key antecedents of executive information system success: a path analytic approach

Ž .Decision Support Systems 22 1998 31–43

Key antecedents of Executive Information System success: a pathanalytic approach

Deepinder S. Bajwa a,), Arun Rai b,1, Ian Brennan c,2

a Department of Management, School of Business and Economics, FayetteÕille State UniÕersity,FayetteÕille, NC 28301, USA

b Department of Decision Sciences, Georgia State UniÕersity, Atlanta, GA 30303, USAc Department of Marketing and Business Education, School of Business and Economics, FayetteÕille State UniÕersity,

FayetteÕille, NC 28301, USA

Accepted 2 July 1997

Abstract

Ž .Over the past decade, a number of firms have been developing Executive Information Systems EIS to support theirexecutives and managers. This paper draws upon the existing literature in EIS to explain key factors affecting EIS success.The study uses data collected from sixty-nine firms to examine the relationships between top management support, ISsupport, vendorrconsultant support, and EIS success. A structural equation model is proposed to assess the relationshipsamong these constructs. EQS is employed to empirically test the theoretical model and hypothesized relationships. Theresults indicate that IS support in EIS efforts is directly related to EIS success and that both IS support and vendorrcon-sultant support in EIS efforts are influenced by top management support. No direct links between vendorrconsultant supportand EIS success, and between top management support and EIS success were found. However, high levels of topmanagement support indirectly influence EIS success by creating a supportive context for the IS organization andvendorsrconsultant undertakings in a firm’s EIS efforts. Implications of these findings for practitioners and researchers areoutlined. q 1998 Elsevier Science B.V.

Ž .Keywords: Executive Information Systems EIS ; Vendor support; IS support; Top management support; EIS development and implementa-tion; EIS maintenance; EIS enhancement; EIS success

1. Introduction

A number of firms are developing Executive In-Ž .formation Systems EIS to support their executives

w x42 . Although it has been estimated that almost 70%

) Corresponding author. Tel.: q1-910-486-1595; e-mail:[email protected]

1 Tel.: q1-404-651-4060; e-mail: [email protected] Tel.: q1-910-486-1593; e-mail: [email protected]

of all large firms either have already installed an EISw xor are actively considering one 26 , recent develop-

ments in software indicate that even small firms aregetting involved in EIS efforts. Trends indicate thatoverall sales of EIS software are expected to growfrom six million dollars in 1985 to about 230 million

w xdollars by 1995 30 . The growth of EIS can beattributed to two primary benefits of these systems.First, it is believed that EIS have a significant impact

w xon executive productivity 18,6 . By providing on-

0167-9236r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.Ž .PII S0167-9236 97 00032-8

( )D.S. Bajwa et al.rDecision Support Systems 22 1998 31–4332

line, easy, and faster access to internal and externalinformation, EIS facilitate a better understanding ofthe business and greatly reduce response in decision

w xsituations 19 . Second, EIS can have a tremendousimpact on a firm’s planning and control systems asthey can lead to realignment of reporting systems,changes in forecasting processes, and improvements

w xin project management capabilities 33 . Such im-pacts eventually lead to higher levels of organiza-

w xtional effectiveness 29 . In spite of its benefits tofirms, research in EIS continues to be primarilyanecdotal in nature with only a handful of large scale

w xempirical investigations 29,11,42,41,33 . While casestudies and consultant reports have been popularw x22,4,2,31,16 in EIS research, only recently haveresearchers begun to test frameworks and hypothesesw x19,20,5 . Although case studies and exploratory sur-veys are critical to explore any new phenomenon,their usefulness can only be extended if researcherscan share frameworks, constructs, and variable setsto facilitate comparisons across studies. Hence, whilecase studies in EIS may continue to spawn hypothe-ses, there is an urgent need to subject these hypothe-

w xses to empirical testing 18 .It has been widely reported by researchers and

consultants that support from top management, thefirm’s IS function, and vendorsrconsultants are criti-

w xcal for EIS success 29,31,16,42,33 . Accordingly,this paper builds upon past research in EIS to assessthe validity of conventional wisdom about thesesystems. The primary purpose of this paper is toempirically assess the impact of top managementsupport, IS support, and vendorrconsultant supporton EIS success. A research model is proposed andfive hypotheses are formulated between top manage-ment support, IS support, vendorrconsultant sup-

port, and EIS success. These hypotheses are thentested using survey data and a structural equation

Ž .modelling SEM package.In the next section, we define the constructs un-

derlying the research model and formulate hypothe-ses for empirical validation. This is followed bydetails of the research methodology adopted and theresults of our analysis. Finally, we provide the impli-cations of our study’s findings.

2. Development of research model and hypotheses

An EIS can be defined as a computer-based infor-mation system that supports communication, coordi-nation, planning, and control functions of executivesand managers in an organization. Despite its impor-tance to the competitiveness of firms, developing anEIS is not an easy task and many organizationsencounter significant difficulties when doing so. Infact, several unsuccessful EIS endeavors have been

w xreported by researchers 29,40,33 . On the other handmany factors critical for EIS success have beenidentified. Perhaps, the most widely claimed notionis that successful EIS efforts require support fromtop management, IS function, and vendorsrcon-

w xsultants 29,42,33,24 . While lack of such support islikely to impede successful efforts, the validity ofachieving success in the presence of such supporthas not been assessed empirically across firms inmultiple industries. Most of the arguments support-ing these claims are based on insights from casestudies, interviews, and exploratory surveys.

