268 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, …€¦ · ganization can effectively innovate...

268 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 54, NO. 2, MAY 2007

Exploring Ambidextrous Innovation Tendencies inthe Adoption of Telecommunications Technologies

Varun Grover, Russell L. Purvis, and Albert H. Segars

Abstract—As the importance of information technology has in-creased within the business domain, so too has the significance ofinnovating within those information technologies. The recent pro-liferation of telecommunications technologies, coupled with con-ventional information technology, has resulted in a new class ofapplications with important competitive implications. An impor-tant issue for organizations, then, is the causal sequence that leadsto more innovative telecommunications adoption.

Previous innovation research has shown radical and incrementalinnovation employing vastly different strategy-structure sequenceconfigurations. Two proposals have been offered on how an or-ganization can effectively innovate incrementally and radically:first, through the use of semi-structures, and second, by utilizingboth configurations simultaneously, termed ambidextrous. Thispaper seeks 1) to determine whether organizations are balancinginnovation efforts, and 2) if so, are organizations managing theeffort using semi-structures or an ambidextrous approach. Theresearch is conducted within the telecommunications industryby employing theoretical typologies of radical and incrementalinnovation developed in the literature. Based on a sample of 154organizations the findings suggest that organizations are indeedusing a balanced approach to overall innovativeness by usingparadoxical, dual models of innovation simultaneously. Implica-tions for researchers and practitioners are discussed.

Index Terms—Ambidextrous organization, innovation, struc-tural equation modeling, telecommunications technologies.

I. INTRODUCTION

THE INCREASING demands of globalization, implemen-tation of sophisticated enterprise systems and the critical

need to be interconnected and networked to customers andsuppliers are but a few of the drivers of the powerful fusionof telecommunications and information systems. Combined,these technologies are becoming a vital component of the or-ganizational strategy [1]. Organizations are harnessing thesetechnologies for supply chain and logistic initiatives, customerresource management applications and e-commerce initiativesby merging process, storage, and communications technologiesinto a seamless system of transactions that are independent of theunderlying hardware or geographic locale. Diverse industriesincluding air travel, manufacturing, financial and retail institu-tions are exploiting these technologies and changing the waycompanies compete.

Manuscript received December 1, 2003; revised December 1, 2004,November 1, 2005, and April 1, 2006. Review of this manuscript was arrangedby Department Editor R. Sabherwal.

V. Grover and R. L. Purvis are with the College of Business & BehavioralScience, Clemson University, 301 Sirrine Hall, Clemson SC 29634-1305 USA(e-mail: [email protected]; [email protected]).

A. H. Segars is with the Kenan-Flagler Business School, The Universityof North Carolina at Chapel Hill, Chapel Hill, NC 27599-3490 USA (e-mail:[email protected]).

Digital Object Identifier 10.1109/TEM.2007.893995

Indeed, today’s technological climate is intense, offering nu-merous opportunities for innovation, any one of which couldprove pivotal to the competitiveness of the firm. Clearly, the ar-rival of these advanced communications networks has enormousconsequences for the mechanisms that govern the transfer of in-formation and reconciliation of transactions within and betweenorganizations. Traditional methods of information dissemina-tion within organizations as well as corporate policy manualsand standard operating procedures have quickly been replacedby intranets, extranets, and email. Further, structures of decisionrights and channel power between organizations have also beenradically altered as electronic forms of commerce supplementand, in many instances, replace traditional mechanisms for lo-cating and purchasing products and information.

While advanced communications technologies present avast array of possibilities in favorably redefining businessrelationships, they also represent a potential source of compet-itive concern for many organizations. The declining half-lifeof telecommunications technologies and the rapid prolifer-ation of new products in this arena challenge the ability oforganizational leaders to institute structures that facilitatethe identification and adoption of technologies necessary foran ever-changing competitive landscape. Often, traditionalorganizational structures associated with growth such as de-centralization and formalization inhibit rather than facilitatetechnological innovation [2]. Therefore, along with recognizingthe importance of communications technologies in the strategicagenda of the firm, top-management must also ensure that theorganizational structure supports technological innovativeness.

Technological innovations can be categorized as radical orincremental-the distinction being the perceived degree of newknowledge embodied in a technology [3]. Radical innovationsincorporate a technology that is a clear, risky departure from ex-isting practice [4], while incremental innovations are routine en-hancements to an existing technology [5]. Previous innovationresearch has shown radical and incremental innovation resultingfrom vastly different strategy-structure sequence configurations[6]–[8]. In general, incremental innovation is associated with or-ganizational structures more fit for enhancing and exploiting ef-ficiencies while radical innovation is associated with structuresmore fit for experimentation and exploration [6], [9]–[11].

Innovation within organizations has long been conceptual-ized as long periods of small, incremental innovation within or-ganizations that are interrupted by brief periods of discontin-uous, radical innovation [12], [13]. Recent work on innovationhowever, offers compelling arguments suggesting that to sustaincompetitive advantage, organizations must balance their innova-tion efforts—innovating incrementally on existing products andservices by enhancing short-term efficiencies through stability

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GROVER et al.: EXPLORING AMBIDEXTROUS INNOVATION TENDENCIES IN THE ADOPTION OF TELECOMMUNICATIONS TECHNOLOGIES 269

and control, while innovating radically for the long-term bytaking risks and learning-by-doing [11], [14], [15]. And whilearguments for the conceptual difference between radical and in-cremental innovation and their implications for strategy, struc-ture and management have been intensely studied (e.g., [7], [8],[16]), there is a paucity of empirical investigation of organiza-tions using a balanced approach to innovation, in part due to thedifficulty in doing such research [17].

Utilizing the theoretical typology of radical and incrementalinnovation developed in the literature base of organizational in-novation, the purpose of this study is to investigate whetherfirms innovating within adopted telecommunications technolo-gies subscribe to a balanced strategy-structure configuration ofinnovation or to a single strategy-structure configuration of in-novation. Further, considering if a balanced innovation effortis occurring, how it is being managed? Two proposals exist:one suggesting that organizations utilize semistructures lyingbetween the extremes of rigid strategy-structure configurationsdefined for radical and incremental innovation [18]. The otherproposal suggests that organizations utilize both structures si-multaneously in an ambidextrous manner [9], [11], [15].

In this study, models of strategy-structure archetypes for rad-ical and incremental innovation are formulated and empiricallytested in an effort to better understand varying structures, pro-cesses and consequences of decision making regarding telecom-munication technologies. The setting is organizations adoptingtelecommunication technologies during the data collection pe-riod of this study (1995). This is an attractive time period asorganizations faced a growing convergence of telecommunica-tions and information technologies, a rise in multimedia appli-cations, and the emergence of the internet; all of which put apremium on the ability to change continuously. In the next sec-tion, the theoretical underpinnings of radical versus incrementalinnovation are developed.

