determinants of sourcing during technology growth and maturity: an empirical study of e-commerce...

DETERMINANTS OF SOURCING DURING TECHNOLOGY GROWTH AND MATURITY 47

Journal of Management Information Systems / Winter 2004–5, Vol. 21, No. 3, pp. 47–82.

© 2005 M.E. Sharpe, Inc.

0742–1222 / 2005 $9.50 + 0.00.

Determinants of Sourcing DuringTechnology Growth and Maturity:An Empirical Study ofe-Commerce Sourcing

RAJIV KISHORE, MANISH AGRAWAL, ANDH. RAGHAV RAO

RAJIV KISHORE is an Assistant Professor in the School of Management at the StateUniversity of New York at Buffalo. His research interest is in understanding howorganizations can improve their IT services delivery capability through IT outsourcing,adoption of IT innovations, and software process improvement. His papers have beenpublished or accepted for publication in Communications of the ACM, Decision Sup-port Systems, Information Systems Frontiers, and Journal of Healthcare InformationManagement. Dr. Kishore has presented his research at ICIS, AMCIS, SIM, and othernational and international conferences. He received a best paper award at AMCIS2001 and was nominated for a best paper award at AMCIS 2003. He is also the recipi-ent of a multiyear National Science Foundation research grant as a coprincipal inves-tigator in the area of IT outsourcing. He has consulted with a number of large companiesincluding BellSouth, Blue Cross Blue Shield of Minnesota, IBM, and Pioneer Stan-dard Electronics.

MANISH AGRAWAL is an Assistant Professor in the Department of Information Sys-tems and Decision Sciences at the University of South Florida in Tampa. He com-pleted his Ph.D. at SUNY Buffalo. His research interests include information systemsoutsourcing, electronic intermediaries, and software quality. His articles have appearedor have been accepted for publication in Decision Support Systems, Journal of Orga-nizational Computing and Electronic Commerce, and Communications of the ACM.His work received the best paper award at the proceedings of the Americas Confer-ence on Information Systems, 2001.

H. RAGHAV RAO is a Professor of MIS and an Adjunct Professor of Computer Sys-tems Engineering at SUNY Buffalo. He is also co–Editor-in-Chief of InformationSystems Frontiers and Associate Editor of Decision Support Systems, IEEE Transac-tions on Systems, Man, and Cybernetics, and Information Systems Research. He haspublished over 100 papers, of which over 60 are in archival journals such as Journalof Management Information Systems, Information Systems Research, Decision Sup-port Systems, IEEE Transactions on Systems, Man, and Cybernetics, MIS Quarterly,Management Science, and others. His research has been supported by the NSF, theCanadian Embassy, and the Department of Defense. He is the recipient of a Univer-sity (Lily) teaching grant.

ABSTRACT: This paper conducts a two-period dynamic analysis of sourcing modechoices for e-commerce projects implemented by large firms during 1999–2002. We

48 KISHORE, AGRAWAL, AND RAO

differentiate e-commerce assets that are the focus of a sourcing decision in terms ofwhether they are in the growth or maturity stages. We also consider hybrid gover-nance mechanisms, such as minority equity arrangements, as a potential sourcingmode in addition to the conventional distinction between insourcing (i.e., hierarchi-cal governance) and outsourcing (i.e., market governance). The rapid evolution in e-commerce technologies and their markets during this period allows us to test whetherasset maturity plays any role in sourcing decisions. Results indicate that when thestrategic intent of an e-commerce project is more business focused during the growthphase, hybrid governance is preferred over hierarchical governance for sourcing ofe-commerce assets. Strategic intent is found not to influence sourcing mode choicesduring the technology/market maturity phase. Hierarchical governance is the pre-ferred sourcing mode during the growth phase, when task complexity is high. Formanaging task complexity, as technologies and their markets mature, both hierarchi-cal and hybrid governance modes become preferable to the market governance mode.

KEY WORDS AND PHRASES: asset life cycle, content analysis, e-commerce projects,e-commerce sourcing, governance forms, project strategic intent, project task com-plexity, sourcing determinants, sourcing modes, technology growth phase.

E-COMMERCE HAS GROWN RAPIDLY IN THE RECENT PAST. The U.S. Commerce De-partment stated that U.S. retail sales over the Internet grew 6.6 percent in the thirdquarter of 2003 to $13.29 billion, representing a growth of 27 percent compared to2002 [7, 29, 102]. Although e-commerce technology has often been considered asubset of information technology (IT), there are significant differences in terms of thetechnical and managerial issues encountered. Traditional IT applications mainly fo-cused on relatively mature functions such as desktop support, and functions such asdata center and network operations that help a company run its own business [68]. Onthe other hand, e-commerce systems (e.g., Internet-based applications) often providean interface between a firm and its customers and suppliers, and provide anotherchannel to market products or services. The real strength of e-commerce (and e-busi-ness) is that the Internet makes it fast and easy to get information to clients and cus-tomers, wherever they are located. E-commerce implementations also depend moreextensively on the development and use of standards than traditional IT systems.Thus, in contrast to traditional electronic data interchange (EDI), where each retailercan impose its own standard, in the Internet version of EDI (EDIINT) for the retailindustry, for example, a single standard, AS2, is used to connect to all retailers [105].

E-commerce technologies and applications are an exemplar of new IT assets thathave rapidly progressed through growth and maturity phases in recent times, as pre-dicted by Klepper [49],1 and the boundary between their growth and maturity phasesis also quite clear. Along with the growth in e-commerce, outsourcing of e-commercetechnologies has become increasingly important in recent years. The industry pressabounds with stories of enterprises ranging from the large to the small and mid-sizedthat are involved with e-commerce outsourcing (www.gartner.com). A case in pointis that of Walgreens, a firm that first outsourced its e-commerce Web site for process-ing digital photographs to Kodak and subsequently to Fuji [8].


This paper investigates the determinants of e-commerce sourcing during the technol-ogy growth and maturity phases. Three aspects differentiate this research from prioroutsourcing studies. First, there are few published scholarly studies of e-commercesourcing in the outsourcing literature—an important gap in outsourcing research, con-sidering that e-commerce technologies are now mainstream, and there is hardly anybusiness organization that does not use them. Our study is, in large part, informed byprior information systems (IS) research on outsourcing, which has used a variety oftheoretical lenses to understand the motivations, drivers, contractual aspects, and con-sequences of this IT governance strategy [25, 35, 39, 53, 56, 65, 82]. In this paper, wescientifically extend it to the e-commerce sourcing area. Second, the outsourcing lit-erature has not considered IT assets from the perspective of growth and maturity stagesof the product life cycle. It has only performed a static analysis of outsourcing driverswithout considering that outsourcing motivations/drivers may actually change overtime as IT assets and their markets move from the growth phase to the maturity phaseon the product or evolutionary life cycles [26, 49, 91]. This distinction is quite impor-tant, because previous research has shown that, as technological products pass throughtheir life cycle stages, product demand, product and process innovations, user learning,adopter base, and market structures change [49, 61, 78, 91, 97]. We argue that productlife cycle should be an important consideration of users’ e-commerce sourcing deci-sions to account for changes in market maturity and user learning commensurate withproduct life cycle stages [3, 20, 44, 93]. Third, the outsourcing literature has addressedonly two polar governance modes—outsourcing and insourcing—and has ignored hy-brid governance modes, such as minority equity alliances, which began to be utilizedduring the Internet boom in the 1990s and are now a common mode for sourcing e-commerce assets. We not only consider markets (outsourcing) and hierarchies(insourcing) but also include hybrid governance as potential sourcing modes. The pa-per thus contributes to outsourcing research in general (e.g., [2, 4, 5, 6, 45, 48, 53, 54,59, 73, 84, 92, 98]), and e-commerce outsourcing research in particular.

This paper explores e-commerce sourcing via an empirical study and seeks to ad-dress the question: For e-commerce outsourcing, what influence does strategic intentbehind sourcing decisions and project task complexity have on firms’ sourcing modechoices, including hybrid governance modes, during periods of technology/marketgrowth and maturity? We consider e-commerce projects that were sourced both dur-ing the growth phase (1999–2000) and the maturity phase (2001–2002) of thee-commerce industry. We choose January 1, 2001, as the starting point for the growthperiod of the e-commerce industry based on general agreements in the trade pressabout the time when consolidation in this industry started, in the absence of hard dataabout the same.

Theory

Prior Literature

PRIOR RESEARCH IN IS OUTSOURCING has examined the outsourcing phenomenon froma number of perspectives. The highlights of the literature dealing with motivations


behind outsourcing suggest that outsourcing decisions are propelled by high IT coststructures [59, 84, 92], perceived production cost advantages [4, 5, 6], external influ-ences [4, 45, 60], and environmental uncertainty [73]. Outsourcing has even been seenas a way to overcome internal organizational politics to achieve organizational out-comes [53, 54].

Two other drivers that have been considered in other areas of research are projecttask complexity and strategic intent. Task complexity has been considered in the soft-ware engineering literature [51, 85], and strategic intent has been discussed in thecontext of managing outsourcing contract relationships [27]. However, we know offew empirical studies on sourcing that consider project task complexity and that pro-pose strategic intent to be a driver of outsourcing decisions. We are also not aware ofany study that looks at the influence of evolutionary life cycles on sourcing decisions.We consider these important gaps in the context of e-commerce outsourcing in thisresearch. (Note: We use the terms e-commerce and e-business interchangeably in thispaper.)

Research Model

E-commerce Sourcing Modes

E-COMMERCE SOURCING MODE IS DEFINED in this research as the governance formthat is utilized to manage the development of e-commerce goods and services(e-commerce assets hereafter). Transaction cost economics identifies three distincteconomic institutions—firms (i.e., hierarchies), markets, and hybrid forms—for or-ganizing productive economic activity [99]. These provide different governance formsfor organizing economic transactions, and utilize the governance mechanisms of hi-erarchical control, classical arm’s-length contracting, and relational contracting, re-spectively, for managing those transactions [100, 101]. In our context, sourcing ofnew e-commerce assets is the economic transaction of interest and it can be con-ducted using either one of three governance forms. The governance forms, or sourc-ing modes, can be distinguished in terms of the extent to which firm managers havehierarchical control over the e-commerce assets sourcing transaction [6]. On one endof the spectrum of sourcing modes is the insourcing mode, which provides the hierar-chy of firm managers with full control in the task of sourcing of an e-commerceproject in terms of having complete authority and responsibility for the project. Onthe other end of the spectrum is the outsourcing mode, which uses market mecha-nisms governed by arm’s-length contractual arrangements for procurement of e-com-merce assets and affords firm managers little, if any, hierarchical control over theproject. The hybrid sourcing mode lies in the middle of this spectrum and includes avariety of governance forms, such as relational contracting, strategic alliances, mi-nority equity investments, and vertical contracting [9, 62, 76, 99]. Hybrid forms pro-vide some degree of hierarchical control to firm managers over their e-commerceprojects through various governance mechanisms including board-level oversight,incentive design, joint decision-making, information sharing, and so on [43, 76, 86,


87]. A typical example of hybrid governance in the form of a minority equity invest-ment is provided below.

