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Article

Andy El-Zayaty and Russell Coff

Many discussions of the creation and appropriation of value stop at the firm level. Imperfections in the market allow for a firm to gain competitive advantage, thereby appropriating rents from the market. What has often been overlooked is the continued process of appropriation within firms by parties ranging from shareholders to managers to employees. Porter’s “five forces” model and the resource-based view of the firm laid out the determinants of value creation at the firm level, but it was left to others to explore the onward distribution of that value. Many strategic management and strategic human capital scholars have explored the manner in which employees and managers use their bargaining power vis-à-vis the firm to appropriate value—sometimes in a manner that may not align with the interests of shareholders. In addition, cooperative game theorists provided unique insights into the way in which parties divide firm surplus among each other. Ultimately, the creation of value is merely the beginning of a complex, multiparty process of bargaining and competition for the rights to claim rents.

Article

Nydia MacGregor and Tammy L. Madsen

A substantial volume of research in economic geography, organization theory, and strategy examines the geographic concentration of interconnected firms, industries, and institutions. Theoretical and empirical work has named a host of agglomeration advantages (and disadvantages) with much agreement on the significance of clusters for firms, innovation, and regional growth. The core assertion of this vein of research is that geographically concentrated factors of production create self-reinforcing benefits, yielding increasing returns over time. The types of externalities (or agglomeration economies) generally fall into four categories: specialized labor or inputs, knowledge spillovers, diversity of actors and activity, and localized competition. Arising from multiple sources, each of these externalities attracts new and established firms and skilled workers. Along with recent advancements in evolution economics, newer research embraces the idea that the agglomeration mechanisms that benefit clusters may evolve over time. While some have considered industry and cluster life-cycle approaches, the complex adaptive systems (CAS) theory provides a well-founded framework for developing a theory of cluster evolution for several reasons. In particular, the content and stages of complex adaptive systems directly connect with those of a cluster, comprising its multiple, evolving dimensions and their interplay over time. Importantly, this view emphasizes that the externalities associated with agglomeration may not have stable effects, and thus, what fosters advantage in a cluster will change as the cluster evolves. Furthermore, by including a cluster’s degree of resilience and ability for renewal, the CAS lens addresses two significant attributes absent from cyclical approaches. Related research in various disciplines may further contribute to our understanding of cluster evolution. Studies of regional resilience (usually focused on a specific spatial unit rather than its industrial sectors) may correspond to the reorganization phase associated with clusters viewed as complex adaptive systems. In a similar vein, examining the shifting temporal dynamics and development trajectories resulting from discontinuous shocks may explain a cluster’s emergence and ultimate long-term renewal. Finally, the strain of research examining the relationship between policy initiatives and cluster development remains sparse. To offer the greatest theoretical and empirical traction, future research should examine policy outcomes aligned with specific stages of cluster evolution and include the relevant levels and scope of analysis. In sum, there is ample opportunity to further explore the complexities and interactions among firms, industries, networks, and institutions evident across the whole of a cluster’s evolution.

Article

Though concern for environmental issues dates back to the 1960s, research and practice in the field of sustainability innovation gained significant attention from academia, practitioners, and NGOs in the early 1990s, and has evolved rapidly to become mainstream. Organizations are changing their business practices so as to become more sustainable, in response to pressure from internal and external stakeholders. Sustainability innovation broadly relates to the creation of products, processes, technologies, capabilities, or even whole business models that require fewer resources to produce and consume, and also support the environment and communities, while simultaneously providing value to consumers and being financially rewarding for businesses. Sustainability innovation is a way of thinking about how to sustain a firm’s growth while sustainably managing depleting natural resources like raw materials, water, and energy, as well as preventing pollution and unethical business practices wherever the firm operates. Sustainability innovation represents a very diverse and dynamic area of scholarship contributing to a wide range of disciplines, including but not limited to general management, strategy, marketing, supply chain and operations management, accounting, and financial disciplines. As addressing sustainability is a complex undertaking, sustainability innovation strategies can be varied in nature and scope depending upon the firm’s capabilities. They may range from incremental green product introductions to radical innovations leading to changes in the way business is conducted while balancing all three pillars of sustainability—economic, environmental, and social outcomes. Sustainability innovation strategies often require deep structural transformations in organizations, supply chains, industry networks, and communities. Such transformations can be hard to implement and are sometimes resisted by those affected. Importantly, as sustainability concerns continue to increase globally, innovation provides a significant approach to managing the human, social, and economic dimensions of this profound society-wide transformation. Therefore, a thorough assessment of the current state of thinking in sustainability innovation research is a necessary starting point from which to improve society’s ability to achieve triple bottom line for current and future generations.

