NEBIC: A Dynamic Capabilities Theory for Assessing Net-Enablement

NEBIC: A Dynamic Capabilities Theory for Assessing Net-Enablement Bradley C. Wheeler Kelley School of Business, Indiana University, 1309 East 10th Street, Bloomington, Indiana 47405 [email protected]

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e propose the Net-Enabled Business Innovation Cycle (NEBIC) as an applied dynamic capabilities theory for measuring, predicting, and understanding a firm’s ability to create customer value through the business use of digital networks. The theory incorporates both a variance and process view of net-enabled business innovation. It identifies four sequenced constructs: Choosing new IT, Matching Economic Opportunities with technology, Executing Business Innovation for Growth, and Assessing Customer Value, along with the processes and events that interrelate them as a cycle. The sequence of these theorized relationships for net-enablement (NE)1 asserts that choosing IT precedes rather than aligns with corporate strategy. The theory offers a logically consistent and falsifiable basis for grounding research programs on metrics of net-enabled business innovation. (Theory Building; IS Research Frameworks; Net-Enabled Organizations (NEOs); Innovation; Digital Business; e-Commerce; e-Business)

1. Introduction The emergence of pervasive digital networks—especially the public Internet—has created business opportunities in both established and emerging sectors of the economy. Firms that have embraced these digital networks—net-enabled organizations (Straub and Watson 2001)—can execute transactions, rapidly exchange information, and innovate through new business processes at an unprecedented pace (Weill and Vitale 2001). Net-enabled organizations (NEOs) have new channels for accessing customers, real-time integration with supply chain partners, new efficiencies in internal operations, and offer new digital products or services. These net-enabled business innovations, which are the first step in an organizationwide process of netenablement (NE), require timely and ongoing reconfiguration of firm resources. Opportunities for net-enablement are also creating a 1

NE will stand for either net-enablement or net-enabled, depending on the grammatical context.

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strategic and tactical quagmire for many firms. They struggle to assimilate the rapid pace of innovation in information technologies (IT) and the emerging business practices they make possible. It is in this context that business leaders must often make defensive and offensive strategic investments in new net-enabled business practices before credible measurement of prior investments can be ascertained (Sambamurthy 2000, Sambamurthy et al. 2000). On face value, some firms seem to be better at managing and executing NE business innovation than other firms. Some firms with outstanding brands in the physical world have net-enabled their products and services to the delight of their customers, while other great brands have suffered from tardy and dismal efforts at net-enablement. Our research question asks, are there measurable, organizational capabilities that comprise the ongoing work of net-enablement? If so, what are these capabilities? Do these capabilities distinguish successful NEOs from less successful organizations? Information Systems Research,
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There is a clear need for a theoretically rigorous and practically relevant framework for understanding netenablement, the innovative actions that create and recreate it through IT evolution, and the metrics for assessing its effects. Benbasat and Weber (1996) have argued that the information systems discipline has “a responsibility to build our own theories to account for those phenomena that differentiate our discipline” (p. 398) while at the same time providing a basis for working together. We engage this challenge by proposing the Net-Enabled Business Innovation Cycle (NEBIC) as an applied dynamic capability theory for net-enablement. It is a holistic theory that encompasses a full range of organizational actions from recognizing emerging IT to measuring the customer value created through network enablement in the marketplace.2 As a theory, it integrates and builds upon prior academic research to propose specific constructs, relationships among those constructs, propositions, and a research agenda for theory-driven measurement of digital net-enabled innovation. Further, we assert that in the dynamic capability of net-enablement, a deep and dynamic understanding of new IT developments must precede the formulation of business strategy rather than simply configuring IT to align with strategy. The next section outlines the definitions and objectives of the NEBIC theory. This is followed by a review of relevant literature. Section 4 explains the NEBIC theory, and §5 outlines a research agenda. We conclude by addressing implications for business practice.

2. Definitions and Assumptions 2.1. Net-Enablement Many scholars have set forth useful definitions of e-business or e-commerce (Barrett and Konsynski 1982, Kalakota et al. 1999, Rayport and Jaworski 2001). Storey et al. (2000) define it as activities that directly support commerce by means of electronic (networked) 2

This theoretical formulation is in the tradition of IS stage models such as Nolan’s (1973) model of IS growth. In that NEBIC is a testable stage theory, it can be studied to see if it fares better empirically than the Nolan model (Weill et al. 1991, King and Kraemer 1984).

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solutions. Because the clever and timely use of digital networks for economic purposes is the heart of ebusiness, we will focus on the larger concepts of digital network enablement and the capabilities of NEOs that facilitate harnessing this potential. NEOs employ innovative uses of digital networks to reduce barriers of time and distance, substitute information for physical processes, and engage in innovation that aligns the firm to its competitive environment. The need for net-enablement (and the development of NEOs) is most visible in hypercompetitive environments. Hypercompetitive industries are characterized by rapid changes in technology, relative ease of entry and exit by rivals, ambiguous consumer demands, and fleeting periods of competitive advantage (Bogner and Barr 2000). Others refer to similar market dynamism as “high velocity markets” where successful business models and industry structure are unclear (Eisenhardt and Martin 2000). These competitive conditions fuel a demand for innovation and speed while digital networks offer both speed and an opportunity for innovating (Sambamurthy et al. 2001). Both require firms to develop reliable capabilities for continual IT innovation for competitive necessity and to exploit shortterm competitive advantage. The utility of net-enablement is also applicable in nonhypercompetitive environments. Even mature industries where competitive advantage may still flow from industry position or ownership of unique resources are subject to opportunities, new efficiencies, or even competitive threats posed by digital networks. Net-enablement can provide new growth opportunities or establish defensive positions with customers and suppliers. Firms can preemptively become NEOs even though they do not currently experience the pace of competitive change in hypercompetitive environments. Alternatively, they may use a series of netenabled innovations to erode the existing basis of longterm competitive advantage while they reap a series of imitable, short-term gains. The dominant business configuration for NEOs is a network, web, or hub connected via IT. Suppliers, customers, complementors, and alliance partners engage in “coopetition” as they collaborate via alliances and compete via coalitions (Brandenburger and Stuart 1996, Moore 1996, Singh and Mitchell 1996, Afuah 2000). As firms become net-enabled, their competitive Information Systems Research Vol. 13, No. 2, June 2002

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advantage may rest on tacit, inimitable collaborative relationships as a network or hub with its coopetitors. These coopetitors provide a critical source of innovations (Allen 1977, von Hippel 1988, Ahujah 1996), knowledge transfer (Kogut 1988), complementary products (Grove 1996), and critical resources (Bower 1970) for collectively garnering competitive advantage as a network of resources or complementary competencies. We believe that participation in these network relationships provides greater potential to lead in netenabled business innovation. 2.2. Objectives of Net-Enablement There is reasonable evidence to believe that unabated technical innovation will continue to create greater capabilities in digital networks, computer hardware, and software for the foreseeable future. These disruptive technological forces are now understood as the normal state of the external technical environment rather than as an anomalous and transitory disruption. These technological forces, and the new business processes that they enable, are reshaping industries beyond any specific net-enabling initiative (e.g., the Internet-based sales channels), technology (e.g., ERP, Enterprise Resource Planning, software), or business practice (e.g., online auctions). Many objectives for NE initiatives are possible, but we contend that the dependent variable of primary interest is customer value. In Management, Drucker (1974, p. 79) states that “To satisfy the customer is the mission and purpose of every business,” and NE provides an additional venue to address this foundational principle. We will use the term value proposition to refer to the bundle of attributes that comprise a complete product or service offering (Keeney 1999). They may include the product or service itself, the channel(s) through which it is delivered, pricing, the brand(s) associated with the offer, and the postsale interactions via support or warranty. Value propositions are created through a configuration of a firm’s resources. The marketplace assigns rewards to a firm’s value propositions as customers vote with their purchases to signal if actual customer value is being created (Woodruff 1997). The second objective is to build sustainable capabilities for turning the IT that furthers net-enablement into customer value in a consistent and reliable way. There is Information Systems Research Vol. 13, No. 2, June 2002

a need to identify and understand the organizationallevel routines that drive NE business innovation towards the creation of customer value. The following section overviews the foundational literature for the formulation of the Net-Enabled Business Innovation Cycle (NEBIC) theory.

