – personal innovativeness – onthis relationship. Two, the study seeks to shed fur-ther light on the relative efficacy of mass media andinterpersonal communication channels in facilitatingthe development of perceptions.

In addition to addressing some theoretical andempirical gaps in existing work with regard to per-ceptions and technology acceptance, the research

( )R. Agarwal, J. PrasadrDecision Support Systems 22 1998 15–29 17

reported here has implications for practice also.Clearly, the overall problem of technology accep-tance is a key issue for organizations who investsubstantial resources in information technology. In-sights into how perceptions about a new informationtechnology may be developed as well as the effectsuch perceptions have on adoption decisions couldassist those responsible for implementing new infor-mation technologies. If the existence of moderatingeffects is confirmed, it would alert managers to thepossibility that some individuals may require more

w xintervention 14 in order to make a positive adoptiondecision. An understanding of the relative impor-tance of alternate communication channels in devel-oping perceptions would help managers make betterinformed and more effective resource allocation de-cisions with regard to these channels.

The paper is organized as follows. Section 2presents the theoretical background and sets up thespecific research hypotheses constructed to addressthe two research objectives. The study context, con-duct, as well as the operationalization of researchvariables are described in Section 3. Data analysis,results, and discussion are presented in Section 4.The implications of these results for theory andpractice are drawn in the last section.

2. Theoretical background and research hypothe-ses

The research model underlying this study is shownin Fig. 1. The overall model is conceptually based on

w xRogers’ 36 work where he posits a theory of the

diffusion of innovations. In this theory, innovationadoption is viewed as a process of uncertainty reduc-tion and information gathering. Information aboutthe existence of the innovation as well as its charac-teristics and features flows through the social systemwithin which adopters are situated. Potential adoptersengage in information seeking behaviors to learnabout the expected consequences of using the inno-vation; an assessment and evaluation of this informa-tion determines adoption behavior. Thus, communi-cation channels and information processing by poten-tial adopters play a central role in Roger’s theory.This conceptualization of the innovation process,

w xalthough criticized by some 20 , nevertheless hasw x.received wide support from several studies 4,5 .

In innovation diffusion theory, a significant out-come is an individual’s decision whether to accept or

w xreject the innovation. According to Rogers 36 , thisdecision is predicated upon five key perceptionsabout the characteristics of the innovation: relativeadvantage, compatibility, complexity, trialability, andobservability. Although many other factors such asorganizational characteristics, innovator character-

w xistics, etc. 22 have been hypothesized as influenceson technology adoption, the crucial role played bysuch perceived characteristics in driving the adoptiondecision has been recognized in a variety of researchw x. w x11,29,37 . Recently Moore and Benbasat 29 ex-panded the perception set to include seven perceivedcharacteristics of an innovation. However, in ameta-analysis of much of the same work on innova-tion characteristics as utilized by Moore and Ben-

w x w xbasat 29 , Tornatzky and Klein 39 found that only

Fig. 1. The research model.


three innovation characteristics – compatibility, rela-tive advantage, and complexity – have been relatedconsistently to adoption. Given the persistence ofperceptions in the research literature on innovationadoption, the central focus of this study is on twobroad issues: one, the possibly contingent effect ofthese perceptions on adoption decisions, and two, theprocesses involved in the development of these threeperceptions.

2.1. Perceptions and their consequents

As noted above, although several perceptions havebeen proposed and, to a limited extent, shown to bepredictors of adoption behavior, only three haveconsistently emerged as salient. RelatiÕe adÕantagecaptures the extent to which a potential adopterviews the innovation as offering an advantage overprevious ways of performing the same task. Recentempirical studies in the information technology do-

w xmain 1,29,13,21 support the importance of relativeadvantage in predicting adoption behavior. Although

w xDavis et al. 13 labelled the construct "perceivedw xusefulness", Moore and Benbasat 29 claim that

relative advantage is very similar to the notion ofw xusefulness in the technology acceptance model 13 ,

where usefulness is defined as the user’s subjectiveassessment of the extent to which using an innova-tion will increase his or her job performance within agiven organizational context.

A second construct, ease of use, recurs in severalstudies as a significant determinant of adoption be-

w xhavior 13 . Ease of use is similar in definition tow xRogers’ notion of complexity 29 and encapsulates

the degree to which a potential adopter views usageof the target technology to be relatively free of effortw x13 . Innovations that are perceived to be easier touse and less complex have a higher likelihood ofbeing accepted and used by potential users.

The final user perception examined here, compat-w xibility, was proposed by Rogers 36 and subse-

quently confirmed to be a good predictor of usagew xbehavior by Moore and Benbasat 29 . Compatibility

is "the degree to which an innovation is perceived asbeing consistent with the existing values, needs, and

w x Ž .past experiences of potential adopters" 36 p. 195 .All three perceptions are relative concepts and notinnate attributes of the innovation, and can be per-ceived differently by different individuals.