W.W. Grainger Inc. and Works.com [are creating] an online purchasing systemand e-marketplace for small and midsize businesses. . . . Grainger said it willcontribute more than $21 million cash to Works.com. In exchange, Graingerwill receive a 40% stake in Austin-based Works.com, subject to certain votingand transfer restrictions. Grainger Group President . . . will hold one of sevenseats on Works.com’s board. [28, p. 1]

As with most organizational decisions, no one particular sourcing mode is inher-ently superior to the others, and the choice is contingent upon organizational goalsand contextual and project-specific factors. For e-commerce sourcing, this researchinvestigates the role of a key organizational goal—project strategic intent—and aproject-specific feature—project task complexity—and we develop hypotheses fortheir roles in selecting an appropriate sourcing mode for e-commerce projects duringthe technology growth and maturity phases.

E-Commerce Project Strategic Intent

Strategic intent [27, 42], in the context of investments in new e-commerce assets andcapabilities (hereafter referred to as e-commerce project strategic intent), essentiallycaptures a firm’s strategic goals for appropriating returns from these investments.DiRomualdo and Gurbaxani [27] have identified three distinct IT project strategicintents—IS improvement, business impact, and commercial exploitation—on a spec-trum of intents, with IS improvement at one end of the spectrum, commercial exploi-tation at the other, and business impact occupying the middle. These intents can bedirectly adapted to the e-commerce context, where improvement projects are focusedon upgrading or acquiring e-commerce capabilities that serve to enhance a firm’sinternal systems [12, 21, 30, 79]. E-commerce investments made with the intent ofbusiness impact are focused on developing new IT-intensive business processes andassociated application systems that allow a firm to engage in competitive actions [31,34, 81]. Firms may go a step further and exploit their new e-commerce assets in acommercial manner by creating new businesses that sell information products andservices in the marketplace, and this will obviously provide the firms with the mostdirect and tangible returns on e-commerce investments [27]. Because business im-pact and commercial exploitation intents are both business oriented and more directlylinked to firm performance, we refer to them in the discussion below as business-focused projects/intents. For instance, exchanges in industries such as electrical powercreated opportunities for regulated utilities to explore revenue opportunities in re-lated businesses outside their core regulated businesses as shown below:

[Along with other U.S. utilities], Ameren Corp. [and Kansas City Power andLight have] signed on as partners in the development [of a business-to-businesse-commerce vertical exchange for the electrical industry worldwide. The


exchange] is expected to go live in second quarter 2000. . . . The vertical ex-change seeks to streamline companies’ purchasing processes while aggregatingcompanies for increased buying power of equipment and services ranging fromoffice supplies to transformers to heavy machinery.

[Executives at the technology partner, bex.com, said], “This vertical exchangefor the electrical utilities industry effectively brings an old economy marketinto the new economy and [creates] enhanced revenue opportunities for thetightly regulated electric utility market.” [Senior utility company executivessaid], “This platform is consistent with [our] commitment to lowering the costof operations through the use of leading technologies . . . the venture [will alsohelp in] maximizing shareholder value by capturing growth opportunities out-side our core regulated utility business.” [17, p. 1]

E-commerce project strategic intent is expected to guide the choice of an appropri-ate sourcing mode as part of a firm’s overall e-commerce investment decision. Whena firm makes an investment for developing unique IT-intensive business processesand innovative information products and services using new technologies with theintention of engaging in competitive actions or for commercially exploiting thesee-commerce assets, it is more likely to adopt hierarchical governance for sourcingthese assets. Organizational and managerial processes and their associated IS embeda high degree of firm-specific tacit knowledge, which has been recognized in theknowledge-based view of the firm as an inimitable and inappropriable organizationalasset [38, 74, 89, 90]. The larger the organizational span and higher the richness ofthese processes and knowledge systems, and the higher the uniqueness of their infor-mation products/services, the higher will be the extent of embedded firm-specifictacit knowledge in these processes and products. To gain competitive advantage fromthis unique knowledge asset, a firm will have to protect tacit knowledge from leakage[15, 58] to external vendors, as sharing it with vendors will erode the competitiveadvantage and economic rents that may otherwise be appropriated by the firm.

Further, the intellectual property that is created as a result of investments in develop-ing unique e-commerce–enabled business processes has the potential to generate eco-nomic rents for the firm only if this property is protected properly and utilized effectivelyby the firm. The need for protection of e-commerce assets is highest when informa-tion products and services are sold in the open marketplace with commercial intent.However, protection of intellectual and knowledge property is quite difficult usingproperty rights instruments such as patents, copyrights, and trade secrets, as they arenarrowly defined under the law and are costly to write and enforce [58, 88]. It hasbeen argued that firms with hierarchical controls are better positioned than markets toprotect their unique knowledge assets from imitation by competitors using institution-alized capabilities available to them, such as employee conduct rules, job designs, andreducing employee mobility by promises of future incentives [32, 58].

Protection of knowledge by firms is expensive, and firms should protect only uniqueand valuable knowledge that can repay the costs of protection [58]. The above sug-gests that a firm will choose hierarchical modes of governance for sourcing e-commerceassets when the tacit knowledge component in this intellectual property is high, as is


the case when investments are being made for creating innovative and unique digitaloptions and information products and services using new IT. On the contrary, the firmis likely to choose markets for sourcing of projects that are geared toward e-com-merce capability improvement, which may include physical infrastructure improve-ment (such as upgrades in hardware and software related to computing,communications, network services, database management, etc.), technical skill setimprovement, and implementation of new standards [21]. This is because knowledgepertaining to these types of projects is generally generic e-commerce knowledge andnot firm specific, and it need not be protected through hierarchical governance. Fur-ther, generic knowledge is not only available in the marketplace; vendors are morelikely to possess superior generic e-commerce knowledge due to their core compe-tencies in e-commerce that are developed through a number of projects at a numberof client organizations [57], indicating that markets are a better choice for sourcingprojects geared toward e-commerce capability improvement.

Furthermore, firms will need to manage, maintain, and upgrade their business ap-plication systems using hierarchical governance on a continuing basis to developfirm-specific tacit knowledge embedded in these systems. This would also imply thatfirms would need to build capabilities in these systems and their underlying technolo-gies at the outset by sourcing these application development projects using hierarchi-cal governance modes, an argument quite consistent with recent research that positsthat firm capabilities affect boundary decisions [9]. Initial development of in-housee-commerce capabilities through insourcing of application development projects isimportant, because capability building is path dependent in general [9, 90] and ismore so in the context of software development [13]. Thus, firms are likely to choosehierarchical governance for developing business application systems using new ITbased on the logic of in-house capability development as well.

Growth Versus Maturity Periods. Whether e-commerce project strategic intent willinfluence the choice of a particular sourcing mode depends upon the maturity of theunderlying technologies and their markets with respect to the e-commerce assets tobe sourced. In a two-period scenario—the first being the technology/market growthperiod and the second the technology/market maturity period, as discussed earlier—strategic intent is expected to be a significant predictor of sourcing mode only duringthe first period for two reasons. First, protection of tacit knowledge and intellectualproperty from leakage and expropriation—a primary reason behind the choice ofhierarchical modes of governance with respect to business-focused e-commerce in-vestments—matters only in the first period. Over time, all knowledge will leak, in-cluding firm-specific tacit knowledge, because knowledge resides in individuals [37],and as individuals move from one organization to the next, so will knowledge. Fur-ther, e-commerce professionals who are the holders of the firm-specific tacit knowl-edge are not only organizational members but are also members of, and participate in,professional communities and networks, and these networks provide another conduitfor knowledge leakage [15]. Erstwhile unique business processes and e-commerceapplications owned by a firm will also be eventually imitated by vendors and com-petitors [58]. In fact, over time large vendors and consulting firms integrate the unique


and value-generating aspects of individual firms’ e-commerce business processes,practices, and application systems into what has come to be known as “best prac-tices,” based on their experiences with a number of client firms on a number of projects,which they then sell or otherwise make available to their clients.

Second, if firms are, for some reason, not able to build capabilities pertaining tobusiness application systems development using new e-commerce technologies inthe first period, they have missed the boat, and it will be very difficult for them todevelop capabilities in the second period due to the path-dependent nature of organi-zational capabilities [9, 13, 90]. There are several potential reasons why firms maynot be able to develop capabilities in the first period. All firms may not choose in-house application systems development in the first period, when their intent ise-commerce–enabled business improvement, thereby making the capability-buildingrationale irrelevant in the second period. Even if firms make appropriate investmentsin the first period in acquiring/developing appropriate skill sets in project manage-ment, business processes and applications, and new technologies, and then develop-ing the intended business application systems, there is no guarantee that theirinvestments in capability building will bear fruit. As technologies and markets ma-ture, skilled professionals may be lured away from client firms by vendors who canoffer more stimulating environments and challenging assignments, since IT ande-commerce development are their core competencies [57], thereby crippling the ca-pabilities client firms may have developed during the technology growth period. Thisagain makes the capability-building rationale irrelevant in the second period.

Hybrid Versus Hierarchical Governance. As discussed above, firms will wish toutilize hierarchical governance when they invest in business-focused e-commerceprojects, as the resulting e-commerce assets typically embed a high degree of firm-specific tacit knowledge and trade secrets and represent intellectual property that needsto be protected from imitation and commercial exploitation by competitors. How-ever, client firms may not be able to go it alone, simply because new technologies arehighly complex and they cannot expect to match the deep and broad knowledge aboutITs that vendors have accumulated over time through multiple projects at multipleclients with related technologies [10, 57]. The depth and breadth of prior accumu-lated knowledge in related areas contributes to absorptive capacity and enables thefaster and successful assimilation of new knowledge [24]. Therefore, although ven-dors in the marketplace may be on the same level as client firms in terms of knowl-edge and capabilities about new information technologies during the technology growthperiod, vendors are better positioned than client firms, owing to their higher absorp-tive capacity for acquiring and effectively utilizing new knowledge pertaining to newITs.