3. Foundational Literature The strategic management literature has long addressed how firms adapt to their external environment towards profitable competitive advantage.3 In particular, the Dynamic Capabilities Perspective provides a foundation for further research on net-enablement. 3.1. Dynamic Capabilities Perspective As digital networks provide business processes with enormous capabilities for speed, strategy is fast becoming a dynamic process of recreating and executing innovation options to gain and sustain competitive advantage (Teece et al. 1997). The essence of this process is captured by the Dynamic Capabilities Perspective (DCP). DCP refers to the ability of a firm to achieve new forms of competitive advantage by renewing competences—organizational resources—to achieve congruence with the changing business environment (Teece et al. 1997, Eisenhardt and Martin 2000). This capability is dynamic because the firm must continually build, adapt, and reconfigure internal and external competences to achieve congruence with the changing business environment when time-to-market and product timing are critical, the rate of technological change is rapid, and the nature of future competition and markets are difficult to determine (Teece et al. 1997). More narrowly, dynamic capabilities can be defined as [firm] processes that use resources—specifically the processes to integrate, reconfigure, gain, and release resources—to match and even create market change . . . [T]hey are organizational routines through which firms achieve new resource configurations (Eisenhardt and Martin 2000, p. 1107).

Examples of dynamic capabilities in the literature 3

Appendix A summarizes alternative views of competitive advantage and fitting the firm to its competitive environment.

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include product development routines, alliancing routines, exit routines, and knowledge management routines (Eisenhardt and Martin 2000). Dynamic capabilities are not in themselves a source of long-term competitive advantage. They are a means to achieving resource configurations that provide advantage, though possibly short term, in the marketplace based on Schumpeterian rents as market opportunities emerge, collide, evolve, and die. Dynamic capabilities are imitable, can be developed through multiple learning paths, and have commonalities across firms and industries. The development of dynamic capabilities reflects management’s ability: (1) to demonstrate timely responsiveness and rapid innovation and (2) to effectively coordinate and redeploy internal and external resources or competencies based on managerial and organizational processes, market positions, and path dependencies (Teece et al. 1997, Leonard-Barton 1992). Dynamic capabilities create resource configurations that generate value-creating strategies. Their advantage lies in applying them sooner, more astutely, or more fortuitously than rivals (Eisenhardt and Martin 2000). The nature of dynamic capabilities, however, varies with market dynamism. In moderately dynamic markets these capabilities resemble organizational routines that rely on existing knowledge and linear execution to produce predictable outcomes. In highvelocity markets, they resemble simple, experiential, and unstable processes that produce adaptive but unpredictable outcomes. In both high-velocity and traditional markets, knowledge- and learning-based mechanisms guide the evolution of dynamic capabilities and underlie path dependence in acquiring, reconfiguring, and integrating resources. Finally, dynamic capabilities can be viewed as combinations of “simpler capabilities” and their related routines. In these combinations, “sequence steps” imply a temporal order for developing these simpler capabilities or for their interaction in practice (Brown and Eisenhardt 1997). Consistent with DCP, we contend that net-enablement is a dynamic capability. NEOs continually reconfigure their internal and external resources to employ digital networks to exploit business opportunities. Thus,

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NEOs exemplify the characteristics of dynamic capabilities as they engage routines, prior and emergent knowledge, analytic processes, and simple rules to turn IT into customer value (Clark et al. 1997, Bharadwaj et al. 2000, Sambamurthy et al. 2001). 3.2.

Assimilation, Adoption, and Absorptive Capacity The organizational routines associated with introducing new technology in organizations have a rich history, and Roger’s (1962) diffusion of innovation model has played an important role in shaping research on IT adoption. At the organizational level, assimilation describes the organizational routines stretching from an initial awareness of an innovation to its possible formal adoption as a full-scale deployment in an organization (Fichman 1992, 2000; Fichman and Kemerer 1999). Organizations continuously assimilate and adopt new technologies. However, not all adoption efforts are successful. Firms can err by adopting too few innovations or too many, adopting innovations that do not contribute to competitive advantage, adopting the right innovations with poor timing (leading to consequent failures), or they may simply fail in implementing those innovations (Fichman 2000). Net-enablement, as a dynamic capability, invokes the organizational routines of assimilation and adoption. The firm’s ability to assimilate and adopt new IT may be limited by its absorptive capacity—prior related knowledge that confers an ability to recognize external emerging opportunities (Cohen and Levinthal 1990). A lack of absorptive capacity may hinder a firm’s ability to recognize and begin assimilating new technologies or cause overdependence on its own innovations that may not be keeping pace with changes in the external environment. Low absorptive capacity may limit investment in strategic options that have path dependencies. In moderately dynamic markets, absorptive capacity, experience, and routines regarding IT assimilation are essential for evolving net-enablement as a dynamic capability. In high-velocity markets; however, prior knowledge may be less valuable. Assimilation routines for net-enablement in high-velocity markets rely much more on real-time knowledge creation or simple rules Information Systems Research Vol. 13, No. 2, June 2002

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(Eisenhardt and Martin 2000, Fichman 2000). Alternatively, some companies relied on other strong dynamic capabilities in making acquisitions, alliances, or joint ventures to access emerging IT knowledge that they may not be able to quickly assimilate on their own. 3.3. Literature Summary Recent perspectives on strategy argue that the basis for achieving competitive advantage, even short-term advantage, lies in the configuration of resources that enable value creation. Dynamic capabilities are the means through which managers continually achieve these resource configurations that match, or even create, marketplace change. The persistent evolution of IT presents an ever-changing stimulus that may increase or erode the potential value of a firm’s resource configurations. In responding to this stimulus, NEOs develop net-enablement as a dynamic capability. Routines in net-enablement can generate a portfolio of NE initiatives as strategic options (Sambamurthy et al. 2001) that can be exercised to gain periods of competitive advantage, industry position, and to extract Schumpeterian rents. Well-researched routines in the assimilation and adoption of IT contribute to NE though the utility of prior knowledge may vary with the pace of market change. 3.4. Need for Applied Theory DCP asserts that identifying specific routines in terms of their functional relationship to resource manipulation provides for empirical falsification (Eisenhardt and Martin 2000, p. 1108). Thus, a detailed explication of NE as a dynamic capability can provide a sound basis for IS research. Just as Adaptive Structuration Theory (DeSanctis and Poole 1994) is an applied version of the molar theory of Structuration4 (Giddens 1979) or the Technology Acceptance Model (Davis 1989) is an applied version of the Theory of Reasoned Action (Fishbein and Ajzen 1975), there is a need for an applied theory—at a meso- or lower level of mediation—to guide empirical research on netenablement.

In the next section, we provide an explication of the NEBIC as an applied dynamic capabilities theory. NEBIC provides a basis for research on net-enablement as a specific dynamic capability.

4. Net-Enabled Business Innovation Cycle Theory Theory building is an essential part of the research process (Van de Ven 1989, see Huber 1990 for an IT example). The purpose of a theory is to impose order on unordered experiences and observations to increase human understanding and prediction in the real world. In the positivist research tradition, theories provide the essential guidance for determining what data need to be collected when studying or developing a new conceptualization of phenomena (Forrester 1961). In the interpretivist tradition, theories may evolve as the product from a series of case studies (Eisenhardt 1989). In critiquing the competencies/capabilities literature, Williamson (1999) asserts that “sooner or later, a would-be theory must be asked to show its hand. . . there is a need to sort the wheat from the chaff. Predictions, data, and empirical tests provide the requisite screen” (p. 1093). While the term theory has been applied to a variety of academic ideas, not all ideas, models, perspectives, or frameworks constitute a theory. In Theory Building, Dubin (1978) asseverates that the specific purpose of a theory is to generate testable hypotheses—a theory that is not subject to empirical testing remains in the realm of speculation (p. 12). Thus, as an applied theory, NEBIC attempts to articulate netenablement as an empirically testable dynamic capability. It sets forth specific metrics such as constructs, relationships, and predictions for empirical testing. See Appendix B to review the tenets of theory construction. 4.1. Overview of NEBIC The main thesis of the NEBIC asserts that

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The term molar refers to causal laws stated in terms of large and often complex objects. Mediation at micro levels refers to the specification of causal connections at a level of smaller particles that make up the molar objects, and on a finer time scale (Cook and Campbell 1979, pp. 32–36).