Prior empirical work grounded in diffusion ofinnovations theories that has examined the effects of

w xperceptions on adoption decisions 29 implicitly as-sumes that this effect is invariant across adopters.Consequently, no intervening moderating or mediat-ing variables have been examined. The existence ofmediating effects – viz., attitude toward the behavior– has been acknowledged in other research in tech-

Žnology acceptance e.g., in the technology accep-w x.tance model 13 but moderating effects have not

been explicitly considered in these research streams.This assumption that the influence of perceived char-acteristics of an innovation in adoption is identicalfor all adopters is particularly surprising in light of

w xthe fact that Rogers 36 himself points to the con-trary. For example, he recognizes that perceptions ofrelative advantage are used differently to arrive atthe adoption decision by adopters from differingsocial contexts. In fact, research in social psychologyhas shown that several factors such as environmentalcharacteristics and personality characteristics canmoderate the development of behavioral intentionsw x25 . Hence, the relationship between perceptionsand the adoption decision can potentially be moder-ated by personality factors; our first research objec-tive is to examine the influence of one such factor,personal innovativeness.

Research in individual decision making suggeststhat individual choices are based on both beliefsabout outcomes as well as the utility an individual

w xassociates with a particular consequence 18,34 .Thus, two individuals may hold identical beliefs butmay make different decisions based on their personalutility functions. One aspect of this utility is the

w xinherent risk taking propensity of an individual 23 .In the context of innovation adoption decisions, anindicator of risk seeking behavior is the personalinnovativeness of an individual adopter. Consistentwith the construct defined by Flynn and Goldsmithw x19 , personal innovativeness is the willingness of anindividual to try out an innovation. Innovations areinherently risky, and although the potential benefitsof adoption may be recognized by all adopters, thereis no guarantee that adoption will, in fact, producethe anticipated consequences. Of two individualswho perceive the innovation as equally desirable, themore innovative individual may be more willing toadopt the innovation in the face of uncertainty about


benefits. Similarly, as a result of their risk takingpropensity, more innovative individuals may developstronger intentions to use the innovation at the samelevel of perceived complexity and congruence withwork style as a less innovative individual. Personalinnovativeness as a moderator has been utilized in

w xother work also 24 and leads to the first threeresearch hypotheses:

H1: Personal innovativeness positively moderatesthe relationship between perceptions of relativeadvantage and the decision to adopt an innovation.H2: Personal innovativeness positively moderatesthe relationship between perceptions of ease of useand the decision to adopt an innovation.H3: Personal innovativeness positively moderatesthe relationship between perceptions of compati-bility and the decision to adopt an innovation.

2.2. The antecedents of perceptions

w xAs noted by Zmud 42 , the adoption of an inno-vation is an activity entailing extensive communica-

w xtion. In Rogers’ 36 view of the adoption process,communication channels are directly instrumental inthe development of perceptions; individuals areposited to use these channels for uncertainty reduc-tion and information gathering. Although the role ofcommunication channels in innovation adoption has

w x.been recognized by prior research 42,32 , no workthat we are aware of has specifically investigated theeffects of communication channels on the develop-ment of these key antecedents to the adoption deci-

w xsion. For example, Zmud 42 examined the effectsof many different varieties of external informationchannels in facilitating the adoption of modern soft-ware practices among systems professionals. How-ever, his study did not look at the effects of thesechannels on the development of perceptions. The

w xstudy by Nilakanta and Scamell 32 of databasedevelopment practices was similar in that it did notinclude a consideration of perceptions. Although theydid examine the effects of both communicationsources as well as channels on adoption decisions,the distinction they draw between channels andsources is not very clear; they also do not character-ize channels in terms of their relative effectiveness infacilitating adoption.

The role of communication channels in innovationadoption is more explicitly addressed by Rogers whodistinguishes between two broad channel types: massmedia channels which enable large amounts of infor-mation to reach a wide audience, although the infor-mation is depersonalized, and interpersonal channels,which involve customized communication. Channelsare further classified as cosmopolite, i.e., originatingoutside the social system being examined, or localite,i.e., internal to the system under study. Differenttypes of channels facilitate the dissemination of dif-ferent types of information. For example, mass me-dia and cosmopolite channels are hypothesized asbeing relatively more effective in creating awarenessabout the overall worth of the innovation in generaland fostering pro-innovation attitudes, while localiteand interpersonal channels help emphasize the per-sonal value of the innovation to the potential adopter.As noted by Rogers, "mass media channels are toogeneral to provide the specific kinds of reinforce-ment that an individual needs to confirm hisrher

w x Ž .beliefs about the innovation" 36 p. 170 . Supportfor Roger’s characterization of communication chan-nels and the role they play in imparting differenttypes of information about the innovation has been

w xprovided recently by Brancheau and Wetherbe 4 inthe context of individual adoption of spreadsheet

w xsoftware. Brancheau and Wetherbe 4 , however,stated hypotheses related to the role of communica-tion channels in adoption stages and did not examinethe effects of channels on perceptions.