As a consequence, client firms will prefer to use hybrid or intermediate governanceforms, including strategic alliances, minority equity investments, and vertical con-tracting with e-commerce service providers and other vendors, instead of pure hierar-chical governance forms [9, 62, 76, 100] for sourcing e-commerce assets withbusiness-focused strategic intents during the growth phase.


This governance strategy allows client firms to gain access to and leverage theknowledge assets owned by their strategic partners for developing innovative e-com-merce products and services using new e-commerce technologies while ensuring thatthey have adequate control over their e-commerce projects through the governancemechanisms of partner selection, incentive design, information sharing, monitoring,joint decision-making, and joint action [43, 76, 86, 87]. However, they are expectedto utilize equity-based rather than contract-based alliances, as transfer of technologi-cal capabilities is much better in the former than the latter type of hybrid governanceforms [71]. For example,

Emerson Electric Co. worked with Click Commerce, a leader in Internet-enabledchannel management solutions, and created a business-to-business e-commerceplatform [to] enable its divisions to seamlessly integrate their systems—be-tween divisions and with virtually thousands of channel partners located allaround the world. [According to senior company executives], “This will ulti-mately reap top-line benefits from increased sales by reaching new customersand new markets, and [create] other benefits such as improved customer satis-faction and brand loyalty.” [As gathered from personal communication withthe lead manager for the project], Emerson took a minority equity position inthe service provider, Click Commerce. [16, pp. 1–2]

Based on the above discussions, we hypothesize that:

H1a: During the technology/market growth phase, firms are more likely to usehybrid over hierarchical governance forms for sourcing of new e-commerceprojects when their strategic intent with respect to these e-commerce investmentsis more business focused.

H1b: During the technology/market growth phase, firms are more likely to usehybrid over market governance forms for sourcing of new e-commerce projectswhen their strategic intent with respect to these e-commerce investments is morebusiness focused.

H1c: During the technology/market growth phase, firms are indifferent in theirpreference between hierarchical and market governance forms for sourcing ofnew e-commerce projects with respect to their strategic intent.

H2: During the technology/market maturity phase, strategic intent behind newe-commerce investments will not have any influence on the choice of sourcingmode for sourcing of new e-commerce assets.

E-Commerce Project Task Complexity

In a widely cited review, Campbell [19] takes an information processing perspectiveand defines task complexity as emanating from four sources that have the potential to


increase information load, information diversity, or the rate of information changeduring the course of performance of a task. The four sources of task complexity havebeen further discussed by Zigurs and Buckland [104] and Rao and An [75] and in-clude (1) outcome multiplicity (i.e., the presence of multiple desired outcomes orend-states to be attained), (2) solution scheme multiplicity (i.e., the presence of mul-tiple potential ways or paths to arrive at a desired end-state), (3) conflicting interde-pendence (i.e., the presence of conflicting interdependence among paths to multipleoutcomes), and (4) solution scheme/outcome uncertainty (i.e., the presence of uncer-tain or probabilistic links among paths and outcomes).

E-commerce projects are exemplar embodiments of task complexity. Multiple andoften conflicting goals of different stakeholder groups, the rapidly changing and com-plex nature of ITs and the still incipient nature of e-commerce development method-ologies2 contribute to task complexity in e-commerce projects [75].

McKeen and colleagues have studied task complexity in the context of user partici-pation in IS development [66, 67]. McKeen et al. [67] report that the effect of userparticipation on user satisfaction is higher when task and system complexity are higher,and user participation does not significantly affect user satisfaction when task/systemcomplexity is lower. In a later paper, McKeen and Guimaraes [66] report that userparticipative behaviors across the four phases of the systems development life cycleare significantly related to user satisfaction in “high need for participation” projects(i.e., those where the combination of task and system complexity is above the medianvalue) and not in “low need for participation” projects. Both of these studies implythat user participation may be a necessary condition for achieving higher levels ofuser satisfaction when either task complexity or system complexity or both are higher.

Task complexity has also been found to affect coordination needs. As task com-plexity increases, so does the need for increased coordination using less of impersonalrule-based coordination modes and more of personal and group-based coordinationmodes [96]. Recent studies in the organizational literature dealing with governanceissues and buyer–supplier relationships have also started considering task complexityas an important variable that may affect governance choices [11, 47]. Jones et al. [47]argue that task complexity adversely affects the problem of coordination and, there-fore, include it in their theory of network governance.

There is ample evidence in the organizational and strategic management literaturethat organizational hierarchies possess superior coordination capabilities, which isessentially “managing (inter)dependencies among activities” [64, p. 90]. Malone notesthat firms (product and functional hierarchies) are better than markets (centralizedand decentralized) in terms of coordination costs, as a task processor in a hierarchy isconnected with fewer other agents, and fewer task assignment and scheduling mes-sages flow among agents in a hierarchy [63]. Grant [38] and Kogut and Zander [50],in a knowledge-based view of the firm, suggest that coordination involves integrationof individuals’ specialized and tacit knowledge for use in production of goods andservices, and firms are better equipped for this task because they use routines, com-mon language, and shared meaning that they develop over time. Further, in a study ofstrategic alliances, Gulati [41] proposes and finds that the greater the anticipated in-


terdependence in an alliance, the more hierarchical the governance structure that isused to organize it, providing further evidence that hierarchical structures yield supe-rior coordination capabilities. Organizations also possess better information process-ing mechanisms [33, 94], and using their superior communication and coordinationmechanisms, they can effectively meet the varying information processing needsemanating from varying levels of task and environmental complexity [72, 95].

While we are not aware of formal studies that compare internal organizations (hier-archies) with markets in terms of their capabilities to support user participation insystems development activities, it would appear that intensive user participation wouldbe more effectively supported within organizational hierarchies. A high degree ofuser participation would involve the division of systems development tasks betweendevelopers and users, which would create a higher degree of task interdependenceand task uncertainty and the consequent need for a higher degree of coordination.

The above discussion about task complexity, systems development, and governanceforms provides the rationale for considering task complexity as a determinant ofe-commerce sourcing mode. A higher degree of task complexity, which e-commerceprojects often exhibit, creates the need for a higher degree of coordination, informa-tion processing, and user participation. These needs can be met effectively by hierar-chical structures, as they possess superior coordination and information processingcapabilities as compared to other governance forms. This would suggest that high-complexity e-commerce projects are more likely to be sourced using hierarchical gov-ernance mechanisms (insourcing) than using markets. Further, while the capabilitiesof markets and hierarchies with respect to managing task complexity, supporting ef-fective user participation, and providing effective coordination may evolve over time,firms are expected to remain superior to markets over time in these respects. Theseadvantages of firms over markets will not erode over time, thereby providing firmswith superior coordination capabilities for managing task complexity during both theperiods of technology/markets growth and technology/markets maturity. The examplebelow shows a typical instance during the technology growth phase where insourcingwas chosen for managing the complexity of building a first-of-a-kind, high-task-com-plexity e-commerce portal in the airline industry during the growth phase.

TRW Aeronautical Systems announced plans to launch a global e-business aero-space marketplace to enable electronic transactions with its customers, suppli-ers and peer group. TRW Aeronautical Systems believes that the marketplacewill be the first announced, all-encompassing, lean-based aerospace e-market-place incorporating buy side and sell side transactions, engineering collabora-tion, and supply chain management across the aerospace industry.

[Executives involved in the project said], “We . . . wanted an e-business solu-tion that supported [our] mindset. In the end, we decided to create our ownfunctionally rich solution, and . . . would actively encourage other like-mindedcompanies to join in. TRW recognizes that we will have to work with otherformed e-business groupings. . . . E-business fundamentally changes the wayyou do business and can streamline processes if properly deployed. We . . . see


this launch as a significant investment in our future.” [In direct correspondencewith one of the authors], the VP-in-charge of the project confirmed that theproject was implemented using internal resources without the involvement ofservice providers. [18, p. 1]

Similarly, an example of insourcing during the technology maturity phase in thepresence of task complexity, driven by the need to develop/modify an online strategy,is provided by Wal-Mart.

Wal-Mart announced [that it would] buy back its independent Web site,Walmart.com . . . and reintegrate it into its core business. The Web site [had]been a financial sinkhole [estimated to lose $100 million in 2000]. The idea thata general merchandise store with its myriad of offerings could survive on theWeb was unproven. In the physical world, one-stop shopping is convenient. Onthe Web, store hopping is much easier. [14, pp. 1–2]

Based on the above discussions, we hypothesize:

H3a: During the technology/market growth phase, firms are more likely to usehierarchical over market governance forms for sourcing of new e-commerceprojects when the project task complexity is high.

H4a: During the technology/market maturity phase, firms are more likely to usehierarchical over market governance forms for sourcing of new e-commerceprojects when the project task complexity is high.

There is a growing body of evidence that sociological and relational factors such astrust and macroculture make hybrid governance forms effective in dealing with theproblems of uncertainty and coordination. Trust between exchange partners in aninterorganizational relationship [36, 77] has been found to positively affect joint ac-tion (a relational governance mechanism) [103], which essentially “involves the par-ties carrying out the focal activities in a cooperative or coordinated way” [43, p. 25].Further, social systems, such as macroculture, rather than bureaucratic structures preva-lent in hierarchical forms, may improve coordination among network partners in thenetwork governance model (a hybrid governance form) [47].

However, trust in interorganizational relationships develops over time [77]. Fur-ther, familiarity between exchange partners through prior ties also contributes to trustin interorganizational relationships [40]. But markets are dominated by a large num-ber of new vendor firms during the technology/market growth phase [49], and thelikelihood of client firms’ having had long relationships or prior ties with new vendorfirms supplying the new focal technologies will be quite low. This implies that hybridalliances between vendors and clients are not likely to enjoy high levels of coordina-tion capabilities that emanate from interorganizational trust and macroculture andappear to be similar to markets and inferior to hierarchical governance during thisearly period in terms of coordination capabilities. As a result, client firms are ex-pected to prefer hierarchies over hybrids in the context of task complexity, and are


likely to be indifferent between hybrid and market governance forms during the tech-nology/market growth phase. We, therefore, hypothesize:

H3b: During the technology/market growth phase, firms are more likely to usehierarchical over hybrid governance forms for sourcing of new e-commerceprojects when the project task complexity is high.