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Emerging/Enabling Technologies (ET ) lead to Economic Opportunities (EO). Selected opportunities can enable growth through Business Innovation (BI ) for the purpose of creating Customer Value (CV ).

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This thesis is depicted in Figure 1 along with the axes of time and value. Each element of the theory is explained in turn throughout §4. A brief illustration of the thesis in action is provided in Appendix C. Dubin (1978) advocates that theory builders facilitate understanding of a theory by sharing the logic employed in its construction. The logic of the NEBIC is built upon several foundational assumptions that represent our subjective understanding of how organizations create value via net-enabled business practices. (1) Net-enabled business innovation is an organizational-level phenomenon that involves a reconfiguration of a firm’s resources. (2) Both the variance and process theory perspectives are needed to capture the organizational complexity of NE activities. (3) Time must be explicitly addressed to understand the recursive nature of NE routines and sequences. (4) Emerging IT represents the leading edge of NE business innovation. All NE business innovations originate with and are made possible via IT.5 (5) There are at least four distinct organizational capabilities that enable the selection and transformation of IT into customer value. (6) These four key capabilities are brought to bear on a net-enabled business opportunity in a consistent, sequenced order. (7) Each new IT begins a new cascade for potentially applying the four capabilities. (8) The time required for each NE business innovation to interact with each capability ranges from very short to very long. (9) Activities conducted inside the organization (and its virtual supply chain) contribute to value potential. Customer responses to offers or value propositions made in the marketplace are measured as value realized. (10) There are formal and informal communication

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Some views would suggest that Assumption 4 overstates the role of IT in net-enabled innovation. For example, switching to a new direct sales channel or gaining a critical mass of industry participation in a B2B marketplace are e-business innovations that are largely business rather than technology achievements. Our view, however, is that these efforts would not have been conceivable without the enabling potential of pervasive digital networks, hardware, and software.

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routines and events that interact among the capabilities to evolve and refresh net-enablement as a dynamic capability. (11) As a dynamic capability, NE involves processing multiple, concurrent innovations through an organization at any given point in time. (12) Improvements in the net-enablement dynamic capability occur via human action that is triggered by organizational learning though feed-backward and feed-forward communication. The following sections define the theory’s units of study, relationships, boundaries, and propositions. The NEBIC uses elements of both variance and process theory. It is a hybrid, Type 1 theory in the Shaw and Jarvenpaa (1997, p. 74) taxonomy. As a hybrid, it is comprised of specific variables and events, temporal relationships among variables, sequences of events, and predictions in the form of probabilistic outcomes. Empirical indicators and research approaches for hypotheses development are found in §5. 4.2. Units of Study Each of NEBIC’s four theorized constructs is viewed as a “simple capability” (Eisenhardt and Martin 2000, p. 1116). These constructs were developed from the reviewed literature, observation, and through many discussions with practitioners. As introduced in the thesis statement, each capability is expressed as a verb (e.g., choosing) and an object (e.g., IT). These four simple capabilities combine along with their routines and sequenced steps to form the dynamic capability of netenablement. 4.2.1. Choosing Emerging/Enabling Information Technologies. The first construct is the activity of Choosing Emerging and Enabling IT (ET). New IT is of two types—emerging or enabling technologies. Emerging technologies are the technologies that are still in a development lab. They are beyond the proof-ofconcept stage, but they are not yet commercially viable. Enabling technologies have already become commercially available and are becoming pervasive in an industry, target customer segment, or region of the world. For example, the Internet was an emerging technology until the early 1990s. Arguably, the release of the Information Systems Research Vol. 13, No. 2, June 2002

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Figure 1

Net-Enabled Business Innovation Cycle

graphical Web browser fueled personal and corporate interest in the Internet to the point that it became an enabling technology by 1995 (in many parts of the world). Not all emerging technologies mature to the point of becoming pervasive enabling technology. For example, firms that chose to invest in push technology (Wired 1997) were largely disappointed with the technology’s reliability. It never matured into a pervasive, enabling IT. In 2001, scent generators (the ability to convey fragrance via a digital network) were emerging lab technologies promoted by companies such as DigiScents. It is unclear when, or if, scent generators will ever become a pervasive enabling technology as part of home appliances (e.g., PCs, high-definition televisions, refrigerators, etc.). The inputs to the Choosing capability include the Information Systems Research Vol. 13, No. 2, June 2002

world of seemingly relevant and irrelevant developments in IT, standards, IT vendor market power, costs, and broad cultural attitudes towards technology. The Choosing capability involves routines for identifying, assessing, filtering, and reaching conclusions regarding the timing and viability of ET. It is the wise vetting of these inputs that signal timely recognition of relevant ET for a particular firm as an ET that is high potential for one firm or industry may be a meaningless distraction for another. NEBIC capabilities can be viewed as strong or weak, and they may exist in various parts of an organization. A strong Choosing capability is indicated by a timely and well-vetted flow of ET choices to the Matching capability (described below). Choosing—or failing to choose—a particular ET gives little real insight into the

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strength of the ET capability. Rather, it is the consistency in a pattern of choices over time that gives a clear signal. As depicted in Figure 1, the Choosing ET construct is represented as low on the potential value vertical axis. The reason is that even a strong capability in choosing ET cannot be directly translated into customer value. As described in §4.3 below, ET is an antecedent to other NEBIC constructs that collectively act to transform ET into customer value. This differs from the view that IT choice strictly follows from or aligns with the formulation of business strategy. Finally, the Choosing ET capability is often, though not always, the responsibility of the IT area of an organization. Some chief information or chief technology officers create a specific emerging technologies group in their departments while other companies diffuse this responsibility to line-of-business units. 4.2.2. Matching Economic Opportunities with ET. The second NEBIC construct addresses an organization’s capability to effectively see how ET Match to the Economic Opportunities (EO) that ET create or reveal. ET and business opportunities can combine to spur NE innovations to serve customers (Afuah 1998).6 ET often have unforeseen potential to enhance a firm’s value propositions, position in the industry, or to even create or redefine an industry. In recent years, examples of NE business innovations have included real-time personalization with direct connections to customers, online self-service, reconfigurations of supply chains via electronic exchanges, and location-based mobile commerce systems for handheld devices. ET often creates new sales, service, and profit opportunities that remain hidden until entrepreneurial efforts bring them to market. Industry incumbents are often blind to these new ET-induced opportunities (Christensen 1997, Moore 2000). The creation of new companies and brands such as Yahoo, eBay, and Priceline attest to the challenges that incumbents face in identifying and seizing new opportunities in hypercompetitive environments. The inputs to the Matching capability include the carefully vetted technologies from the Choosing capability, current business strategy, and environmental 6

Matching is not precisely a “fit” construct.

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scanning to identify shifting customer or business trends. The essence of the Matching capability is to distill these inputs into strategic options and tactical business changes that enable timely value propositions— not too early or too late—to the marketplace. As the matching capability reveals new ET-induced economic opportunities, not all of these will be of interest to a company. Matching also incorporates selection routines to pursue those identified economic opportunities that may create strategic options with path dependencies or that have other obvious business value (e.g., cost reduction, increased customer satisfaction, etc.). The portfolio of strategic options that a company develops increases its improvisational possibilities for net-enablement. This is consistent with Porter (1996), that the process of innovation cannot be separated from a firm’s strategic and competitive context. As a dynamic capability, the Matching capability invokes continual dialogue and sense-making routines to achieve new resource configurations that fit developing economic opportunities. In hypercompetitive environments, organizations continually need to refocus their business. Yet new opportunities do not present themselves cohesively or in a systematic order. Therefore, if the Choosing ET capability is weak, it cannot effectively prescribe the strategic choices available to firms in volatile environments. The Matching capability, then, cannot effectively see the full range of real economic possibilities. This results in strategic direction and tactical initiatives being selected from an incomplete set. The Matching capability also factors in the firm’s willingness to take risks. Because the acceptability of emerging technologies and new business practices in the marketplace is unknown, lead time is required for product development, sales and supply channel configuration, marketing, etc. Business initiatives selected during the matching process require commitments of capital, and more importantly, irrecoverable allocations of scarce time, talent, and management attention for execution (Moore 2000). These risks may also involve timing of invoking exit routines regarding existing resource configurations (e.g., a direct sales force or an expensive toll-free call support center) to pursue new opportunities. Information Systems Research Vol. 13, No. 2, June 2002

