ieee transactions on engineering · pdf fileby adopting dwa, a ﬁrm could be ... [52], [84],...

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 51, NO. 3, AUGUST 2004 253

Effects of Environmental Uncertainty onOrganizational Intention to Adopt

Distributed Work ArrangementsChoon-Ling Sia, Hock-Hai Teo, Bernard C. Y. Tan, and Kwok-Kee Wei, Senior Member, IEEE

Abstract—Uncertainty in the external environmental contexthas been shown to affect organizational change and innovation.Distributed work arrangement is an organizational innovationthat has the potential to enable a firm to meet the challenges of anuncertain environment more effectively. With the emergence ofvirtual organizations, such work arrangements are likely to gainincreasing popularity. This exploratory empirical study employsa structural model to examine how environmental uncertaintyaffects organizational predisposition (adoption intention) towarddistributed work arrangements. Environmental uncertainty hastwo different dimensions: environmental complexity (hetero-geneity) and environmental variability (dynamism). In this paper,environmental dimensions are modeled to influence adoption ofdistributed work arrangements through shaping the organiza-tional perceptions of three innovation characteristics: perceivedrelative advantage, compatibility and complexity. Data analysesusing partial least squares statistical technique revealed thatenvironmental complexity is negatively associated with perceivedrelative advantage, and perceived compatibility. Perceived relativeadvantage and perceived compatibility are in turn positivelyrelated to adoption intention for distributed work arrangements.However, environmental variability has no significant effect on thethree innovation characteristics. Contrary to past findings thatsuggest organizations are more predisposed toward innovationsin a complex environment, our study found that organizations inan environment of lower, rather than higher complexity are morelikely to adopt distributed work arrangements. Implications fororganizations are discussed.

Index Terms—Diffusion of innovation, distributed work, organi-zational environment, partial least squares, , .

I. INTRODUCTION

ORGANIZATIONAL design involves the structuring oflateral and vertical communications, the division of

labor, the choice of physical locations, the streamlining of in-formation and decision processes, and the institutionalizing ofequitable reward systems [9], [49], [82], [84]. One increasinglysignificant and popular organization design is distributed workarrangements, made feasible by information technology (IT)and the Internet [47], [115]. Distributed work arrangements(DWAs) involve the performance of organizational work in

Manuscript received July 1, 2003; revised January 1, 2004. Review of thismanuscript was arranged by Department Editor R. T. Keller.

C.-L. Sia and K.-K. Wei are with the City University of Hong Kong, Kowloon,Hong Kong (e-mail: [email protected]).

H.-H. Teo and B. C. Y. Tan are with the National University of Singapore,Singapore 119260, Republic of Singapore.

Digital Object Identifier 10.1109/TEM.2004.830859

geographical locations outside the traditional boundaries oforganizations [57]. In this paper, DWA is defined as organiza-tional schemes, whereby workers work away from the office(at home, customers’ sites, or anywhere deemed conduciveand appropriate) through the application of information andcommunication technology. Examples include, but are notlimited to, supplying workers with computers, modems, andother equipment so that they can access organizational infor-mation, while meeting with clients, with other colleagues, orworking from their homes. These work arrangements are likelyto gain widespread acceptance with the emergence of virtualorganizations.

DWAs have enormous potential for organizations to reduceoperating costs, confer competitive advantage and agility, gainaccess to a wider pool of organizational talents, manage tightlabor conditions, and improve employee flexibility, effective-ness, and productivity (e.g., [27], [75], [91], [96], [107], [115]).For example, VeriFone is a virtual organization that utilizesextensive distributed work supported by advanced informationand communications technology to position itself as a globalcompetitor [101]. Its CEO, Hatim Tyabji, described how anemployee working intensively at a company’s site in Greecewas able to clinch a critical deal from a major competitor byresponding rapidly (within 24 hours) to the local customer’sneeds, through his understanding of the local business de-mands and using technology to tap on the expertise of VeriFoneemployees worldwide. By adopting DWA, a firm could beperceived as a forward-looking organization that effectivelyharnesses technology to manage its manpower and improvethe welfare of its employees [96]. Besides these organizationalbenefits, DWAs also have important social and societal impli-cations (e.g., [27], [57], [97]). They could help improve qualityof work life and provide employment opportunities for peoplewho are otherwise unable to work (such as the handicapped,or parents with young children). Managing these social andsocietal issues through the adoption of DWAs could permit anorganization to project itself as socially responsible, an imagethat could be leveraged during its recruitment and marketingcampaigns.

Despite its many potential benefits, the adoption of DWAs hasnot been as extensive as widely expected (e.g., [58], [64]), par-ticularly in Asia. DWA can be considered an organizational in-novation [5], [96], because it entails fundamental restructuringof the organization design with regards to its governance struc-ture, coordination and control mechanisms, and reward systems.As an organizational innovation, the study of DWA using inno-vation literature could offer insights on its less-than widespread

0018-9391/04$20.00 © 2004 IEEE

254 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 51, NO. 3, AUGUST 2004

adoption. An important factor often found to have a signifi-cant influence on organizational innovation is the environment[23], which is a major source of contingencies for organizations[112]. To date, studies of distributed work had largely been con-fined to organizational factors [96], [107], task and employeecharacteristics (e.g., [36], [74], [88]), and technological charac-teristics (e.g., [57]). Little empirical work has been expendedto examine the relations between the environment in which anorganization is situated and the adoption of DWAs. The envi-ronment could have several implications for distributed workadoption. First, uncertainty in the environment has often ledto greater innovative behaviors within organizations [108], andDWAs have often been considered an innovation to adopting or-ganizations [5], [96]. Second, uncertainty due to restructuring ofthe labor market and increasing complexity of the competitivesituation and customer needs, which are important elements ofthe organizational environment, motivates the search for a fun-damentally new organizational response [71], such as the alter-native offered by DWAs [107]. Third, effective management ofa turbulent environment necessitates improving organizationalprocesses and structure so as to enhance their abilities to processinformation effectively [49], [84]. This could be achieved withthe adoption of decentralized work such as DWAs [84], [120].Fourth, social trends increase the need for organizations to re-think how they could tap the skills of knowledgeable workers,while meeting their demands for higher quality of work life orgreater flexibility in scheduling their work [35].

Overall, the environment plays a strategic and crucial rolein influencing organization design, actions, and outcomes[49],[52], [84], [112], [117], particularly in virtual organizations[95], [98]. Executives are often required to redesign theirorganizations to manage the uncertainties that are inherent intheir environments [71]. For instance, intensity of competitionin the financial and insurance services has led to the growingnumbers of consultants who offer personalized and immediateadvice at their customers’ sites, through the use of portablecomputers with access to their corporate databases (a formof DWA). Recent empirical studies have indeed found manyorganizations adopting virtual organization-like structures aspart of their strategies to counter demand uncertainties andcompetition in the global market [95], [98].

This exploratory study aims to contribute to extant literatureon organizational innovation in general, and DWAs in particular.It is designed to provide insights into how environmental un-certainty could shape organizational attitudes toward adoptinginnovative work practices such as DWAs. To provide a betterunderstanding of organizations’ adoption behavior within theirenvironmental settings, the study solicits the views of chiefexecutives on the environment in which their organizationsare operating within, on DWAs and on their predispositiontoward DWAs. It proposes a path model in which environ-mental factors affect organizations’ perceptions of distributedwork, which in turn affect adoption intentions. This paperreviews literature on organizational innovation and innovationdiffusion to identify the relevant factors for study. Throughunderstanding how the environment affects organizations’ per-ceptions of DWAs, this paper could provide practical implica-tions for organizations on how distributed work arrangementscould be implemented and marketed to employees. The re-luctance of organizations to adopt DWA underscores the need

to understand factors affecting managerial attitudes and pre-disposition toward it [96]. This study could also provide thebasis for organizations to assess the strategic need to assimilatesuch work-arrangements innovation, by taking into accounttheir environmental realities.

II. THEORETICAL PERSPECTIVES AND HYPOTHESES

An innovation is an idea, product, or process that is newto an adopter [59], [94], [119]. Rogers [94] and Tornatzkyand Fleischer [108] viewed an organizational innovation as theintroduction of a concept, practice, or device that is perceivedas new by the adopting organization. Whether a concept is newis not absolute, but is situational. Thus, a concept can be newin a given setting, even if it is not elsewhere. Awareness orknowledge of the concept for some time does not preempt itsconsideration as an innovation. An organization often embarkson innovation behaviors when it recognizes either the needfor change when a problem or opportunity arises, or whena new technology that can increase its performance becomesavailable [7], [113], [121].

Adoption of DWAs as an alternative form of work arrange-ment for employees would necessitate fundamental and radicalchanges in structure, coordination and control mechanisms, andrewards systems in an organization and would, thus, constitutean innovation [5], [96]. It is a process innovation that couldinvolve structural, administrative, and technological changesrather than a pure technological innovation [31], [40]. Thenotion of DWA has yet to be widely accepted by organizations[58], [96], particularly those in Asia. This paper, therefore,focuses on potential adopting organizations. It seeks to examinehow the external environmental context affects organizationalpredisposition toward DWA through shaping organizationalperceptions. The external environmental context is examinedprimarily from the perspectives of environmental complexityand environmental variability, while organizational perceptionsof DWAs are taken primarily from innovation diffusion theory[94].