II. THEORY AND RESEARCH QUESTIONS

Burns and Stalker [6] originally discussed the dichotomy ofradical versus evolutionary innovation to distinguish differentorganizational structures better suited for different types of in-novations. Mechanistic structures are appropriate for relativelystable conditions and incremental innovation, and are charac-terized by a hierarchic structure, specialized differentiation, pre-cise rights and obligations and technical methods, among others.While organic structures are “appropriate for changing condi-tions, which give rise consistently to fresh problems and unfore-seen requirements for action which cannot be broken down ordistributed automatically arising from the functional roles de-fined within a hierarchic structure [p. 121].” Organic structures,then are for volatile environments and radical innovations, andare characterized by the adjustment and continual re-definitionof individual tasks, the contributive nature of special knowledgeand experience, coupled with a loose network structure of con-trol, authority, and communication, among others [6].

The focus on structural theories that consider the importanceof organizational design characteristics leading to innovationhas been a dominant theme in the innovation literature [e.g., [7]and [8]. Reviews and meta-analysis of past innovation researchhas found that “systematically different patterns of structure and

process exist between innovations of different degrees of radi-calness or “novelty” [8, p. 699].”

So why and when would an organization switch configura-tions? The prominent theoretical framework for organizationaltransformation and innovation [e.g., [12] and [13] has been thatof punctuated equilibrium. As described by its proponents, or-ganizations establish initial patterns of activity [19]–[21] basedon prevailing environmental conditions and managerial deci-sions made during their time of founding. Structures and pro-cesses develop quickly as well as organization members viewingthe dominant configuration as the only way of succeeding [20].The more a configuration is utilized, the higher the efficienciesgained and the deeper the configuration is engrained and institu-tionalized, becoming a repository for organizational knowledge[22].

Organizational learning research suggests that repetitionthrough established routines offers two benefits: 1) reducedtime to carry out an activity and 2) reduced variance in per-formance of the routine, reflecting increased proficiency [23].Consequently, as incremental learning associated with processimprovements extend through an organization, these improve-ments ultimately apply to product development processes thatdirectly affects the firm’s innovations [23]. Organizations willinnovate more rapidly as they incrementally improve innova-tion processes, while the variance in the resulting innovationswill also be reduced [23].

Benner and Tushman [23] offer a “crowding-out” hypoth-esis. That is, powerful incremental learning effects incurred byprocess improvements favor incremental innovation at the ex-pense of radical innovation. Their results indicate that processmanagement activities spur exploitation over and above the nat-ural tendencies that unfold with age and size [20], [21].

Times of stability are infrequently punctuated by radicalchanges within the environment (e.g., a major product break-through or a new technology [10]) or when the organization’sconfiguration is so incongruent with the environment that a rad-ical change is necessary to break the grip of inertia [24]. Often,such changes destroy existing firm competences, requiringsubstantial changes to an organization’s configuration [10]. Insummary, punctuated equilibrium theory depicts organizationsas evolving through relatively long periods of stability andevolutionary changes to their patterns of behavior and activitythat are punctuated by relatively short bursts of revolutionarychange. Revolutionary periods significantly disrupt establishednorms and activity patterns [12], [13].

Recent discussions and work on innovation, however, sug-gests that while thoughts of an organization being structuredto innovate in a single strategy-structure sequence are parsi-monious and generalizable, it comes at the expense of reality[11], [15], [25]. The real world is messy, filled with examplesof pluralism and paradox, making it difficult to conceptualizeorganizational change and subsequent innovation as “occurringthrough quantum leaps between frozen states [25, p. 703].”

Instead, organizations can only sustain their competitiveadvantage by balancing their incremental and radical inno-vation efforts. Organizations must manage current, existingmarkets by exploiting efficiency gains and incremental innova-tions through a bureaucratic organizational configuration that


requires formalized roles and responsibilities, centralized pro-cedures, efficiency-oriented structures, strong manufacturingand sale capabilities, older, experienced human resources,and functional structures [11], [14], [15]. Simultaneously,organizations must radically innovate for future markets byutilizing an organic configuration, founded on new experiencesand knowledge developed through experimentation, successesand failures, in the hands of relatively younger, more entrepre-neurial human resources that are void of history, quotas andestablished profit margins [11], [14], [15].

Assuming organizations use a balanced approach, there hasfurther been conflicting conjecture on how a firm should or-ganize and manage such a feat. Considering “a house dividedcannot stand,” one proposition suggests that organizations uti-lize quasi-formal structures, or “semi-structures” that offer a“third kind of process that is neither incremental nor radical [18,p. 31].” Closely tied to this perspective is the recent work onchaos and complexity theory [26], [27]. These perspectives sug-gest that rather than an organization ever reaching a steady-stateor equilibrium, organizations keep continuously changing andadapting and consequently remaining on the “edge of chaos.”These organizations stay constantly poised between order anddisorder and experience the highest order of complex and con-tinuous change [26], [27].

Organizations sustain this position by utilizing semi-struc-tures, offering some features that are prescribed or determinedbut others that are not and in this manner can adapt to innovateincrementally or radically [18]. As discussed by Brown andEisenhardt [18], “the effective management of current projects(lies) between very structured, mechanistic organization, inwhich bureaucratic procedures were tightly determined, andvery unstructured, organic organization, in which there werefew, if any, rules, responsibilities, or procedures. Searching forsuch ‘semi-structures’ that lie between radical and incrementalmodels or facilitate both, are key to navigating successfullythrough contemporary environments [18, p. 31].”

Another proposal postulates that organizations utilize the twostrategy-structure configurations, long considered contradictoryand conflicting, simultaneously within the same organization,a position “more consistent with nonlinear notions as op-posed to a more Newtonian view of the world [25, p. 703].”Organizations that operate in this mode have “an ambidextrouscapability to manage in two very different fashions within thebounds of the same organization [9, p. 162].” The organizationsustains its competitive advantage, then, by operating in bothmodes—managing for short-term, incremental gains through ef-ficiencies by utilizing a bureaucratic configuration while simul-taneously managing for long-term, radical innovations by uti-lizing an organic configuration.