Article

Likoebe Maruping and Yukun Yang

Open innovation is defined as an approach to innovation that encourages a broad range of participants to engage in the process of identifying, creating, and deploying novel products or services. It is open in the sense that there is little to no restriction on who can participate in the innovation process. Open innovation has attracted a substantial amount of research and widespread adoption by individuals and commercial, nonprofit, and government organizations. This is attributable to three main factors. First, open innovation does not restrict who can participate in the innovation process, which broadens the access to participants and expertise. Second, to realize participants’ ideas, open innovation harnesses the power of crowds who are normally users of the product or service, which enhances the quality of innovative output. Third, open innovation often leverages digital platforms as a supporting technology, which helps entities scale up their business. Recent years have witnessed a rise in the emergence of a number of digital platforms to support various open innovation activities. Some platforms achieve notable success in continuously generating innovations (e.g., InnoCentive.com, GitHub), while others fail or experience a mass exodus of participants (e.g., MyStarbucksIdea.com, Sidecar). Prior commentaries have conducted postmortems to diagnose the failures, identifying possible reasons, such as overcharging one side of the market, failing to develop trust with users, and inappropriate timing of market entry. At the root of these and other challenges that digital platforms face in open innovation is the issue of governance. In the article, governance is conceptualized as the structures determining how rigidly authority is exerted and who has authority to make decisions and craft rules for orchestrating key activities. Unfortunately, there is no comprehensive framework for understanding governance as applied to open innovation that takes place on digital platforms. A governance perspective can lend insight on the structure of how open innovation activities on digital platforms are governed in creating and capturing value from these activities, attracting and matching participants with problems or solutions, and monitoring and controlling the innovation process. To unpack the mystery of open innovation governance, we propose a framework by synthesizing and integrating accreted knowledge from the platform governance literature that has been published in prominent journals over the past 10 years. Our framework is built around four key considerations for governance in open innovation: platform model (firm-owned, market, or community), innovation output ownership (platform-owned, pass-through, or shared), innovation engagement model (transactional, collaborative, or embedded), and nature of innovation output (idea or artifact). Further, we reveal promising research avenues on the governance of digital open innovation platforms.

Article

Llewellyn D. W. Thomas and Erkko Autio

The concept of an “ecosystem” is increasingly used in management and business to describe collectives of heterogeneous, yet complementary organizations who jointly create some kind of system-level output, analogous to an “ecosystem service” delivered by natural ecosystems, which extends beyond the outputs and activities of any individual participant of the ecosystem. Due to its attractiveness and elasticity, the ecosystem concept has been applied to a wide range of phenomena by a variety of scholarly perspectives and under varying monikers such as “innovation ecosystems,” “business ecosystems,” “technology ecosystems,” “platform ecosystems,” “entrepreneurial ecosystems,” and “knowledge ecosystems.” This conceptual and application heterogeneity has contributed to conceptual and terminological confusion, which threatens to undermine the utility of the concept in supporting cumulative insight. In this article, we seek to reintroduce some order into this conceptual heterogeneity by reviewing how the ecosystem concept has been applied to variably overlapping phenomena and by highlighting key terminological and conceptual inconsistencies and their sources. We find that conceptual inconsistency in the ecosystem terminology relates to two key dimensions: the “unit” of analysis and the type of “ecosystem service”—that is the ecosystem output collectively generated. We then argue that although there is considerable heterogeneity in application, the concept nevertheless offers promise in its potential to support insights that are distinctive relative to other concepts describing collectives of organizations, such as those of “industry,” “supply chain,” “cluster,” and “network.” We also find that despite such proliferation, the concept nevertheless describes collectives that are distinctive in that they uniquely combine participant heterogeneity, coherence of ecosystem outputs, participant interdependence, and nonhierarchical governance. Based on our identified dimensions of conceptual heterogeneity, we offer a typology of the different ecosystem concepts, thereby helping reorganize this proliferating domain. The typology is based upon three distinct ecosystem outputs—ecosystem-level value offering for a defined audience, the collective generation of business model innovation, and the collective generation of research-based knowledge—and three research emphases that resonate with alternative “units” of analysis—community dynamics, output cogeneration, and interdependence management. Together, these allow us to clearly differentiate between the concepts of innovation ecosystems, business ecosystems, platform ecosystems, technology ecosystems, entrepreneurial ecosystems, and knowledge ecosystems. Based on the three distinct types of ecosystem outputs, our typology identifies three major types of ecosystems: innovation ecosystems, entrepreneurial ecosystems, and knowledge ecosystems. Under the rubric of “innovation ecosystems,” we further distinguish between business ecosystems, modular ecosystems, and platform ecosystems. We conclude by considering innovation ecosystem dynamics, highlighting the important role of digitalization, and reviewing the implications of our model for ecosystem emergence, competition, coevolution, and resilience.