Innovation diffusion theory [94] posits that five perceivedinnovation attributes influence adoption: relative advantage,compatibility, complexity, observability, and trialability. Ofthese attributes, only relative advantage, compatibility, andcomplexity were included in the research model for severalreasons. First, given our focus of assessing the pros and consof DWAs adoption in response to environmental uncertainty,observability, and trialability of DWAs become less relevantas they do not have much direct impact on how organizationshandle environmental uncertainty. Second, since the impactof DWAs is long term in nature and given its very limitedextent of adoption in Asia, observability is less of a concernto management. Third, DWAs entail substantial organizationalrestructuring and is hard to reverse its effects. Thus, trialabilitywould unlikely be a major managerial consideration. Fourth,these three attributes have consistently been found to be im-portant in influencing adoption behavior, but not observabilityand trialability (e.g., [56], [109]). Hence, this paper assessesthe extent to which these three perceived characteristics couldpredict organizational predisposition toward DWAs. Fig. 1depicts the research model.

SIA et al.: EFFECTS OF ENVIRONMENTAL UNCERTAINTY ON ORGANIZATIONAL INTENTION TO ADOPT DISTRIBUTED WORK ARRANGEMENTS 255

Fig. 1. Research model.

A. Perceived Innovation Characteristics and AdoptionIntention

1) Relative Advantage: Relative advantage is the degree towhich an innovation is perceived as being more advantageousthan its precursor. It is manifested as increased efficiency andeffectiveness, economic gains, and enhanced status [94]. Po-tential organizational benefits of DWAs include reduced oper-ating costs (e.g., space savings), improved recruitment/retentionof skilled workers, heightened employee performance and pro-ductivity, greater responsiveness to an uncertain environment,and faster processing time [32], [35], [53], [107]. Organizationalbenefits of a less tangible nature include favorable publicity fortheir “enlightened” work style, especially if they provide em-ployment opportunities for the physically disadvantaged [89].By projecting the image of a socially responsible organizationthat uses technology to extend the potential of its manpowerand reduce pollution resulting from increased traveling by em-ployees, organizations could reap substantial tangible benefitsin their future marketing and recruitment campaigns. Althoughorganizations may be concerned about the implications of someforms of DWAs like social isolation [97], such concerns couldbe alleviated to some extent by implementing flexible part-timeschemes. In general, when organizations perceive clear overallorganizational benefits of DWAs, they are more likely to adoptit [96]. Hence, the following.

H1: Perceived relative advantage is positively related toadoption intention for DWAs.

2) Compatibility: Compatibility is the degree to which aninnovation is considered consistent with existing organizationalgoals, values, systems, and experience. Greater congruence orfit among components of the organizational arrangements, suchas between work arrangements and the organization design andvalues, is desirable because it could lead to increased organi-zational effectiveness [85]. Greater compatibility between aninnovation and the organization would also be preferable be-cause it presents the potential adopter with less uncertainty andpermit the interpretation of the innovation in a more familiarcontext [94]. It is also likely to encounter less overall resistanceduring implementation. Thus, when organizations perceivethat DWA is compatible to their organizational arrangements,they would have a positive predisposition to adopt it. Positiveempirical association between compatibility and innovationadoption behavior has been found (e.g., [41], [67], [109]).Research has indicated that for DWAs to be adopted and imple-mented successfully, enlightened management, decentralized

structures, and proper technological infrastructure have to bein place [35], [57], [96], [107]. Since DWAs involve the useof technology to work in decentralized settings, organizationswith poor telecommunications infrastructure, highly central-ized and bureaucratic structures (need to “see” their employeesworking), and managers unfamiliar to organizing and managingremote work would be less likely to adopt DWAs [89].

H2: Perceived compatibility is positively related to adop-tion intention for DWAs.

3) Complexity: Complexity is the degree to which an inno-vation is perceived as difficult to understand and implement.Being a hybrid innovation with technological (e.g., security andconnectivity of computer network) and administrative (e.g.,changes to work styles and structures that affect the rewardsystem, control system, and coordination system) implications,DWAs have been perceived as a complex innovation [53].Researchers have suggested that a complex innovation requiresgreater skills and implementation efforts to adopt, and requiresincreased cognitive effort on the part of the potential adopter,thus reducing likelihood of adoption (e.g., [20], [29], [66],[114]). Complexity has been widely recognized as an inhibitorto adoption (e.g., [76], [94]). Hence, the following.

H3: Perceived complexity is negatively related to adoptionintention for DWAs.

B. External Environment Context and Perceived InnovationCharacteristics

The environment of an organization consists of factors out-side the organization, including individuals, groups, other or-ganizations, and technological and social forces that have apotentially large impact on organizational performance [85].Specifically, the organizational environment is the arena inwhich an organization operates its primary business. It com-prises the industry (suppliers and customers), the competitors,access to resources, and dealings with regulatory bodies suchas the government [108].

The external environmental context has a significant ef-fect on decision making [69] and innovation [26], [108]. Acritical aspect of the environment influencing innovation is en-vironmental uncertainty. Research has established a significantpositive relationship between environmental uncertainty andorganizational innovations such as changes in organizationalform, strategy, and culture [24], [68], [90], [100], [117]. In en-vironments of low uncertainty, organizations have been foundto be neither structurally complex nor innovative. Heightenedinnovation and complexity would result from environmentsof relatively high uncertainty. Organizations that perceive ahigh degree of environmental uncertainty were more likelyto pursue an aggressive technology policy [39]. Such orga-nizational changes were carried out to enable organizationsto be more responsive and adaptable to external cues [90].Environmental uncertainty has two distinct and separate dimen-sions: environmental complexity and environmental variability[13], [34], [40], [111]. Environmental complexity (also knownas heterogeneity) refers to the diversity and interdependenceof environmental factors that organizations have to contendwith [16], [28], [34], [105]. Analyzability and predictability ofenvironmental factors are especially difficult in a complex en-vironment [21], [34]. A greater degree of decentralization and


specialization, and the use of integrative coordination mecha-nisms, would have to be utilized to manage the diverse issuesassociated with a complex environment [14], [48], [77], [79].It would also require organizations to scan extensively forthe range of environmental factors, such as emerging trends,threats and opportunities, that contributes to their complexenvironment [1], [61].

Environmental variability (also referred to as dynamism orenvironmental volatility) is the rate and volume of changes inthe environmental factors. Rapid and large volume of changescould decrease confidence in predicting outcomes [22]. Greatertime and effort would be devoted to collecting, analyzing, andinterpreting information when the environment is perceived asvariable [80]. Thus, dynamic environments necessitate a greateramount of information processing and task analysis [79]. Fur-ther, organizations in variable or dynamic environments needto acquire the capability to continually learn and readapt tothe changing environment [34]. Between the two dimensionsof environmental uncertainty (complexity and variability),Duncan [34] found that environmental variability contributedsignificantly more to organizational decision makers’ overallperceptions of environmental uncertainty than environmentalcomplexity, with the dynamic and complex environmentsinducing the greatest amounts of uncertainty.

Both environmental complexity and variability form thebasis of organization design frameworks [49]. They necessi-tate changes to resource allocations, schedules, and prioritiesduring task execution. They also increase the need for greaterflexibility and speed in coordination and control, which wouldpermit the organization to more effectively detect and respondto unforeseen problems and opportunities in the environment[120]. These changes require greater amounts of informationprocessing by decision-makers during task performance. Envi-ronmental complexity and variability, thus, increase the amountand variety of information about the external environment thatan organization has to process. They also increase the timeand effort needed to collect and process this information [49],[52], [84]. To circumvent these environmental factors, organi-zational forms are designed to the extent that they increase thecapacity to gather and process information, reduce the needto process information, and increase the flexibility to adapt toenvironmental changes [49].

DWAs (decentralized structures) have been proposed aspossible strategies for organizations to manage and adapt to en-vironmental changes (e.g., global competition, changes in workforce preferences, skilled labor shortage). Druke et al. [32]suggested that DWAs should improve the reacting capability oforganizations to adapt to external structural changes, which in-clude shifts in industry structure, changes in customers’ needs,cyclical demand fluctuations, cyclical changes in labor market,technological changes, and others. This could be achievedbecause DWAs have the potential to increase informationprocessing. DWAs may contribute to increased informationprocessing capacity of an organization through “promotingthe processing of information among those organizationalunits, groups, or individuals who are closest to the work beingperformed” [84, p. 110]. Decentralized work, such as thoseoffered by DWAs, permits employees to diagnose problems,generate response alternatives, and implement solutions at thepoint of occurrence much more efficiently, effectively, and

creatively through the use of information technology than ifthe problems had to be referred up the organizational hierarchyin traditional organizations [18], [120]. Besides problem reso-lution, employees could also draw upon their experience andunderstanding of the business processes to generate creativesolutions, identify innovative business opportunities, and spotchanging customer trends. VeriFone provides an illuminatingexample of how distributed work could help an organization torespond rapidly and effectively to local customer demands byleveraging on the local contextual and worldwide expertise ofits employees through the use of information and communica-tions technology [101].