The importance of communication channels infacilitating desired organizational behaviors is em-phasized and supported by an alternate research

Ž .stream: media richness theory MRT . According tow xMRT 9 , information processing takes place in orga-

nizations to reduce uncertainty and resolve equivo-cality for organizational actors. The theory positsthat certain media are more efficacious in addressingthe needs of uncertainty reduction while others arebetter for equivocality resolution. Uncertainty reduc-tion requires the exchange of large amounts of fairlystructured data while equivocality resolution de-mands that all participants in the communicationachieve semantic convergence. Thus, the ability toquestion, challenge, and obtain feedback is crucial

w xfor equivocal situations. Daft and Lengel 9 suggestthat structural mechanisms or communications chan-


nels used for information dissemination such as for-mal rules and regulations, planning, and direct orface-to-face contact can be situated along a "rich-ness" continuum, based on their relative ability toaddress the needs of uncertainty or equivocality.

Following from the discussion above, there ap-pears to be a conceptual correspondence between theclassification of media as utilized by innovation dif-fusion theory and the concept of media richness asexplicated in MRT. Mass media channels fall on theless "rich" end of the continuum; their efficacy intransmitting large amounts of structured data andknowledge to reduce uncertainty is recognized inboth paradigms. Conversely, interpersonal channelswhich involve direct contact and feedback are more"rich" because of the personalized communicationthey entail. Consequently, they are of value whenthere is a need to address differing viewpoints oropinions and to persuade, i.e., to resolve equivocal-ity.

In the research model underlying this study, con-sistent with innovation diffusion theory, communica-tion channels are responsible for the dissemination oftwo kinds of information about an innovation: gen-eral knowledge about the innovation, as well asspecific knowledge that is personalized for individu-als. As proposed by MRT and supported by diffusiontheory, the former type of information disseminationis facilitated by less rich media or mass mediachannels. As these channels are capable of deliveringinformation to large numbers of people, they can be

w xinstrumental, through a multiplicative effect 16 , inraising the overall level of awareness in a socialsystem. In this context, awareness does not connotesimply acknowledging the existence of an innova-tion; in order for awareness to play a role in subse-quent adoption behavior, it must reflect a generallyfavorable attitude toward the innovation. The lattertype of information, on the other hand, is focused onthe expected personal outcomes of adopting theinnovation, and consequently, can be more valuablein developing individual perceptions about the inno-vation. Personalization and the ability to obtain an-swers to questions such as "What will its advantagesand disadvantages be in my situation?", "How com-plex will the innovation be for me to use?", and"How congruent is the innovation with my work

w xstyle?" 36 are key to successful communication

here. Following from MRT, "richer" channels of theinterpersonal variety are expected to be of greatervalue in the dissemination of such specific informa-tion.

A priori expectations about the role of differentcommunications channels are summarized in the re-search hypotheses below:

H4. Use of mass media channels is associated withmore positive awareness than interpersonal chan-nels.H5. Use of interpersonal channels is associatedwith more positive perceptions of relative advan-tage than mass media channels.H6. Use of interpersonal channels is associatedwith more positive perceptions of ease of use thanmass media channels.H7. Use of interpersonal channels is associatedwith more positive perceptions of compatibilitythan mass media channels.An assumption implicit in the statement of these

hypotheses, consistent with prior research in innova-w xtion adoption 22 , is that not only does the innova-

tion possess some intrinsic, positive value for poten-tial adopters, but the implementors also believe in

w xthe existence of this positive value 36 . Clearlysome innovations originating either within or outsidethe social system being studied may be discardedafter an initial determination has been made that theinnovation does not serve the needs of the system inany substantive way. However, we are interested inexamining innovations that have gone beyond thisstage and whose value is not in question to imple-mentors. Consequently, it is reasonable to assumethat any messages or information transmitted aboutthe innovation would be focused on emphasizingsuch positive value; and hence, depending on thechannel, would serve to heighten and sharpen eitherpositive awareness or positive perceptions.

Recall that we have defined awareness as a favor-able attitude toward the innovation. This notion of afavorable attitude is important because of the likeli-hood that information about many innovations maysimultaneously be flowing through the social system.It is an adopter’s acknowledgement that one or moreof these innovations hold promise because of their

w xability to address a felt need 41 that causes infor-mation seeking behavior. Such awareness of theinnovation, although not a direct predictor of adop-


tion behavior, compels potential adopters to seekfurther information. This view is consistent withprior research where awareness precedes other pro-

w xcesses in innovation adoption 22 . Awareness is,thus, a crucial prerequisite to the development ofspecific, positive perceptions which, in turn, lead toinnovation adoption. Support for such an effect is

w xalso provided by Ajzen and Fishbein 2 in theirconceptualization of general attitude toward an ob-ject. In their theory of reasoned action, this generalattitude is treated as an external variable that influ-ences behavioral beliefs about the consequences ofadopting the target innovation. Note that this attitudetoward an object or target is different from attitude

Ž .toward the behavior such as actual system usage ;the latter is a consequence of perceptions whereasthe former is an exogenous factor in their theory andis a determinant of perceptions. The final set ofhypotheses examined here is, thus,

H8. Awareness about the innovation will posi-tively influence perceptions of relative advantage.H9. Awareness about the innovation will posi-tively influence perceptions of ease of use.H10. Awareness about the innovation will posi-tively influence perceptions of compatibility.