H3c: During the technology/market growth phase, firms are indifferent in theirpreference between hybrid and market governance forms for sourcing of newe-commerce projects when the project task complexity is high.

As new technologies and their markets mature, consolidation in the marketplacetakes place, most of the erstwhile new and smaller vendor firms exit the industrythrough mergers, acquisitions, and bankruptcies, and only a few larger and older firmsremain in the market [49]. As a result, in this period the likelihood of client firms’having had either longer relationships or a number of prior exchanges with currentvendors in the marketplace is quite high. Client firms will either be dealing with largecompanies (e.g., IBM, EDS, etc.) with whom they will have had prior business rela-tionships in the context of other older technologies or they would be dealing with newvendors who survived the growth phase in the industry and with whom clients mayhave had prior commercial exchanges in the context of new technologies. In eitherevent, time and prior exchanges will have contributed to the development of highlevels of mutual interorganizational trust between exchange partners, thereby creat-ing an environment in which hybrid forms enjoy high coordination capabilities ema-nating from these relational mechanisms and, thus, becoming similar to hierarchicalforms in terms of these capabilities. As a result, client firms are expected to be neutralin terms of their preference between hierarchies and hybrids in the context of taskcomplexity, but are likely to prefer hierarchies over markets during the technology/market maturity phase. For example, with high task complexity driven by the “indus-try-first” nature of its initiatives, Eastman Chemical chose hybrid governance with itstechnology partners:

[Adapting ideas from other industries], Eastman [is] using Web technologies torevamp its in-house and business transaction processes [and is one of the firstcompanies in its industry to do so. The company is even helping] its smallercustomers to get tech-enabled. The company also invested in auction softwarepartner Moai Technologies and in vertical Internet portal paintandcoatings.com.Eastman is also working to create industry XML standards to facilitate elec-tronic buying, selling and delivery of products . . . the company is updating itse-commerce storefront. [These efforts are driven by the belief that] being outahead gives [the company] a much better chance to win. [70, pp. 1–4]

Based on the above discussions, we hypothesize:

H4b: During the technology/market maturity phase, firms are more likely to usehybrid over market governance forms for sourcing of new e-commerce projectswhen the project task complexity is high.


H4c: During the technology/market maturity phase, firms are indifferent in theirpreference between hybrid and hierarchical governance forms for sourcing ofnew e-commerce projects when the project task complexity is high.

Method

WE TEST THE ABOVE HYPOTHESES using content analysis, conducted following theprocedures used by Ang and Slaughter [5], Gulati and Singh [41], and Slaughter andAng [83], and logistic regression. We gathered sourcing announcements pertaining toe-commerce projects during the 1999–2002 period from the Dow Jones Interactivedatabase. The sourcing choice for the project included in the announcement was usedas the dependent variable. Content analysis was conducted using the NVivo contentanalysis software.

Sample

Since e-commerce projects were significant initiatives for firms during the periodunder study, they were typically announced publicly in reasonable detail through thebusiness press. Sourcing announcements were collected using a full text search ofannouncements made by companies from 1999 through 2002 in the news sourcesmonitored by the Dow Jones Interactive database. These sources provide comprehen-sive coverage of public announcements by firms and have been used in prior IS re-search [22]. Relevant announcements were retrieved using a search string to matchwords in the announcements of interest. While selecting the search string, the goalwas to maximize the collection of relevant announcements while screening out irrel-evant announcements. After examining a number of candidate search strings and re-sulting announcements, we found the following search string to be quite effective inidentifying announcements of interest and used it to search the database for e-commercesourcing announcements. The resulting announcements were scanned to select thosethat provided information on the selected sourcing mode, and these were added to theNVivo database.

(co=<list of companies>) and ((dns=internet) or (key=e-commerce)) and(wc>300) and (lp=e-commerce or e-commerce or e-business or e commerce or(online near1 business) or (online near1 sales))

The search string looks for announcements in the Dow Jones Interactive databasethat feature companies provided in the list following the term “co.” We used the list ofcompanies in the S&P 500 index. The terms “dns” and “key” denote the news cat-egory descriptor and key words, respectively, and were used to restrict the search tothose announcements that related to “Internet” or “e-commerce” or “e-business.” Thiseliminated announcements made by companies that were not directly related to e-commerce activities. The term “wc” denotes word count, and a minimum limit of 300words was used because we found that a large number of shorter announcementssimply informed the press about their new projects without providing details relevant


for our research. The final term “lp” denotes lead paragraph and was used to narrowthe announcements to those where some e-commerce activity was mentioned in thelead paragraph. We did not retain announcements that merely indicated interest in aspecific sourcing mode; only confirmations were noted.

We restricted our sampling frame to the firms in the S&P 500 index, as this indexconsists of 500 firms chosen for market size, liquidity, and industry group representa-tion and is one of the most widely used benchmarks of U.S. business performance.The initial search on the Dow Jones Interactive database yielded 208 announcementsin the 1999–2000 period and 64 in the 2001–2002 period. The elimination of an-nouncements for which sufficient information was not available pertaining to thevariables of interest resulted in 100 announcements for the 1999–2000 period and 47for the 2001–2002 period. After we completed the coding for sourcing mode for theentire sample, we found that there were six joint venture announcements for the 1999–2000 period, but none in this sample for the 2001–2002 period. To be able to compareresults across the two periods, we removed the six announcements from the 1999–2000 sample. The final sample, therefore, consists of 94 announcements during the1999–2000 period and 47 during the 2001–2002 period, for a total of 141. A profileof the firms included in the sample is provided in Tables 1 and 2.

After collecting the initial announcements as described above, we collected de-tailed information about each announcement by searching for articles related to thesubject firm around the date of the announcement in the Dow Jones Interactive data-base. This database includes most publications that cover IT and business issues, andthis search helped in gathering additional relevant, publicly available informationpertaining to the announcements. This procedure improved the precision of the cod-ing in a significant manner.

Content Analysis

Content analysis is a research technique that allows for the objective, systematic, andquantitative description of the manifest content of communication and is extensivelyused in management and IS research (e.g., [1, 5, 41, 46, 52, 57, 80, 83]).

Following the steps recommended for content analysis [52, 69], we first used priorconceptual and empirical research to create a coding scheme for categorizing thevarious constructs in this research. Several steps were taken to ensure coding reliabil-ity following prior research [41]. The first step was to develop a precise coding scheme,described later in this section. The announcements were initially coded by one of theauthors, who checked for test–retest reliability by recoding announcements about aweek after the initial coding. In every case, the recoding was very close to the initialcoding, and more than 95 percent of the recoded values were identical to the initialvalues. To further check the reliability of the coding, two independent coders, whowere not involved with the study, coded all the announcements separately. One coderhad two years of experience in leading IS development and two years of CMM (capa-bility maturity model) level-4 implementation at a major multinational bank, and theother was a graduate student with prior work experience in engineering design. Cohen’s


kappa was calculated for each construct between each pair of coders. The kappa co-efficient reflects the extent to which the observed agreement between coders is supe-rior to what could have been obtained by chance [23]. Following Ang and Slaughter[5], both coders first coded 15 documents from the first-period sample, yielding akappa coefficient exceeding 0.8 for each construct. The observed disagreements werethen reconciled by discussion among the coders, moderated by a faculty memberwith more than 15 years of experience in IS research. The two coders then coded theremaining announcements, yielding a kappa exceeding 0.95 for each construct. Fi-nally, for 53 companies in the 1999–2000 sample for which contact information wasavailable in the announcements, we contacted the identified representatives in subjectfirms to validate our coding. We received 24 responses (45 percent), and the match

Table 1. Size Distribution of Firms Included in the Sample (in billions of U.S.dollars)

First period Second period(1999–2000) (2001–2002)

Sales Assets Sales Assets

< $1 12 15 2 3$1–$10 47 41 17 19> $10 35 38 28 25

Total 94 94 47 47

Table 2. Industry Distribution of Firms Included in the Sample

First period Second periodIndustry (1999–2000) (2001–2002)

Aerospace and defense 2 0Automobile 3 5Chemicals and metals 10 5Personal accessories 3 4Finance 15 2Food 0 2Health care 5 2Heavy industry 14 7Hospitality 3 1Technology 4 2Retail 15 11Telecommunications 4 2Transport 9 4Utilities 7 0

Total 94 47


between the responses and coding was greater than 90 percent. As a result of theseextensive precautions, the coding of constructs is expected to be highly reliable.

Sourcing Mode

As discussed in the theory section, we follow the typology of governance forms basedon the degree of hierarchical control developed by Gulati and Singh [41]. In decreas-ing order of hierarchical control are internal organizations (insourcing/hierarchicalgovernance), joint ventures, minority equity ownerships, and contractual relations(outsourcing/markets). Internal organizations or hierarchies have the highest degreeof hierarchical control over their projects. Following Lacity and Willcocks [55], ven-dor buy-in contracts, where vendors supply skilled IT personnel who work under thesupervision of client managers, are included in the hierarchies category. Followingthe transaction cost economics (TCE) theory [62, 76, 99], hierarchies also include thecase of vertical integration, which occurs when a client firm buys a vendor firm toexecute its IT project in-house. In joint ventures, partners create a separate entity withownership distributed among the partners, and a separate hierarchy of managers over-sees day-to-day operations and addresses problems as they arise. Minority equityownerships are those arrangements where one firm takes a minority stake in a partnerfirm without creating a separate organization. These provide a lesser degree of hierar-chical control, because supervision is typically in the form of board membership forthe investing partners in the invested firm. Although these members are not involvedin day-to-day operations of the firm, their presence on the board helps share informa-tion, ratify decisions, and can help resolve conflicts as they arise. Classical contrac-tual arrangements are the arm’s-length market exchanges and do not involve anyshared ownership or administrative structures for project control. None of the ele-ments of a hierarchical relationship are necessarily part of a contractual arrangement,and decisions are negotiated between partners as the need arises.