As organizational architects of their organization, managersmust successfully align their strategy, structure, culture andhuman resources for peak performance [14]. Proponents ofthe ambidextrous hypothesis suggest that successful managerslearn what works well and incorporate this learning into theorganizational architecture [14]. As the environment continuesto get more competitive, strengths of organizations must beexploited through new architectures that simultaneously pursueboth incremental and radical innovation. For example, large

organizations can work in smaller, autonomous, organic units,with each scrambling relentlessly for new products and mar-kets; employees “feel a sense of ownership and are responsiblefor their own results [11, p. 25].” This offers an entrepreneurialculture where risk taking and experimentation endure that couldnot exist in a centralized organization [9], [11]. Yet the compa-nies exploit their overall size and use it to leverage economiesof scale and scope in customer and supplier relationships[11], [14]. This simultaneous exploitation requires a delicatebalance between size, autonomy, teamwork, speed, exploitationand experimentation and ambidextrous organizations able tosuccessfully achieve [9], [11], [14].

Consequently, the research questions posited:R1) Are organizations using a punctuated equilibrium ap-

proach to innovate within implemented telecommunica-tions technologies?

If not:R2) Are organizations balancing innovation structures by using

an ambidextrous approach or a semi-structured approach?

In summary, theoretical development on strategy-structureconfigurations has evolved over several decades and now of-fers three viable options explaining how organizations utilizestrategy-structure configurations to radically and incrementallyinnovate. First, the theory of punctuated equilibrium suggeststhat organizations utilize a single strategy-structure archetype.In eras of technological ferment, organizations structure for rad-ical innovativeness. When a dominant design emerges and al-ternative designs are crowded out, organizations morph to astrategy-structure sequence for incremental innovation, com-peting though exploitation of the dominant design through ef-ficiency. The second theory posits that a balanced approach toinnovation is necessary, and is implemented via semi-structures.Though such design certain radical and incremental featuresare prescribed while others are not, offering maximum flexi-bility and adaptation to innovate incrementally and/or radically.The strategy-structure sequence for such an organization wouldbe hybrid, not fitting either the radical or incremental strategy-structure sequence. The third theory, ambidexterity, also sug-gests a balanced approach is necessary but is implemented usingboth radical and incremental strategy-structure sequences si-multaneously. Consequently, the organization would fit bothstrategy-structure sequences.

To assess these questions, strategy-structure sequence modelsare developed for both radical and incremental models of inno-vation. The models developed and tested by Ettlie, Bridges andO’Keefe are the starting point, being adapted for the uniquenessof telecommunication innovations and additional insights intoinnovativeness culled over the last several decades of empiricalresearch. Overall fit of these models is then tested using struc-tural equation modeling. General support is offered for the firsttheory, punctuated equilibrium, if only one strategy-structure se-quence (radical or incremental) fits organizations implementingtelecommunications innovations. Support is offered for semi-structures if organizations fit neither model (radical or incre-mental), suggesting the organizations are utilizing a hybrid mixstrategy-structure sequence. Finally, support is offered for am-bidexterity if both strategy-structure models simultaneously fitorganizations implementing telecommunications innovations.


Fig. 1. A conceptual model of radical innovation in organizations and telecommunications innovation.

Fig. 2. A conceptual model of incremental innovation in organizations and telecommunications innovation.

III. THE CONCEPTUAL MODEL

The configurations for radical and incremental innovationwere developed by utilizing the approach followed by Ettlie,Bridges and O’Keefe [4] as well as their findings. As shownin Figs. 1 and 2, organizational strategy and size impactsthe structural arrangements of the organization that generatecertain preinnovation conditions resulting in either radical or

incremental innovation. The general theme of these modelsis that one set of strategy-structure sequences predict rad-ical technology innovation while another segregated set ofstrategy-structure configurations likely predicts incrementaltechnology adoption.

It should be noted that the spirit of the two models reflectsthe proactive nature of radical innovation and the adaptivenature of incremental. However, several changes have been


made to the original models. These changes exploit addedunderstanding from new research and consider the uniquenessof telecommunications as an internal technological innovation(rather than a product innovation in the original model). There-fore, the variables selected reflect plausible implementation ofEttlie et al.’s concepts within the telecommunications context.To discuss these changes, each of the overarching constructs,as well as the individual elements are discussed below.

A. Radical Innovation Configuration

1) Organizational Strategy and Size: Radical innovationadoption is promoted by an aggressive technology policydirectly by supporting the development of a concentration oftechnical specialists [4]. An aggressive technology policy isdefined as “a preemptive, long-range strategy for technolog-ical innovation [4, p. 684].” The proposed model follows thespirit of Ettlie, et al. [4] but is more explicit by identifyingenvironmental scanning, risk management, and integration oftechnology and corporate planning as independent higher-orderfactors that are formative of such an aggressive technologypolicy concept.

a) Environmental Scanning: Environmental scanning is animportant process and the first link in the chain of perceptionsand actions that permit an organization to adapt to its environ-ment [28]. Environmental scanning is a key component of orga-nizational learning as the enterprise continually seeks new infor-mation that may change its overall position in the marketplace[29]. This process is central in the development of strategic plansand policies, the assessment of new information, and the adjust-ment of internal operations to meet new markets, prospectivecustomers and emerging technologies [30]. Consequently en-vironmental scanning is important in developing an atmospherethat is rich in ideas and knowledge and fosters dynamism neededfor radical innovativeness.

b) Risk Management: To be effective, a technology policyencourages risk management. More organizations are adoptingportfolio management strategies and score card techniques toassess and manage risk. These approaches mitigate an organ-ization from becoming too risk averse by evaluating potentialrewards of radical innovations against the risks associated withsuch endeavors [31]. McDermit and O’Connor [32] observedorganizations using several approaches to manage radical inno-vations that are risky (e.g., high in market and technological un-certainty) with strategies such as leveraging known capabilities,outsourcing, and choosing not to face all the issues of uncer-tainty concurrently.

c) Integration of Technology and Corporate Planning: In-formation technology represents a major investment for orga-nizations in today’s business environment. In the face of anincreasingly dynamic business and technology environment, akey to success for the 21st century information technology or-ganization lie in its ability to be not only adaptive and respon-sive, but also aligned to business needs [33]. Business leadersin today’s global and digital economy often look toward IT tosuggest new and innovative ways in which products, processesand services might be improved utilizing communication andinformation technologies [34]. Indeed, a common view is that

IT can serve as a key source of competitive advantage [33]. Asinformation technology organizations reposition themselves tobecome strategic business partners, it is evident that they requirealignment with corporate strategies that will enable and facili-tate such a role [35]. A technology policy promotes tighter in-tegration, and consequently alignment between technology andcorporate planning.