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For some opportunities, speed is of the essence as disproportionate market share and rewards flow to early innovators, or hypercompetition provides only short periods of advantage. For example, early movers that garner a critical mass of buyers and sellers in a B2B exchange will have erected substantial barriers to entry for late followers who wish to create a competing exchange. Thus, the Matching capability incorporates competitive agility (Christensen 1997, Venkatraman and Henderson 1998, Byrnes and Judge 1999, Sambamurthy et al. 2001) to quickly and effectively sense ET, or to sense discontinuities in incrementally growing product-market spaces. The Matching capability is depicted as higher in potential value in Figure 1 than Choosing ET. A firm that is able to effectively utilize both of these capabilities is closer to taking an NE offer to market than a firm with only the Choosing capability. Relationships among the capabilities are further developed in §4.3. 4.2.3. Executing Business Innovation for Growth. The third NEBIC construct, Executing Business Innovation (BI) for Growth, focuses on an organization’s capability to reconfigure its products, services, sales channels, supply chain, etc. in a timely manner, or more simply, its ability to get the change done. Some IT-induced changes, such as adoption of PCs or e-mail, are competitive necessities for industry participation and have no implications for real value growth or competitive advantage. Executing these types of changes, though challenging, is the daily work of organizational participants. In contrast, the Executing BI construct describes the capability to be an industry leader in seizing growth opportunities via net-enablement. Executing routines exemplify taking NE initiatives from concept to a value proposition in the marketplace with expedience, and they are especially critical in high-velocity markets where competitive advantage periods are relatively short. The period of advantage may be understood as a learning lag as rivals discover how to imitate the resource configurations, particularly the components involving digital networks, or wrestle with the cost of resource reconfiguration (some firms enjoy cost advantages in their technology change routines). Therefore, a combination of choosing, matching, and getting to market through rapid execution, along with any competencies imbuing cost advantages, can Information Systems Research Vol. 13, No. 2, June 2002

be very helpful in exploiting periods of short-term advantage. Executing assumes that an organization has vetted technologies as inputs, matched them with economic opportunities, selected strategic options for execution, and committed to reconfiguring its organizational resources. The capability is comprised of routines for project management, employee education, and a culture that embraces rapid change. Some best practices have emerged in rigidly scoping NE initiatives into 90day projects where the scope may be trimmed if problems arise, but the new value proposition is still taken to market in 90 days. Execution is a sequenced step with antecedents, as failures in the Choosing and Matching capabilities may allow execution routines to reconfigure resources without strategic guidance. Similarly, execution may require overcoming significant internal obstacles as NE initiatives require reconfiguring a firm’s resources. These obstacles may include political resistance, turf battles among functional areas, supplier or sales channel dissension, etc. The Executing capability reconfigures, integrates, acquires, or divests the organization’s resources to align with the new initiatives. This realignment is evidenced via new value propositions in the marketplace. Some organizations have cultivated an excellent Execution capability for net-enablement. Amazon.com demonstrated this by leveraging their brand and customer relationships beyond books to quickly create zShops (storefronts for others) and consumer-toconsumer auctions. Other firms have severely struggled with executing NE business innovations (e.g., Xerox, Boo.com). In Figure 1, the Executing capability represents the highest level of value potential, as it is the last internal capability prior to taking a value proposition to the marketplace. 4.2.4. Assessing Customer Value. The fourth NEBIC construct is an organization’s capability to Assess Customer Value (CV). Woodruff (1997) defines customer value as a customer’s perceived preference for and evaluation of those product attributes, attribute performances, and consequences arising from use that facilitate (or block) a customer’s goals and purposes in a use situation. The process of communicating a value

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proposition to the marketplace precedes value assessment. It is also important to note that assessing customer value is not the dependent variable in the NEBIC theory. Creating actual customer value is the objective of net-enablement, and the Assessing capability represents a firm’s routines to measure, understand, and communicate value signals in a timely manner. We also note that some important NE initiatives are targeted at internal clients rather than external customers. For example, a human resources Web site initiative for listing internal job position openings is likely to be valued by employees as clients of the services provided by human resources. It is unlikely, however, that the external customers who pay for a firm’s products and services will even be aware of the innovation or value it. Nevertheless, assessment approaches described below can be applied to internal clients as well. Customer value may be assessed via three classes of measures: financial, perceptual, and behavioral measures. Many large firms have evolved elaborate financial measurement routines using accounting and financial reporting systems. Best practices provide financial profitability analysis by product line, region, or even by individual customer. Financial indicators such as balance sheets and income statements are at best, however, lagging indicators. They provide reasonable information regarding the past, but have limited utility in understanding a firm’s strategic position or the degree of loyalty that customers feel to a brand. Aggregate financial measures may also prove inadequate when trying to assess the value created via NE initiatives that complement other activities of the firm (e.g., a website that provides sales or product support information). Equities markets provide another type of financial measure. Moore (2000) argues that stock price is the uniform indicator of firm performance. The equities markets assign a value to a firm’s stock based on the firm’s perceived competitive advantage gap from its rivals and the length of its competitive advantage period (CAP). Both Gap and CAP are based in customer value creation and the cash flows that they create. Perceptual measures have long been a part of marketing research. Customer (or internal client) satisfaction or product evaluation surveys tap into psychometric beliefs, attitudes, and intentions. These measures can be forward looking in understanding

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changes in customers’ likely actions regarding a firm’s products (e.g., plan to purchase again, feel less trustful of the brand, very satisfied and have recommended to a friend). Stewart (1997) views this intangible customer capital as essential to value creation, yet few firms have sophisticated routines for systematically assessing and interpreting it. Useful perceptual measures are uniquely tailored to each industry. The Balanced Scorecard approach recognizes the value of perceptual measures (Kaplan and Norton 1996). Behavioral measures represent a third way of measuring customer value. While financial measures report outcomes and perceptual measures assess intent, behavioral measures provide insight regarding the actual choices and decision processes used during human-mediated e-commerce interactions.7 For example, web server logs can provide clickstream analysis that give indications of which web pages were viewed, in what sequence, and for how much time (Novak and Hoffman 1997). Similarly, bidding data from supply chain exchanges can provide new insights regarding actual customer behavior relative to a firm’s value propositions. Measures from behavioral data can provide rare insights into what customers actually value or internal clients actually use. A strong Assessing capability would demonstrate proficiencies in valuing NE business initiatives using all three types of measures. The routines used for assessing may exist in various forms in the finance, marketing, IS, operations, or other units of a firm. In Figure 1, the Assessing capability is viewed on a different scale than the other three NEBIC constructs. Because Assessing activities occur after taking a value proposition to the market, NE business initiatives are no longer viewed as value potential. They are now assessed as value realized as customer reactions in the marketplace demonstrate the value of an NE initiative.

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Some net-enabled transactions do not involve any human behavior as they are computer-to-computer execution of preprogrammed decision rules. For example, order an additional 1,000 units when the on-hand quantity drops below 250. Human-mediated transactions provide a greater assessment challenge, giving greater value to behavioral measures.

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4.3.

Laws of Interaction, Boundaries, System States, and Propositions Dubin (1978) asserts that a complete theory sets forth laws of interaction among constructs, identifies boundaries beyond which the theorized relationships do not hold, defines system states that describe the values of constructs with some persistence through a period of time, and ultimately makes propositions or truth statements derived from the theory. NEBIC addresses each of these requirements below. Prediction and understanding are distinct objectives of theory, and they must be addressed separately in specifying the laws of interaction among the constructs.8 Prediction focuses on foretelling the value of a specific variable based on the values of other variables in a system. It draws on the notions of variance theory and targets predicting the value of outcomes or dependent variables with little or no insight regarding how or why those values were established. Creating a level of understanding draws on the notions of process theory to describe the relevant processes of interactions among the constructs. NEBIC theorizes distinct laws of interaction for the unique objectives of prediction and understanding. 4.3.1. Variance Theory Predictions. For prediction, variance theories require a dependent variable. The variable of interest for net-enablement is creating customer value. This introduces a possible tautological criticism9 of NEBIC arising from conceptualizing netenablement as a dynamic capability. If customer value flows from resource configurations that align with or that create marketplace opportunities, how can the value of these resource configurations be assessed a priori to predict customer value? As defined, dynamic capabilities are a means to achieve market-aligned resource configurations, but strong dynamic capabilities do not in themselves confer marketplace value. Eisenhardt and Martin (2000, p. 1108) address this issue by contending that dynamic capabilities are defined in terms of their “functional relationship to re8 See Dubin (1978, pp. 18–26) for compelling examples regarding the distinction between laws of interaction for variance theory that provide prediction and process theory that provide understanding. 9

See Appendix A for citations and summary of recent tautology criticisms of the resource-based view.