The overall impact of distributing expertise and informationaccess by utilizing information technology would be the cre-ation of opportunities for continuous organizational learning[65], [116], [122]. Thus, decentralized structures could in-crease an organization’s flexibility and speed in detecting andresponding to unforeseen problems and opportunities presentedin an uncertain environment [18], [120]. For example, intensecompetition in the personal insurance industry has led to theincreasing use of mobile technologies by agents to generateand approve proposals dynamically tailored to needs and re-quirements gathered directly from customers. Agents couldthen detect changing trends in customers’ needs and concernsthrough the use of advanced technologies, and respond directlyto such changes by adjusting their individual sales strategy.

Several studies have offered examples of how informationprocessing capabilities could be increased for distributedworkers (see Table I). Specifically, Gordon [53] suggested ev-idence of increased information processing capacity resultingfrom the effects of distributed work. Gerstein [51] also offeredexplanations of how advanced communications technologiescould be employed in DWAs to improve an organization’sinformation processing capabilities. Gupta et al. [57] presentedvarious applications of advanced information and commu-nications technologies that could increase the informationprocessing capacities of distributed workers.

Our argument is that organizations operating in complex envi-ronments would require work designs that permit decentralizedinformation processing and decision making, and organizationsin variable and dynamic environments would require greater in-formation processing and analytical capacity, in order to ensureorganizational effectiveness and viability. Since DWAs have thepotential to offer decentralized information processing and en-hanced information processing analyzability capacity, and couldbe an effective strategy to manage environmental uncertainty[95], [107], organizations embedded in complex and variableenvironments are likely to have more positive perceptions ofDWAs than those that are not.

1) Environmental Complexity and Perceived Relative Ad-vantage: A complex external environment increases theamount and diversity of information that an organization hasto manage [48], [79]. To increase their information processingcapacity, organizations could decentralize decisions at thesource of problem or opportunity [49], [84]. This would permitorganizations to more effectively manage the complexity oftasks and factors by compartmentalizing and delegating tasks todistributed workers. DWAs could provide employees with theflexibility and autonomy of working in places where they findit most productive [97], [115], thereby increasing their ability


TABLE IINCREASED INFORMATION PROCESSING CAPACITY OF DWA ADOPTERS

to effectively gather and act on relevant information as theneed arises [83], [84]. Conversely, a less complex environmentwould be relatively simple for organizations to manage. Suchorganizations would have less need for distributed informationprocessing and decision making. Thus, environmental com-plexity is likely to be positively correlated to perceived relativeadvantage of DWAs.

H4a: Perceived environmental complexity is positively re-lated to perceived relative advantage of DWAs.

2) Environmental Variability and Perceived Relative Advan-tage: In situations of high environmental variability, fast de-cisions have been found to be positively associated with better

performance [72]. Miller and Friesen [79] argued that managersstudy the organizational environment more carefully when itis dynamic and variable. The gathered information is then in-terpreted and used to construct strategic and operational plansand actions [21], [69]. Since distributed work could improvethe efficiency and analytical ability of employees using thearrangement [27], [35] and could also permit them to maketimely decisions when necessary [84], organizations operatingin environments of high variability could be in the advantageousposition to be able to respond quickly to rapidly changingconditions. In contrast, such advantages would be less usefulto organizations in less variable environments.


H4b: Perceived environmental variability is positively re-lated to perceived relative advantage of DWAs.

3) Environmental Complexity and Perceived Compati-bility: A good fit between the environment and formal or-ganizational arrangements is an important factor influencingorganizational effectiveness [78], [84]. Organizations oftenhave to restructure themselves toward greater decentralizationto respond more effectively to complexities in their environ-ment [49], [84]. To achieve higher performance [50], [77],organizations within complex environments are likely to havedecentralized structures and management procedures [79], [84].Organizations have also been known to take on virtual organ-ization-like designs to meet the challenges of uncertainties intheir environment [95], [98]. Indeed, the goals of organizationswithin uncertain environments appear to coincide with theespoused objectives of DWAs. Since DWAs involve working indistributed settings with decentralized structures and manage-ment procedures, organizations in highly complex environmentsshould view DWAs to be more compatible to their organizationsthan organizations in environments of lower complexity.

H5a: Perceived environmental complexity is positively re-lated to perceived compatibility of DWAs.

4) Environmental Variability and Perceived Compati-bility: Organizations operating in highly variable environ-ments had to acquire higher levels of analytical and informationprocessing abilities [1], [79], higher levels of innovation [14],[77], [119], and learn to readapt themselves continually [34]more than those in less dynamic environments. The dynamicenvironment should be studied more carefully, so as to lead tosuperior organizational performance [37]. The work practices,values, and norms arising from the adoption of DWA providesa conducive condition for distributed workers to acquire higherlevels of information processing, learning, and innovativeabilities and, thus, should be perceived to be compatible withorganizations in environments of high variability.

H5b: Perceived environmental variability is positively re-lated to perceived compatibility of DWAs.

5) Environmental Complexity and Perceived Com-plexity: DWA could be a complex innovation to an adoptingorganization because it involves the redesign of both techno-logical and administrative infrastructure. On the other hand, tomanage the heterogeneity of factors affecting them, organiza-tions in complex environments have to restructure themselvesto operate in a distributed manner [79]. Through these restruc-turing, organizations in highly uncertain environments learnwhat is workable for them, while developing a capacity forchange at the same time [25], [73], [99]. Hence, insofar thatthese organizations have gathered considerable experiencein such reorganizations, they are more likely to view DWAsas less complex than those organizations in less complexenvironments.

H6a: Perceived environmental complexity is negatively re-lated to perceived complexity of DWAs.

6) Environmental Variability and Perceived Com-plexity: Organizations in dynamic environments, like thosein complex environments, are likely to acquire the ability toreadapt itself [25], [34], [73], [99]. Given the extensive infor-mation processing and analysis that had to be performed bysuch organizations [79] to manage the variable environment,

adoption of DWA should not be perceived as particularlycomplex as compared to firms in less variable environments.

H6b: Perceived environmental variability is negatively re-lated to perceived complexity of DWAs.

III. RESEARCH METHODOLOGY

This study employed a questionnaire survey method to gatherdata on the perceptions and intentions of top-level executives to-ward DWAs. A literature review was performed on the areas ofenvironmental uncertainty, innovation diffusion theory, and dis-tributed work to generate the survey instrument. The opinionsof five executives were then sought to assess the face validityof the instrument. A pilot study involving 20 executives fromvarious industry sectors (insurance, manufacturing, and real es-tate) was conducted to assess the reliability and validity of theresearch constructs. The survey questionnaire was administeredto the chief executive officers (CEO) of 720 organizations listedin Dun and Bradstreet.

A. Survey Instrument

Environmental uncertainty was operationalized with twoconstructs, perceived environmental complexity and perceivedenvironmental variability. Perceived, rather than actual, envi-ronmental factors were measured in this study because researchhas found that perceptions and beliefs about the organizationalenvironment had a significantly greater impact on top manage-ment decision making than actual environmental realities [69].Perceived environmental complexity is the variety of environ-mental factors believed to affect organizations [16], [28], [34],[105]. It increases the diversity of environmental informationthat an organization needs to handle. In this paper, perceivedenvironmental complexity is measured by whether the organi-zation environment leads to difficulties in gathering sufficientand necessary information about the environment, analyzingthe causes and effects of the environment, and predicting thetrends and outcomes of external events. Perceived environ-mental variability is defined as beliefs about the frequency ofchanges in the environmental factors [28]. It is measured as therapidity of changes in external events, in external trends, andthe number of possible outcomes in the environment.

Organizational attitudes were assessed using three factorsof innovation diffusion theory that were consistent significantpredictors of adoption behavior [109]: perceived relative ad-vantage, perceived compatibility, and perceived complexity.Perceived relative advantage was measured by whether DWAscould increase productivity, responsiveness to customers’needs, and performance [27], [35], [84], [107]. Perceived com-patibility was measured by whether DWAs would be acceptableto organizations’ management, supported by organizations’ ITinfrastructure and management practices, and consistent withorganizations’ human resources policies [57], [84]. Perceivedcomplexity was measured by whether it would be difficult forthe organization to coordinate work, build employee’s com-mitment to the organization, control the quality of work, andachieve organizational learning, when the organization adoptsDWA [27], [35], [84], [107]. Adoption intention for DWA wasmeasured by whether the organization would adopt it within thenext two years. All questions were anchored on a seven-pointscale from strongly disagree (1) to strongly agree (7).