There are two approaches to developing EIS:w xmarket pull vs. supplier push 33 . While supplier

push emphasizes the promotion of EIS by developers

Fig. 1. Research model.

( )D.S. Bajwa et al.rDecision Support Systems 22 1998 31–43 33

of the technology, market pull requires that the needfor an EIS come from the top management. Al-though, both approaches are popular, the literaturesuggests that the chances of success are greater ifdemand for an EIS comes from the top management.

w xAs executives face tremendous time pressures 25 ,they may simply demand an EIS to cope with their

w xactivities 33 . This top-down approach then requiresthat the system be developed either using the firm’sinternal IS resources or by linking up withvendorsrconsultants. The conceptual model is shownin Fig. 1. The rest of this section is devoted todefining the model constructs and formulating hy-potheses for empirical validation.

2.1. EIS success

Evaluating the effectiveness of any IS is difficultdue to its multidimensionality and different view-

w xpoints forwarded by different evaluators 14 . Re-viewing the past literature on IS effectiveness, De-

w xLone and McLean 10 conclude that, ‘‘It is apparentthat there is no consensus on the measure of informa-tion systems success. Just as there are many steps inthe production and dissemination of information, sotoo are there many variables which can be used as a

ww x xmeasure of IS success’’ 10 , p. 80 . Building EIS isw xoften viewed as an ongoing activity 39 . For an EIS

to be successful, it must be continuously maintainedand enhanced after the initial version has been devel-

w xoped and implemented 32 . In the present study, wedo not assess EIS success in terms of usage or otherpossible psychological or behavioral states of theuser. Rather, EIS success is conceptualized in thecontext of overall EIS development and implementa-tion, maintenance, and enhancement activities.

Initial EIS development and implementation typi-cally proceeds by identifying a business problem,developing a quick prototype, and providing the useraccess to the system. Although EIS may initially bedemanded by one or few executives, over time, thesesystems spread to other executivesrmanagers,thereby requiring subsequent development and im-

w xplementation 42 . While successful EIS develop-ment and implementation are critical, EIS mainte-nance and enhancement are important in determiningthe overall success with EIS efforts.

EIS need to be maintained as executivermanagerial information needs change. At a point in

time, executivesrmanagers may desire informationrelated to a specific business problem. Once theproblem has been addressed and other problemssurface, EIS must be able to accommodate newinformation related to the changed nature of theproblem.

EIS enhancement, on the other hand, can beviewed in terms of the evolution of an EIS. In theinitial stages, an EIS may support only limited exec-utivermanagerial functions. For example, an EISmay provide access only to internal information aboutcritical success factors to support executivermanagerial control function. However, at a laterstage an EIS can incorporate modelling applicationsand provide access to external information to supportexecutivermanagerial planning function. ThereforeEIS evolve as more capabilities are added to supportexecutivermanagerial functions. Thus successful EISefforts require that designers be able to achievesuccess not just with EIS development and imple-mentation but also with EIS maintenance and en-hancement activities.

2.2. IS support

IS support is defined as the extent to which the ISfunction of the firm participates and involves itself inthe development and implementation, maintenance,and enhancement of EIS. All EIS may not be devel-oped by in-house IS personnel. However, the chancesof success are greater when EIS development effortsare undertaken by the mainstream IS function of the

w xorganization 33 . Current trends also indicate in-creased participation of IS management in EIS de-

w xvelopment 38 .Two reasons support the need to involve the IS

function in EIS efforts. First, developing successfulEIS requires business as well as technical skills.While business skills typically come from experi-

Ženced people who have worked in the company e.g.,the executive sponsor, functional managers etc. who

.are part of the team , the inventory of technical skillsneeded for EIS development often reside with the IS

w xpersonnel of the organization 42 . For example, EISapplications frequently require accessing and inte-grating information from several databases. There-fore, tapping on the expertise of the firm’s IS func-tion to ensure the feasibility of data availability tosatisfy executive needs becomes critical for EIS suc-


w xcess 4 . Thus if the IS function is not involved inEIS efforts, developers may face potential problemsin delivering EIS applications. Second, since EISusually spread to other executivesrmanagers overtime, the burden of expansion of these systems andcontinuous maintenance and enhancement can createa bottleneck for the designers. As a result, it isabsolutely necessary for designers to involve thein-house IS function in EIS efforts. This can ensuresupport for ongoing development and implementa-tion, maintenance, and enhancement activities.Therefore, it follows that:

H1: Higher level of IS support in a firm’s EIS effortsis directly and positively related to EIS success.