3. Methodology

3.1. The study context

This study was conducted at a Fortune 500 corpo-ration headquartered in the northeastern United StatesŽ .henceforth, Beta . Beta is a manufacturing firm andis the largest in the world in its industry, with annualsales over $4 billion. Streamlining the organizationalprocesses used to deliver a quality product withprompt service is a major strategic goal which man-agement determined could be achieved through ordercycle automation. To meet this goal, a decision wasmade by Beta management to develop a knowledge-based system to support the configuration and order-ing of its products.

The information systems application, henceforthCONFIGURATOR, configures a set of parts for aparticular product series based on customer request.While this is not a task that requires considerableexpertise and heuristics in the sense that is conven-

tionally understood, its complexity arises from thenumber of design combinations that have to be con-sidered before an equipment model can be chosen tomeet a customer need. The potential payoff rests inthe ability of the system to address several weak-nesses that were inherent under the old method forconfiguring such equipment; including order process-ing delays attributable to configuration errors, ship-ment delays when some of these errors propagated tothe manufacturing and assembly floor, and pricingerrors.

CONFIGURATOR was conceived for use bysalespeople or sales assistants to fill orders which are

Žcomplete and correct i.e., devoid of any design.dependency errors . Design dependencies are stored

in a database and accessed by the knowledge-basedsystem. Valid orders prepared by CONFIGURATORthen serve as key inputs for pricing and bill ofmaterial preparation. Although the initiative for thedevelopment of the system came from the corpora-tion, the actual users of the system for the purposesof this study are salespeople and order correspon-dents who work out of field offices; some of whichare owned by the corporation, while others are inde-pendent distributors. The system evolved following aprototyping development methodology that washighly user-centered; feedback from users was con-tinually solicited and incorporated into the design ofthe system. The production version of the systemwas rolled out to the field following a phased imple-mentation plan. CONFIGURATOR’s functionality aswell as the manner in which it was developed andimplemented are consistent with the assumption ofpositive worth underlying the hypotheses stated pre-viously. In fact, the system was designed to addressa sharply felt need of both the corporation, becauseof its desire to remain competitive, and potentialusers, because their compensation depended on theirability to provide reliable service to customers in atimely manner.

A field study of the users of CONFIGURATORwas conducted following the design and pretest of asurvey instrument for data collection. A total of 306surveys were distributed to all potential users of the

Ž .system i.e., salespeople and order correspondents ,with a total of 76 usable responses being returned fora response rate of approximately 25%. At the time ofdata collection, six months had elapsed since roll-out


Table 1Research constructs and definitions

Construct Definition

RELADV Perceptions of relative advantageEASEUSE Perceptions of ease of useCOMPAT Perception of innovation being compatible

with innovator’s work behaviorINTENTIONS Intentions to use the innovation in the futurePERINN The personal innovativeness of a potential

adopterAWARENESS A positive attitude toward the innovationCOMMCHAN Communication channel type: mass media

or interpersonal

Ž .began and all field personnel i.e., salespeople nowhad access to the system. This point in time afterinitial roll out was viewed by the sponsoring man-ager as appropriate in that all potential adopterswould have had an opportunity to obtain informationabout the system and to have made an adoptiondecision, even if they did not have the opportunity tobegin using the system.

3.2. Operationalization of Õariables

Table 1 lists the various constructs and the labelsused for them in the subsequent discussion. Althoughthe adoption decision could potentially be measured

w xusing a binary construct, Wynekoop et al. 40 em-phasize that extent of actual use is a far moresensitive measure of adoption success. However, dueto the timing of data collection and the fact that thesystem had not been in place long enough for poten-tial adopters to engage in routinized use, we opera-tionalized the adoption decision as intentions to usethe system in the future. Indeed, previous researchw x2,13 has shown that actual use is predicted byintentions to use. Intentions were measured through atwo item scale, where the items are consistent with

w xthose typically recommended by TRA 2 .As reviewed previously, three key perceptions

were included in the research model: relative advan-tage, ease of use, and compatibility. The items forthese scales were obtained from the work of Moore

w xand Benbasat 29 . Moore and Benbasat subjectedthe user perception scales to an intensive validationprocedure to determine both reliability and validityand the scales were, hence, deemed a satisfactorysource for the present study. To keep the length of

the instrument reasonable, the items for each percep-tion were selected from those developed by Moore

w xand Benbasat 29 based on face validity for theparticular system being examined. Each scale con-sisted of a minimum of three items: statements re-garding CONFIGURATOR that respondents scoredon a 7-point Likert-type scale with the endpointsbeing "strongly disagree" and "strongly agree".Personal innovativeness was assessed using a three-item scale following the recommendations of

w xLeonard-Barton and Deschamps 24 and Flynn andw xGoldsmith 19 . In keeping with the guidelines pro-

w xvided by Flynn and Goldsmith 19 , the items refer toŽdomain-specific i.e., pertinent to the use of new

.sales tools innovativeness as opposed to generalinnovativeness. Recall that awareness was defined asa pro-innovation attitude that is conceptually similarto the construct of attitude toward the object or targetw x2 ; the three items used for this construct are basedon this definition. See Appendix A for all scales anditems.