2) Organization Structure: Ettlie et al. [4] found that aggres-sive technology policy leads to pooling of technical specialistsand ultimately radical innovation. This pool of experts has theabsorptive capacity necessary to think “outside the box” whileguided by the technology policy. The conceptual model variesfrom this for telecommunications innovation by also identifyingthe integration of IS and telecommunications groups, and a pow-erful IS function as important structural components for radicalinnovation [[36]–[39].

a) Integration of Telecommunications and InformationSystems Activities: Sophisticated information systems usedtoday require networks and telecommunications technology.This convergence or fusion of computers and telecommu-nications epitomized the era of the mid 1990s [e.g., [40].This convergence requires the integration of specialists fromtelecommunications and information systems as well as theintegration of the activities performed within each specialtyto develop “communities of practice” found to be essential ininnovative organizations [41]. These “communities of practice”provide the capacity for requisite knowledge to be developed;and work, learning and innovation coalesce in the adoption andexpansion of radical innovations [41].

b) Powerful Information Systems Function: An importantdifference in the conceptual model compared to the radicalmodel offered by Ettlie et al. [4] is that the innovation cham-pion is modeled as reflective of IS power and treated as astructural variable rather than a preinnovation condition. Incontrast to a particular process or product innovation whichunderlies the theoretical network of Fig. 1, the pervasivenessof telecommunications technologies and their increased inte-gration with computing technologies requires an organizationalstate of technology championship in contrast to an individualtechnology champion. Therefore, many studies characterizethe championing of technology as a structural phenomena of ISpower reflecting the established power base of the functionalIS organization within the firm [37], [42]–[44]. This structuralcharacteristic is viewed as a precursor to the preinnovationactivity of vendor interaction that is related to congruence ofIT and organizational needs as well as innovativeness [39],[43], [45].

3) Preinnovation Conditions:a) Partnership With Vendors: There are numerous deci-

sions that need to be made for the effective use of telecommu-nications and its integration with computer technology. “Notleast among the problems is the daunting range of possibilities.Where to go for the best equipment, how to be sure of its relia-bility, and what kind of hardware and software to choose fromthe myriad offerings are among the tough questions managersface. Further, making these choices depends on technical con-siderations and a better understanding than now usually existsbetween technical and general managers [46, p. 91].”


An important source of information and intelligence inmaking the right decisions are the outsourcers and vendors of thetelecommunications products and services. But all outsourcingis not the same. Some organizations view telecommunications asa utility service such as water, gas or electricity [47]. While thisperspective offers an organization opportunities in cutting costsand focusing on their core competencies, it severely limits theradical innovation opportunities of the technology.

Other organizations see outsourcing as a strategic acquisi-tion of complementary resources and capabilities that fill gapsonly after a thorough evaluation of internal strengths and defi-ciencies [47]. This strategic sourcing perspective requires devel-oping a long-term interactive partnership with vendors that pro-mote mutual cooperation, sharing risks and benefits, while mit-igating exploitive behavior from either side [48]. Consequentlypartnerships with vendors is added to the model as it providesstrong preinnovation conditions for radical innovation withintelecommunications.

b) IS-Corporate Congruence: The IS organization moreclosely aligned with the business, serving strategic ends, haswide-ranging implications for the skills, behaviors, and orienta-tions of IS staff [49]. IS professionals are increasingly asked toassume entrepreneurial roles and to seed the process of IT inno-vation. A broad-based expectation is that rather than wait for thebusiness to provide requirements, IT professionals will proac-tively seek to create opportunities for the deployment of infor-mation technology to serve business needs. Moreover, with theincreasing incidence of outsourcing in IT work, IT professionalsare key players in the complex activity of managing a host ofrelationships with external vendors and consultants in additionto managing internal relationships with business partners [49].These new responsibilities provide strong preinnovation condi-tions for radical innovation within telecommunications.

B. Incremental Innovation Configuration

The overarching construct within the incremental model ofinnovation is organization size and the structural bureaucraticcoping mechanisms implemented to be effective [50]. Burnsand Stalker [6] found that people in mechanistic organizationscould not reorganize, despite pressures of unstable environ-ments, because “the orthodox bureaucratic system was seenas the only possible mode of organization ” While the Ettlieet al. [4] predicates a market dominated growth strategy anddiversification as pertinent dimensions that drive an organiza-tion to bureaucratic structures and incremental innovation, thisconceptual model considers organizational size coupled withenvironmental uncertainty as the antecedents of organizationalstructure.

1) Organizational Strategy and Size:Environmental Uncertainty and Size: Environmental

uncertainty is determined by the complexity and variability ofenvironmental components. As uncertainty increases within theenvironment, confidence by management in its predictabilitydecreases [8]. Consequently, organizations collect, analyzeand interpret more information for decision making in higherenvironmental uncertainty. Additionally, organizational sizecreates a need for traditional organization structures such as

increased formalization, increased integration, increased com-plexity, and decentralization [2], [56]. Further, the organizationwill incorporate information technologies into various aspectsof its processes to improve coordination of and adaptation to itsincreasingly diverse structure [51]. Together, these associatedstructures will lead organizations to innovate only incremen-tally from known methods of operation [3], [4], [52]–[54].

2) Organizational Structure: The conceptual model againfollows that of Ettlie et al. [4], with the additional constructsof integration and IT infusion needed to assist organizationsprocess additional information to cope with an uncertain en-vironment. These structures, along with other bureaucraticnorms of centralized decision making, formalized rules andincreased structural complexity—increase the rigidity of theorganizational structure, further stifling change and being moreconducive to incremental innovation.

Integration: An important component of organization isthat of integration; the “state of collaboration that exists amongdepartments that are required to achieve unity of effort by thedemands of the environment [55, p. 11].” As discussed earlier,large organizations facing environmental uncertainty processmore information and develop tighter links within the organiza-tional functions and departments. Integration mechanisms andthe information technologies utilized to share information createanother layer of process, control and operating procedures thatcreate more inflexibility within bureaucratic structures. Overtime, this inflexibility stifles organizational vision, imaginationand innovativeness [56].

3) Preinnovation Condition:IT Infusion: IT infusion is the incorporation of information

technology into the work structures that the technology supports.Infusion culminates in the technology being used within the or-ganization to its fullest potential [57]. As organizations institu-tionalize and weave information technology and work tightly to-gether [58], it becomes difficult to dissect one from another. Andwhile this improves efficiencies within the organization, inflex-ibility also sets in as organizations unite with the existing infor-mation technologies. Consequently IT infusion is conceptual-ized as a delimiting factor considering innovation.

In summary, the incremental model of telecommunicationsadoption is predicated on the notion of adaptation. Therefore,we assume that organizational growth strategies are in responseto environmental uncertainty [4], [16], [36], [59]–[61]. Sub-sequently, environmental uncertainty and organizational sizecreate a need for traditional bureaucratic organization structures[4], [62], [63]. In addition, the organization will incorporateinformation and information technologies into various aspectsof its processes to improve coordination of (i.e., adapt to) itsincreasingly diverse structure [51]. Together, these associatedstructures will lead organizations to innovate only incremen-tally from known methods of operation [3], [4], [52]–[54],[64]. In short, the structural and geographic complexity ofgrowth-oriented organizations is generally not conducive to thecreation of needed preinnovation conditions1 for adoption ofradical technologies. Therefore, adoption patterns are expectedto be less aggressive than the patterns of the radical model.