2.3. Vendorrconsultant support

Vendorrconsultant support refers to the extent towhich vendorsrconsultants involve and participatein the development, maintenance, and enhancementof EIS. Past research suggests that when new com-puter-based technology is complex and relatedknowledge difficult to transfer, mediating institutionsŽ .i.e., vendors and consultants play an important role

w xin the diffusion of the technology innovation 3 . Inthe context of EIS efforts, vendorsrconsultants playa critical role in delivering EIS applicationsw x29,42,33 . Two primary reasons can be forwarded tosupport involvement of vendorsrconsultants in anorganization’s EIS efforts. First, EIS usually involvesophisticated applications and the skills or know-howrequired to deliver state-of-the art applications may

w xnot be found in-house 29 . As a result, most firmscreate alliances with vendorsrconsultants to providethe necessary training for development. This is espe-cially important in the initial phases of developmentw x42 .

Second, since the main clientele for EIS are theorganization’s executives and managers, the cost offailure to deliver EIS is high. Thus, to enhancechances of success, EIS designers are likely to linkup with vendors and consultants to get the technical

w xsupport when needed 33 . Therefore, it follows that:

H2: Higher level of vendorrconsultant support in afirm’s EIS efforts is directly and positively related toEIS success.

2.4. Top management support

Top management support is defined as the extentto which firm’s toprcorporate management involvesand participates in EIS efforts. Top managementmust play an active role in EIS efforts as theirsponsorship and support is critical for successw x22,31,16,33 . Sponsorship from top managementcomes in many forms. Since EIS often changestraditional flows of information, it is absolutely nec-essary to lock in support from a politically securesenior executive in the early phases of EIS develop-ment. At the same time involvement of executives inthe specification phases of EIS should not be over-

w xlooked 31 . A member of the top management teammust be committed to devote considerable time to

w xoversee EIS efforts 16 . Another reason for topmanagement to get involved is to avoid development

w xof unrealistic applications 22 . Finally, as EIS ef-forts require substantial amounts of resources, it isessential that top management supports such effortsand provide the necessary resources. Therefore, itfollows that:H3: Higher level of top management support for EISefforts is directly and positively related to EIS suc-cess.

Not only is top management support directly re-lated to successful EIS efforts, their high level ofsupport can also provide impetus for the IS functionto involve themselves in EIS efforts. With chances ofincreasing their strategic importance and visibility ina firm’s operations, the IS function is more likely tosupport those EIS efforts that are strongly supportedby top management. However, when the skills anduser friendly technology needed for developing anEIS are not available in-house, and top managementstrongly supports EIS efforts, they may provide asupportive context for vendorsrconsultants to under-take EIS efforts. Thus, in the absence of adequatein-house skills, vendorrconsultant support in EISefforts is likely to be influenced by top managementsupport for EIS efforts. Therefore, it follows that:H4: Higher level of top management support in afirm’s EIS efforts has a direct and positive influenceon IS support in EIS efforts.H5: Higher level of top management support in afirm’s EIS efforts has a direct and positive influenceon vendorrconsultant support in EIS efforts.


3. Research methodology

M ost of the past stud ies on E ISw x19,20,11,42,41,39,5 have used selective samplingmethodologies primarily because EIS are in theirinfancy and only some firms are believed to have anEIS in place. In order to explore EIS efforts inmultiple industries across U.S. firms, a cross-sec-tional survey design was employed to collect datafrom a random sample of 1423 organizations listedin the 1992 edition of The Directory of Top Com-puter Executives. 3 Questionnaires were mailed tothe top computer executive in all 1423 organizations.Each questionnaire contained a short section explain-ing the purpose of the study and a precise and cleardefinition of an EIS. A cover letter accompanyingeach questionnaire also explained the purpose of thestudy and sought cooperation for participation. Thetop computer executive was requested to forward thequestionnaire to the person most knowledgeableabout EIS efforts, if other than them. A follow-upquestionnaire was mailed approximately fourteenworking days after the first mailing.

3.1. Instrument deÕelopment

To operationalize each of the variables underinvestigation, a measuring instrument was developed

w xalong the guidelines proposed by 36,35 . The relia-bility and validity of measures were assessed using afour-step instrument development and validation pro-cess. In the first step, a thorough review of theliterature was conducted to identify a set of itemscharacterizing each of the variables under investiga-tion. Where appropriate, measures used in previousstudies were adopted and modified in the context ofthe present study. In the second phase, an interviewwas conducted with the executive and operatingsponsors of a leasing firm where an EIS had beensuccessfully developed. In the interview, questionswere posed to verify the items that had been formu-lated in the first phase and to identify other itemsthat would be appropriate measures of the variablesunder consideration. In the third phase, a pilot study

3 The Directory of Top Computer Executives. Applied Com-puter Research, Phoenix, AZ.

was undertaken to qualitatively assess the reliabilityof the measures. Six organizations in the Chicagoarea were selected for the pilot study. A member ofthe EIS development team in each of the six organi-zations was requested to participate in an interview.All six firms varied considerably in their EIS effortsand organizational context. In each case, participantswere asked to comment on the appropriateness andclarity of all the items. Results of the pilot studywere used to further refine the items accordingly. Inthe fourth stage, data gathered from the survey wassubjected to statistical techniques to further assessthe reliability and validity of the measures. Thesetechniques are discussed later in the data analysissection. Operationalization of the variables is dis-cussed next.