The dependent variable e-commerce project sourcing mode therefore measures theextent of substitution of hierarchical controls by market mechanisms and is inferredfrom the information provided in the announcement. This variable was initially codedin the decreasing order of hierarchical controls, with internal IS organizations codedas 0, joint ventures coded as 1, minority investments as 2, and contractual arrange-ments as 3. However, since no joint ventures were found in the second period (2001–2), the variable was recoded as internal IS organizations 0, minority investments 1,and contractual arrangements 2.

E-Commerce Project Strategic Intent

The e-commerce project announcements were content analyzed for e-commerce projectstrategic intent using the three-tier strategic intent framework developed byDiRomualdo and Gurbaxani [27], discussed earlier, and the hierarchical frameworkof e-commerce developed by Zwass [106]. Zwass’s framework provides for threehierarchical metalevels of e-commerce, with e-commerce products and structures at


the highest level followed by e-commerce services and ending with e-commerce in-frastructure at the lowest level. E-commerce products and structures are business-focused e-commerce assets that are developed either with business impact strategicintent or commercial exploitation strategic intent. Therefore, these announcementswere coded as either 2 (business impact) or 3 (commercial exploitation), dependingupon whether the announcement explicitly alluded to a commercial intent. The com-mercial intent was evident when the announcement included statements referring tothe sale of information products/structures in the marketplace or to the starting ofnew lines of business. E-commerce services and e-commerce infrastructure are foun-dational e-commerce assets that provide the platform for developing business appli-cations and information products and services normally not sold by client firms whopossess domain expertise and would sell e-commerce products and structures. There-fore, services and infrastructure type of e-commerce projects are developed with theintent of e-commerce system improvement and were coded with a value of 1 (forimprovement intent). The integrated coding framework used for coding strategic in-tent of e-commerce announcements is shown in Table 3.

E-Commerce Project Task Complexity

Task complexity can be viewed as (1) a primarily psychological perception of the taskperformer with respect to the task being performed, (2) a person–task interaction thatacknowledges both the objective complexity of a task and the perception of complex-ity of that task by a task performer, or (3) emanating purely from objective task char-acteristics [19]. We consider task complexity in this research as emanating fromobjective task characteristics—that is, objective task complexity—because a task canbe “objectively” labeled by a researcher as less or more complex as compared toanother task, whereas the other two views of task complexity depend upon percep-tions of the organization that are not always included in press announcements.

Following McKeen and colleagues [66; 67], we divide task complexity into twocategories: (1) business task uncertainty, which pertains to the business tasks (pro-cesses) for which the e-commerce solution is being developed, and (2) technologytask uncertainty, which pertains to the technologies used in developing and imple-menting an e-commerce–based solution. By definition, task complexity is low whenthe likelihood of a task’s achieving its desired outcome is high. This will occur whensufficient overall industry familiarity and experience with the particular task has beengained, and empirical evidence gained over time has been used to refine the task forachieving its intended outcomes with near certainty. For business task complexity,this implies that the business processes to be supported by a proposed e-commercesolution have been in vogue for a long time, are well understood, and to some extenthave become industry standard. For technology complexity, this implies that the taskof developing and implementing the e-commerce infrastructure or business solutionfollows a proven or an industry standard methodology. Some example phrases thatwere found in the announcement sample indicating high or low business or e-com-merce task uncertainty are shown in Table 4.


Tabl

e 3.

Cod

ing

Fram

ewor

k fo

r e-

Com

mer

ce P

roje

ct S

trat

egic

Int

ent (

adap

ted

from

[10

6])

Met

alev

el

Lev

elFu

nctio

nE

xam

ples

Cod

ed a

s

Pro

duct

s an

d7

Ele

ctro

nic

mar

ketp

lace

sE

lect

roni

c au

ctio

ns,

brok

erag

es,

2 (f

or b

usin

ess

impa

ct s

trat

egic

inte

nt),

or

stru

ctur

esan

d el

ectr

onic

hie

rarc

hies

.de

aler

ship

s, a

nd d

irect

sea

rch

mar

kets

;3

(for

com

mer

cial

exp

loita

tion

stra

tegi

cin

tero

rgan

izat

iona

l sup

ply

chai

nin

tent

).m

anag

emen

t.6

Pro

duct

s an

d sy

stem

s.R

emot

e co

nsum

er s

ervi

ces

(ret

ailin

g,P

rodu

cts

and

stru

ctur

es w

ere

code

dba

nkin

g, s

tock

bro

kera

ge);

as 3

onl

y if

the

anno

unce

men

t cl

early

info

tain

men

t-on

-dem

and

(fee

-bas

edid

entif

ied

a di

rect

com

mer

cial

exp

loita

tion

cont

ent

site

s, e

duca

tiona

l offe

rings

);in

tent

by

mak

ing

stat

emen

ts a

bout

sel

ling

ofsu

pplie

r–cu

stom

er li

nkag

es;

onlin

ein

form

atio

n pr

oduc

ts/s

ervi

ces

or s

tart

ing

ofm

arke

ting;

ele

ctro

nic

bene

fit s

yste

ms;

new

line

s of

bus

ines

s, a

nd s

o on

.in

tran

et-

and

extr

anet

-bas

ed c

olla

bora

tion.

Ser

vice

s5

Ena

blin

g se

rvic

es.

Ele

ctro

nic

cata

logs

/dire

ctor

ies,

sm

art

1 (fo

r e-

com

mer

ce im

prov

emen

t st

rate

gic

agen

ts; e

-mon

ey,

smar

t ca

rd s

yste

ms;

inte

nt).

digi

tal a

uthe

ntic

atio

n se

rvic

es; d

igita

llib

rarie

s, c

opyr

ight

pro

tect

ion

serv

ices

;tr

affic

aud

iting

.

4S

ecur

e m

essa

ging

.E

DI,

e-m

ail,

elec

tron

ic f

unds

tra

nsfe

r (E

FT

).

Infr

astr

uctu

re3

Hyp

erm

edia

/mul

timed

iaW

orld

Wid

e W

eb w

ith J

ava.

obje

ct m

anag

emen

t.

2P

ublic

and

pri

vate

Inte

rnet

and

val

ue-a

dded

net

wor

ksco

mm

unic

atio

n ut

ilitie

s.(V

AN

s).

1W

ide

area

tel

ecom

mun

icat

ions

Gui

ded-

and

wire

less

-med

ia n

etw

orks

.in

fras

truc

ture

.


We coded overall task complexity of an e-commerce project as low (value of 0)when both the project’s business and technology complexity are judged to be low. Aproject’s task complexity has been coded as high (value of 1) when either its businesstask complexity, or its technology complexity, or both its business and technologycomplexity are judged to be high. This is to ensure that e-commerce projects that areprimarily infrastructural in nature and have no direct business component can becoded with high overall task complexity when their technology complexity is indeedhigh.

A summary of the frequency of announcements pertaining to the various codedvalues for the research variables is shown in Table 5. Announcement examples per-taining to the coding of the research variables are shown in the Appendix.

Results

THE E-COMMERCE PROJECT BEING SOURCED is the unit of analysis in this study.Spearman rank correlations indicate that there is no significant problem of multi-collinearity and all correlations are less than 0.5. Next, we tested the hypotheses us-ing the multinomial logit model provided by the Limdep 7.03 software. The generalspecification of the logit model is

( )= + ⋅0ln / ,ij j j jP P a b X

where Pij is the probability of the ith event occurring and P0j is the probability of the0th event occurring for the jth case. The 0th event is generally the base event withrespect to which we wish to calculate the odds ratio and is a choice made by theresearchers. In our case, we wish to estimate the likelihood ratios of the three gover-nance modes with the two independent variables as the predictors over two differentperiods. We also used firm size as a control variable, following prior IS research onoutsourcing [6]. Further, to check for robustness of results, we used two differentmeasures of firm size—natural logarithm of firm sales and firm assets at the end ofthe year prior to the announcement, based on data from Research Insight (i.e.,Compustat). Therefore, we created eight distinct logit models for the two base events

Table 4. Coding Examples for e-Commerce Project Task Complexity

Low business/technology High business/technologytask complexity task complexity

Automate existing processes Develop/modify online strategyLink existing processes Build “industry-first” applicationUse out-of-the-box functionality Build first-of-a-kind applicationsMaintain existing Web site Integrate multiple technology platformsUse EDI and other standards Navigate rapid technological changeUse proven e-commerce infrastructure Develop and create new infrastructure or

standards for e-business


Table 5. Frequency of Codes in the Sample for the Research Constructs

First Secondperiod period

E-commerce asset sourcing modeHierarchical governance 35 9

(37.23%) (19.15%)

Hybrid governance 22 8(23.41%) (17.02%)

Market governance 37 30(39.36%) (63.83%)

Total cases 94 47E-commerce project strategic intent

Improvement 16 12(17.02%) (25.53%)

Business impact 45 16(47.87%) (34.04%)

Commercial exploitation 33 19(35.11%) (40.43%)

Total cases 94 47E-commerce project task complexity

Low task complexity 54 30(57.45%) (63.83%)

High task complexity 40 17(42.55%) (36.17%)

Total cases 94 47

(markets and hierarchies), two firm-size measures (sales and assets), and two periods(growth and maturity). We first ran these models with only the control variable (firmsize) included. Then we included the two predictors in the model. Results of the eightmodels with predictors included as estimated by Limdep are presented in Tables 6and 7. Table 6 includes results for the first period (technology growth phase; 1999–2000) and Table 7 includes results for the second period (technology maturity phase;2001–2002).

The coefficients shown in the cells in Tables 6 and 7 provide estimates for theincrease (decrease) in the log likelihood ratio for the chosen sourcing mode over thebase sourcing mode. For example, a β coefficient of 1.33 for e-commerce projectstrategic intent (Table 6, model 1) means that a unit increase in e-commerce projectstrategic intent will increase the log likelihood of hybrid governance over hierarchi-cal governance by 1.33, implying that as strategic intent increases (i.e., becomes morebusiness focused), hybrid governance becomes a more likely governance choice.

As can be seen from Tables 6 and 7, the χ2 values for all the eight logit models aresignificant at 0.01 or better levels, indicating that the models are significant overall.Further, the firm size is not a significant predictor of the log likelihood ratios in sevenof eight logit models. It is weakly significant at the 0.10 level only in one model


Tabl

e 6.