Article

Erik E. Lehmann and Julian Schenkenhofer

The pursuit of economic growth stands out as one of the main imperatives within modern economies. Nevertheless, economies differ considerably in their competitiveness. Theories on the endogeneity of growth agree on the value of knowledge creation and innovativeness to determine a country’s capability to achieve a sustained performance and to adapt to the dynamics of changing environments and faster information flows. To this effect, national institutional regimes shape nation-specific contexts and embed individuals and firms. The resulting incentive structures shape the attitudes and behavior of individuals and firms alike, whose interactions contribute to the accumulation and flow of knowledge among the nodes of their networks. National systems of innovation (NSIs) therefore embody a concept that aims to analyze the national innovation performance of economies. It rests its rationale in the variation of national institutions that shape the diffusion of technologies through the process of shared knowledge creation and the development of learning routines. Both public and private institutions are thought to interact in a given nation-specific institutional context that essentially affects incentive schemes and resource allocation of the involved economic agents in creating, sharing, distributing, absorbing, and commercializing knowledge. To this effect, public policy plays a key role in the NSI through building bridges between these actors, reducing information asymmetries, and providing them with resources from others within the system. The different actors contributing to the creation and diffusion of knowledge within the system are needed to exchange information and provide the engine for sustained economic growth. Universities, research institutes, companies and the individual entrepreneur are in charge of shaping their economic system in a way that resource and skill complementarities are exploited to the mutual benefit.

Article

Samer Faraj and Takumi Shimizu

Online communities (OCs) are emerging as effective spaces for knowledge collaboration and innovation. As a new form of organizing, they offer possibilities for collaboration that extend beyond what is feasible in the traditional hierarchy. OC participants generate new ideas, talk about knowledge, and remix and build on each other’s contributions on a massive scale. OCs are characterized by fluidity in the resources that they draw upon, and they need to manage these tensions in order to sustain knowledge collaboration generatively. OCs sustain knowledge collaboration by facilitating both tacit and explicit knowledge flows. Further, OCs play a key role in supporting and sustaining the knowledge collaboration process that is necessary for open and user innovation. As collective spaces of knowledge flows, OCs are mutually constituted by digital technologies and participants. The future is bright for OC research adopting the knowledge perspective and focusing on how to sustain their knowledge flow.

Article

Jennifer Kuan

Open Innovation, published in 2003, was a ground-breaking work by Henry Chesbrough that placed technology and innovation at the center of attention for managers of large firms. The term open innovation refers to the ways in which firms can generate and commercialize innovation by engaging outside entities. The ideas have attracted the notice of scholars, spawning annual world conferences and a large literature in technology and innovation management (including numerous journal special issues) that documents diverse examples of innovations and the often novel business models needed to make the most of those innovations. The role of business models in open innovation is the focus of Open Business Models, Chesbrough’s 2006 follow-up to Open Innovation. Managers have likewise flocked to Chesbrough’s approach, as the hundreds of thousands of hits from an online search using the term open innovation can attest. Surveys show that the majority of large firms were engaging in open innovation practices in 2017, compared to only 20% in 2003 when Open Innovation was published.