3.2. EIS success

No formal measures of EIS success were avail-able in the literature. Based upon what constitutessuccessful EIS efforts, three items were formulatedto measure success with the three critical aspects ofEIS efforts outlined earlier. The first item measuredoverall success with EIS development and imple-mentation, a second measured overall success withEIS maintenance, and a third item measured overallsuccess with EIS enhancement. The appropriatenessof the above three items was assessed in the pilotstudy. All participants agreed that the three itemsappropriately represented overall success with EISefforts. A five-point scale used to measure successwith each of the three aspects of EIS efforts. The

Ž . Ž . Žscale ranged from 1 low to 5 high with 3 mod-.erate as the mid anchor.

3.3. IS support

No measuring instrument for IS support in EISefforts was available in the literature. Therefore, thefirst phase of instrument development process consti-tuted a comprehensive review of the literature toidentify the possible types of IS support in EISefforts. Several sources w ere identifiedw x4,2,42,33,26,12,38 and a preliminary list of itemswas generated based upon their insights.

The list was then refined and reduced to six itemsafter feedback from the executive and operating


Table 1Industry profile

Industry Total mailed Returned EIS

NA P A

Banking 61 04 03 00 01Diversified finance 43 07 01 02 04Education 144 31 19 05 07GovernmentFederal 63 08 02 01 05State 53 10 04 01 05Local 95 17 10 02 05Health services 84 14 06 04 04Insurance 59 11 04 01 06Manufacturing 680 92 58 11 23Retail 62 08 04 02 02Transport 21 02 00 01 01Utilities 41 12 06 02 04Others 17 04 02 00 02Totals 1423 220 119 32 69

NA—non-adopters; P—planners; A—adopters.

sponsors, and the pilot study participants. The sixŽ .aspects of IS support in EIS efforts included: 1 ISŽ .participation in meetings concerning EIS, 2 IS

Ž .cooperation in identifying data sources, 3 IS coop-eration in resolving technical problems in EIS devel-

Ž . Ž .opment, 4 IS’s accountability for EIS, 5 two-waycommunication between IS management and top

Ž .management on EIS, and 6 high IS involvement inEIS development. A seven-point likert type scaleŽstrongly disagree, disagree, disagree slightly, neu-

.tral, agree slightly, agree, strongly agree was usedfor each of the six items.

3.4. Vendorrconsultant support

No multi-item measure for vendor support wasfound in the literature reviewed. The initial list ofitems to measure vendorrconsultant support wasgenerated by reviewing the role of vendorsrcon-

w xsultants in the diffusion of business computing 3 ,w xexternal support in CBIS operations 9 , and vendor

w xsupport in EIS efforts 29,42,33 . In addition to this,the 1992 Midwest EIS User Group meeting held inChicago also provided some input for formulatingitems to measure vendor support in EIS efforts.

The list was then refined and reduced to fiveitems after feedback from the operating sponsor andpilot study participants. The five items used to opera-

Ž .tionalize vendorrconsultant support related to: 1vendorrconsultant participation in initial stages of

Ž .EIS development, 2 cooperation in resolving tech-Ž .nical problems, 3 training in initiating EIS efforts,

Ž .4 communication to ensure product satisfaction,Ž .and 5 user group meetings to transfer know-how.

As in the earlier case, a seven-point likert type scaleŽ .strongly disagree to strongly agree was used foreach item.

3.5. Top management support

To formulate a measure for top management sup-port, a review of past literature was conducted toidentify measures of top management involvementand participation or top management support in ISactivities. Five such studies were identifiedw x23,37,34,17,9 . A comprehensive list of items wasgenerated from all these studies. In addition to this,other items measuring top management support,based upon the insights provided in the EIS literaturew x29,22,31,16,33 , were also identified. The list was

Žthen further refined by deleting inappropriate i.e.,.items not very meaningful in the context of EIS ,

redundant items, and modifying others in the EIScontext.

After feedback from the operating sponsor andpilot study participants, the list was modified to asix-item measure of top management support. The

Ž .six items related to: 1 sponsor participation in EIS,Ž .2 top management contact with an executive spon-

Table 2Respondent position profile

Respondent position Adopters Overall

IS top management 36 123Ž .VPs, Directors, etc.IS middle management 24 061Ž .ManagersIS lower management 04 006Ž .Programmers and analystsCorporate management 02 018Ž .Pres., CEOs, VPsFunctional middle management 02 007Ž .ManagersLower management 01 002Ž .branch mgrs. supervisors


Ž . Ž .sor, 3 resources allocated for EIS, 4 top manage-Ž .ment perception of EIS, 5 top management feed-

Ž .back on EIS applications, and 6 Priority given to

EIS by top management. A seven-point likert typeŽ .scale strongly disagree to strongly agree was used

for each of the six items.