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source manipulation” (not marketplace performance), a viewpoint that argues against the tautological criticism. The efficacy of a dynamic capability in resource reconfiguration alone, however, is not the real variable of interest for net-enablement. The value of reconfigured resources—especially innovative configurations for net-enablement—cannot be asserted independently of marketplace signals. In fact, timely execution of netenablement is intended to influence market evolution through a series of (possibly brief) advantage periods. Thus, for practical purposes of operationalizing prediction in NEBIC, we make clear the Dynamic Capabilities View’s implied assumption. Assumption. Dynamic resource configurations provide the best opportunity to create customer value via alignment with or creation of a marketplace advantage (see views on organizational fit in Miller 1992, 1996; Lengnick-Hall and Wolf 1999). Given this assumption, the NEBIC’s variance theory predictions assert the relationships of interest between net-enablement’s simpler capabilities (e.g., Choosing, Matching, etc.) and the dependent variable of customer value. The strength of each NEBIC capability can vary on a continuum from weak to strong—we will address issues of operationalizing specific empirical indicators for measurement in §5. In considering the relationships among the constructs, we will simplify the states of the constructs by referring to them as having categorical values of low, medium, or high. From a variance theory perspective for prediction, NEBIC asserts that when all four capabilities are high, then high customer value will be achieved—though it may only provide a fleeting advantage relative to rivals if a firm operates in a hypercompetitive environment. As depicted in Figure 1 and described in §4.2, the Matching, Executing, and Assessing capabilities rely on outputs from their antecedent capabilities. Thus, if the choosing capability is low, then the efficacy of high Matching, Executing, and Assessing capabilities will be diminished—either through a late awareness of the ET, compressed time for executing, or being late to market. In sum, there is sequenced step interdependency among the capabilities even when considered from the variance perspective. Table 1 conveys

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Table 1

Variance Perspective Theory Predictions and System States Capabilities

Marketplace

Choosing Matching Executing Assessing Customer ET EO BI CV Value H L H H H

H H H H L H H L H H 2 or more low

H H H H L

H M L L H–M L

Reference Label Marketplace Leader Fast Follower Rudderless Tractionless Unsustainable Low-Margin Laggard

H  High (strong); M  Medium; L  Low (weak).

the predicted laws of interaction among the NEBIC constructs along with the predicted system states. We have added a shorthand reference label for each prediction that conveys the essence of its NE innovation performance over time. The “Marketplace Leader” has cultivated a strong set of sustainable NEBIC capabilities. These allow netenablement to rapidly achieve new resource configurations that strive to turn selected ET into customer value in the marketplace. The Assessing capability provides enhancement towards sustainability through organizational learning routines to strengthen the other capabilities (described further below). Proposition 1. Firms with strong capabilities in Choosing ET, Matching EO, Executing BI, and Assessing CV will consistently create high levels of customer value. The “Fast Follower” differs from the leader only in the lag of time. The weak Choosing ET capability implies that the firm is unaware of ET in a timely manner and fails to amplify those relevant ET to the strategic options formulation process. Thus, its business plans and NE initiatives are designed from an incomplete set of alternatives. Their strengths in the Matching, Executing, and Assessing capabilities somewhat atone for their tardy awareness of ET and give them moderate success in the marketplace. Proposition 2. Firms with a weak Choosing ET capability—though with strong Matching EO, Executing BI, and Assessing CV capabilities—will create moderate levels of customer value.

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The “Rudderless” firm squanders the value-creating potential made possible by a strong Choosing ET capability. For some reason, business leaders are unable to effectively match ET to market potential in a timely manner—potential explanations are explored below. Even strong abilities to Execute and Assess are unable to provide the necessary speed in resource reconfiguration when a firm fails to match and select strategic options in a timely manner. The rudderless firm fails in its Schumpeterian efforts to reconfigure its resources for the next market opportunity. Proposition 3. Firms with a weak Matching EO capability—though with strong Choosing ET, Executing BI, and Assessing CV capabilities—will fail to create substantive customer value. The “Tractionless” firm fails in its abilities to reconfigure its resources even though it has produced timely NE plans and strategic options. Its net-enabling potential is rendered inefficacious through ineffective routines to reconfigure its resources, work force, relationships with suppliers or customers, or business processes. Whatever the reason, business innovation expressed as NE business initiatives are not executed in a timely manner. Thus, the firm’s value propositions to the marketplace do not capture strategic opportunity, and it is a very late follower. Proposition 4. Firms with a weak Executing BI capability—though with strong Choosing ET, Matching EO, and Assessing CV capabilities—will fail to create substantive customer value. The “Unsustainable” firm can achieve resource configurations that succeed in the marketplace, though unlike the Fast Follower, it cannot be sustained. Customer value is directly created via the Choosing, Matching, and Executing capabilities; thus, high customer value would be predicted when these three capabilities are high. The weakness in the Assessing capability, however, will ultimately undermine the strength of those three capabilities as they atrophy in the absence of organizational learning. Without a strong Assessing capability, marketplace signals in terms of perceptual and behavioral data cannot be amplified back to the antecedent capabilities. A firm may persist with these capability strengths for a period of Information Systems Research Vol. 13, No. 2, June 2002

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time with some success, but it is an unsustainable system state over a longer period of time. Proposition 5. Firms with a weak Assessing CV capability—though with strong Choosing ET, Matching EO, and Executing BI capabilities—will create high levels of customer value during the limited persistence of this state. Finally, the “Low-Margin Laggard” firms suffer from weaknesses in two or more capabilities that effectively mute any potential for other strong capabilities to achieve timely resource configuration to affect customer value. The value propositions that they express to the marketplace will offer very little netenabled innovation over the offers of the marketplace leaders. Their failure to turn ET into CV in a timely manner allows leading firms to secure the more lucrative segments of a market and short-term advantages. Thus, laggards find themselves relegated to uncontested, low-margin market segments that have been abandoned or are undeveloped by leaders. As a set, these five propositions predict the ability of a firm to create customer value by knowing the strength of its four NEBIC capabilities. Evidence that supports or refutes the predictive power of these propositions will be of interest, but both researchers and practitioners will also desire a deeper understanding beyond the abilities of variance theories. For example, what events, sequences of events, or situations can provide greater understanding and explanation? The following set of NEBIC propositions addresses the laws of interaction from the process theory perspective. 4.3.2. Process Theory Explanations. The process perspective in NEBIC asserts laws of interaction among the constructs for the purpose of providing explanation and understanding. Knowledge regarding the strength of each capability only provides a necessary, but not sufficient, condition to understand a particular outcome. Figure 1 posits both sequences of relationships among constructs, e.g., Matching precedes Executing, and arrows describing the communication processes between the constructs. These communication processes establish the sequence for ordering the four capabilities. The presence of these communication processes in an organization provides only the necessary conditions for the NEBIC to explain how a firm Information Systems Research Vol. 13, No. 2, June 2002

turns ET into CV. The feed-forward arrows from the lower part of Figure 1 are now addressed as specific propositions of NEBIC. No matter how a firm chooses to operationalize its Choosing ET capability, those choices must be effectively communicated to business leaders for consideration in crafting strategic options. To the extent that there are clear, frequent, and trustful communication routines between human actors involved with the Choosing and Matching capabilities, timely NE business innovation is possible. Proposition 6. Effective communication processes that convey and change understanding are necessary between the Choosing and Matching capabilities to create customer value. Similarly, those who plan business strategy and new initiatives must effectively communicate those plans to line managers, knowledge workers, and those responsible for reconfiguring the firm’s resources. This communication may be in the form of formal documents such as business cases, strategic plans, or initiatives, or it may be communicated in more informal ways through social networks. Thus, effective communication processes that clarify priorities and objectives between the Matching and Executing capabilities are necessary for timely NE business innovation. Proposition 7. Effective communication processes that clarify priorities and objectives are necessary between the Matching and Executing capabilities to create customer value. The third arrow represents communicating and delivering a value proposition to the marketplace. It does not involve further resource reconfiguration; rather, it is the communication to the marketplace of the reconfigured resources or the value propositions that they enable. Communicating value propositions involves wellunderstood business practices from the fields of Marketing and Advertising. These communications must be backed up with actual product experiences in service delivery, product quality, and support (e.g., 24 x 7 x 365 website reliability). Long-standing practices from the fields of Operations and Management provide insight regarding the actions required for effective