1The preinnovation condition of infusion is simply an adaptation rather thana proactive endeavor.


The next section describes in depth the methodology usedto test these alternative models. While both models have sub-stantial support in the literature, they represent significant philo-sophical and pragmatic differences. As discussed earlier, manyresearchers view these as “conflicting” models [4], [6]–[9], [11],[14], [15], [17]–[19], [25], [65]–[67]. It is our contention thatthe existence of such conflict is an empirical question. Our hy-pothesis suggests that both models (radical and incremental) canoccur concurrently. As such, we conceptualize the unit of studyas a nomological network of relationships rather than individualrelationships between variables.

IV. RESEARCH METHODOLOGY

Each construct in the model was operationalized using care-fully designed item-scales. The initial instrument was admin-istered to seven local IS executives in charge of telecommu-nications in manufacturing, financial, government and educa-tional institutions through a series of face-to-face interviews.The primary purpose of these interviews was to obtain feedbackon issues of content validity, item wording, and to obtain andfine-tune a representative set of telecommunications technolo-gies. Each interview lasted about an hour and revisions weremade to the instrument prior to subsequent interviews.

A sample frame of senior IS executives were chosen for thefinal administration based on the ability of the respondents to bewell versed in both: 1) the technologies prevalent within theirorganization, and, 2) the strategy, structure, and innovative con-ditions surrounding the deployment of these technologies. Thesample frame of 1000 was randomly selected from larger firms(sales million) in Standard and Poor’s Corporate Guideand the Information Week 500 list. The names of listed vice pres-idents and directors of IS were collected and 960 questionnaireswere mailed. The effective mailing list (accounting for bad ad-dresses) was 777, of which 165 responses were obtained overthree rounds of data collection, resulting in a response rate of21.23%. However, 11 of these responses could not be used fordata analysis, leaving a final sample of 154.2

A. Operationalization of Model Variables

Multi-item scales were used to measure the constructs wher-ever possible. Also, an attempt was made to use validated con-structs if available. In some cases however, items were cre-ated based on the content domain of the construct, and theo-retical guidance from the literature. The complete list of itemsused, along with their source and is provided in Tables I–III. InTable III, the 15 telecommunications technologies used for thestudy are listed. These were initially based on a review of textsand articles, and subsequently revised in the pilot interviews.Given the intent of this study, while a comprehensive list is desir-able, it was more important to obtain technologies that: 1) werecurrently being used; 2) were widely deployed; 3) contain a mixof application, infrastructure, and media technologies; 4) wouldcollectively exhibit variance in innovativeness from low (e.g.,

2Later respondents (obtained after the first two weeks) when used as a proxyfor non-respondents showed no significant difference from early respondentsin any of the study’s variables. This demonstrated a lack of significant non-response bias.

TABLE IPREDICTOR CONSTRUCTS AND MEASURES OF RADICAL INNOVATION MODEL

FAX) to high (e.g., ISDN). Appendix A provides a brief descrip-tion of each of these technologies. Each technology representsan organizational initiative that might vary in perceived innova-tiveness across organizations.

Measuring radical versus incremental innovations is a prob-lematicproposition [17], [23]. Inaddition,compellingargumentshave been made that the innovation continuum, with radical andincremental innovation at the extreme points, is incomplete;architectural innovations reside within the extremes but offersignificant innovations by reconfiguring existing components ina new way [68]. Where incremental innovations build on corecompetencies and are “competency enhancing” [10] and radicalinnovations create extreme challenges for established firms asthey are often “competency destroying” [10], architectural inno-vations utilize existing skills for an innovation, but destroys othercompetencies as new knowledge is needed and applied. Con-sequently, “the distinctions between radical, incremental, andarchitectural innovations are matters of degree [68, p. 140].”

Accordingly, instead of trying to measure radical and in-cremental innovations while ignoring architectural innovation,overall innovativeness was computed in each organizationalunit with respect to this slate of technologies, further explainedin Table III. Three scales were used for each technology: onefor assessing innovativeness in general, a second for assessinginnovativeness3 with respect of the particular organizationbeing surveyed, and a third measuring the extent of implementa-tion. The mean of the first scale across all respondents was usedas an indicator of the general innovativeness of each technology(where the respondents collectively represented a group of ex-perts) and was then used to weight individual technologies in

3Innovativeness is presented to the respondent as implying a major techno-logical advancement, thereby reflecting concepts of newness, uniqueness, andimpact in Rogers (1983) conceptualization of innovation.


TABLE IIPREDICTOR CONSTRUCTS AND MEASURES OF INCREMENTAL INNOVATION MODEL

computation of organizational innovativeness and implemen-tation, aggregated across all 15 technologies. This method isconsistent with some prior studies in innovation, where a panel ofexperts is used to assess the extent of innovativeness of differentinnovations. The scores are then used to assess organizationalinnovation, based on the number of innovations deployed [3]. Inthis case however, despite a small possible method-bias, we feelthat using a large experienced sample of 154, is as good if notbetter than using a small (4-5) panel of independent experts.

B. Sample Profile

The 154 responses represented a variety of industries with32% in Finance, 31% in Manufacturing, 11% in Wholesale and7% in Transportation. The sales profile also indicates a bias to-ward larger firms with 12% having sales over $1 billion, 59%between $0.5 and 1 billion, and 15% over $100 million. Whilethe larger firm has the obvious advantage of having a poten-tially broader profile of technologies, the bias does limit the gen-eralizability of the study. The respondents themselves had se-nior representation, with 64% assuming the position of Director,Vice President or CIO and 22% were at the managerial level.

Finally, over 80% of the firms surveyed had the telecommuni-cation function fully within the responsibility of the IS group,adding credibility to the quality of responses.