Table 3Comparison of EIS studies

w xAuthors Study context Sampling method Responses n Response profile

Industry Region)Leidner, D.E. EIS’s impact on deci- 100 companies identified 46 responses received Financial svcs., not reported)and Elam, J.J. sion making from trade journals and from senior managers in Electronics mfg.,)business periodicals as 23 firms. P u b lic u tility ,)most likely to have and Telecommunications,)EIS. 34 firms agreed to Oil and gas,)participate. Food products,) Consulting industry) Ž .Benard, R. and User satisfaction with Questionnaires mailed to Questionnaires received Finance 3 , not reported) Ž .Ahmet, S. EIS top executives in 493 from 74 firms. Only 46 Sales 12 ,) Ž .Canadian organizations firms had implemented Transportation 6 ,) Ž .that were part of the Fi- and were using an EIS. Public svcs. 10 ,) Ž .nancial Post 500 compa- 28 firms indicated no EIS. Construction 4 ,) Ž .nies firms. Mfg. 25 ,) Ž .Others 14) Ž .Guy Fitzger- Factors for successful Questionnaires mailed to 77 questionnaires were Finc. svcs. 2 , not reported) Ž .ald EIS development in 500 individuals in U.K. returned. 36 question- Oilrgas 1 ,) Ž .U.K. that had expressed inter- naires were from organi- Public sector 6 ,) Ž .est in EIS to Business zations where EIS was in Hotelrtransport 5 ,) Ž .Intelligence, via atten- practical use by senior Food 5 ,) Ž .dance at conferences and executives. Electronics 4 ,) Ž .seminars or by purchas- Svcs. 4 ,) Ž .ing EIS research reports. Misc. industrial 3 ,) Ž .Retail 2 ,) Ž .Chemicals, 3) Ž .Mech. egnn. 2 ,) )Ž . Ž .Watson, H.J., Framework for devel- Survey population chosen Two mailings resulted in Finance 18% , W est 1 2% ,) )Ž . Ž . Ž .Rainer, R.K., opment and survey of from three groups: 1 at- 112 usable responses. Off M f g . 2 8 % , South 16% ,) )Ž . Ž .and Koh, C.E. current practices tendees at DSS-87 or these, 50 firms had an C om m . 14% , Midwest 26% ,) )Ž Ž . Ž .DSS-88 conferences 185 EIS. Health care 8% , Northeast 40% ,) )Ž . Ž .questionnaires send to U tilities 8% , Other 6%). Ž . Ž .this group , 2 100 firms Other 24%

identified by Computer-world as having invested

Ž .most effectively in IS. 319 firms known by theauthors to have an EIS.18 firms appeared morethan once in the abovegroups. A total of 286questionnaires w eremailed.

) Ž . ) Ž .Watson, H.J., Ongoing study of cur- Questionnaires mailed to 68 questionnaires were Finc.rbank. 29% , West 20% ,) )Ž . Ž .Rainer, R.K., rent EIS practices 300 firms listed in The returned: 51 indicated Mfg. 33% , South 22% ,) )Ž . Ž .and Frolick, University of Georgia’s they had an EIS, 10 indi- Insurance 24% , Midwest 16% ,) )Ž . Ž .M.N. EIS database. cated they had planned U tilities 8% , Northeast 34% ,) )Ž . Ž .for EIS, 6 could not be Other 6% Other 8%

delivered


Ž .Table 3 continued

w xAuthors Study context Sampling method Responses n Response profile

Industry Region

Watson, H.J. Information require- 54 firms selected for ini- 133 questionnaires were Virtually all indus- All fromand Frolic, ments of an EIS tial interviews from from returned: 98 responses tries represented. No N o r t hM.N. The University of Geor- from firms with an EIS breakdown reported. A m erica.

gia’s EIS database of over and 35 responses from No break-400 firms. Final question- firms with no EIS. down re-naires mailed to 300 firms ported.in the database.

3.6. Response profiles

A total of 238 responses were received after twomailings, resulting in a response rate of 16.7%. Ofthese 238 responses, eighteen were discarded due toinsufficient data. Table 1 shows the respondent pro-file by industry. All key industries are represented inthe responses. In the overall response, 119 firmsŽ .54% indicated that they had neither initiated nor

Ž .planned any EIS efforts, thirty-two firms 14% indi-cated that they had planned EIS efforts for the future,

Ž .and sixty-nine firms 32% had already adopted EISto support at least one executive. One of the EISadopting firm did not provide industry informationand was included in the other category.

Table 2 shows the organization ranks of the re-Ž .spondents. A total of 141 65% of the respondents

Ž .held top management positions. Of which 123 57%of them were IS positions like senior VP, assistant

Ž .VP, and Director IS, and 18 8% of them heldcorporate positions like CEO, President, VP Opera-tions, CEO, Chief Operating Officer, etc. While 68Ž .31% of the respondents held middle management

Ž .positions, the remaining eight 4% belonged to thelower level of management. Positions of respondentsfrom EIS adopting firms are also shown in the table.

Approximately one third of the responses receivedin each of the two mailings indicated that EIS hadbeen adopted. Assuming no response bias, this im-

Žplies that only a third of our overall sample 474 of.1423 firms are likely to have adopted EIS. There-

fore, sixty-nine EIS adopters that responded to thesurvey constitute a response rate of about 14.6% ofthe firms that are likely to have adopted an EIS inthe overall sample. A low response rate necessitatedcomparison with previous empirical studies in EIS.

Toward this end, six studies were identifiedw x Ž .19,11,42,41,39,5 see Table 3 . Even though a ran-dom sample was selected for this study, on a closerlook, our response rate and response profile is com-parable with these past studies.