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service or product delivery. Failure in either communicating or executing can significantly reduce customer value created in the marketplace by the firm’s new value proposition. Proposition 8. Effective communication processes are necessary from the Executing capability to the marketplace to create customer value. Proposition 9. Effective delivery processes are necessary from the Executing capability to the marketplace to create customer value. The set of arrows across the top of Figure 1 represent the feed-backwards organizational learning (OL) communication processes. The Assessing capability measures financial, perceptual, and behavioral indicators from the marketplace, yet that data must be contextualized and amplified back throughout an organization if it is to become part of a firm’s collective learning on which NEBIC capabilities are based. Nuances of these communication processes are well researched (see books by Leonard-Barton 1995, Nonaka and Takeuchi 1995, Brown and Duguid 2000, and special themed issues of Organization Science 1991, California Management Review 1998), but they are simply referred to here as OL communication. NEBIC asserts that there are primary and secondary OL communication processes. The primary processes, the heavy dotted lines in Figure 1, are distinguished in that their insights flow from real marketplace data gathered via the Assessing capability. No matter how compelling an NE business innovation idea might be, it is ultimately the marketplace that will arbitrate its value. Thus, OL that is anchored in solid marketplace measurement and contextualized through communication mechanisms and routines will provide the valuable insights that are necessary to strengthen a firm’s capabilities. Proposition 10. The Choosing capability is strengthened when organizational learning communication is based on contextualized marketplace data. Proposition 11. The Matching capability is strengthened when organizational learning communication is based on contextualized marketplace data.

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Proposition 12. The Executing capability is strengthened when organizational learning communication is based on contextualized marketplace data. Interestingly, even the Assessing capability itself is improved via OL communication processes. Measurement processes are piloted, discussed, and improved for accuracy. New classes of relevant predictive measures emerge through building a firm’s core competencies for measuring the right things in the right ways. Proposition 13. The Assessing capability is strengthened when organizational learning communication is based on contextualized marketplace data. Secondary OL communication processes, the light dotted arrows in Figure 1, also play an important role in strengthening NEBIC capabilities. Both the Executing and Matching capabilities can strengthen their antecedent capabilities via OL communication of soft insights, hunches, and ideas for improved technology vetting and initiative planning. These insights are not signals from customers, but they may be wisdom from within the organization to guide future NE initiatives. For example, the IT group might convey back to business leaders that the firm’s IT staff is suffering burnout from the pace of implementing the last initiative. The next initiative should be broken into two projects or risk losing key people. Eisenhardt and Martin (2000) identify the learning routines of practice, mistakes, and pacing of experience as mechanisms for contributing to strengthening capabilities. Proposition 14. Antecedent capabilities are strengthened when organizational learning communication conveys soft insights from adjacent capabilities. Effective capabilities, communication among those capabilities, and communication or learning routines to strengthen capabilities are essential to sustaining NE business innovation in a world of perpetual IT change and hypercompetition. When we integrate the process theory explanations of the NEBIC for turning ET into customer value, we can assert two macro-level process propositions that speak directly to dynamic capability of net-enablement. Feed-forward communication processes move ET through awareness, assimilation, adoption, and execution to make offers to customers. Information Systems Research Vol. 13, No. 2, June 2002

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Feed-backward communication processes provide the clarity of signal to improve and evolve capabilities through experience. Proposition 15. Firms with a strong net-enablement dynamic capability will have strong feed-forward communication processes. Proposition 16. Firms that consistently transform ET into customer value will have strong feed-backward communication processes. Obvious combinations of the variance and process propositions from NEBIC are possible. Such combinations may prove useful after the efficacy of these individual propositions has been established. 4.3.3. Boundaries. The predictions and explanations of the NEBIC are proposed for profit-oriented firms—particularly large firms—that operate in market-based economies. Its tenets may not prove insightful for other contexts (e.g., not-for-profits). We see the NEBIC theory and the dynamic capability of netenablement as equally applicable to firms in hypercompetitive and nonhypercompetitive environments. Eisenhardt and Martin (2000) make many valuable contrasts regarding how dynamic capabilities are applied variously in moderately dynamic or highvelocity markets. Their insights are applicable to the routines, processes, and simpler capabilities that comprise the net-enablement dynamic capability. 4.4. Cycle Summary The Choosing ET, Matching EO, Executing BI, and Assessing CV are four essential capabilities for NE business innovation that create customer value. The strengths or weaknesses of these capabilities can be used to predict the firm’s abilities to create value through net-enablement. Organizational learning communication processes are essential to understand why firms may create or fail to create customer value from their net-enabled business efforts.

5. A Research Agenda Theories provide an essential early step in the research process, but until real-world data provide supporting evidence, they remain only a proffered representation Information Systems Research Vol. 13, No. 2, June 2002

of a real-world phenomenon. This section begins to operationalize the NEBIC theory as a research agenda for empirical measurement of net-enablement as a dynamic capability. It completes Dubin’s (1978) requirements for identifying specific empirical indicators for measurement and overviews potential research approaches. Finally, it demonstrates, via an example, the process for instantiating specific research hypotheses from the NEBIC propositions. 5.1. Empirical Indicators Each of the four NEBIC capabilities constructs can be discerned from empirical indicators, though as organizational capabilities, they will rarely be found in a single person, group, or business unit. Evidence regarding their existence and strength must be discerned from artifacts, perceptions, and behaviors of organizational actors. Table 2 identifies some candidate indicators for each construct or event. The list is not exhaustive, but rather indicative of the types of artifacts, perceptions, and behaviors that can be examined for evidence. Specific approaches to measuring these indicators follow in the next section. 5.2. Research Approaches We contend that multiple research approaches are needed to understand the complex organizational phenomena associated with net-enablement. Lee (1991) illustrates the interplay among the subjective, interpretivist, and positivist understandings. The NEBIC theory presented here represents the subjective understanding articulated as testable theory for methodologies from both the interpretivist and positivist research approaches. It is unlikely that a single research study will methodologically engage both the approaches. The more likely development is a series of research studies from a variety of perspectives that are anchored in the NEBIC theory. This common theoretical basis can then greatly facilitate integrating the unique contributions of each approach to generate a common understanding (Lee 1991) of the dynamic capability of net-enablement. Table 3 conveys these as described by Markus and Robey (1988). 5.2.1. A Positivist Research Agenda. The NEBIC propositions satisfy the requirement of falsifiability, logical consistency, relative explanatory power, and

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Table 2

Sample Empirical Indicators Constructs/Processes

Sample Empirical Indicators

Choosing New Emerging/Enabling Technologies

• • • •

Consistent set of IT standards for enabling technologies within and across operational units. Formal responsibility and accountability assigned for monitoring emerging technologies. Designated funding for experimenting to assess emerging IT viability. Consistent record in choosing IT standards and IT infrastructure upgrades.

Matching with Economic Opportunities

• • • • •

Business leaders are well informed regarding ET. Formulation of strategic options explicitly considers both current enabling and newly emerging IT. Early to see new IT-enabled market opportunities. Frequency of new NE initiatives. Breadth of new NE initiatives throughout a firm’s operations (e.g., supply chain, intranet, sales channels, etc.).

Executing Business Innovation for Growth

• • • • •

Extent to which firms can rapidly implement NE initiatives. Firmwide NE governance mechanisms align incentives for change. Top-executive leadership creates a climate for and an understanding of change. High proportion of the firm’s energy is spent on growth-oriented opportunities. New value propositions emerge on schedule.

Assessing Customer Value

• NE initiatives have clearly defined metrics tied to customer value. • Suites of metrics assess the financial, perceptual, and behavioral outcomes of NE initiatives.

Conveying New IT Insights

• Timely memos, briefings, demonstrations of ET to business leaders. • Communications demonstrate trust, common language, and clarity.