Factor analysis to confirm the construct validityof all the scales could not be performed adequatelybecause of the limitation of sample size relative tothe total number of items in the scales. However,

w xMoore and Benbasat 29 rigorously developed theperception scales and demonstrated their favorablepsychometric properties. While all the other scalesare based on prior published work, the only twoscales that have not been used extensively in priorwork are awareness and personal innovativeness. Inorder to further establish construct validity, a factoranalysis using varimax rotation with six items –those comprising the awareness and personal innova-

Table 2Factor analysis for awareness and personal innovativeness items

Items Factor 1 Factor 2

A1 0.89292 0.13494A2 0.88966 0.34059A3 0.85710 0.13518P1 0.18370 0.81915P2 0.17697 0.80057P3 0.14655 0.69131

Eigen value 2.61 1.53Percent of variance 43.5 25.6

Notes: A-items are awareness; P-items are personal innovative-ness.


Table 3Descriptive statistics

Construct Number of items Reliability Mean S.D. Correlations

1 2 3 4 5 6

1. RELADV 6 0.93 5.21 1.31 1.00) )2. EASEUSE 5 0.80 4.64 1.20 0.72 1.00) ) ) )3. COMPAT 3 0.74 4.41 1.49 0.80 0.72 1.00) ) ) ) ) )4. INTENTIONS 2 0.84 5.61 1.30 0.65 0.50 0.60 1.00) ) ) ) ) ) )5. PERINN 3 0.66 4.93 1.23 0.28 0.32 0.40 0.36 1.00) ) ) ) ) ) ) )6. AWARENESS 3 0.84 5.87 1.12 0.49 0.39 0.32 0.62 0.21 1.00

Notes: Cronbach’s alpha is reported for reliability.All constructs are measured on a 1–7 scale.Pearson correlation coefficients are reported.) Significant at p-0.05; ) ) significant at p-0.01.

tiveness scales – was run. Results of the factoranalysis are shown in Table 2; the results reinforcethe convergent and discriminant validity of these twoscales.

Interviews with the sponsoring manager revealedthat five alternative media channels were available topotential adopters. Salespeople could obtain informa-tion about CONFIGURATOR by attending a seriesof presentations made by the project leader promot-ing and describing CONFIGURATOR and the pro-cedures for its use; by viewing a video that containedessentially the same material; by reading a manualthat described the system and its operation; throughlearning by doing, trial and error, and hands onexperimentation using the context-sensitive systemhelp and error detection facility; or by asking desig-nated experts for information, assistance, and clarifi-

w xcations. According to Rogers 36 , mass media chan-nels exhibit the characteristics of being able to reacha large audience rapidly and creating awareness;however, they do not possess the capability to pro-vide information customized to an individual easily.On the other hand, interpersonal channels providethe capability for feedback and customization. Fol-lowing this conceptual distinction made by Rogersw x36 , the first three channel types were classified asmass media channels, while the last two channeltypes were categorized as interpersonal channels. Amajority of the respondents selected one of these fivechannels listed on the instrument; only seven se-lected more than one, but in each case their selec-tions belonged to exactly one category: either massmedia or interpersonal.

Prior to data analysis mass media channels werecoded 1 and interpersonal channels coded 0. Com-munication channel information was missing for onerespondent; of the remaining 75 observations, 57respondents indicated they utilized mass media chan-nels while 18 used interpersonal channels.

4. Results and discussion

Descriptive statistics for all research variables areprovided in Table 3. Included are the number ofitems comprising each scale and Cronbach’s alpha

w xfor scale reliability 8 . The reliability coefficient ofone scale, personal innovativeness, is slightly lessthan the value of 0.70 often recommended for field

w xstudies 33 . The implications of this reliability forinterpreting the results are discussed subsequently.

Sample size did not permit a simultaneous test ofall hypotheses and, hence, alternative analysis tech-niques were utilized. Table 4 contains the results ofregression procedures used to address hypotheses 1through 3. The following analysis was conducted: amultiple regression with intentions as the dependentvariable and each of the three perceptions and per-sonal innovativeness as independent variables, to-gether with a multiplicative term for personal inno-vativeness and each of the three perceptions wasrun. 1 A significant coefficient for the multiplicative

1 The interaction terms were introduced into the regressionequation after the rest of the independent variables. The change inR2 was significant at p-0.05.


Table 4Regression analysis results

2Relationship Beta p-value Adj. R2 ) )INTENTIONS s RELADVq 0.416 0.000

EASEUSEq nsCOMPATq nsPERINNq ns 0.47RELADV ns=PERINNqEASEUSE ns=PERINNq

) )COMPAT 0.338 0.005=PERINN

Notes: standardized betas are reported; ) ) p-0.01; ns, not signif-icant.

terms was interpreted as suggestive of interactionw xeffects 3 . Although Table 3 shows that most of the

user perceptions are significantly correlated with eachother, an examination of variance inflation factors

w xshowed that multicollinearity was not significant 31 .Hence, regression analysis was appropriate.