3.7. Data analysis and results

The unidimensionality of top management sup-port, IS support, vendorrconsultant support, and EISsuccess was supported by a Principal Componentsanalysis of the twenty items used to measure these

w xfour constructs. As suggested by 13 , componentsthat explained less variance than a single variableŽ .i.e., those with eigen values less than 1 wereeliminated from further analysis. The factor loadingsŽ .after varimax rotation on the four factors exceedingeigen value of 1 are shown in Table 4.

The pattern of loadings on the four factors whichappear in Table 4 is consistent with the hypothesizedsix item top management scale, six item IS supportscale, five item vendorrconsultant support scale, andthree item EIS success scale. Although a 1:4 item to

w xobservation ratio has been suggested by 13 , therespective item to observation ratio in this study isapproximately 1:3.5. Therefore, support for the va-lidity of the scales identified in the present studyshould be interpreted with caution.

Test for reliability necessitated computing ofCronbach’s alpha for all the four factors. Table 5shows the standardized alpha for each of the fourfactors. All the reliability coefficients were wellabove the lower acceptable limits of 0.50 to 0.60w x28 . The descriptive statistics and the intercorrela-tions between top management support, IS support,


Table 4Factors, items, and loadings

Factors and items Loadings

Top management support( )Eigen Õalues6.57. Ž .1 Executive sponsor s participation 0.81

in EIS development.2 Top management contact with 0.85

sponsor on EIS related issues.3 Resource support for EIS 0.69.4 Top management perception of 0.73

importance of EIS.5 kTop management’s constructive 0.81

feedback on EIS application.6 EIS regarded as high priority by 0.71

top management

( )IS support Eigen Õalues 3.25.1 IS executive participation 0.75

in EIS development.2 IS cooperation in identifying 0.88

data sources for EIS.3 IS cooperation in resolving technical 0.89

problems in EIS efforts.4 IS accept accountability for EIS 0.65.5 Comm. between IS and top 0.68

management on role of EIS.6 High IS involved in EIS development 0.69

Vendorrconsultant support( )Eigen Õalues 2.51.1 Participation in initial phases of 0.82

EIS development.2 Cooperation in resolving technical 0.86

problems.3 Helpful training for initiating EIS 0.82

development.4 Communication to ensure product 0.84

satisfaction.5 Participation in vendor user group 0.69

meetings

( )EIS success Eigen Õalues 2.33.1 EIS development and implementation 0.83

success.2 EIS maintenance success 0.92.3 EIS enhancement success 0.89

vendorrconsultant support, and EIS success are alsoshown in Table 5.

The hypotheses were tested using Bentler’s EQSw xstructural equations modelling package 7 . A test of

the proposed research model through SEM wasdeemed more appropriate than multiple regression

analysis for two primary reasons. First, the researchmodel contains a number of dependent constructsŽ .see Fig. 1 . However, multiple regression analysisallows the researcher to test the relationship betweena set of independent variables and only a singledependent variable. In contrast SEM allows the re-searcher to examine a model that includes a series of

w xdependent relationships simultaneously 13 . Second,in contrast to multiple regression, SEM allows theresearcher to incorporate the fact that not all con-structs within a theoretical framework will be mea-sured with perfect reliability. Accordingly, the factsthat none of the constructs relevant to research model

Ž .were measured with perfect reliability see Table 5indicates that this second advantage of SEM overmultiple regression is pertinent to the present study.

3.8. Goodness of fit

The model was estimated by employing the EQSw xmaximum likelihood procedure 7 . Measurement

model error terms were fixed at 1-reliability coeffi-cient multiplied by the variance of the respective

w xindicator 27 . Table 6 shows the Chi Square andŽ .Bentler Bonett Non Normed Fit Index BBNNFI

goodness of fit measures for the proposed model.ŽBoth the Chi Square statistic Chi Squares0.013,

. Žd.f.s1, p)0.908 and the BBNNFI statistic BBN-.NFIs1.21 provide strong support for the proposed

Žmodel. Given the relatively small sample size ns.69 of the present study, the Chi Square goodness of

fit measure should be interpreted with caution sincein samples less than 100, the Chi Square statistic isrelatively insensitive to differences between the pro-posed model and the data. In contrast, the BBNNFI

Table 5Descriptive statistics and intercorrelations

Variables N Mean Range SD Std. 1 2 3Alpha

.1 Top mgmt. 69 4.61 1–7 1.37 0.87 1.00support

).2 IS support 69 5.51 1–7 1.22 0.89 0.40 1.00).3 Vendorrcon. 67 3.86 1–7 1.53 0.87 0.25 0.10 1.00

support) ).4 EIS success 65 3.38 1–5 0.92 0.88 0.32 0.48 0.10

) Significant at p-0.05.