B. Data Collection

The survey questionnaire was sent to 720 CEOs of smalland medium organizations randomly selected from the Dunand Bradstreet directory. CEOs, the key decision-makers, werechosen because they are likely to be cognizant with manyaspects of their organizations. The Theory of Planned Behaviorpredicts that a decision-maker’s attitudes toward an innovationhave significant influence on actual adoption behavior [2]. Thisprediction has received empirical support in past research on al-ternative work arrangements [35], which found that managerialadoption of nontraditional forms of work arrangements suchas partial and full-time work-at-home, flextime, compressedwork week schemes, can be predicted by their current attitudes.Tomaskovic-Devey and Risman [107] also found that positive“gut” reaction of the chief executive is strongly related bothto the potential adoption, as well as actual adoption behavioramong the current adopters. In this paper, the chief executives’attitudes toward distributed work could also serve as a usefulsurrogate for organizational perceptions toward it for severalreasons [23]. First, distributed work involves major restruc-turing and rethinking of communication needs of employeesand thus requires infrastructural planning. When adopting radi-cally new innovations like distributed work, the attitudes of topmanagement toward the innovation are of critical importance[23]. The chief executive is likely to be the key decision-makerof such strategic issues, and his or her views and endorsementare vital, particularly in the small and medium enterprisessurveyed in this research [44], [62]. Second, the chief executiveplays a boundary-spanning role, being involved in industryassociations, professional committees, or public committees.Thus, the chief executive is probably the most suitable personto assess the nature of the environment in which the organi-zation exists. Third, the chief executive is often the person totranslate inputs from the environment into issues that should beaddressed by the organization.

A definition and description of DWAs were included in theinitial portion of the questionnaire to ensure that all respon-dents had a consistent concept of what is involved in distributedwork, and to minimize confusion. In this study, DWAs are de-fined as organizational schemes, whereby employees work awayfrom the office (at customers’ sites or anywhere deemed con-ducive and appropriate) through the application of informationtechnology. Examples include, but are not limited to, supplyingemployees with computers, modems, and other equipment sothat they can access organizational information, while meetingwith clients or working away from the office. Besides the ques-tionnaire, a cover letter stating the purpose of the study, and aself-addressed return envelope with postage was sent in a parcelto each potential respondent. A hot line was available to respon-dents to clarify any doubts. Follow-up calls were made to thosewho had not responded after two weeks. Another round of callswas made two weeks later to help increase the response rate.Among the 720 parcels delivered, 46 were returned because thetargeted organizations had closed down or relocated. Responseswith too much missing information and those from adopters ofDWAs were removed from data analyses. Among 131 usablequestionnaires received, 55 were from the manufacturing in-dustry, while 76 were from the service industry. This yieldeda response rate of 19.4%. Similar response rates had been con-sidered adequate in studies of a similar nature (e.g., [63]).

Industry sector and organization size in terms of number ofemployees were used separately as the criteria for the responsebias tests because they could indicate organizations’ willingnessto adopt innovations [24], [84] such as DWAs. No significantdifference was detected between responding and nonrespondingorganizations.

IV. DATA ANALYSES

PLS, a second-generation causal modeling statistical tech-nique [118], was used in this study. It permits the simultaneousassessment of the measurement model within the context of atheoretical structural model [45]. It attempts to maximize vari-ance explanation and theoretical model prediction and is moresuitable for exploratory research than LISREL, another struc-tural equation modeling technique [6]. PLS has been extensivelyemployed in information systems [3], [93], [103], [106].

A. Evaluating the Measurement Model

Convergent and discriminant validities of the research instru-ments were examined to establish the strength of the constructsused in the research model. Convergent validity of a constructrefers to the extent to which two or more attempts to measurethe construct are consistent with one another [19]. Convergentvalidity could be determined using three tests in PLS [46]: relia-bility of each item in a scale (the squared loading), the compositereliability or internal consistency of each scale, and the averagevariance extracted by each scale. In addition, Cronbach’s al-phas were also used to establish reliability of the constructs. Theresults of these tests on the measurement model are shown inAppendix A (Table III). The individual item reliabilities for allmeasures in the constructs were higher than the threshold valueof 0.5 ([45], [60]), indicating that each measure had more ex-planatory power than error. The composite reliabilities of eachconstruct with multiple measures were greater than 0.9, whichexceeded the recommended value of 0.8 [87]. These constructsalso had average variances extracted exceeding 80% [see Ap-pendix B (Table IV)], and had Cronbach alphas higher than 0.8.Thus, the constructs used in the research model had adequateconvergent validity and reliability.

Discriminant validity refers to the extent to which measuresof each construct are distinct from one another [15]. This isdetermined by ensuring that the average variance extracted foreach construct is greater than the squared correlations betweenconstructs [46], [54]. These statistics are shown in Appendix B.Results showed that the correlation between two constructs wasless than the square root of the average variance extracted by themeasures of a construct for all cases. This indicates that there issatisfactory discriminant validity among the construct measuresof the research model. In addition, since the squared correlationsin the correlation matrix did not exceed 0.8, and the variance in-flation factors in the collinearity diagnostics were not greaterthan 10, there should not be a problem of multicollinearity be-tween constructs [3], [60].

B. Evaluating the Structural Model

The structural model was assessed for its explanatory powerand path significance using the bootstrapping technique [86].The hypotheses were examined for the sign, size, and signifi-cance of the path coefficients. Since this is an exploratory study,


TABLE IIDESCRIPTIVE STATISTICS OF INDEPENDENT AND DEPENDENT VARIABLES

Fig. 2. Path estimate (standard error) of PLS analyses.

a 10% significance level was employed. The descriptive statis-tics is presented in Table II, while the results of PLS analysesare shown in Fig. 2.

The research variables accounted for 27.8% of the variance inthe intention to adopt DWAs. The explained variance exceededthe recommended threshold of 10% [42]. This indicates that theresearch variables could substantially predict the organizationpredisposition toward the adoption of DWAs. The data analysesrevealed that the standardized coefficients of paths between en-vironmental complexity and perceived relative advantage, andbetween environmental complexity and perceived compatibility,were significant (in the negative direction) at the 10% level ofsignificance. H4a and H5a were significant in the oppositedirection. Additionally, the standardized coefficients of pathsbetween perceived relative advantage and adoption intention,and between perceived compatibility and adoption intention,were significant at the 5% level of significance. H1 and H2 weresupported.

V. DISCUSSION

The results of the PLS analyses on the structural modelrevealed that an organization’s perceptions of environmentalcomplexity could affect its perceptions of the relative advan-tages and compatibility of DWAs. However, the directionsfor these correlations were opposite to that hypothesized. Theperceptions of the two innovation factors in turn had a pos-itive influence on the adoption intention of distributed work(H1 and H2, respectively). Environmental variability did nothave any significant impact on all the innovation diffusion fac-tors investigated in this study. Similarly, the innovation factorperceived complexity did not affect the adoption intention of

distributed work. To assess whether differences exists in theway different industry types perceive their environments, at-test comparing the environmental complexity perceived bymanufacturing versus service organizations, and another t-testcomparing the perceived environmental variability of manu-facturing against service organizations were performed. Theresults found no significant differences in the perceived envi-ronmental complexity and perceivedenvironmental variability of manufac-turing versus service firms. Thus, the subsequent discussionsdo not differentiate between both types of organizations.

A. Environmental Complexity and Perceived InnovationCharacteristics

In this study, environmental complexity was found to havea significant negative influence on both perceived relative ad-vantage and perceived compatibility. Contrary to expectations,environmental complexity was not positively associated withbetter perceptions of the relative advantage and compatibility ofdistributed work in this study, despite the need for organizationsin complex environments to adopt distributed structures [79],[48]. This contradicts past literature that indicates a positive cor-relation between environmental uncertainty and organizationalchange/innovation [24], [90]. There are a few plausible expla-nations. First, the organizations in this study may not be willingto go through an organizational change necessitated by adoptingDWA when they are operating in environments of higher com-plexity. This could be due to the preference of firms to maintaina certain level of internal structural and process stability in theface of a more complex environment [78]. Organizations mayalso perceive greater risk in carrying out such changes in anuncertain environment [11], [69]. Concerns such as being un-able to directly supervise workers, or the absence of synergismfrom employees working together at the same place to handleproblems in an uncertain environment, could contribute to thenegative perceptions of DWAs when environments are complex.It is also possible that decentralized structures necessitated byDWA may not be compatible with the need to have centralizedstructures when organizations are undergoing radical innova-tion adoption [41]. Empirically, greater risk has been found asa deterrent to the organizational adoption of a financial elec-tronic data interchange system [102]. This situation could alsoapply to the perceptions of DWAs in complex environments.Second, the positive relationship between environmental com-plexity and the adoption of innovations may be moderated bysome other important organizational variables, such as structuralcomplexity and organization size [24], [49], alignment between


environmental realities and organizational structures and pro-cesses [78], and the technology-organization congruence [10],[41]. These relationships could be tested in future research.

This study found no significant impact of environmental com-plexity on the perceived complexity of DWAs. A possible reasonfor this finding could be that perceived complexity is not an im-portant issue to many of the respondents, as compared to relativeadvantage and compatibility.