An analysis of residuals was also performed toverify that the assumptions underlying regressionanalysis – independence, homoscedasticity, and nor-mal distribution of the error terms – were not vio-lated. All assumptions were confirmed except homo-geneity of variance. A square transformation of thedependent variable eliminated this problem. Asshown in Table 4, personal innovativeness had asignificant moderating effect on the relationship be-tween perceptions of compatibility and usage inten-tions. Neither of the other two interactions weresignificant. Thus, hypotheses H1 and H2 were notsupported while H3 was.

The relative effectiveness of the two communica-tion channel types for the enhancement of awarenessŽ . Ž .H4 was examined by means of a t-test Table 5 .The hypothesis was supported at p-0.05; interper-

Table 5t-Test results for channel type effects on awareness

Channel type Mean t-value p-value)Mass media or passive 6.06 y2.41 0.019

Interpersonal or active 5.36

) Significant at p-0.05.

sonal channels were less effective than mass mediachannels for enhancing awareness.

The remaining hypotheses, H5 through H10, weretested by means of a multivariate multiple regressionŽ .run using the SPSS-X MANOVA procedure , withthe three perceptions as dependent variables and thecommunication channel type and awareness as theindependent variables. In order to control for differ-ences in the length of time for which respondentshad been exposed to the particular channel type, anadditional independent variable – EXPOSURE, theelapsed time since the particular channel type beganto be utilized by each respondent to learn about theinnovation – was also included in the analysis. Theresults of this procedure are presented in Table 6.The overall relationship between the two sets of

Žvariables i.e., perceptions, and communication chan-.nel type and awareness was significant using Pillai’s

criterion. All of the hypotheses except H6, whichproposed that the use of interpersonal channel typeswould be associated with more positive ease of useperceptions than the use of mass media channels,were supported at p-0.05 or better.

As predicted by the theory underlying the re-search model, seven of the 10 hypotheses weresupported. The lack of support for H1 and H2, whichhypothesized interaction effects between perceptionsand personal innovativeness and their relationship tointentions, is surprising at first glance. Moderatingeffects were confirmed for compatibility but not forthe other perceptions. On further reflection, however,there does appear to be one key difference betweenperceptions of relative advantage and ease of use onthe one hand and compatibility on the other. Of thethree, compatibility is the only perception that indi-cates a need for a significant modification of workbehaviors on the part of the individual adopter. Itmay be the case that the cognitive costs associatedwith a lack of compatibility are so high that it needsa higher level of risk-seeking behavior on the part ofthe individual to overcome this hurdle. In otherwords, potential adopters who are inherently moreinnovative will make the same adoption decisions asthose who are less innovative at significantly lowerlevels of perceived compatibility.

Further analysis of this result was performed bydividing the sample into two groups based on themedian value of personal innovativeness. Intentions


Table 6MANOVA results

Pillai’s test Relative advantage Ease of use Compatibility2 2 2Fs2.928, ps0.003 R s0.270, ps0.000 R s0.109, ps0.013 R s0.132, ps0.006

Beta p Beta p Beta p) )COMMCHAN y0.269 0.014 y0.087 0.465 y0.252 0.034) ) ) ) )AWARENESS 0.449 0.000 0.340 0.005 0.287 0.017) )EXPOSURE 0.231 0.032 0.156 0.187 y0.235 0.044

) Significant at p-0.05; ) ) significant at p-0.01.

were regressed on the three perceptions for eachsubsample to examine the nature of the effects ofcompatibility for each of the two groups. Compatibil-ity had a positive coefficient for both groups but wasstatistically significant only for the more innovativegroup. This result is suggestive of a somewhat linearand sequential approach to the consideration of theperceived attributes of the innovation. Less innova-tive individuals need to be convinced first about theother perceptions that are believed to be important,

w xi.e., the utility and complexity of the innovation 39 ;without such conviction, compatibility may neveremerge as a determinant of their decision making.More innovative adopters might be more willing to

Žaccept the utility and ease of use or lack of com-.plexity of the innovation at face value; perhaps they

tend to look beyond these perceptions and seek toŽevaluate the extent of behavior modification due to

.compatibility considerations that a positive adoptiondecision might entail.

The lack of support for H6 suggests that there wasno difference in the effectiveness of the two types ofcommunication channels in enhancing ease of useperceptions. Following from the theory, we hypothe-sized that interpersonal channel types would be moreeffective than mass media channel types. One possi-ble explanation for this finding is that the systemwas inherently easy to use and, therefore, interper-sonal channels did not add anything over and abovemass media channels. Indeed, user friendliness andease of use was an extremely important design re-quirement for the system, given that the intendeduser population was not highly computer literate.This explanation, however, does not appear to beconfirmed by the data as the mean value for ease ofuse was towards the mid-point of the scale. Thus, thefact that H6 was not supported might well be an

idiosyncratic result for the technology and sampleexamined here.