Table 6Path analysis results for the research model

Path Standardized path coefficientsŽ . Ž .ns69 ns200

) )Path 1: Top Management Support´ IS Support 0.451 0.451) )Path 2: IS SupportÉIS Success 0.443 0.443) )Path 3: Top Management Support´VendorrConsultant Support 0.289 0.289

Path 4: VendorrConsultant SupportÉIS Success 0.010 0.010Path 5: Top Management SupportÉIS Success 0.183 0.183

Fit statisticsŽ .a ns69Chi Square 0.013Degrees of Freedom 1p value 0.908BBNNFI 1.21

Ž .b ns200Chi Square 0.039Degrees of Freedom 1p value 0.843BBNNFI 1.06

) Path significant at p-0.05.

has a major advantage of reflecting model fit at allw xsample sizes 43,21,1 . Given the relative insensitiv-

ity of the Chi Square statistic to small sample sizesdiscussed above, greater importance must be placedon the BBNNFI index which in the present case is

w xwell above the 0.9 threshold used in research 8 ,thereby, indicating a good fit between the proposedmodel and the data.

In view of the fact that small samples render theChi Square statistic relatively insensitive to the de-tection of differences between the model and thedata, it has been recommended to test structuralequation models under the assumption that ns200,

w xirrespective of the original sample size 15 . Accord-ingly the proposed model was retested under the

Ž .assumption that ns200. The results see Table 6Žstill show strong support for the overall model Chi

Squares0.039, d.f.s1, p)0.843 and BBNNFIs. Ž .1.06 . Thus at both the original sample size ns69

Ž .and the simulated sample size ns200 , the modelprovides a good fit to the data.

Table 6 also shows the standardized path coeffi-cients for sample size of sixty-nine and the simulatedsample size of 200. As indicated in the table, three ofthe five study hypotheses were supported by ouranalyses. Structural paths 1, 2, and 3 were significant

at p-0.05, thereby providing support for H1, H2,and H3. The structural path 1 indicates that ISsupport is directly influenced by top management

Ž .support for EIS efforts Zs3.54 and the structuralpath 2 indicates that IS support directly affects EIS

Ž .success Zs3.13 . Finally, structural path 3 indi-cates that vendorrconsultant support in EIS efforts is

Ž .influenced by top management support Zs2.15 .The other two structural paths, i.e., path 4 and path 5were not statistically significant at p-0.05, therebyproviding no support for H4 and H5. Therefore, ouranalysis indicates that vendorrconsultant supportdoes not affect EIS success and that top managementsupport has no direct impact on EIS success.

4. Discussion and conclusions

The purpose of this study was to validate conven-tional wisdom about EIS by assessing the relation-ship between top management support, IS support,vendorrconsultant support, and EIS success. Ourfindings have several implications for researchersand practitioners. For practitioners embarking uponEIS efforts, the study provides insights into therelationship between top management support, IS


support, vendorrconsultant support, and EIS suc-cess. Several aspects of support from top manage-ment, IS, and vendorsrconsultants that are criticalfor EIS success are identified to guide practitionersin their EIS endeavors. Our findings suggest that ISsupport and vendorrconsultant support in EIS effortsis influenced by top management support. Further, itwas found that IS support directly affects EIS suc-cess. This second finding supports earlier claim thatIS support is critical for successful EIS effortsw x4,42,33,38 .

However, our findings also suggest thatvendorrconsultant support has no effect on EISsuccess. This finding should be interpreted with cau-tion. Past research clearly emphasizes the importanceof the role played by vendors in developing success-

w xful EIS 29,42,33 . Our results do not support thisclaim. Two explanations could be forwarded for thiseffect. First, a substantial proportion of our respon-

Ž .dents 52% indicated that EIS applications werebeing delivered using a variety of in-house or home-grown software packages as opposed to popular ven-dor EIS software products. Given this, it is possiblethat vendorrconsultant support is critical for EISsuccess only in organizations where vendor devel-oped EIS software packages have been adopted todeliver EIS applications. In other cases, where EISapplications are being delivered using in-house de-veloped packages, support from EIS software ven-dors and consultants in an organization’s EIS effortsis likely to be minimal. Second, vendorrconsultantsupport in a firm’s EIS efforts is usually important in

w xthe initial stages of development 42 . As firm’s gainthe skills necessary to deliver EIS applications, theneed to maintain strong links with vendorsrcon-sultants diminishes because they are able to sustainin-house application development. Since our measureof EIS success captured overall success with EISdevelopment and implementation, maintenance, andenhancement activities, most of the responding firmshad sufficient experience in delivering EIS applica-tions. As a result, respondents did not perceive ven-dorrconsultant support to be critical for overall EISsuccess. It is possible that due to these two reasons,our findings did not show any significant relation-ship between vendorrconsultant support and EISsuccess.