B. Environmental Variability and Perceived InnovationCharacteristics

The results of this study also indicated that environmentalvariability did not have a significant effect on all the innovationdiffusion factors investigated. There are several possible ex-planations. First, while DWA could permit a greater amount ofinformation to be processed by individual distributed workers,organizations may not view DWA to be a work arrangement thatwould allow more information processing and analysis to becarried out at the organizational level, as is required by organiza-tions in volatile environments. Further, organizations in highlyvariable environments maynot perceive DWA to be able to help them to continually learnto readapt themselves, which is an important characteristic offirms in dynamic environments [34]. The net effect would bethat neither firms in more variable or firms in less variableenvironments would consider DWA adoption to be beneficialand compatible to them. Second, scholars have contended thatorganizations in highly variable environments are often over-whelmed in their abilities for prediction and management ofenvironmental factors [38], [104]. This is consistent with theresults of Baron and Hannan [8], which found that even inhighly turbulent environments, high-technology startups thatattempt to change their organizational work practices wouldexperience increased employee turnover and decreased organi-zational performance. This is contrary to the expectation thatthey would have developed the capability to adjust themselvesto such new work practices. Given such concerns, firms in thisstudy that are functioning in dynamic environments could havefound their organizational environments to be so uncertain thatthey would not want to consider introducing even more un-certainty factors with the adoption of DWAs. A third possibleexplanation could be that environmental variability did nothave a direct impact on executives’ perceptions of these inno-vation factors. Rather, the relationship could be mediated bythe executives’ abilities to interpret and understand a variableenvironment, which had been identified as being particularlyimportant to their decision-making in such environments [12],[37]. These contentions should be tested in future researchso as to develop insights into how organizations in variableand dynamic environments perceive innovative work arrange-ments, the types of work practices that would be beneficialto organizations in such environments, as well as the decisionmaking criteria and concerns of executives when adopting suchwork arrangements.

In summary, the results on environmental uncertainty andinnovation diffusion factors indicate that management tends tohave a better perception of the advantages of DWAs, and ofits compatibility to the organization, when the organizationalenvironment is perceived to be less complex. Environmentvariability does not appear to have any direct effect on theseperceptions.

C. Perceived Innovation Characteristics and AdoptionIntention

Perceived relative advantage and perceived compatibilitywere found to be positively related to adoption intention forDWAs. This finding agrees with past innovation diffusionresearch that found relative advantage and compatibility to beimportant factors influencing adoption behavior [41], [56], [67],[109]. The findings of this study suggest that relative advantageand compatibility of distributed work are important predictorsof organizational decision-makers’ adoption intentions.

Perceived complexity was not found to have a significant im-pact on the adoption intention of the respondents, despite nu-merous innovation studies indicating a negative association be-tween complexity and adoption [56], [109]. A plausible expla-nation could be that many respondents did not perceive com-plexity to be a very important criterion in deciding whether toadopt distributed work. This contention could be investigated infuture research.

D. Implications for Organizations

The results of this study highlight the importance of un-derstanding the relative advantages and compatibility ofDWA when organizations decide on whether to adopt theinnovative work arrangement, within the environmentalcontext of the firm. Specifically, firms in environmentsof lower complexity have been found to view DWA asmore beneficial and compatible to their organizations thanfirms in environments of higher complexity. However, en-vironmental dynamism ,which is higher in this study than environmental complexity

, did not seem to have animpact on executives’ attitudes on the benefits and fit of DWAto their organizations. This could be because the environmentaluncertainty for these organizations may have been perceived tobe so high (both complexity and variability dimensions con-tribute to environmental uncertainty, with variability having aneven greater impact on uncertainty perceptions than complexity[34] that they would not find the introduction of new work prac-tices to be acceptable. Overall, these findings suggest that themore firms view their environments to be uncertain, the morethey would be unwilling to adopt DWA. This is consistent withthe findings of research of Emery and Trist [38], Terreberry[104], and Baron and Hannan [8] that organizations in highlyuncertain environments often exceeded their organizationalcapability to handle the exigencies of the environment. Theywould strive to achieve a smooth and stable functioning ofinternal processes and practices before attempting to introducedisruptive changes [78] that would nevertheless have to beinstituted continually to achieve organizational survival andcompetitiveness [71].

The importance of environmental complexity has implica-tions on how organizations could adopt distributed work. For or-ganizations in environments of higher complexity, the findingshave indicated that organizations tend to have relatively negativeperceptions of DWAs’ advantage and compatibility as comparedwith organizations in lower complexity environments. Lack ofcapability [4], [55] to deal with the environment could be animportant concern for potential adopters of DWAs in complexenvironments, especially if the organizational architecture doesnot fit the requirements of the situation [85]. Besides, managers


tend to have a strong need for certainty and stability [30]. To ad-dress the concerns of firms when adopting innovations [23], par-ticularly in environments of high complexity, decision-makersneed to be convinced of the advantages of distributed work totheir organizations, and are informed of ways in which compat-ibility between DWA and their organizations can be achieved,such as by restructuring their organizations and processes, andby upgrading their technological resources. This is because thelack of awareness and capability could be a critical impedimentto the adoption of innovations [4]. Thus, executives could firstalter their organizational structures to be more compatible withDWAs. Compatibility between DWAs and organizations couldbe achieved by various means. First, the technological infra-structure has to be brought up to the level required to coordinateand perform the distributed tasks of workers. For instance, thiscould be facilitated by providing employees with ready accessto organizational systems and informational resources throughadvanced telecommunications infrastructure, thereby creating asupportive environment for distributed work. Second, admin-istrative processes, reward structures that emphasizes on theuse of objective and measurable performance indicators, per-formance monitoring/reporting mechanisms, and ultimately thework norms and value system would have to be adapted so asto be aligned to the requirements and needs of distributed workenvironments [78]. This could be attained by empowering em-ployees or functions to gather and evaluate relevant informa-tion [17], [79], and the institutionalization of flexible organi-zational structures that facilitate decentralized decision-making[24], such as those in virtual organizations.

Successful decision-makers in environments of high vari-ability tend to engage in comprehensive information processingand cognitive processes [37], [52] to increase their under-standing of environmental conditions [21], [69]. This wouldincrease their confidence during decision-making and imple-mentation [12], [37], [80], [81]. Such organizations would feelmore confident about adopting DWA in highly turbulent envi-ronments if they could first increase the organizational abilityto gather and process information about the environment so asto better understand it. Ways for organizations to achieve thisinclude enhancing their environmental scanning capability, hireor develop in-house capability to analyze and make sense of thegathered environmental data, or enlist the help of sophisticatedbusiness intelligence systems to highlight critical trends andissues.

Since relative advantage and compatibility have been foundto be important predictors of adoption intention, top manage-ment within organizations should actively seek information onthe benefits and compatibility of distributed work once an organ-ization has made the decision to adopt. The gathered informa-tion, together with the success stories from other organizations,would provide the marketing tool to sell DWA to employees ofthe organization.

VI. LIMITATIONS AND FUTURE RESEARCH

This research has its limitations. Specifically, perceptual mea-surements were mainly used to assess respondents’ attitudestoward DWAs. Concerns about gathering data on perceptionsrather than actual behavior were alleviated to some extent in thisstudy by conducting an extensive literature review on the vari-ables of interest, and subjecting those variables to convergent

and discriminant validity assessments. Another possible limita-tion of this study is that there exists a potential for differentialimpacts of perceived versus actual environmental factors on de-cision-making among the respondents. The decision to measureperceived rather than actual environmental factors in this studywas informed by the research of [69] and [70], among others,that managerial decisions and actions are predicated more bytheir beliefs about the environment, rather than what the actualenvironmental reality is. This is particularly true for decisionmakers in small and medium firms, as was the case in this study,who tend to make organizational decisions based on intuitionand beliefs rather than a rational decision process that takes intoaccount a comprehensive set of objective information [92]. Nev-ertheless, it could still be interesting to compare the effects ofperceived versus actual environmental influences on the adop-tion of DWAs in future research.

Several avenues of further work could be suggested. First,the risk involved in introducing DWA to organizations in un-certain environments would be an interesting theme for futurestudies. Bourgeois [11] noted that dynamic environments tendto increase the risk and difficulty of effective strategy formula-tion. Thus, the perception of risk among decision-makers couldprovide interesting insights into their intention to adopt dis-tributed work in environments of varying uncertainties. Second,Eisenhardt [37] suggested that the certainty resulting from un-derstanding the organizational environment is critical to thedecision-making of top management teams. Thus, future workcould investigate whether the effectiveness of managementin successfully interpreting and understanding the organiza-tional environment has an effect on their intentions to adoptDWAs, under conditions of both environmental certainty anduncertainty. Third, past research mainly sought to establishwhich of the organizational innovation diffusion factors hadan impact on adoption behavior. Very few seek to establish therelative salience of those innovation factors, which is an im-portant criterion proposed by the Theory of Planned Behaviorto predict behavior intentions [2]. Fourth, less than widespreadadoption of DWAs has limited the study to that of adoptionintentions. Thus, future work could compare the effects ofperceived versus actual environmental uncertainties, and theimpact of different sectors of the environment [111] on actualdecisions to adopt distributed work when it becomes morewidely accepted with the emergence of virtual organizations,in the tradition of Eisenhardt’s research on high velocity en-vironments (e.g., Eisenhardt, [37]).

This study seeks to explore the effect of environmental influ-ences, specifically environmental complexity and variability, onthe perceptions of decision-makers toward DWAs. The resultsindicate that these decision-makers have a positive perceptionof DWAs when their organizational environment is less com-plex, contrary to popular expectations. Organizations that seekto implement DWAs should focus on assessing the relativeadvantages of DWA to their firms, and direct their efforts at estab-lishing its compatibility with the organization. Distributed workarrangement has the potential to be an effective organizationalstrategy to meet the challenges of an uncertain environment,especially in virtual organizations. Systematic research in thisarea would provide organizational decision-makers with thenecessary knowledge to consider their next strategic move.