Before presenting the implications of our results,certain limitations which constrain their interpreta-tion need to be acknowledged. The fact that thestudy was conducted in the field is both a strengthand a limitation. The strength lies in the realism ofthe sample and the study context; the weakness is thelack of controls inherent in a field study. However,precautions were taken wherever possible in theconduct of the study to mitigate any such weak-nesses. For example, in a field study it was notpossible to ensure that the elapsed time between theuse of a communication channel and data collectionwas the same for all respondents. Although we alle-viated this potential problem by utilizing a controlvariable which took the influence of time into ac-count, a more precise measure might have been theactual number of hours that each respondent usedeach channel type for gathering information aboutthe system. Further, although an alternative explana-tion for our results might be that perceptions are aresult of individual differences such as personal in-novativeness, and that these differences also guidethe choice of communication channel, this is unlikelyas a t-test revealed that there was no difference inpersonal innovativeness across the two channel types.

We had a response rate of 25%, not atypical offield research, which may have contributed to someunknown response bias. A profile of the overallpopulation of users was not available to comparewith the profile of respondents. Perhaps some of theinteraction effects did not emerge as significant be-cause the reliability of the personal innovativenessscale was less than ideal. This, however, should notreduce the validity of the relationship found to besignificant. Because of the phased implementation of


the system, respondents had been exposed to thetechnology for differential amounts of time, andhence, had varying opportunities to develop percep-tions about the system. However, they were all at thestage of ‘‘initial use’’ where the technology had notbeen institutionalized and become a part of the regu-lar work behaviors. Finally, the size of our sample,though adequate for the study questions, could beimproved. In spite of this sample size, assumptionsunderlying the analysis procedures used were notviolated. The sample size should not diminish theresults found to be significant. A larger sample sizemight have yielded greater statistical power to detecta significant coefficient for compatibility during sub-sample analysis.

The implications of these results for theory andpractice are discussed next.

5. Implications and conclusions

This study sought to achieve two objectives: one,to investigate the presence of moderating influenceson the relationship between user perceptions aboutan information technology innovation and adoptiondecisions; and two, to examine the relative efficacyof alternative communications channels in the devel-opment of perceptions.

Theoretically, our results suggest that a premiseunderlying some dominant technology acceptancemodels – the absence of moderating influences onthe perceptions to intentions link – may need to bereexamined. Moderation implies that perceptions arenot equally efficacious in developing usage inten-

w xtions for everyone; the theory of reasoned action 17indirectly acknowledges such differences by askingpotential adopters to assess the importance of eachbehavioral belief to them personally. The technol-

w xogy acceptance model 11 , on the other hand, doesnot allow for such differences. We confirmed theexistence of a moderating effect; however, we uti-lized only one key moderating variable: the personalinnovativeness of an adopter. Future work shouldexamine the effects of other individual differencevariables. If our finding of moderation is corrob-orated, researchers who are studying technology ac-ceptance models might wish to consider alternatetheoretical formulations that recognize this effect.

Practical implications that follow from our resultshave to do with organizational initiatives to facilitatethe adoption of new technologies. Extensive work ininnovation adoption has highlighted the key role ofperceptions. Our results suggest that perceptions canplay a different role in adoption for different individ-uals. Organizations might target the most innovativepeople if they wish to implement a system that needsto be utilized only by a subset of employees. Confir-mation of the role that personal innovativeness playsin adoption only serves to underscore the importanceof creating a work atmosphere and organizationalnorms which reward innovative and risk-seeking be-haviors so that individuals have the appropriate in-centives to be personally innovative. This idea wasrecognized over three decades ago by Burns and

w xStalker 6 and continues to be important for organi-zations wishing to avail themselves of information

w xtechnologies for strategic advantage 10 .For systems that need to be adopted by all, orga-

nizations should expect to expend differentialamounts of effort at building perceptions of compati-bility. In this regard, our results underscore the cru-cial importance of the early stages of the systemsdevelopment life cycle for less innovative individu-als. It is critical that their work patterns and flows bethoroughly understood during the systems analysisstage so that systems may be designed to be compat-ible with preferred work flows. Hence, a socio-tech-

w xnical approach to systems design 30 might beneeded so that systems fit in with preferred work-flows and behavior patterns. Methodologies such asprototyping and joint application development mightenable designers to better elicit such preferences.

Since the regression coefficient for compatibilityfor the less innovative group, although positive, wasnot statistically significant, our results do not providea definitive answer to the role of compatibility indetermining intentions. If future work, perhaps utiliz-ing larger samples, replicates the non-significance ofthe coefficient, the possibility of the linear elimina-tion of hurdles to adoption that we alluded to earliershould be investigated further. If the explanation issupported, for less innovative individuals, prior toattempts at enhancing compatibility perceptions, re-sources might better be expended on developingperceptions of relative advantage and ease of use. Of

w xthese two perceptions, other studies 12,21 point to


the predominant influence of perceived utility; hencemanagement might wish to focus attention on rela-tive advantage first.