Log

it R

egre

ssio

n R

esul

ts f

or th

e Fi

rst P

erio

d (T

echn

olog

y G

row

th P

hase

, 199

9–20

00)

Sour

cing

mod

e

Firm

siz

e m

easu

red

in f

irm

sal

esFi

rm s

ize

mea

sure

d in

firm

ass

ets

Mod

el 1

Mod

el 2

Mod

el 3

Mod

el 4

(with

ref

eren

ce to

(with

ref

eren

ce to

(with

ref

eren

ce to

(with

ref

eren

ce to

hier

arch

ical

gov

erna

nce)

mar

ket g

over

nanc

e)hi

erar

chic

al g

over

nanc

e)m

arke

t gov

erna

nce)

Inde

pend

ent

Hyb

rid

Mar

ket

Hie

rarc

hica

lH

ybri

dH

ybri

dM

arke

tH

iera

rchi

cal

Hyb

rid

vari

able

sgo

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

ce

Inte

rcep

t–3

.5**

–0.0

490.

049

–3.4

6**

–3.9

7***

–0.8

10.

81–3

.16*

*

(0.0

45)

(0.9

7)(0

.97)

(0.0

5)(0

.007

)(0

.49)

(0.4

9)(0

.03)

Log

(firm

siz

e)0.

400.

15–0

.15

0.25

0.51

*0.

34–0

.34

0.17

(0

.31)

(0.6

5)(0

.65)

(0.5

4)(0

.10)

(0.2

1)(0

.21)

(0.6

0)

Pro

ject

str

ateg

ic1.

33**

*–0

.07

0.07

1.40

***

1.33

***

–0.0

50.

051.

38**

*in

tent

(0

.008

)(0

.86)

(0.8

6)(0

.004

)(0

.008

)(0

.90)

(0.9

0)(0

.005

)

Pro

ject

tas

k–0

.53

–0.9

9*0.

99*

0.46

–0.4

8–0

.97*

0.97

*0.

48co

mpl

exity

(0.3

8)(0

.07)

(0.0

7)(0

.45)

(0.4

3)(0

.08)

(0.0

8)(0

.43)

N94

9494

94

Log

likel

ihoo

d–9

2.74

–92.

74–9

1.69

–91.

69

χ216

.57*

**16

.57*

**18

.68*

**18

.68*

**(0

.01)

(0.0

1)(0

.005

)(0

.005

)

Not

es:

p-va

lues

are

sho

wn

in p

aren

thes

es;

* is

sig

nifi

cant

at

0.10

; **

is

sign

ific

ant

at 0

.05;

***

is

sign

ific

ant

at 0

.01;

bol

dfac

e en

trie

s in

dica

te s

tatis

tical

ly s

igni

fica

nt v

alue

s.


Tabl

e 7.

Log

it R

egre

ssio

n R

esul

ts f

or th

e Se

cond

Per

iod

(Tec

hnol

ogy

Mat

urity

Pha

se, 2

001–

2002

)

Sour

cing

mod

es

Firm

siz

e m

easu

red

in f

irm

sal

esFi

rm s

ize

mea

sure

d in

firm

ass

ets

Mod

el 5

Mod

el 6

Mod

el 7

Mod

el 8

(with

ref

eren

ce to

(with

ref

eren

ce to

(with

ref

eren

ce to

(with

ref

eren

ce to

hier

arch

ical

gov

erna

nce)

mar

ket g

over

nanc

e)hi

erar

chic

al g

over

nanc

e)m

arke

t gov

erna

nce)

Inde

pend

ent

Hyb

rid

Mar

ket

Hie

rarc

hica

lH

ybri

dH

ybri

dM

arke

tH

iera

rchi

cal

Hyb

rid

vari

able

sgo

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

cego

vern

ance

gove

rnan

ce

Inte

rcep

t–4

.94

–3.0

23.

02–1

.92

–7.8

4*–2

.95

2.95

–4.8

9

(0.2

4)(0

.30)

(0.3

0)(0

.61)

(0.0

6)(0

.26)

(0.2

6)(0

.18)

Log

(fir

m s

ize)

0.68

1.07

–1.0

7–0

.39

1.41

1.08

–1.0

80.

33(0

.50)

(0.1

5)(0

.15)

(0.6

7)(0

.14)

(0.1

1)(0

.11)

(0.6

8)

Pro

ject

str

ateg

ic1.

100.

77–0

.77

0.32

0.10

0.74

–0.7

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(Table 6, model 3), indicating that firm size is not a significant predictor of e-com-merce project sourcing mode.

Further examination of the β coefficients and their p-values in Tables 6 and 7 indi-cates that all hypotheses except H3b are supported. We hypothesized that a high de-gree of strategic intent would lead to a preference for hybrid governance overhierarchical (H1a) and market (H1b) forms during the growth period. In this period,we also hypothesized that firms would be indifferent between hierarchical and mar-ket governance as far as strategic intent is concerned (H1c). The β coefficients inmodel 1 (growth period; sales as a measure of firm size; 0th event is hierarchicalgovernance) and model 3 (growth period; assets as a measure of firm size; 0th eventis hierarchical governance) for hybrid governance are positive and significant at the0.01 level, indicating that the likelihood of hybrid governance over hierarchical gov-ernance increases as strategic intent increases (i.e., becomes more business focused),providing strong support for H1a. Similarly, the β coefficients in models 2 and 4 forhybrid governance are positive and significant at the 0.01 level, indicating that thelikelihood of hybrid governance over market governance increases as strategic intentincreases in value (i.e., becomes more business focused), providing strong supportfor H1b. Further, market governance over hierarchical governance is not more likelywith respect to strategic intent during the first period (Table 6), as the β coefficientsfor market governance in both models 1 and 3 are not significant, supporting H1c.4

Coefficients for e-commerce project strategic intent for the second period (Table 7)provide support for H2. We hypothesized that e-commerce project strategic intentwould not have any influence in the choice of sourcing mode in the maturity phase.None of the coefficients for strategic intent in models 5 through 8 are significant,indicating that no particular governance mode is more likely than any other withrespect to strategic intent. Thus H2 is fully supported.

H3a through H3c deal with the effect of task complexity on the choice of sourcingmodes during the first period. During the growth period, we predicted a preferencefor hierarchies over markets (H3a) and hybrids (H3b). We also hypothesized indiffer-ence between hybrids and markets (H3c) as far as task complexity is concerned. Theβ coefficients for hierarchies over markets in models 2 and 4 for task complexity arepositive and significant at the 0.10 level, providing weak support for H3a. H3b is notsupported, as the β coefficients for hybrids over hierarchies in models 1 and 3 for taskcomplexity are statistically insignificant. The β coefficients for hybrids over marketsin models 2 and 4 for task complexity are statistically not significant, indicating thatH3c cannot be rejected. With respect to task complexity for the second period, wepredicted a preference for hierarchies over markets (H4a), a preference for hybridsover markets (H4b), and an indifference between hierarchies and hybrids (H4c). Re-sults support all these three hypotheses fully. The β coefficients for hierarchies overmarkets in models 6 and 8 for task complexity are positive and significant (0.05 level),providing support for H4a. Similarly, the β coefficients for hybrids over markets inmodels 6 and 8 for task complexity are positive and significant (0.01 level), providingstrong support for H4b. Finally, coefficients for hybrids over hierarchies in models 5and 7 with respect to task complexity are not significant, providing support for H4c.


The eight models shown in Tables 6 and 7 also show an improvement in the loglikelihood function and χ2 value over their respective control models (models withonly the appropriate firm-size measure included), indicating a better model fit result-ing from the inclusion of hypothesized predictors. The log likelihood value reflectsthe odds that the observed values of the dependent variable may be predicted from theobserved values of independent variables. The χ2 value is used to test the significanceof the logistic model, and a significant χ2 rejects the null hypothesis that none of theindependent variables are linearly related to the log odds of the dependent variable.Improvement in the χ2 values in models 1 through 8 over their respective controlmodels resulting from the inclusion of predictor variables also increases our confi-dence in the results. The final results are summarized in Table 8.

Discussion and Conclusions

THE AIM OF THIS PAPER WAS TO DISTINGUISH between the influence of drivers ofsourcing mode choice during the technology growth and maturity phases. Focusingon e-commerce projects, we identified two sourcing determinants—e-commerceproject strategic intent and e-commerce project task complexity—that have receivedscant attention in prior IT outsourcing research, and we performed a two-period analysisof sourcing modes. E-commerce projects were used because the growth and maturityphases could be easily identified. January 1, 2001, was used as the cutoff point be-tween the technology growth and maturity phases.

In addition to the conventional distinction between insourcing and outsourcing, weused a classification of sourcing modes that also included minority equity alliances, ahybrid governance form. This governance form combines characteristics found inhierarchical governance, such as managerial oversight, with characteristics commonlyassociated with market mechanisms, such as contractual obligations. The advantageof examining sourcing modes on a continuum of governance forms is that it helpsprovide a better understanding of the determinants of sourcing choices, as technolo-gies being sourced evolve on their product life cycles.

The hypotheses were tested by content-analyzing public announcements made bylarge firms during 1999–2002. These announcements were collected from the DowJones Interactive database and coded according to a scheme created for this research.We found 94 announcements during 1999–2000 and 47 during 2001–2002 that metour requirements and for which all information necessary for coding was available.Support for hypotheses was based on the significance of coefficients of the multino-mial logit regression models relating sourcing mode choice to the sourcing drivers.Magnitudes of the coefficients showed the extent to which changes in independentvariables increased the likelihood of a particular sourcing mode compared to the ref-erence.

We found, as hypothesized, that during the technology growth phase, firms aremore likely to use hybrid governance mechanisms for e-commerce projects whentheir strategic intent with regard to these projects is business focused. They do this not


Tabl

e 8.

Sum

mar

y of

Res

earc

h H

ypot

hese

s an

d F

indi

ngs

Inde

pend

ent v

aria

ble

Tim

e pe

riod

Hyp

othe

sis

Find

ings

E-c

omm

erce

pro

ject

str

ateg

ic in

tent

Firs

t per

iod—

H1a

: Hyb

rid g

over

nanc

e pr

efer

red

over

hie

rarc

hica

lS

uppo

rted

grow

th p

hase

gove

rnan

ce.

H1b

: Hyb

rid

gove

rnan

ce p

refe

rred

ove

r m

arke

tS

uppo

rted

gove

rnan

ce.

H1c

: Ind

iffer

ence

bet

wee

n hi

erar

chic

al a

nd m

arke

tS

uppo

rted

gove

rnan

ce.