APPENDIX ARESULTS OF TESTS ON CONVERGENT VALIDITY

TABLE III


APPENDIX BCORRELATION AND SQUARE ROOT OF AVERAGE VARIANCE EXTRACTED OF CONSTRUCTS

TABLE IV

REFERENCES

[1] F. J. Aguilar, Scanning the Business Environment. New York:Macmillan, 1967.

[2] I. Ajzen, “The theory of planned behavior,” Org. Behav. Human Dec.Processes, vol. 50, no. 2, pp. 179–211, 1991.

[3] D. L. Amoroso and P. H. Cheney, “Testing a causal model of end userapplication effectiveness,” J. Manage. Inform. Syst., vol. 8, no. 1, pp.63–89, 1991.

[4] P. Attewell, “Technology diffusion and organizational learning: The caseof business computing,” Org. Sci., vol. 3, no. 1, pp. 1–19, 1992.

[5] L. Bailyn, “Toward the perfect workplace?,” Commun. ACM, vol. 32,no. 4, pp. 460–471, 1989.

[6] D. C. Barclay, C. Higgins, and R. Thompson, “The partial least squaresapproach to causal modeling: Personal computer adoption and use as anillustration,” Technol. Stud., vol. 2, no. 2, pp. 285–308, 1995.

[7] N. R. Baker and J. R. Freeland, “Structuring information flows toenhance innovation,” Manage. Sci., vol. 19, no. 1, pp. 105–116,1972.

[8] J. N. Baron and M. T. Hannan, “Organizational blueprints for successin high-tech start-ups: Lessons from the stanford project on emergingcompanies,” Calif. Manage. Rev., vol. 44, no. 3, p. 8, 2002.

[9] A. Barua, S. C. H. Lee, and A. B. Whinston, “Incentives and com-puting systems for team-based organizations,” Org. Sci., vol. 6, no. 4,pp. 487–504, 1995.

[10] F. Belanger, R. W. Collins, and P. H. Cheney, “Technology requirementsand work group communication for telecommuters,” Inform. Syst. Res.,vol. 12, no. 2, pp. 155–176, 2001.

[11] L. J. Bourgeois, “Strategic goals, perceived uncertainty and economicperformance,” Acad. Manage. J., vol. 28, no. 3, pp. 548–573, 1985.

[12] L. J. Bourgeois and K. Eisenhardt, “Strategic decision processes inhigh velocity environments: Four cases in the microcomputer industry,”Manage. Sci., vol. 34, no. 7, pp. 816–838, 1988.

[13] B. K. Boyd and J. Fulk, “Executive scanning and perceived uncertainty:A multidimensional model,” J. Manage., vol. 22, no. 1, pp. 1–21, 1996.

[14] T. Burns and G. Stalker, The Management of Innovation, London: Tavi-stock, 1961.

[15] D. T. Campbell and D. W. Fiske, “Convergent and discriminant valida-tion by the multitrait-multimethod matrix,” Phys. Bull., vol. 56, no. 1,pp. 81–105, 1959.

[16] J. Child, “Organizational structure, environment and performance: Therole of strategic choice,” Sociology, vol. 6, no. 1, pp. 2–22, 1972.

[17] J. Child, “Organizational design and performance: Contingency theoryand beyond,” Org. Admin. Sci., vol. 8, no. 2, pp. 169–183, 1977.

[18] P. D. Collins, J. Hage, and F. M. Hull, “Organizational and technologicalpredictors of change in automaticity,” Acad. Manage. J., vol. 31, no. 3,pp. 512–543, 1988.

[19] T. D. Cook and D. T. Campbell, Quasi-Experimentation: Design andAnalysis Issues for Field Settings. Boston, MA: Houghton Mifflin,1979.

[20] R. B. Cooper and R. W. Zmud, “Information technology implementationresearch: A technological diffusion approach,” Manage. Sci., vol. 36, no.2, pp. 123–139, 1990.

[21] R. L. Daft and K. E. Weick, “Toward a model of organizations as in-terpretation systems,” Acad. Manage. Rev., vol. 9, no. 2, pp. 284–295,1984.

[22] R. L. Daft, J. Sormunen, and D. Parks, “Chief executive scanning, en-vironmental characteristics, and company performance: An empiricalstudy,” Strategic Manage. J., vol. 9, no. 1, pp. 123–139, 1988.

[23] F. Damanpour, “Organizational innovation: A meta-analysis of effectsof determinants and moderators,” Acad. Manage. J., vol. 34, no. 3, pp.555–590, 1991.

[24] F. Damanpour, “Organizational complexity and innovation: Developingand testing multiple contingency models,” Manage. Sci., vol. 42, no. 5,pp. 693–716, 1996.

[25] D. R. Denison and A. K. Mishra, “Toward a theory of organizationalculture and effectiveness,” Org. Sci., vol. 6, no. 2, pp. 204–223, 1995.

[26] R. DePietro, E. Wiarda, and M. Fleischer, “The context for change: Or-ganization, technology, and environment,” in The Processes of Techno-logical Innovation, L. G. Tornatzky and M. Fleischer, Eds. Lexington,MA: Lexington Books, 1990, pp. 151–175.

[27] G. DeSanctis, “Attitudes toward telecommuting: Implications forwork-at-home programs,” Inform. Manage., vol. 7, no. 3, pp. 133–139,1984.

[28] G. G. Dess and D. W. Beard, “Dimensions of organizational task envi-ronments,” Adm. Sci. Quart., vol. 29, no. 1, pp. 52–73, 1984.

[29] M. D. Dickerson and J. W. Gentry, “Characteristics of adopters andnonadopters of home computers,” J. Consumer Res., vol. 10, no. 2, pp.225–235, 1983.

[30] P. J. DiMaggio and W. W. Powell, “The iron cage revisited: Institutionalisomorphism and collective rationality in organizational fields,” Amer.Sociol. Rev., vol. 48, no. 2, pp. 147–160, 1983.

[31] G. W. Downs Jr. and L. B. Mohr, “Conceptual issues in the study ofinnovation,” Adm. Sci. Quart., vol. 21, no. 4, pp. 700–714, 1976.

[32] H. Druke, G. Feuerstein, and R. Kreibich, “Trends of decentralizationof white collar activities by means of information and communicationstechnologies,” in Telework: Present Situations and Future Developmentof A New Form of Work Organization, W. B. Korte, S. Robinson, and W.J. Steinle, Eds, Amsterdam, The Netherlands: Elsevier, 1988.

[33] Dun and Bradstreet, Dun’s Asia/Pacific Key Business Enter-prises. Murray Hill, NJ: Dun and Bradstreet International, 1994.

[34] R. B. Duncan, “Characteristics of organizational environments and per-ceived environmental uncertainty,” Adm. Sci. Quart., vol. 17, no. 3, pp.313–327, 1972.

[35] L. E. Duxbury and G. Haines Jr., “Predicting alternative work arrange-ments from salient attitudes: A study of decision-makers in the publicsector,” J. Bus. Res., vol. 23, no. 1, pp. 83–97, 1991.

[36] L. E. Duxbury, C. A. Higgins, and S. Mills, “After-hours telecommutingand work-family conflict: A comparative analysis,” Inform. Syst. Res.,vol. 3, no. 2, pp. 173–190, 1992.


[37] K. M. Eisenhardt, “Making fast strategic decisions in high velocity en-vironments,” Acad. Manage. J., vol. 32, no. 3, pp. 543–576, 1989.

[38] F. E. Emery and E. Trist, “The causal texture of organizational environ-ments,” Hum. Relations, vol. 18, no. 1, pp. 21–31, 1965.

[39] J. E. Ettlie, “Organizational policy and innovation among suppliers tothe food-processing sector,” Acad. Manage. J., vol. 26, no. 1, pp. 27–44,1983.

[40] J. E. Ettlie and W. P. Bridges, “Environmental uncertainty and organiza-tional technology policy,” IEEE Trans. Eng. Manage., vol. EM–29, pp.2–10, 1982.

[41] J. E. Ettlie, W. P. Bridges, and R. D. O’Keefe, “Organizational strategyand structural differences for radical versus incremental innovation,”Manage. Sci., vol. 30, no. 6, pp. 682–695, 1984.

[42] R. F. Falk and N. B. Miller, A Primer for Soft Modeling. Akron, OH:Univ. Akron Press, 1992.

[43] S. Finkelstein, “Power in top management teams: Dimensions, measure-ment, and validation,” Acad. Manage. J., vol. 35, pp. 505–539, 1992.

[44] S. Finkelstein and D. C. Hambrick, “Top-management-team tenure andorganizational outcomes: The moderating role of managerial discretion,”Admin. Sci. Quart., vol. 35, no. 3, pp. 484–503, 1990.

[45] C. Fornell, A Second Generation of Multivariate Analysis, Methods:Volume 1. New York: Praeger, 1982.

[46] C. Fornell and D. F. Larcker, “Structural equation models with unob-servable variables and measurement errors,” J. Marketing Res., vol. 18,no. 1, pp. 39–50, 1981.

[47] M. B. W. Fritz, S. Narasimhan, and H. S. Rhee, “Communication andcoordination in the virtual office,” J. Manage. Inform. Syst., vol. 14, no.4, pp. 7–28, 1998.