Communicating Net-Enabled Business Initiatives

• • • •

Taking New Value Propositions to Market

• Effective communication of new net-enabled business value proposition(s) to the marketplace. • Effective delivery of new value proposition(s) via order fulfillment, service, support, and reliability.

Organizational Learning Communication

• Measurements are contextualized for the organization and amplified throughout. • Decision processes incorporate market-derived measurements. • NE metrics lead to behavior improvements in an organization’s capabilities (e.g., more precise vetting of emerging technologies).

Table 3

Clearly articulated business cases or strategic plans for NE business initiatives. Rationale and purpose for the initiative are clearly explained and understood. Priorities and trade-offs are understood. Executive commitment to executing a strategic option requiring resource reconfiguration.

Process and Variance Research Approaches for NEBIC NEBIC Capabilities Measured with a Variance Approach (Positivist)

Role of time/view Definition

• Snapshot view (survey, etc.). • Cause is necessary and sufficient for the outcome. Capture customer value realization at time “t.”

Assumptions

• Outcomes will occur when necessary and sufficient conditions are present at time “t.” Capture the “outcome” at a fixed point of time. • NEBIC capabilities as variables. • If x, then y; if more x, then more y.

Elements Logical form

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NEBIC Arrows Measured with a Process Approach (Interpretivist) • Longitudinal case study. • Causation consists of necessary conditions, in sequence. The influence of unpredictability, chaos/randomness of hypercompetitive environment will be studied over time. • Predictable outcomes may or may not occur, even when the processes are present. Subjectivism and interpretivism needed as the triangle by Lee (1991) indicates. • NEBIC arrows as processes for discrete outcomes. • If not x, then not y; cannot be extended to more x, more y.

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survival (Lee 1991). The positivist approach would begin by substituting specific empirical indicators into the propositions to form testable hypotheses. Because the propositions are broad “truth” statements about the model, the hypotheses will have to focus on one or two constructs at a time rather than the entire NEBIC theory all at once. Small steps will be necessary to establish construct validity and to discern which empirical indicators provide the best evidence. For example, the main point of Proposition 2 is that a weak Choosing ET capability will hinder the timely reconfiguration of resources to create customer value—assuming that other capabilities are strong. Because this assumption cannot be known in the early stages of NEBIC research, a small subset of P2 related to the Choosing ET construct will be articulated as a hypothesis. Substituting terms from Table 2 into a portion of Proposition 2 can yield the following hypotheses: Sample Hypothesis 1a. Business leaders will demonstrate higher levels of understanding of ET when there is formal responsibility for monitoring ET. Sample Hypothesis 1b. Business leaders will demonstrate higher levels of understanding of ET when designated funding exists for experimenting with ET. These hypotheses, and others that can be derived from the NEBIC propositions, specify the empirical indicators and routines of the constructs for instrument development. Rigorous instrument development is needed for NEBIC constructs (see Moore and Benbasat 1991 and Smith et al. 1996 for detailed examples of instrument development). In general, instrument development invokes three required research activities: First, items need to be created ensuring content validity tied to the empirical indicators. Second, scale development can be done to know the coverage of the domain of constructs. The items should demonstrate convergent validity with related construct and discriminant validity with others. Finally, instrument testing can be done to assess the Cronbach Alpha value and reduce the number of questions for efficiency (if possible). Data collection would involve perceptual surveys using the instruments. Data might also be gathered via rigorous analysis of Information Systems Research Vol. 13, No. 2, June 2002

an organization’s artifacts (e.g., percent of sales budget spent on IT, percent of IT budget spent on ET monitoring, number of people assigned to ET monitoring, etc.). The objectives of the early work would be to identify the most relevant empirical indicators and to create reliable scales for measuring them. After reliable measurement instruments are established, the broader propositions and system states can be tested using these new measures. Evidence may refute or support the predictions expressed in the propositions and Table 1. 5.2.2. An Interpretivist Research Agenda. Where the positivist research approach begins with theory and constructs, the interpretivist approach often desires not to be blinded by them. As noted by Mohr (1982) and Pare´ and Elam (1997), we believe that interpretivist research methods can help provide understanding for complex net-enablement phenomena by assessing the process theory tenets of the NEBIC theory. They can provide insight to identify the external forces and probabilistic processes that constitute the means through which organizational events unfold (Pare´ and Elam 1997). The communication processes, routines, and relevant external events are uncovered based on principles of phenomenological sociology, hermeneutics, and ethnography. Data collection occurs through detailed case studies where data collection and data analysis often occur concurrently. Analysis within and between cases looks for common patterns, events, and sequences of events that provide understanding. Emergent propositions are compared, revised, and reassessed, looking for a derivation that fits the case data. We contend that these emergent propositions can be compared with the broad process propositions of the NEBIC theory. The identified sequences of events and relevant external forces can be valuable for revising and increasing the explanatory power of the NEBIC theory. 5.2.3. The Perspective of Time. Time plays an important role in the NEBIC theory, and varying it provides options for any research design. One tactic for NEBIC research is to follow a single ET, such as Wireless Application Protocol or collaborative filtering,

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over time through its migration from ET to CV. Measurements could assess perceptions and the events that shaped its journey, elapsed time, levels of resource commitments, or obstacles that it encountered during its development. A second tactic is to hold time constant to capture the status of a firm’s net-enablement business innovation portfolio as a snapshot. New insights would surely emerge when considering a firm’s many concurrent NE business initiatives. A third tactic combines the two by conducting a longitudinal series of snapshot measurements of a firm’s net-enablement initiatives at three- to six-month intervals. 5.3. Empirical Indicators Summary In summary, empirical indicators are the link to turning broad propositions into testable hypotheses. The subjective understanding of net-enabled business innovation as expressed in the NEBIC theory can be supported, refuted, or modified via the interpretivist or positivist understandings. Rigorous research studies that employ either approach are necessary to assess specific components of the NEBIC theory. At this stage of early NEBIC theory development, using interpretive insights for understanding the positivist results will create synergy for improving the subjective understanding of the phenomena. The following section addresses the use of the NEBIC as a decision-making framework for the practice of net-enablement in modern organizations.

6. Applications to Practice for Managerial Action Thus far, we have explained net-enablement and the NEBIC theory in terms for academic researchers, yet the NEBIC also can be viewed as a framework to provide useful guidance for practitioners. It is already being employed to steer net-enablement capabilities development and business initiatives in several large organizations. First, the NEBIC makes clear that the efficacy of generating strategic options, executing business innovation, and taking new value propositions to market are all supported or constrained by a firm’s ability to choose enabling and emerging technologies. High levels of customer value are unlikely to develop when an organization views its IT group in a nonstrategic way.

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Second, the NEBIC makes the distinction between choices of emerging technologies and choices of enabling technologies for NE business initiatives. Each requires distinct rules for choosing. There are three bases for choosing emerging technologies: First, does the technology have the potential to create customer value for a particular organization? Second, when will it be commercially available at viable prices for the target group? Third, how does it fit with a firm’s and its customers’ existing investments? The questions differ for choosing enabling technologies such as PCs, mobile phones, Internet connections, etc. Because these technologies are already proven and viable, the basis for choosing enabling technologies is largely one of timing. When, if ever, will the target group (e.g., customers, suppliers, etc.) sufficiently adopt the technology so that it can be incorporated in a firm’s net-enablement initiatives? Third, the NEBIC helps line business managers see and integrate the whole of the net-enabled business innovation process. In our work with many executives around the world, this integration of the whole, or “putting it all together,” was their most valued insight from the NEBIC. From this holistic view, practitioners can begin to informally assess their NE innovation capabilities. They can use the framework to map the status of a firm’s NE business innovation pipeline in terms of initiatives and strategic options. Finally, practitioners can draw on the NEBIC to examine the efficacy of their organizational learning processes. The NEBIC makes clear that continual netenabled business innovation is a nested and repeating cycle, and that insight from market-based data must be amplified back through the organization to strengthen future innovation cycles.