Article

Fariborz Damanpour

Innovation is a complex construct and overlaps with a few other prevalent concepts such as technology, creativity, and change. Research on innovation spans many fields of inquiry including business, economics, engineering, and public administration. Scholars have studied innovation at different levels of analysis such as individual, group, organization, industry, and economy. The term organizational innovation refers to the studies of innovation in business and public organizations. Studies of innovations in organizations are multidimensional, multilevel, and context-dependent. They investigate what external and internal conditions induce innovation, how organizations manage innovation process, and in what ways innovation changes organizational conduct and outcome. Indiscreet application of findings from one discipline or context to another, lack of distinction between generating (creating) and adopting (using) innovations, and likening organizational innovation with technological innovation have clouded the understanding of this important concept, hampering its advancement. This article organizes studies of organizational innovation to make them more accessible to interested scholars and combines insights from various strands of innovation research to help them design and conduct new studies to advance the field. The perspectives of organizational competition and performance and organizational adaptation and progression are introduced to serve as platforms to position organizational innovation in the midst of innovation concepts, elaborate differences between innovating and innovativeness, and decipher key typologies, primary sets of antecedents, and performance consequences of generating and adopting innovations. The antecedents of organizational innovation are organized into three dimensions of environmental (external, contextual), organizational (structure, culture), and managerial (leadership, human capital). A five-step heuristic based on innovation type and process is proposed to ease understanding of the existing studies and select suitable dimensions and factors for conducting new studies. The rationale for the innovation–performance relationship in strands of organizational innovation research, and the employment of types of innovation and performance indicators, is articulated by first-mover advantage and performance gap theory, in conjunction with the perspectives of competition and performance and of adaptation and progression. Differences between effects of technological and nontechnological innovation and stand-alone and synchronous innovations are discussed to articulate how and to what extent patterns of the introduction of different types of innovation could contribute to organizational performance or effectiveness. In conclusion, ideas are proposed to demystify organizational innovation to allure new researches, facilitate their learning, and provide opportunities for the development of new studies to advance the state of knowledge on organizational innovation.

Article

Pankaj Setia, Franck Soh, and Kailing Deng

Organizations are widely building digital platforms to transform operations. Digital platforms represent a new way of organizing, as they leverage technology to interconnect providers and consumers. Using digital technologies, organizations are platformizing operations, as they open their rigid and closed boundaries by interconnecting providers and consumers through advanced application programming interfaces (APIs). Early research examined platformized development of technology products, with software development companies—such as Mozilla Foundation—leading the way. However, contemporary organizations are platformizing nontechnology offerings (e.g., ride-sharing or food delivery). With growing interest in platforms, the basic tenets underlying platformization are still not clear. This article synthesizes previous literature examining platforms, with the aim of examining what platformization is and how and why organizations platformize.

Article

Vinícius Chagas Brasil and J.P. Eggers

In competitive strategy, firms manage two primary (non-financial) portfolios—the product portfolio and the innovation portfolio. Portfolio management involves resource allocation to balance the important tradeoff of risk reduction and upside maximization, with important decisions around the evaluation, prioritization and selection of products and innovation projects. These two portfolios are interdependent in ways that create reinforcing dynamics—the innovation portfolio is the array of potential future products, while the product portfolio both informs innovation strategy and provides inputs to future innovation efforts. Additionally, portfolio management processes operate at two levels, which is reflected in the literature's structure. The first is a micro lens which focuses on management frameworks to boost portfolio performance and success through project-level selection tools. This research has its roots in financial portfolio management, relates closely to research on new product development and marketing product management, and explores the effects of portfolio management decisions on other organizational functions (e.g., operations). The second lens is a macro lens on portfolio management research, which considers the portfolio as a whole and integrates key organizational and competitive concepts such as entry timing, portfolio management resource allocation regimes (e.g., real options reasoning), organizational experience, and the culling of products and projects. This literature aims to set portfolio management as higher level organizational decision-making capability that embodies the growth strategy of the organization. The organizational ability to manage both the product and innovation portfolios connects portfolio management to key strategic organizational capabilities, including ambidexterity and dynamic capabilities, and operationalizes strategic flexibility. We therefore view portfolio management as a source of competitive advantage that supports organizational renewal.

Article

Scientific advance and innovation are major sources of economic growth and are crucial for making development socially and environmentally sustainable. A critical question is: Will private enterprises invest sufficiently in research technological development and innovation and, if not, to what degree and how should governments engage in the support of science, technology, and innovation? While neoclassical economists point to market failure as the main rationale for innovation policy, evolutionary economists point to the role of government in building stronger innovation systems and creating wider opportunities for innovation. Research shows that the transmission mechanisms between scientific advance and innovation are complex and indirect. There are other equally important sources of innovation including experience-based learning. Innovation is increasingly seen as a systemic process, where the feedback from users needs to be taken into account when designing public policy. Science and innovation policy may aim at accelerating knowledge production along well-established trajectories, or it may aim at giving new direction to the production and use of knowledge. It may be focused exclusively on economic growth, or it may give attention to impact on social inclusion and the natural environment. An emerging topic is to what extent national perspectives continue to be relevant in a globalizing learning economy facing multiple global complex challenges, including the issue of climate change. Scholars point to a movement toward transformative innovation policy and global knowledge sharing as a response to current challenges.