[48] J. R. Galbraith, Designing Complex Organizations. Reading, MA: Ad-dison-Wesley, 1973.

[49] , Organization Design. Reading, MA: Addison-Wesley, 1977.[50] J. R. Galbraith and R. K. Kazanjian, Strategy Implementation: Structure,

Systems, and Process. St. Paul, MN: West, 1986.[51] M. S. Gerstein, “From machine bureaucracies to networked orga-

nizations: An architectural journey,” in Organizational Architecture:Designs for Changing Organizations, D. A. Nadler, M. S. Gerstein,and R. B. Shaw, Eds. San Francisco, CA: Jossey-Bass, 1992, pp.11–38.

[52] I. Goll and A. M. A. Rasheed, “Rational decision-making and firm per-formance: The moderating role of environment,” Strategic Manage. J.,vol. 18, no. 7, pp. 583–591, 1997.

[53] G. E. Gordon, “The dilemma of telework: Technology vs. tradition,” inTelework: Present Situations and Future Development of A New Formof Work Organization, W. B. Korte, S. Robinson, and W. J. Steinle, Eds,Amsterdam, The Netherlands: Elsevier, 1988.

[54] R. A. Grant, “Building and testing a model of an information tech-nology’s impact,” in Proc. 10th Int. Conf. Information Systems, Boston,MA, 1989, pp. 173–184.

[55] R. Greenwood and C. R. Hinings, “Understanding radical organizationalchange: Bringing together the old and the new institutionalism,” Acad.Manage. Rev., vol. 21, no. 4, pp. 1022–1054, 1996.

[56] V. Grover, “An empirically derived model for the adoption of customer-based interorganizational systems,” Decision Sci., vol. 24, no. 3, pp.603–640, 1993.

[57] Y. P. Gupta, J. Karimi, and T. M. Somers, “Telecommuting: Problemsassociated with communications technologies and their capabilities,”IEEE Trans. Eng. Manage., vol. 42, pp. 305–318, Nov. 1995.

[58] R. Guthrie, “The ethics of telework,” Inform. Syst. Manage., vol. 14, no.4, pp. 29–32, 1997.

[59] J. Hage and M. Aiken, “Relationship of centralization to other structuralproperties,” Adm. Sci. Quart., vol. 24, no. 4, pp. 603–640, 1967.

[60] J. F. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, MultivariateData Analysis with Readings, 4th ed. Englewood Cliffs, NJ: Prentice-Hall, 1995.

[61] D. C. Hambrick, “Environmental scanning and organizational strategy,”Strategic Manage. J., vol. 3, no. 2, pp. 159–173, 1982.

[62] D. C. Hambrick and P. A. Mason, “Upper echelons: The organization as areflection of its top managers,” Acad. Manage. Rev., vol. 9, pp. 193–206,1984.

[63] J. Hann and R. Weber, “Information systems planning: A model andempirical tests,” Manage. Sci., vol. 42, no. 7, pp. 1043–1064, 1996.

[64] S. J. Harrington and C. P. Ruppel, “Practical and value compatibility:Their roles in the adoption, diffusion, and success of telecommuting,” inProc. 20th Int. Conf. Information Systems, P. De and J. I. DeGross, Eds.,Charlotte, NC, 1999, pp. 103–112.

[65] L. Hirschhorn, Beyond Mechanization: Work and Technology in aPostindustrial Age. Cambridge, MA: MIT Press, 1984.

[66] E. C. Hirschman, “Symbolism and technology as sources for the gener-ation of innovations,” in Advances in Consumer Research, A. Mitchell,Ed. St. Louis, MO: Association for Consumer Research, 1981, vol. 9,pp. 537–541.

[67] S. L. Holak and D. R. Lehmann, “Purchase intentions and the dimen-sions of innovation: An exploratory model,” J. Prod. Innov. Manage.,vol. 7, no. 1, pp. 59–73, 1990.

[68] G. P. Huber, K. M. Sutcliffe, C. C. Miller, and W. H. Glick, “Un-derstanding and predicting organizational change,” in OrganizationalChange and Redesign, G. P. Huber and W. H. Glick, Eds. New York:Oxford Univ. Press, 1993.

[69] L. A. Isabella and S. A. Waddock, “Top management team certainty:Environmental assessments, teamwork, and performance implications,”J. Manage., vol. 20, no. 4, pp. 835–858, 1994.

[70] S. E. Jackson and J. E. Dutton, “Discerning threats and opportunities,”Adm. Sci. Quart., vol. 33, no. 3, pp. 370–387, 1988.

[71] M. Johnson, Managing in the Next Millennium. London, U.K.: Butter-worth, 1995.

[72] W. Q. Judge and A. Miller, “Antecedents and outcomes of decision speedin different environmental contexts,” Acad. Manage. J., vol. 34, no. 2, pp.449–463, 1991.

[73] R. M. Kanter, The Change Masters: Innovations for Productivity in theAmerican Corporation. New York: Simon and Schuster, 1983.

[74] T. R. Kayworth and D. E. Leidner, “Leadership effectiveness in globalvirtual teams,” J. Manage. Inform. Syst., vol. 18, no. 3, pp. 7–40, 2002.

[75] W. B. Korte, “Telework—Potentials, inceptions, operations and likelyfuture situations,” in Telework: Present Situations and Future Develop-ment of A New Form of Work Organization, W. B. Korte, S. Robinson,and W. J. Steinle, Eds, Amsterdam, The Netherlands: Elsevier, 1988.

[76] D. G. LaBay and T. C. Kinnear, “Exploring the consumer decisionprocess in the adoption of solar energy systems,” J. Consumer Res., vol.8, no. 3, pp. 271–278, 1981.

[77] P. Lawrence and J. Lorsch, Organization and Environment: ManagingDifferentiation and Integration. Homewood, IL: Business One Irwin,1967.

[78] D. Miller, “Environmental fit versus internal fit,” Org. Sci., vol. 3, no. 2,pp. 159–178, 1992.

[79] D. Miller and P. H. Friesen, “Strategy making and environment: Thethird link,” Strategic Manage. J., vol. 4, no. 3, pp. 221–235, 1983.

[80] F. J. Milliken, “Three types of perceived uncertainty about the environ-ment: State, effect and response uncertainty,” Acad. Manage. Rev., vol.12, no. 1, pp. 133–143, 1987.

[81] , “Perceiving and interpreting environmental change: An ex-amination of college administrators’ interpretation of changingdemographics,” Acad. Manage. J., vol. 33, no. 1, pp. 42–63, 1990.

[82] D. A. Nadler, “Organizational architecture: A metaphor for change,” inOrganizational Architecture: Designs for Changing Organizations, D.A. Nadler, M. S. Gerstein, and R. B. Shaw, Eds. San Francisco, CA:Jossey-Bass, 1992, pp. 1–8.

[83] D. A. Nadler and M. S. Gerstein, “Determining high-performance worksystems: Organizing people, work, technology, and information,” inOrganizational Architecture: Designs for Changing Organizations, D.A. Nadler, M. S. Gerstein, and R. B. Shaw, Eds. San Francisco, CA:Jossey-Bass, 1992, pp. 110–132.

[84] D. Nadler and M. Tushman, Strategic Organization Design: Concepts,Tools, and Processes. Glenview, IL: Scott, Foresman, 1988.

[85] D. A. Nadler and M. L. Tushman, “Designing organizations thathave good fit: A framework for understanding new architectures,” inOrganizational Architecture: Designs for Changing Organizations, D.A. Nadler, M. S. Gerstein, and R. B. Shaw, Eds. San Francisco, CA:Jossey-Bass, 1992, pp. 39–56.

[86] J. Neter, W. Wasserman, and G. A. Whitmore, Applied Statistics, 4thed. Englewood Cliffs, NJ: Prentice-Hall, 1993.

[87] J. C. Nunnally, Psychometric Theory. New York: McGraw-Hill, 1978.[88] M. H. Olson, “Remote office work: Changing work patterns in space and

time,” in Commun. ACM, vol. 26, 1983, pp. 182–187.[89] M. Olson, “Organizational barriers to telework,” in Telework: Present

Situations and Future Development of A New Form of Work Organiza-tion, W. B. Korte, S. Robinson, and W. J. Steinle, Eds, Amsterdam, TheNetherlands: Elsevier, 1988.

[90] J. L. Pierce and A. L. Delbecq, “Organization structure, individual at-titudes and innovation,” Acad. Manage. Rev., vol. 2, no. 1, pp. 26–37,1977.

[91] S. Qureshi and D. Vogel, “Organizational adaptiveness in virtual teams,”Group Decision and Negotiation, vol. 10, no. 1, pp. 27–46, 2001.

[92] G. H. Rice and R. E. Hamilton, “Decision theory and the small busi-nessman,” Amer. J. Small Bus., vol. 4, no. 1, pp. 1–9, 1979.


[93] S. Rivard and S. L. Huff, “Factors of success for end-user computing,”in Commun. ACM, vol. 31, 1988, pp. 552–561.

[94] E. M. Rogers, Diffusion of Innovations. New York: Free Press, 1995.[95] J. W. Ross and J. F. Rockart, “Enabling new organizational forms: A

changing perspective on infrastructure,” in Proc. 17th Int. Conf. Infor-mation Systems, J. I. DeGross, S. Jarvenpaa, and A. Srinivasan, Eds.,Cleveland, OH, 1996, pp. 455–456.