Communications channels are critical to facilitat-ing innovation adoption. Our study extends the litera-ture on the role of communication channels in inno-vation adoption by examining the relative effects oftwo types of channels for the development of percep-tions. Although the importance of interpersonalchannels has been widely acknowledged in the litera-

w xture 4 , our results suggest that mass media channelsalso have a key role to play. This result is encourag-ing because these channel types are often the moreefficient way to communicate information about aninnovation; their reach relative to cost is greater thanfor interpersonal channels. Organizations need toensure that employees have adequate access to thesechannels through initiatives such as informationalsessions, video tapes, periodical subscriptions and

w xmemberships in professional organizations 42 . Wedo not suggest that interpersonal channels are notimportant; in fact, to the contrary as these channelshave a greater direct effect on perceptions whereasthe less expensive channel types better facilitate onlyan indirect effect through the creation of awareness.Our results point to the feasibility of using a mix ofboth channel types; this is particularly importantwhen resource considerations constrain the use of themore expensive channel varieties.

As is evident from the substantial quantity ofwork in this area, persuading individuals to adopttechnological innovations is a matter of considerableimportance for organizations. In this context of inno-vation adoption, communication plays a central role.The contribution of this work has been to empiricallydemonstrate the existence of moderating influenceson the relationship between perceptions and adoptiondecisions. We have also shown that communicationchannels are instrumental in the development ofperceptions about an innovation; this relationship hasbeen assumed to exist widely in prior research buthas not been confirmed empirically. In particular, wehave identified the process through which mass me-dia channels can facilitate the adoption of new tech-nologies.

Several avenues for future research remain. In ourstudy, communication channels were classified intotwo categories prior to examining their effects. Oth-

ers might wish to investigate the role of individualcommunication channels within a category on thedevelopment of perceptions. This would providegreater insights into the value of specific channels.Due to practical constraints our study was cross-sec-tional in that all measurement was done at a singlepoint in time. Future work could use longitudinalresearch designs to explore similar issues. Finally,this study reflects the ‘‘pro-innovation bias’’ that

w xpervades most research on innovation adoption 36 .While such a technological imperative perspectivedoes have merit, others might wish to use alternative

w xparadigms, e.g., political perspectives 7 to study thephenomena of interest.

Appendix A. Items and scales

A.1. RelatiÕe adÕantage

R1. Using CONFIGURATOR enables me to pro-cess customer quotesrorders more quickly.

R2. Using CONFIGURATOR makes it easier forme to do my job.

R3. Using CONFIGURATOR enhances my effec-tiveness on the job.

R4. Using CONFIGURATOR gives me greatercontrol over my work.

R5. Using CONFIGURATOR improves my pro-ductivity.

R6. Using CONFIGURATOR improves the qualityof work I do.

A.2. Ease of use

E1. I believe that CONFIGURATOR is cumber-some to use.

E2. I believe that it is easy to get CONFIGURA-TOR to do what I want it to do.

E3. Learning to operate CONFIGURATOR is easyfor me.

E4. Using CONFIGURATOR requires a lot ofmental effort.

E5. My interaction with CONFIGURATOR is clearand understandable.


A.3. Compatibility

C1. Using CONFIGURATOR fits into my workstyle.

C2. In order to use CONFIGURATOR I have toalter the way in which I process customerquotesrorders.

C3. CONFIGURATOR is integrated with the way Iperform my job.

A.4. Intentions

ŽI1. I intend to use CONFIGURATOR either my-.self or through a staff intermediary to process

customer quotesrorders.I2. I would use CONFIGURATOR rather than the

old method for processing customerquotesrorders.

A.5. Personal innoÕatiÕeness

P1. I generally like to experiment with new salestools and methods.

P2. I am usually hesitant to try new and unprovensales methods with customers.

P3. I prefer to let other people work out the bugsand problems with a new sales tool before I useit.

A.6. Awareness

A1. I believe that expert systems represent an im-portant innovation.

A2. I believe that this technology is critical for thecompany to get a competitive edge.

A3. I think it is appropriate for the company toadopt this technology.

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Ritu Agarwal is an Associate Professor of MIS in the Depart-ment of Information and Management Sciences at Florida StateUniversity. She received her Ph.D. in MIS and an M.S. inComputer Science from Syracuse University and an M.B.A. fromthe Indian Institute of Management, Calcutta. Dr. Agarwal’spublications have appeared or are forthcoming in the Journal ofManagement Information Systems, Decision Sciences, IEEETransactions, Decision Support Systems, Information and Man-agement, Knowledge-based Systems and elsewhere. Her currentresearch focuses on individual learning and organizational adop-tion and diffusion of new information technologies, as well asobject-oriented technologies. She serves as an Associate Editor forthe International Journal of Human– Computer Studies.

Jayesh Prasad is Associate Professor of Management Informa-tion Systems in the School of Business Administration at theUniversity of Dayton. He earned his Ph.D. in Management Infor-mation Systems at the Katz Graduate School of Business at theUniversity of Pittsburgh. He has an M.B.A. degree from theIndian Institute of Management, Calcutta as well as a bachelor’sdegree in engineering from the Indian Institute of Technology,Kharagpur. His current research interests focus on the manage-ment of information resources in firms with emphasis on theadoption, implementation, and use of information technologies byindividuals and organizations. His research results have beenpublished or are forthcoming in journals such as MIS Quarterly,Communications of the ACM, and Decision Sciences.

Documents

The antecedents and consequents of user perceptions in information technology adoption