Sec

ond

perio

d—H

2: N

o ef

fect

on

the

choi

ce o

f sou

rcin

g m

ode.

Sup

port

edm

atur

ity p

hase

E-c

omm

erce

pro

ject

task

com

plex

ityF

irst p

erio

d—H

3a: H

iera

rchi

cal g

over

nanc

e pr

efer

red

over

mar

ket

Wea

kly

grow

th p

hase

gove

rnan

ce.

supp

orte

dH

3b: H

iera

rchi

cal g

over

nanc

e pr

efer

red

over

hyb

rid

Not

sup

port

edgo

vern

ance

.H

3c: I

ndiff

eren

ce b

etw

een

hybr

id a

nd m

arke

tS

uppo

rted

go

vern

ance

.S

econ

d pe

riod—

H4a

: Hie

rarc

hica

l gov

erna

nce

pref

erre

d ov

er m

arke

tS

uppo

rted

mat

urity

pha

sego

vern

ance

.H

4b: H

ybri

d go

vern

ance

pre

ferr

ed o

ver

mar

ket

Sup

port

ed

gove

rnan

ce.

H4c

: Ind

iffer

ence

bet

wee

n hi

erar

chic

al a

nd h

ybri

d S

uppo

rted

gove

rnan

ce.


only to protect effectively their firm-specific tacit knowledge for gaining competitiveadvantage but also to gain access to the deep and broad knowledge about ITs thatvendors possess. We also found that strategic intent is not a determinant of sourcingdecisions during the technology/market maturity phase, because protecting firm-spe-cific knowledge is unnecessary during this late phase in the technology life cycle (allknowledge eventually leaks), and vendors would have developed superior capabili-ties with regard to the new technologies by this time as compared to client organiza-tions. All but one result is in line with our hypotheses.

E-commerce projects are one of the best examples of task complexity in modernbusinesses. Hierarchies are considered superior to markets in managing task com-plexity because of their superior information processing, communication, and coor-dination capabilities arising from shared identity, common language, and commonroutines. However, over time, hybrid governance forms may also develop communi-cation and coordination capabilities similar to those of hierarchies, due to repeatedties among alliance partners. We found that hierarchical sourcing modes are preferredover market-oriented mechanisms in both the technology growth and maturity phases.Hybrid sourcing modes are preferred over market-oriented mechanisms only in thetechnology maturity phase.

The research has some obvious limitations that point to directions for future re-search. Due to the general slowdown in the e-commerce industry during the technol-ogy maturity phase of our sample, our sample for the second period is only abouthalf the size of that for the first period. Further, our coding scheme for task complex-ity was based only on the task uncertainty dimension. Future research should look atthe other dimensions of task complexity as well. Finally, although we started with aclassification scheme that included two hybrid governance modes—joint venturesand minority equity alliances—our sample for the second period had no joint ven-tures, so the paper presents results using only minority equity as a hybrid governanceform. Future research should attempt to create a finer classification of sourcing modechoices including joint ventures, minority equity alliances, and other forms that en-able relational governance through information sharing, shared decision-making, orjoint action.

Overall, these results provide evidence that the maturity of IT assets and of theirmarkets has an influence on firms’ decisions pertaining to sourcing of those assets.Further, they suggest that research on e-commerce sourcing mode choice should in-clude variables other than those derived from TCE. As our results for strategic intentindicate, firms may choose to invest in developing e-commerce capabilities duringtechnology growth periods, even if these investments may be expensive in the shortterm, in order to derive business advantage in future periods.

We venture some reasons for the lack of support for H3b where no significant pref-erence for hierarchies over hybrid arrangements was found for the technology growthphase to manage project task complexity. The most likely reason is the low resolutionof a content-analytic classification scheme. A finer-grained scale, possibly from asurvey, is likely to bring out the preference for hierarchies over hybrid arrangementsto manage task complexity during the technology growth phase.


There are two key managerial implications of this research. First, managers shouldseriously consider their strategic intent for an e-commerce project while making sourc-ing decisions during periods when technologies and their markets are relatively im-mature. While vendors may offer a cheaper price due to their larger scale and scope,this study suggests that a better option will be to make an equity investment and forma minority equity alliance with a vendor for sourcing e-commerce projects with abusiness-focused strategic intent during the technology growth period. This invest-ment will allow managers to develop in-house e-commerce capabilities by drawingupon the expertise possessed by the vendors while protecting their firm-specific knowl-edge assets. However, when technologies and their markets mature, the rationale forinvesting in developing internal capabilities is diminished, because vendors, consult-ants, and professionals are able to provide their clients with industry “best practices”synthesized from their varied experiences with a number of clients on a number ofprojects. Second, managers should also consider the task complexity of their e-com-merce projects and choose a governance mode that is appropriate for managing thetask complexity involved in the project. During the earlier phases of technologygrowth, high levels of task complexity are best supported by hierarchical governance,but as technologies mature and firms consolidate, clients become increasingly likelyto have had prior relationships with service providers, leading to the formation oftrust that enables hybrid arrangements to be as effective as hierarchies in managingtask complexity.

Acknowledgments: The authors are grateful to Vladimir Zwass and three anonymous reviewers,whose comments on earlier drafts of this paper have significantly improved it. They thank LarrySanders for his encouragement. They gratefully acknowledge the support of the National Sci-ence Foundation for funding this research through grant number 9907325. Any opinions, find-ings, and conclusions or recommendations expressed in this research are those of the authorsand do not necessarily reflect the views of the National Science Foundation. This paper is basedin part on the second author’s dissertation research. The first two authors have contributedequally to this paper and their names are listed in a random order.

NOTES

1. Klepper [49] develops an analytical model and a number of propositions concerning theentry, exit, market structures, and product and process innovations from birth through maturityin technologically progressive industries. He posits that the number of firms in a technologicalindustry rises initially to attain a peak (or it attains a peak at the very beginning of the industry)and then declines over time despite continued growth in the industry. E-commerce technolo-gies and their markets show remarkably similar characteristics and patterns during the courseof their evolution.

2. For example, agile and extreme programming methods have only been recently intro-duced, and process models for these methods have yet to evolve based on empirical experience.

3. Limdep 7.0 is an econometric software program that provides capabilities for data analy-sis with qualitative dependent or independent variables.

4. β coefficients in the first column in model 2—hierarchical governance over market gov-ernance—are a mirror image (i.e., same values with opposite signs) of the second column inmodel 1—market governance over hierarchical governance. This is obviously expected, andthe redundant values are reported only for the sake of completeness of the tables. The same is


true in models 3 through 8. We will use only one of these two columns in our discussion fromthis point onward.

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App

endi

x: C

odin

g E

xam

ples

Var

iabl

e co

ded

asE

xam

ple

anno

unce

men

t

E-c

omm

erce

ass

et s

ourc

ing

mod

e

Hie

rarc

hica

l gov

erna

nce

UT

X J

uly

19,

2000

(in-h

ouse

dev

elop

men

t)C

laim

ing

to b

e th

e w

orld

’s f

irst

Inte

rnet

ele

vato

r co

mpa

ny,

Otis

.com

cur

rent

ly a

llow

s ar

chite

cts

and

build

ers

to s

peci

fy a

ndpr

ice

new

ele

vato

r sy

stem

s on

line.

Bui

ldin

g ow

ners

and

man

ager

s ca

n al

so o

btai

n de

taile

d da

ta a

bout

the

ir el

evat

ors’

perf

orm

ance

. Acc

ordi

ng t

o [c

ompa

ny e

xecu

tives

], O

tis.c

om’s

site

is d

evel

oped

in-h

ouse

usi

ng a

com

bina

tion

of d

iffer

ent

solu

tions

, na

mel

y its

con

tent

man

agem

ent

appl

icat

ion

by V

igne

tte a

nd e

-mai

l man

agem

ent

syst

em b

y eG

ain.

...

[Exe

cutiv

es]

also

adv

ise

that

Otis

.com

is e

ncou

ragi

ng o

nlin

e or

deri

ng w

ith it

s in

-hou

se d

evel

oped

too

ls. T

hese

incl

ude

Pla

nYo

ur P

roje

ct,

Pric

e Yo

ur P

roje

ct,

and

Trac

k Yo

ur P

roje

ct,

as w

ell a

s a

draw

ing

tool

cal

led

Exp

ress

Dra

w t

hat

allo

ws

arch

itect

sto

cre

ate

scal

able

dra

win

gs.

Hyb

rid

gove

rnan

ceE

MN

May

8,

2001

(min

ority

equ

ity p

artn

ersh

ip)

SA

QQ

AR

A(R

) S

yste

ms

Inc.

, a

lead

ing

prov

ider

of

prod

uct

cont

ent

softw

are

and

serv

ices

for

busi

ness

-to-

busi

ness

(B

2B)

e-co

mm

erce

, to

day

anno

unce

d th

at E

astm

an C

hem

ical

Com

pany

(N

YS

E: E

MN

) ha

s jo

ined

as

an in

vest

or. S

AQ

QA

RA

’sin

vest

ors

curr

ently

incl

ude

Cro

ss A

tlant

ic C

apita

l Par

tner

s, D

resd

ner

Kle

inw

ort

Cap

ital,

Edg

ewat

er F

unds

, G

E C

apita

l,Li

am V

entu

res

and

Vis

ion

Cap

ital.

Eas

tman

rec

ently

sel

ecte

d S

AQ

QA

RA

Com

mer

ce S

uite

to

tran

sfor

m it

s pr

oduc

tin

form

atio

n in

to d

iffer

entia

ting

e-co

mm

erce

ena

bled

cat

alog

s th

at w

ill in

crea

se it

s in

tern

atio

nal t

radi

ng p

artn

er b

ase

and

sale

s, w

hile

tim

e lo

wer

ing

cost

s. F

ollo

win

g its

sel

ectio

n of

SA

QQ

AR

A fo

r its

bus

ines

s ne

eds,

Eas

tman

ele

cted

to

furt

her

the

rela

tions

hip

by b

ecom

ing

an in

vest

or.