7. Conclusion In response to the initial research question, we theorize that identifiable and measurable organizational capabilities do comprise the ongoing work of netenablement. The strength of these capabilities, their routines, and the communication processes that interconnect them distinguish firms’ abilities to turn timely net-enabled business innovations into customer value. In an intensively networked world—our apparent destiny—firms must look to new net-enabled innovation Information Systems Research Vol. 13, No. 2, June 2002

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in developing the unique resources, data, or processes that make them competitive in this hypercompetitive environment (Straub and Klein 2001, Weill and Vitale 2001). The capabilities to sense, innovate, execute, and learn through a purposeful cycle will be critical. The Net-Enabled Business Innovation Cycle theory proposes a rigorous and relevant applied theory for assessing those capabilities and communication processes that connect the repeating cycles from emerging technology to customer value and back through organizational learning. As a theory, NEBIC’s purpose is to invite observation, measurement, and testing to build a body of supporting or refuting evidence. A theoretical system exists in the mind of the researcher as a model of the real, empirical one. Research scientists focus on making these two systems as congruent as possible (Dubin 1978, p. 18.). The development of the NEBIC also provides an example for generating applied IS theory from the Dynamic Capabilities Perspective. We see no shortcuts to a quick and easy understanding of the innovative capabilities of net-enabled organizations, simple measurements of their NE initiatives, nor prediction of success with net-enablement. The NEBIC theory can provide a foundation for a program of systematic and rigorous research to provide an understanding of net-enablement. As a dynamic capabilities theory, it is not tied to any transient technology or business practice. As a managerial framework, its purpose is to provide immediate usefulness to executives who seek to strengthen their organizations’ NE innovation capabilities. Its holistic view of net-enablement and e-business can be effectively used to focus an organization’s energy on the capabilities, processes, and competencies that contribute to the creation of customer value. Acknowledgments The development of the NEBIC theory has benefited greatly from the detailed guidance of the senior editor, associate editor, and reviewers. The author also wishes to thank research associates Michael Williams and Arvin Sayam for their valuable assistance and healthy debate in maturing the ideas presented here.

Appendix A.

Strategy Literature

The NEBIC theory is based on the dynamic capabilities perspective. For those interested in a better understanding of the foundations of

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the dynamic capabilities perspective, we review a brief history of competitive advantage. Strategy scholars have devoted much research to two broad perspectives on how firms achieve competitive advantage. The Industrial and Organization Economics (IOE) perspective, notably articulated by Porter (1980, 1985), argues that a firm should view its suppliers, customers, rivals, and potential new entrants as competitors. Strategies are designed to attain a productmarket position that allows bargaining power over suppliers and customers while a firm keeps out new entrants and rivals from its product-market positions. Contemporary strategy research, however, has seen a shift in emphasis from the IOE view toward a Resource-Based View (RBV) of the firm. RBV argues that competitive advantage comes from owning valuable, rare, inimitable, and nonsubstitutable (i.e., so-called VRIN attributes) resources. According to RBV, firms attain sustainable competitive advantage by configuring their VRIN resources into value-creating strategies (Lippman and Rumelt 1982, Wernerfelt 1984, Barney 1991, Peteraf 1993). Unlike IOE that is premised in market position, RBV asserts that internal resources of individual firms are the key determinants of competitive advantage (Amit and Schoemaker 1993, Teece et al. 1997). The RBV (Penrose 1959, Wernerfelt 1984, Barney 1991) attributes advantages in an industry to a firm’s control over bundles of unique material, human, organizational, and locational resources and skills that enable unique value-creating strategies. Resources refer to tangible and intangible assets that give increasing returns. Intangible assets include process, path, and cognitive resources such as knowledge, culture, and reputation (Wernerfelt 1984, Rindova and Fombrun 1999). The RBV has two underlying assertions: (1) resources and capabilities will differ among firms (resource heterogeneity) and (2) these differences may be long lasting (resource immobility) (Mata et al. 1995). Resources can be combined and integrated into unique clusters that enable distinctive abilities within a firm (Teece et al. 1997). These distinctive abilities, called core competencies, can be considered the collective learning in an organization (Prahalad and Hamel 1990). Prahalad and Hamel assert three tests for identifying a core competency: (1) It provides potential access to a wide variety of markets, (2) it makes significant contribution to perceived customer benefits, and (3) it is difficult to imitate. Straub and Klein (2001) apply the RBV perspective to the NE space in their arguments that NE conveys to the firm a resource that cannot be substituted for or imitated: customer proprietary data. Exploitation of this resource, they assert, will lead to sustainable competitive advantage for NEOs. Despite the popularity of the RBV, it has been criticized for several reasons. Notably, Priem and Butler (2001) challenge the basic definitions of the RBV, arguing that, as stated, it is tautological, nonfalsifiable, unbounded, and unworthy of the status of a theory (see also a response from Barney 2001). Along these lines, Williamson (1999) suggests that “big ideas often take a long time to take on definition” (p. 1094), and suggests that the useful operationalization of key terms like “competence” and “capability” may not be refined for many years. Additionally, it is argued that RBV is powerfully descriptive, but fails to prescribe strategic actions a priori. Simply

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advising managers to acquire or develop resources that are valuable, rare, inimitable, and nonsubstitutable does not adequately prescribe effective strategy. Also, one of the basic assumptions of RBV, that VRIN resources lead to sustained competitive advantage, does not seem to apply in high-velocity markets (Eisenhardt and Martin 2000). With the presence of hypercompetition and the increased velocity of change in these markets, competitive advantage is captured in a series of short bursts, not one durative period. RBV has been extended with the dynamic capabilities perspective to address the realities of high-velocity markets. The efficacy of both IOE and RBV perspectives is being questioned in hypercompetitive business environments because competitive advantage from both product-market positioning and configuring distinctive resources can be eroded with speed by disruptive technologies (Tushman and Anderson 1986, Henderson and Clark 1990, Leonard-Barton 1992, Afuah 2000, D’Aveni 2000). In this environment, capabilities that enable rapid and purposeful reconfiguration of a firm’s resources are the means through which both industry position and timely, unique resources can be obtained. This extension to RBV is referred to as the dynamic capabilities perspective (Teece et al. 1997, Eisenhardt and Martin 2000).

Appendix C.

NEBIC Thesis Application Example

Jeff Bezos, founder of Amazon.com, observed in 1994 that the enabling technologies of the Internet, PCs, and a Web-browsing software could interact to provide new connectivity among businesses and their customers (Choosing ET). Upon learning that net traffic was growing at 2,300% per year, he began considering where these technologies would create an attractive net-enabled economic opportunity. Books were identified as being easily described via online media, of interest to a global marketplace, and made more attractive with information-based services (Matching EO). A business plan was formulated to attract capital for creating a company to target the opportunity. Business innovations created new software, content, and strategic alliances among suppliers and physical world partners (Executing BI). The company took its value proposition of online shopping in the world’s largest bookstore to customers, and received a very favorable response in acquiring new customers and repeat business (Assessing CV). These market-based signals of customer satisfaction led to further refinement of Amazon’s capabilities to choose, match, execute, and assess in a hypercompetitive environment.

References Appendix B.

Theory Development

There are many excellent references that describe the role and development of theory for scientific research. For example, see the themed issue of the Academy of Management Review, 1989, Volume 14(4). To develop a model of real-world phenomena into a theory, it must identify the (1) units of study or constructs, (2) laws of interaction, (3) boundaries—beyond which the theory no longer holds, and (4) the system states in which the constructs operate. These four features enable the articulation of logically consistent derivations as (5) propositions of the theory. Terms in the propositions are then converted to (6) empirical indicators for the purpose of stating (7) testable hypotheses for empirical measurement and testing. Other approaches for theory building via case studies are explained in Eisenhardt (1989) and Pare´ and Elam (1997). Theories can be developed using a variance, process, or a hybrid perspective. Pure variance theories posit an invariant and predictable relationship between antecedent variables and outcomes—necessary and sufficient conditions cause outcomes (Mohr 1982, Markus and Robey 1988). Pure process theories explain that outcomes can happen only under a certain set of conditions and sequence of events, but the outcome may also fail to occur even when the conditions are present—outcomes are probabilistic (Markus and Robey 1988). Elements of the variance and process perspectives can also be combined in a hybrid perspective. Hybrid theories are constructed using variables and/or events, relationships and/or temporal sequences, and predictable or probabilistic relationships (Shaw and Jarvenpaa 1997). The NEBIC theory addresses Dubin’s (1978) seven requirements and both the variance and process perspectives for developing a theory.

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Detmar Straub, Senior Editor. This paper was received on December 10, 2000, and was with the author 10 months for 4 revisions.

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