Similarly, no significant direct effect between top

management support and EIS success was found.The IS literature suggests that top management sup-port is critical for the successful implementation ofcom puter-based inform ation technologiesw x23,37,34,17,9 . The EIS literature also strongly sup-ports the notion that top management support is

w xcritical for successful EIS efforts 22,31,16,33 . Ourempirical analysis suggests that top managementsupport does not directly affect EIS success. Rather,there is an indirect relationship between top manage-ment support and EIS success. A possible explana-tion for this finding is rooted in the ground-breaking

w xstudy by Attewell 3 , who observed that diffusion ofcomplex information technologies depends upon thesuccessful elimination of knowledge barriers be-tween the providers of the technology and the poten-tial users of the technology. However, it is importantto understand that the elimination of knowledge bar-riers for successful diffusion of technology cannot bedemanded without top management support. Ourresults suggest that high levels of top managementsupport create a supportive context for the groupsresponsible for confronting knowledge barriers andundertaking EIS efforts. We have limited our empiri-cal analysis to two such groups: the firm’s IS func-tion and vendorsrconsultants. Participation, priority,commitment, feedback, resource support, and politi-cal support from top management create the neces-sary influence base for the IS function andvendorsrconsultants to effect changes in the technol-ogy, knowledge base, and the organization at large,in the process of undertaking EIS efforts. Therefore,top management support has an indirect effect, ratherthan a direct effect on EIS success.

While our analysis provides some interesting find-ings, we also need to point out some of the limita-tions of our study. First, a single informant was usedto gather information about EIS efforts in the firmmainly because of response rate considerations. Thequestionnaire was mailed to the top computer execu-tive in each firm requesting him or her to forwardthe questionnaire to the person most knowledgeableabout their EIS efforts. It is possible that the re-sponses we received may not have been from theperson that was most knowledgeable about EIS ef-forts in their firm. If this is the case, then it woulddefinitely impact respondents’ perceptions about therole played by top management, IS, vendorsrcon-


sultants in EIS efforts, and EIS success. However,almost 55% of our respondents held top managementpositions and 38% held middle management posi-tions. Although, it is appropriate to assume that theserespondents are likely to be knowledgeable abouttheir EIS efforts, we cannot speculate on the level oftheir personal involvement and participation in theirfirm’s EIS efforts to warrant completely accurateresponses.

Second, the findings may be limited by low re-sponse rate. The low response rate could be due tothe fact that, on a national basis, few firms haveactually developed EIS to support their key execu-tivesrmanagers. While EIS are growing rapidly, al-most 54% of our respondents had not even plannedfor EIS efforts. In addition, not mailing the question-naire directly to executivesrmanagers that were mostknowledgeable about EIS efforts could have alsoinfluenced our response rate. Once again, there wasno economically feasible means of identifying theperson most knowledgeable about EIS efforts in theselected sample of firms.

Third, our measure of EIS success focuses ondevelopment, maintenance and enhancement of EIS.There are a variety of measures that can be used todefine the success of an information system. Ourfindings are not generalizable to other measures ofsuccess such as user satisfaction, level of usage,impact of EIS on individuals or team performance,or organizational impact of EIS.

In spite of the above limitations, this study hasimportant implications for research and practice. Itvalidates some of the conventional wisdom aboutEIS and provides a theoretical framework for futureempirical investigations. While most of the EIS re-search is primarily based on case studies, large scale,empirical investigations like the present study arenecessary to demonstrate the validity of qualitativelyfounded knowledge claims. This study is a stepforward in that direction. Although this study pro-vides some interesting findings, the role ofvendorsrconsultants in successful EIS efforts needsto be explored further in different contexts beforedrawing any conclusions from this study on thesame. However, the fact that IS support had a directeffect on EIS success and no relationship was foundbetween vendorrconsultant support and EIS success,it is possible that there may be a major shift in the

way EIS are being developed and implemented inorganizations.

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Ž .latent variables, Sociol. Meth. Res. 16 1987 118–154.Deepinder S. Bajwa is an assistant pro-fessor in the Department of Manage-ment at Fayetteville State University. Heholds a DBA. from Southern IllinoisUniversity at Carbondale. His articleshave been published in Decision Sci-ences and Vikalpa. In addition, he haspresented several papers at international,national, and regional conferences. He isthe recipient of the best paper award inthe POMrSB track at the MidwestBusiness Administration Association

conference. His research interests include executive informationsystems, decision support systems, adoption of emerging tech-nologies, management of information technology, IS service qual-ity, and total quality management.

Arun Rai is currently Associate Profes-sor in the Department of Decision Sci-ences at Georgia State University. Hereceived his Ph.D. from Kent State Uni-versity in 1990 and then spent sevenyears on the faculty at Southern IllinoisUniversity. His present research inter-ests include the diffusion, infusion andimpacts of information technology, in-formation technology design for infor-mation and knowledge management, andmanagement of unstructured processes

such as systems development, innovation, product developmentand decision-making. Dr. Rai has published several articles onthese and other related subjects in journals such as Communica-tions of the ACM, Decision Sciences, Decision Support Systems,European Journal of Information Systems, Journal of ManagementInformation Systems, Omega, and several others. He is the Presi-dent of the Diffusion Interest Group on Information TechnologyŽ .DIGIT and is an Associate Editor for MIS Quarterly and Infor-mation Resources Management Journal.

Ian Brennan is an assistant professor inthe Department of Marketing and Busi-ness Education at Fayetteville State Uni-versity. He holds a Ph.D. from Univer-sity of Texas at Arlington. He has pub-lished in Advances in Consumer Re-search, Journal of Student Employment,and presented papers at national andregional conferences. His research inter-ests include: survey design, data analy-sis techniques, symbolic advertisingmessages, service quality delivery, and

total quality management.

key antecedents of executive information system success: a path analytic approach

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