[96] C. P. Ruppel and S. J. Harrington, “Telework: An innovation where no-body is getting on the bandwagon?,” Data Base Adv. Inform. Syst., vol.26, no. 2 & 3, pp. 87–104, 1995.

[97] B. Shamir and I. Salomon, “Work-at-home and the quality of workinglife,” Acad. Manage. Rev., vol. 10, no. 3, pp. 455–464, 1985.

[98] P. Sieber, “Virtuality as a strategic approach for small and medium sizedIT companies to stay competitive in a global market,” in Proc. 17th Int.Conf. Information Systems, J. I. DeGross, S. Jarvenpaa, and A. Srini-vasan, Eds., Cleveland, OH, 1996, p. 468.

[99] W. H. Starbuck, Organizational Growth and Development, U.K.: Pen-guin, 1971.

[100] P. M. Swamidass and W. T. Newell, “Manufacturing strategy, environ-mental uncertainty and performance: A path analytic model,” Manage.Sci., vol. 33, no. 4, pp. 509–524, 1987.

[101] W. C. Taylor. (1995) At VeriFone, It’s a Dog’s Life (And They Love it)[Online]. Available: http://www.fastcompany.com/online/01/vfone.html

[102] H. H. Teo, B. C. Y. Tan, and K. K. Wei, “Innovation diffusion theoryas a predictor of adoption intention for financial EDI,” in Proc. 16thInt. Conf. Information Systems, J. I. DeGross, G. Ariav, C. Beath, R.Hoyer, and C. Kemerer, Eds., Amsterdam, The Netherlands, 1995,pp. 155–165.

[103] H. H. Teo, K. K. Wei, and I. Benbasat, “Predicitng intention to adoptinterorganizational linkages: An institutional perspective,” MIS Quart.,vol. 27, no. 1, pp. 19–49, 2003.

[104] S. Terreberry, “The evolution of organizational environments,” Adm. Sci.Quart., vol. 12, no. 4, pp. 590–613, 1968.

[105] J. D. Thompson, Organizations in Action. New York: McGraw-Hill,1967.

[106] R. L. Thompson, C. A. Higgins, and J. M. Howell, “Personal computing:Toward a conceptual model of utilization,” MIS Quart., vol. 15, no. 1,pp. 125–143, 1991.

[107] D. Tomaskovic-Devey and B. J. Risman, “Telecommuting innovationand organization: A contingency theory of labor process change,” Soc.Sci. Quart., vol. 74, no. 2, pp. 367–385, 1993.

[108] L. G. Tornatzky and M. Fleischer, The Process of Technological Inno-vation. Lexington, MA: Lexington Books, 1990.

[109] L. G. Tornatzky and K. J. Klein, “Innovation characteristics and in-novation adoption-implementation: A meta-analysis of findings,” IEEETrans. Eng. Manage., vol. EM–29, no. 1, pp. 28–45, 1982.

[110] L. G. Tornatzky, J. D. Eveland, and M. Fleischer, “Technological inno-vation as a process,” in The Processes of Technological Innovation, L. G.Tornatzky and M. Fleischer, Eds. Lexington, MA: Lexington Books,1990, pp. 27–50.

[111] H. Tosi, The Environment/Organization/Person Contingency Model: AMeso Approach to the Study of Organizations, London, U.K.: JAI Press,1992.

[112] H. L. Tosi and J. W. Slocum, “Contingency theory: Some suggested di-rections,” J. Manage., vol. 10, no. 1, pp. 9–26, 1984.

[113] J. M. Utterback, “The process of technological innovation within thefirm,” Acad. Manage. J., vol. 14, no. 1, pp. 75–88, 1971.

[114] , “Innovation in industry and the diffusion of technology,” Science,vol. 183, no. 4125, pp. 620–626, 1974.

[115] A. Venkatesh and N. P. Vitalari, “An emerging distributed work arrange-ment: An investigation of computer-based supplemental work at home,”Manage. Sci., vol. 38, no. 12, pp. 1687–1706, 1992.

[116] R. E. Walton, Up and Running: Integrating Information Technologyand the Organization. Boston, MA: Harvard Business School Press,1989.

[117] P. T. Ward, D. J. Bickford, and G. K. Leong, “Configurations ofmanufacturing strategy, business strategy, environment and structure,”J. Manage., vol. 22, no. 4, pp. 597–626, 1996.

[118] H. Wold, “Systems under indirect observation using PLS,” in A SecondGeneration of Multivariate Analysis, Methods: Volume 1, C. Fornell,Ed. New York: Praeger, 1982.

[119] G. Zaltman, R. Duncan, and J. Holbek, Innovations and Organiza-tions. New York, NY: Wiley and Sons, 1973.

[120] R. F. Zammuto and E. J. O’Connor, “Gaining advanced manufacturingtechnologies’ benefits: The roles of organization design and culture,”Acad. Manage. Rev., vol. 17, no. 4, pp. 701–728, 1992.

[121] R. W. Zmud, “An examination of ‘push-pull’ theory applied to processinnovation in knowledge work,” Manage. Sci., vol. 30, no. 6, pp.727–738, 1984.

[122] S. Zuboff, In the Age of the Smart Machine: The Future of Work andPower. New York: Basic Books, 1988.

Choon-Ling Sia is an Associate Professor of in-formation systems at the City University of HongKong, Kowloon. He is currently on the EditorialBoard of Information and Management and theJournal of Database Management. His researchwork has been published in Information SystemsResearch, IEEE TRANSACTIONS ON SYSTEMS,MAN, AND CYBERNETICS, ACM Transactions onComputer-Human Interaction, Decision SupportSystems, Information and Management, ElectronicMarkets, and Proceedings of the International Con-

ference on Information Systems. His research interests include distributed workarrangements, Internet commerce, virtual organizations, innovation adoption,electronic commerce, and group support systems.

Hock-Hai Teo received the Ph.D. degree in manage-ment of information systems from the National Uni-versity of Singapore (NUS), Singapore, in 1998.

He is currently an Assistant Professor of infor-mation systems with the Department of InformationSystems, NUS. He has published in the MIS Quar-terly, Journal of Management Information Systems,International Journal of Human-Computer Studies,Journal of Educational Computing Research, Infor-mation and Management, and Journal of DatabaseManagement and has presented at numerous inter-

national conferences, including the International Conference on InformationSystems. His research interests include electronic market trading institutions,technological innovation adoption, information privacy, virtual communities,and conceptual modeling.

Bernard C. Y. Tan received the Ph.D. degree in in-formation systems from National University of Sin-gapore (NUS), Singapore, in 1995.

He is an Associate Professor and Head of theDepartment of Information Systems, School ofComputing, NUS. He has won research and teachingawards at NUS. He has been a Visiting Scholar in theGraduate School of Business, Stanford University,Stanford, CA (1996–1997) and the Terry College ofBusiness, University of Georgia, Athens (1992). Heis serving on the Editorial Boards of MIS Quarterly

(Senior Editor), e-Service Journal (Senior Editor), Journal of the AIS, Infor-mation and Management, Journal of Global Information Management, and theInternational Journal of Distance Education Technologies. His research workhas been published in ACM Transactions on Computer-Human Interaction,ACM Transactions on Information Systems, Communications of the ACM,Decision Support Systems, European Journal of Information Systems, the IEEETRANSACTIONS ON ENGINEERING MANAGEMENT, the IEEE TRANSACTIONS

ON PROFESSIONAL COMMUNICATION, the IEEE TRANSACTIONS ON SYSTEMS,MAN, AND CYBERNETICS, Information and Management, Information SystemsResearch, International Journal of Human-Computer Studies, Journal ofManagement Information Systems, Journal of the AIS, Journal of the AmericanSociety for Information Science and Technology, Management Science, andMIS Quarterly. His current research focuses on cross-cultural issues, com-puter-mediated communication, knowledge management, and informationprivacy.


Kwok-Kee Wei is Head and Chair Professor of theDepartment of Information Systems, City Universityof Hong Kong, Kowloon. He has published widelyin the Information Systems field with more than 100publications including articles in MIS Quarterly,Management Science, Journal of ManagementInformation Systems, Information Systems Research,European Journal of Information Systems, and ACMTransactions on Computer-Human Interaction. Heis serving on the Series Editorial Advisory Boardof Idea Group Publishing/Information Science Pub-

lishing and on the Editorial Boards of a good number of international journals.He is on the Editorial Board of the IEEE TRANSACTIONS ON ENGINEERING

MANAGEMENT. He was the Senior Editor of MIS Quarterly (2000–2003). Hisresearch focuses on human–computer interaction, innovation adoption andmanagement, and knowledge management systems.

Dr Wei is currently serving on the Association of Information Systems (AIS)Council (2003–2004), and was elected President of that organization in 2001.His election to the AIS Presidency carries with it three years of AIS office, be-ginning on May 1, 2002 (the first year as AIS President-Elect, the second yearas AIS President, and the third year as AIS Immediate Past President).

ieee transactions on engineering · pdf fileby adopting dwa, a ﬁrm could be ... [52], [84],...

Documents