V. EMPIRICAL ASSESSMENT

As implied, each of the multi-item clusters (or scales) in Ta-bles I and II represents an a priori measurement model of itsunderlying construct. Given the use of validated scales and/ora theoretical basis for defining these constructs, the analyticalframework of confirmatory factor analysis [64], [69], [70] pro-vides an appropriate means of assessing the efficacy of measure-ment among scale items and the consistency of a prespecifiedstructural equation model with its associated network of theo-retical concepts [69]–[71]. Segars [72] reconciles and illustratesthe theoretical and empirical underpinnings of the confirmatoryapproach within the context of IS research. This resulting frame-work suggests that complex variables be modeled in isolation,then in pairs, and then as a collective network. Proceeding inthis manner provides the fullest evidence of measurement effi-cacy and also reduces the likelihood of confounds in full struc-tural equation modeling which may arise due to excessive error


TABLE IIICRITERION MEASURE OF RADICAL AND INCREMENTAL INNOVATION MODELS

(q � �t ) � (r � �t ):

As implied in this formula, telecommunications innovativeness for a particular organization is a functionof an aggregated measure across all respondents (mean innovativeness scores of T1 � T15) as wellas organizational level measures of technology innovativeness (q ) and extent of implementation (r ).The linear combination of these measures is consistent with previous innovation literature (Ettlie et al,1986; Dewar and Dutton, 1984) and incorporates aspects of innovativeness with respect to the specifictechnology and novelty of the technology with respect to the adopting organization.

in measurement [69], [70], [73]. Working within this context,the CALIS procedure of SAS (version 6.12) was utilized as theanalytical tool for testing statistical assumptions and estimationof the measurement and structural equation models discussed inthe following sections. Checks for statistical assumptions andmodel identification followed procedures grounded in prior lit-erature [64], [74]–[76].

A. Convergent Validity and Unidimensionality

Upon the estimation of measurement models for each latentfactor of the radical and incremental models, it is possible to di-rectly assess measurement efficacy [71], [73], [74], [77], [78].The properties for the measurement models of the radical in-novation model are presented in Table IV. Table V contains themeasurement properties associated with the incremental innova-tion model. Overall, the parameter estimates, fit indices, and ob-served residuals imply that the estimated measurement modelswithin both the radical and incremental network are a good fitfor the observed correlations among their respective items. Ineach instance, the value is relatively low, the goodness offit (GOF) index is above 0.90, and the adjusted goodness of fit

index (AGFI) is above 0.90. RMSR is 0.04 (or less) and all indi-cator reliabilities are sufficiently high and statistically differentfrom zero. The residual matrix for each of the models containsno values significantly different from zero and the composite re-liabilities of each construct are all above 0.80. In each instance,the average variance extracted (AVE) is above 0.50 indicatingthat the variance captured by the respective construct is largerthan the variance due to measurement error [3]. In sum, the fitstatistics seem to suggest that each scale is capturing a signifi-cant amount of variation in the complex variables of the radicaland incremental networks.

B. Assessment of Discriminant Validity

Discriminant validity is inferred when measures of each con-struct converge on their respective true scores which are uniquefrom the scores of other constructs. Empirically, this is achievedwhen the correlations between any two dimensions are signif-icantly different from unity [71], [79]. Table VI contains theresults of the pairwise difference tests among constructs ofthe radical innovation model. Table VII contains the pairwisetests for the incremental innovation model. In both variable


TABLE IVMEASUREMENT PROPERTIES: CONSTRUCTS OF RADICAL INNOVATION MODEL

networks, all items exhibited characteristics of unidimensionalmeasurement as evidenced by the values associated withthe unconstrained models [79]. In each case, the normed

TABLE VMEASUREMENT PROPERTIES: CONSTRUCTS OF INCREMENTAL

INNOVATION MODEL

value is well below the suggested cutoff of five [70], [80],suggesting that the scales contain properties of internal andexternal consistency. In addition, the observed reliabilities of


TABLE VIRESULTS OF DISCRIMINANT VALIDITY TESTS: RADICAL MODEL CONSTRUCTS

indicators remained virtually invariant across the esti-mated unconstrained models providing additional evidence ofsolution stability.

As shown in Tables VI and VII, all differences are signifi-cant at . Hence, each scale seems to capture a constructthat is significantly unique from other constructs providing ev-idence of discriminant validity. Importantly, the estimated cor-relation between all construct pairs is well below the suggestedcutoff of 0.90 [80], [81] implying distinctness in construct con-tent. The AVE for all construct pairs is well above the squaredcorrelations between constructs also suggesting strong proper-ties of discriminant validity. In sum, the results of Tables VI andVII suggests that the indicators of the measurement models inTables IV and V are unidimensional and that each construct isdistinct in content.

VI. ESTIMATION OF STRUCTURAL EQUATION MODELS

As theorized, distinct causal paths among strategy andstructural variables predict alternative outcomes with respect

to telecommunications innovativeness. In the present case,empirical testing of this theory through structural equationmodeling is best accomplished by collapsing latent variablesinto single measures [74]. Such an approach greatly simplifiesthe estimation of a path model and creates consistency amongthe complex and measured variables of the alternative models.The recommended approach for developing single measures ofcomplex variables is the computation of factor scores [74], [75].Factor scores are calculated by first multiplying the estimatedfactor loading of a scale item by its observed score. For eachrespondent, the resulting scores for each item cluster are thensummed to yield a single measure of that particular construct.Each factor score represents a single error-free measure ofits associated construct [64], [74]. The computation of factorscores and inclusion of measured variables results in a 9 9covariance matrix of variables for the radical model and a 8 8covariance matrix of variables for the incremental model. Ac-cordingly, the models illustrated in Figs. 3 and 4 were estimatedusing these matrices.


TABLE VIIRESULTS OF DISCRIMINANT VALIDITY TESTS: INCREMENTAL MODEL CONSTRUCTS

VII. RESULTS

Research question 1 inquired as to whether organizations areusing one structure sequence (punctuated equilibrium), and ifnot, research question 2 inquired as to whether an ambidextrousor semi-structure approach is used. These questions were testedby evaluating the fit between the radical and incremental inno-vation strategy-structure configurations with the dependent vari-able of overall innovativeness.4 We contend that if organizationswere utilizing a single strategy-structure configuration a dom-inant configuration would emerge. If organizations were usingsemi-structures, the data would not significantly fit either model,as organizations would utilize components of each model, buthighly doubtful in the specific causal sequence. As noted in theliterature on innovation, firms may employ a set of approachesto foster the innovation needs of particular technologies [8],[16], [65]. In these instances, the firm may adopt a configura-tion of approaches or exhibit an ambidextrous capability in itsefforts to identify and adopt various classes of innovation. In thepresent case, both causal models fit the collected data, offeringsupport for the ambidextrous approach to managing innovative-ness. Specific findings are described below for both models.

4We also did the analysis after demarcating the sample based upon “high”and “low” levels of innovativeness. The radical model was a bit stronger in the“high” sample and the incremental model was stronger in the “low” sample.This validates the basic models (similar to Ettlie et al.’s thesis). We chose not toinclude the detailed results on this—since we believe that our major contributionis to test the simultaneous testing of both models in the sample.