Mar

ket

gove

rnan

ceB

CR

May

22,

200

0(c

ontr

actu

al a

rran

gem

ent)

C.R

. Bar

d In

c. a

nnou

nced

tod

ay t

hat

it ha

s si

gned

a le

tter

of in

tent

with

eM

edE

xpre

ss,

an o

pera

ting

divi

sion

of

Ow

ens

&M

inor

(N

YS

E: O

MI)

, to

est

ablis

h e-

com

mer

ce a

nd e

nhan

ced

supp

ly c

hain

cap

abili

ties

for

C. R

. Bar

d, a

dev

elop

er,

man

ufac

ture

r, an

d m

arke

ter

of h

ealth

-car

e pr

oduc

ts a

nd s

ervi

ces.

Und

er t

he le

tter

of in

tent

, th

e go

als

of t

he in

itiat

ive

are

toes

tabl

ish

a st

ate-

of-t

he-a

rt,

cust

omer

res

pons

ive,

e-c

omm

erce

pre

senc

e fo

r B

ard,

and

to

cons

olid

ate

and

refin

e th

eco

mpa

ny’s

sup

ply

chai

n ca

pabi

litie

s. C

.R. B

ard

Inc.

and

eM

edE

xpre

ss p

lan

to u

se T

ime0

, a

busi

ness

uni

t of

Per

ot S

yste

ms

Cor

pora

tion

(NY

SE

: PE

R)

and

a di

gita

l mar

ketp

lace

par

tner

of

Ow

ens

& M

inor

, to

pro

vide

the

e-c

omm

erce

fra

mew

ork

and

syst

ems

arch

itect

ure

for

this

initi

ativ

e.


E-c

omm

erce

pro

ject

str

ateg

ic in

tent

Com

mer

cial

exp

loita

tion

KLT

Mar

ch 2

3, 2

000

bex.

com

, a

lead

ing

glob

al b

usin

ess-

to-b

usin

ess

Inte

rnet

tra

nsac

tion

infr

astr

uctu

re v

endo

r an

d de

velo

per

of e

-mar

ketp

lace

s,an

noun

ced

it w

ill jo

in w

ith U

.S. u

tiliti

es t

o pu

rsue

a b

usin

ess-

to-b

usin

ess

e-co

mm

erce

ver

tical

exc

hang

e fo

r th

e el

ectr

ical

indu

stry

wor

ldw

ide.

KLT

Inc

., a

who

lly o

wne

d su

bsid

iary

of

Kan

sas

City

Pow

er &

Lig

ht C

o. (

NY

SE

: KLT

), a

nd A

mer

en C

orp.

(NY

SE

: AE

E)

have

sig

ned

on a

s pa

rtne

rs in

the

dev

elop

men

t pr

ojec

t, w

hich

is e

xpec

ted

to g

o liv

e in

the

sec

ond

quar

ter

of20

00. “

Con

solid

ated

buy

ing

pow

er a

nd c

ompl

ete

end-

to-e

nd a

utom

ated

pro

cure

men

t pr

oces

sing

will

res

ult

in c

ost

savi

ngs

and

enha

nced

rev

enue

opp

ortu

nitie

s fo

r th

e tig

htly

reg

ulat

ed e

lect

ric u

tility

mar

ket.

The

bus

ines

s of

util

ities

will

shi

ft fr

om a

regi

onal

to

a gl

obal

focu

s.” “

Thi

s ve

ntur

e is

con

sist

ent

with

Kan

sas

City

Pow

er &

Lig

ht’s

str

ateg

y of

max

imiz

ing

shar

ehol

der

valu

e by

cap

turi

ng g

row

th o

ppor

tuni

ties

outs

ide

our

core

reg

ulat

ed u

tility

bus

ines

s,”

said

Gre

g O

rman

, pr

esid

ent

of K

LT I

nc.

“Thi

s ve

rtic

al e

xcha

nge

for

the

elec

tric

al u

tiliti

es in

dust

ry e

ffect

ivel

y br

ings

an

old

econ

omy

mar

ket

into

the

new

eco

nom

y.”

Bus

ines

s im

pact

TR

W J

une

18, 2

001

TR

W A

eron

autic

al S

yste

ms

has

laun

ched

its

e-B

usin

ess

Por

tal,

Aer

oVan

tixT

M. T

he p

orta

l lau

nch

is t

he r

esul

t of

am

ultim

illio

n do

llar

inve

stm

ent

by T

RW

Aer

onau

tical

Sys

tem

s, d

esig

ned

to m

ake

them

mor

e cu

stom

er r

espo

nsiv

e. “

We

liste

ned

and

talk

ed t

o m

any

com

pani

es in

the

indu

stry

, an

d th

en d

ecid

ed t

o m

ove

forw

ard

and

impl

emen

t a

fully

inte

grat

ed,

bene

fits-

deriv

ed s

olut

ion

that

sho

uld

sign

ifica

ntly

impr

ove

our

serv

ice

and

perf

orm

ance

to

all o

ur c

usto

mer

s,”

said

Ken

Mac

iver

, P

resi

dent

and

CE

O, T

RW

Aer

onau

tical

Sys

tem

s. “

e-B

usin

ess

fund

amen

tally

cha

nges

the

way

you

do

busi

ness

and

can

stre

amlin

e pr

oces

ses

if pr

oper

ly d

eplo

yed.

” A

eroV

antix

is t

he w

orld

’s f

irst

fully

fun

ctio

nal,

all-e

ncom

pass

ing

aero

spac

ee-

Bus

ines

s po

rtal

tha

t en

sure

s T

RW

Aer

onau

tical

Sys

tem

s’ c

usto

mer

s ha

ve 2

4x7

acce

ss t

o th

e co

mpa

ny a

nd it

s su

pply

base

. TR

W A

eron

autic

al S

yste

ms

sele

cted

Izo

dia

as t

he f

ound

ing

tech

nolo

gy p

artn

er in

Aug

ust

2000

afte

r a

rigor

ous

sele

ctio

n pr

oces

s in

volv

ing

mos

t of

the

lead

ing

indu

stry

pla

yers

.

IT im

prov

emen

tB

BY

May

22,

200

2V

alue

-add

ed n

etw

ork

serv

ices

fro

m G

E G

loba

l eX

chan

ge S

ervi

ces

(GX

S)

will

hel

p B

est

Buy

con

tinue

to

stre

amlin

ee-

busi

ness

pro

cess

es a

nd r

educ

e su

pply

cha

in c

osts

. GX

S w

ill b

e pr

ovid

ing

the

follo

win

g se

rvic

es t

o B

est

Buy

:•

trans

actio

n pr

oces

sing

—fo

r th

e ex

chan

ge o

f bu

sine

ss d

ocum

ents

in s

tand

ardi

zed

elec

tron

ic d

ata

inte

rcha

nge

(ED

I)fo

rmat

;•

clie

nt im

plem

enta

tion

serv

ices

—to

hel

p B

est

Buy

suc

cess

fully

impl

emen

t el

ectr

onic

doc

umen

t ex

chan

ge w

ith in

divi

dual

tradi

ng c

omm

unity

mem

bers

;•

elec

tron

ic d

ocum

ent

com

mun

icat

ions

mon

itori

ng a

nd m

anag

emen

t—fo

r 24

-hou

r m

issi

on-c

ritic

al d

ata

tran

smis

sion

betw

een

Bes

t B

uy a

nd it

s tr

adin

g pa

rtne

rs.


Var

iabl

e co

ded

asE

xam

ple

anno

unce

men

t

E-c

omm

erce

pro

ject

task

com

plex

ity

Low

Xer

ox J

anua

ry 1

7, 2

001

To c

omm

unic

ate

mor

e co

nsis

tent

ly a

nd e

ffect

ivel

y w

ith c

usto

mer

s ar

ound

the

wor

ld,

Xer

ox C

orpo

ratio

n (N

YS

E: X

RX

) ha

sre

desi

gned

its

corp

orat

e W

eb s

ite a

nd in

fras

truc

ture

to

serv

e m

ore

coun

trie

s an

d to

offe

r m

ore

onlin

e fe

atur

es,

cust

omiz

able

serv

ices

, an

d sp

eed.

The

glo

bal s

ite..

. inc

reas

es t

he s

ite’s

spe

ed,

flexi

bilit

y, a

nd r

elia

bilit

y. I

t al

so m

akes

it e

asie

r fo

r th

exe

rox.

com

tea

m t

o m

anag

e an

d up

date

pag

es fo

r ea

ch c

ount

ry n

ow s

erve

d. T

he s

ite w

ill r

ecog

nize

whe

n an

Arg

entin

ecu

stom

er,

for

inst

ance

, co

mes

to

ww

w.x

erox

.com

. It

will

the

n di

spla

y al

l Web

pag

es in

Spa

nish

, w

ith u

p-to

-dat

e pr

icin

g in

loca

l cur

renc

y.

Hig

hA

XP

Aug

ust

3, 2

000

Am

eric

an E

xpre

ss C

o. (

NY

SE

: AX

P)

and

Ven

tro

Cor

p. (

NY

SE

: VN

TR

) pl

an t

o fo

rm a

new

com

pany

, M

arke

tMile

LLC

, to

bui

ldan

d op

erat

e an

Int

erne

t-ba

sed

mar

ketp

lace

aim

ed a

t st

ream

linin

g th

e w

ay c

orpo

ratio

ns b

uy e

very

day

busi

ness

pro

duct

s an

dse

rvic

es. A

s fo

r M

arke

tMile

, [a

naly

sts]

say

tha

t A

mE

x m

ust

prov

e to

bus

ines

ses

that

it h

as t

he t

echn

ical

sav

vy,

whi

le V

entr

ow

ill h

ave

to s

how

it is

fin

anci

ally

sta

ble.

Am

eric

an E

xpre

ss is

anc

horin

g M

arke

tMile

to

the

appr

oxim

atel

y 30

,000

mid

size

com

pani

es t

hat

now

use

its

corp

orat

e pu

rcha

sing

car

d. D

urin

g a

pilo

t ea

rlie

r th

is y

ear,

Am

ex fo

und

it la

cked

the

ski

lls n

eede

dto

run

an

e-m

arke

tpla

ce,

so it

beg

an lo

okin

g fo

r a

new

par

tner

. “[M

arke

tMile

] is

a c

ontin

uatio

n of

our

Com

mer

ce N

etw

ork

stra

tegy

, on

ly it

is k

ind

of s

uper

char

ged

by w

orki

ng w

ith V

entr

o an

d cr

eatin

g ou

r ow

n co

mpa

ny,”

said

[A

mE

x ex

ecut

ives

].

determinants of sourcing during technology growth and maturity: an empirical study of e-commerce...

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