A. Radical Model of Telecommunications Innovation

As shown in Fig. 3 the hypothesized model of radical in-novation provides a strong fit for the observed covarianceswith a goodness of fit equal to 0.95. The observed for thismodel is 40.62 . Although the is highlysignificant, it must reconciled with the degrees of freedominherent in the model. Normed , the most commonly usedmetric in thesesituations, is 2.53 implying reasonable modelfit and no evidence of over-fitting [82]. As illustrated, thepath coefficients of the estimated model support the theorizedrelationships of Fig. 2 in direction and magnitude. Particularlystrong links of this model are the paths between the strategyvariable of IS/Corporate integration and the structural vari-ables of specialists (0.40), IS/Telecommunications integration(0.41), and IS power (0.44). Such results seem to underscorethe importance of tightly aligned corporate and informationsystems strategy in creating structural conditions favorable fortechnological innovation. Paths between the aforementionedstructural variables and the preinnovation conditions of congru-ence and vendor interaction also exhibit strength in magnitudeand consistency in direction. Specifically, these paths rangefrom a low of 0.27 between the variables of IS/Telecommuni-cations integration and congruence to a high of 0.42 betweenthe variables of IS/Telecommunications integration and vendorinteraction. These results suggest that favorable structuralconditions such as the concentration of specialists, integrationof information systems and telecommunications activities, and


Fig. 3. Radical model of telecommunications innovation.

Fig. 4. Incremental model of telecommunications innovation.


existence of power within the information systems functionare important in creating favorable preinnovation conditions.Finally, the paths between innovation and the preinnovationconditions of congruence (0.31) and vendor interaction (0.33)suggest that radical innovation outcomes are predicated onfavorable conditions of technology-organizational alignmentand partnership with vendors.

Paths of the radical model that do not exhibit particularlycompelling loadings include links between management riskand IS/Telecommunications integration (0.13) as well as the linkbetween management risk and IS Power (0.10). These resultssuggest that the risk taking propensity of top management maynot be strongly related to the emergence of IS power or integra-tion of IS and telecommunications activities. Perhaps the mostinteresting inference of the paths is that existence of specialistsinfluences innovation through congruence of IT with organiza-tional needs and through collaboration with vendors. This im-plies that mere existence of specialists is not enough to ensureidentification and implementation of radical technologies. In-stead, there is a mediating aspect of aligning technology to or-ganizational needs and collaboration with vendors that shapesinnovation outcomes.

B. Incremental Model Of Telecommunications Innovation

Fig. 4 illustrates the path estimates associated with the in-cremental model of innovation. Similar to the radical model,the statistics of fit associated with this model suggest that thehypothesized structure is also a reasonable fit for the observedcovariances. The observed for this model is 41.85

. The normed is 4.18 and the goodness offit is 0.95 both suggesting adequate model and no evidence ofover-fitting [82].

As hypothesized, the paths between the strategy variables ofsize and environmental uncertainty and the structural variablesof integration, formalization, complexity, and centralization areof significant magnitude and consistent direction. The pathsrange from a high of 0.36 between size and formalization to alow of 0.15 between environmental uncertainty and complexity.These results reinforce previous studies that suggest as organi-zations expand their scope and encounter increasing amountsof environmental turbulence they augment existing structuresby changing integration, formalization, complexity, and de-centralization. As theorized, Fig. 4 also suggests that thesechanging structural arrangements lead to increased infusion ofinformation technologies throughout the organization. Specif-ically, paths between IT Infusion and formalization (0.12),complexity (0.28), and centralization (0.24) are significantlyhigh and positive reinforcing the importance of the relationshipbetween technology and structure.

With the exception of integration, each of the structural vari-ables illustrated in Fig. 4 exhibits a relationship to innovationthat is consistent with the theorized incremental model of Fig. 2.As shown, innovation is negatively associated with formaliza-tion , IT infusion , complexity , andcentralization . Consistent with innovation theory, theseresults suggest that as organizations become more formalized,more complex, and decentralized, they become less innovativewith respect to telecommunications technologies. In addition,

as organizations infuse information technologies to adapt to or-ganizational structure they may become less innovative in theiradoption of communications technologies. In essence, the or-ganization might adopt more technologies in response to thestructural changes but becomes less innovative (as reflected bythe innovativeness score) in the communications technologiesadopted.

VIII. DISCUSSION

This paper utilized three dominant theoretical frames:1) punctuated equilibrium; 2) semi-structures; 3) ambidex-terity to explore how organizations utilize strategy-structuresequences to innovate radically and incrementally in im-plementing telecommunications technologies. Structuralequation modeling fit both models of organizational innovation,suggesting that an ambidextrous approach that is, utilizingboth strategy-structure sequences simultaneously in imple-menting telecommunications innovations was being utilized byorganizations.

This paper makes several contributions to the innovationmanagement literature by providing empirical evidence for theambidextrous hypothesis, that states while the configurationof the organizational components for radical innovation isdiametrically opposed to the configuration for incremental in-novation, these configurations can successfully be bound withinthe same organization—a mechanistic structure for exploitingefficiencies and an organic structure for exploring futuristically.This evidence thwarts the alternative semi-structure hypothesisthat organizations compromise between the two configurations“in some sort of Goldilocks fantasy, rather this duality must bemanaged, as well as the tension created in such a chaotic state[25, p. 709].”

At the cost of redundancy, Table VIII reiterates the major im-plications of the study by highlighting the significant relation-ships in both models.

There are important implications of these findings for prac-ticing managers. As architects of the organizational design,practicing managers need to strategically consider that innova-tiveness with respect to telecommunications technologies mustbe managed differently. Areas within the company chargedwith radical innovation will need to be organizational designedto utilize organic organizational structures and should findthe causal sequence of the radical model a useful basis forcritiquing existing organizational structures. Areas chargedwith incremental innovation will need to be organizationallydesigned to utilize mechanistic forms of organization, relyingon hierarchical growth and information technologies to ac-commodate the increased informational processing associatedwith expansion and increased competition. Care needs to betaken when designing the organization as well as implementingmanagement improvement processes useful for efficiencies andexploitation, as these processes may also cause the firm to beless radically innovative in its adoption of telecommunicationstechnologies. That is, mechanistic approaches to organizationalchange, “force out” tools, techniques and processes requiredfor radical departures in technology adoption. Further, changeswithin the each strategy-structure configurations must be con-sidered from a holistic perspective as structures and processes


TABLE VIIIMODES OF TELECOMMUNICATION INNOVATION BASED ON SIGNIFICANT RELATIONSHIPS IN RADICAL/INCREMENTAL MODELS

become a part of an integrated whole, making it difficult tochange one element without considering the implications onthe other elements of the configuration [19].

For researchers, this study presents a dual model of innova-tiveness that may be tested for other classes of information tech-nologies and information systems. It would be presumptuous toassume that the complex sequences of variables identified hereare the only plausible ones. Further research is needed to furtherenhance and detail the models. In addition, there is much that isstill not understood about the specific managerial strategies, in-terventions, and organizational programs for sustaining multiplestructures that facilitate innovation within the same organiza-tion. For example, Benner and Tushman [23] found that qualityimprovement programs, while increasing the incremental or ex-ploitative innovations comes at the price of thwarting radical orexplorative research. Can an organization successfully leveragequality improvement processes without the sacrifice to explo-rative research? And if so, how? This is just one of a poten-tial host of management improvement tools and techniques thatmust be considered strategically as implementation across theentire organization may be less than advantageous.

Another interesting area of inquiry is whether the ambidex-trous model is a new concept or a new actualization? Thatis, when Burns and Stalker [6] originally proposed linkagesbetween environmental pressures and organizational structure,were these relationships robust enough for the current environ-mental complexities? If so, what complexities and intensitieswithin the environment have heightened to the point wheremany organizations must organize using dual strategy-struc-ture configurations simultaneously? Further, what new forms,or combinations of existing forms will be needed to remaincompetitive and continue to innovate as the global environmentcontinues to increase in complexity and intensity?

The final contribution of this research is providing a novelapproach to measuring overall innovativeness to assess whetherincremental and radical innovation and strategy-structure con-figurations are simultaneously used by organizations utilizingtelecommunication technologies. Often radical and incrementalinnovations are measured using patents offered by the organi-zation as proxies for measuring incremental and radical inno-vativeness [e.g., [23], [73]. Patents along a similar family of in-novation are incremental and patents within new areas are con-


sidered radical innovation. These measures for radical and in-cremental innovation are unworkable when assessing specificareas within in the organization such as telecommunication in-novation within this study. Further, it blindly ignores architec-tural innovations that can have significant impacts on organiza-tions and their competencies [68]. While this construct did notmeasure specifically whether a particular innovation was “rad-ical” or “incremental” it provided a useful measurement for thisresearch. While useful in its current form, adjustments couldbe made to offer measures for a range of innovativeness scalesuseful for future research.

Several limitations warrant mentioning in this research. First,this research takes a rather unique approach in proposing al-ternative path models, supported in innovation literature, toexamine the innovativeness of an increasingly important set ofpervasive technologies. While special care was taken to testthe constructs and their validity to ensure that the structural re-lationships were not artifacts of overlapping constructs, repli-

cation of the strategy-structure sequences would be a usefuleffort. In addition, the limited sample size must be consideredwhen evaluating this research. Finally, there is reason to becautious in generalizing the results beyond the technology setstudied, as changes were made within the conceptual modelto highlight the uniqueness within telecommunication tech-nologies. Future studies can continue to hone important con-structs for different technologies. This study offers guidanceand sets the stage for further examination of strategy-structuralsequences.

IX. CONCLUSION

This research treads new ground in attempting to empiri-cally assess the balance of alternative structural arrangementsrequired for innovation. Using a composite dependent variablethat captures “innovativeness” the study finds preliminarysupport for the presence of structural modes associated withboth radical and incremental innovation. The former reflects an


aggressive approach based upon strategy, power and specializa-tion, while the latter reflects adaptation to structural changes.This suggests that in their quest to balance needs for explorationand exploitation, firms are explicitly or implicitly exhibitingdual structures. We would suggest that this study offers modestbut important support for the concept of ambidextrous organi-zations, as they struggle to reconcile the seemingly paradoxicaldual nature of innovation.

APPENDIX

DESCRIPTION OF 15 TELECOMMUNICATIONS TECHNOLOGIES

See table at the top of the previous page.

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Varun Grover received degrees in electrical engineering and business adminis-tration. He received the Ph.D. degree in management information systems (MIS)from the University of Pittsburgh, Pittsburgh, PA.

He is the William S. Lee Distinguished Professor of Information Systems(Endowed by Duke Energy) in the Department of Management at Clemson Uni-versity, Clemson, SC. He has published extensively in the information systemsfield, with over 150 publications in refereed journals on the organizational andinterorganizational impacts of information technology. Five recent articles haveranked him among the top three most productive researchers in the field basedupon publications in top journals. His work has appeared in journals such as In-formation Systems Research, MIS Quarterly, the Journal of MIS, Communica-tions of the ACM, Decision Sciences, the IEEE TRANSACTIONS ON ENGINEERING

MANAGEMENT, the California Management Review, and numerous others. Heis currently co-editing his third book on business process change and has servedas a Special Editor for issues of JMIS, Database, and Decision Sciences.

Dr. Grover is the recipient of the Outstanding Achievement Award from theDecision Sciences Institute and is currently the Senior Editor for the MIS Quar-terly, the Journal of the AIS, Database, and Associate Editor for five otherjournals.

Russell L. Purvis received the B.S. degree from the University of Miami, CoralGables, FL, the M.B.A. degree from Georgia State University, Atlanta, and thePh.D. degree in business administration (MIS) from Florida State University,Tallahassee.

He is an Associate Professor, Department of Management, Clemson Univer-sity, Clemson, SC. His current research interests include organizational transfor-mation through information technologies, project management, and issues in theimplementation of IT applications within organizations. He has had papers ac-cepted for publication in Management Science, Organization Science, the IEEETRANSACTIONS IN ENGINEERING MANAGEMENT, the IEEE TRANSACTIONS ON

SYSTEMS, MAN, AND CYBERNETICS, among others.

Albert H. Segars is the RBC Centura DistinguishedProfessor of Innovation and Technology Manage-ment at UNC Chapel Hill’s Kenan-Flagler School ofBusiness. He also serves as the Chairperson of the En-trepreneurship Area. His area of research, teaching,and consulting expertise include innovation, tech-nology management, as well as entrepreneurship. Hehas written numerous articles on these topics withinthe context of strategic planning, product innovation,financial investment, and corporate sustainability.His recent research has been recognized as Best in

Practice by The Society of Information Management (SIM), the Society for Lo-gistics Engineers (SOLE), as well as The Association for Computing Machinery(ACM). He has served as an Associate Editor for the MIS Quarterly, the Journalof Management Information Systems, Information Systems Research and Deci-sion Sciences. His recent research projects have been funded by The NationalScience Foundation, Carnegie Bosch Institute, The Kaufman Foundation, Bankof America, The Defense Advanced Research Projects Agency, The Departmentof Navy, The Medical Logistics Agency, CIBER, and Apple Computer.

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