Article

John Bryson and Lauren Hamilton Edwards

Strategic planning has become a fairly routine and common practice at all levels of government in the United States and elsewhere. It can be part of the broader practice of strategic management that links planning with implementation. Strategic planning can be applied to organizations, collaborations, functions (e.g., transportation or health), and to places ranging from local to national to transnational. Research results are somewhat mixed, but they generally show a positive relationship between strategic planning and improved organizational performance. Much has been learned about public-sector strategic planning over the past several decades but there is much that is not known. There are a variety of approaches to strategic planning. Some are comprehensive process-oriented approaches (i.e., public-sector variants of the Harvard Policy Model, logical incrementalism, stakeholder management, and strategic management systems). Others are more narrowly focused process approaches that are in effect strategies (i.e., strategic negotiations, strategic issues management, and strategic planning as a framework for innovation). Finally, there are content-oriented approaches (i.e., portfolio analyses and competitive forces analysis). The research on public-sector strategic planning has pursued a number of themes. The first concerns what strategic planning “is” theoretically and practically. The approaches mentioned above may be thought of as generic—their ostensive aspect—but they must be applied contingently and sensitively in practice—their performative aspect. Scholars vary in whether they conceptualize strategic planning in a generic or performative way. A second theme concerns attempts to understand whether and how strategic planning “works.” Not surprisingly, how strategic planning is conceptualized and operationalized affects the answers. A third theme focuses on outcomes of strategic planning. The outcomes studied typically have been performance-related, such as efficiency and effectiveness, but some studies focus on intermediate outcomes, such as participation and learning, and a small number focus on a broader range of public values, such as transparency or equity. A final theme looks at what contributes to strategic planning success. Factors related to success include effective leadership, organizational capacity and resources, and participation, among others. A substantial research agenda remains. Public-sector strategic planning is not a single thing, but many things, and can be conceptualized in a variety of ways. Useful findings have come from each of these different conceptualizations through use of a variety of methodologies. This more open approach to research should continue. Given the increasing ubiquity of strategic planning across the globe, the additional insights this research approach can yield into exactly what works best, in which situations, and why, is likely to be helpful for advancing public purposes.

Article

Pierre-Yves Donzé

The Swiss watch industry has enjoyed uncontested domination of the global market for more than two decades. Despite high costs and high wages, Switzerland is the home of most of the largest companies in this industry. Scholars in business history, economics, management studies, and other social sciences focused on four major issues to explain such success. The first is product innovation, which has been viewed as one of the key determinants of competitiveness in the watch industry. Considerable attention has been focused on the development of electronic watches during the 1970s, as well as the emergence of new players in Japan and Hong Kong. Yet the rebirth of mechanical watches during the early 1990s as luxury accessories also can be characterized as a product innovation (in this case, linked to marketing strategy rather than pure technological innovation). Second, brand management has been a key instrument in changing the identity of Swiss watches, repositioning them as a luxury business. Various strategies have been adopted since the early 1990s to add value to brands by using culture as a marketing resource. Third, the evolution of the industry’s structure emphasizes a deep transformation during the 1980s, characterized by a shift from classical industrial districts to multinational enterprises. Concentration in Switzerland, as well as the relocation abroad of some production units through foreign direct investment (FDI) and independent suppliers, have enabled Swiss watch companies to control manufacturing costs and regain competitiveness against Japanese firms.Fourth, studying the institutional framework of the Swiss watch industry helps to explain why this activity was not fully relocated abroad, unlike most sectors in low-tech industries. The cartel that was in force from the 1920s to the early 1960s, and then the Swiss Made law of 1971, are two major institutions that shaped the watch industry.

Article

For decades researchers have studied various aspects of the technology transfer and commercialization process in universities in hopes of discovering effective methods for enabling more research to leave the university as technologies that benefit society. However, this effort has fallen short, as only a very small percentage of applied research finds its way to the marketplace through licenses to large companies or to new ventures. Furthermore, the reasons for this failure have yet to be completely explained. In some respects, this appears to be an ontological problem. In their effort to understand the phenomenon of university commercialization, researchers tend to reduce the process into its component parts and study each part in isolation. The result is conclusions that ignore a host of variables that interact with the part being studied and frameworks that describe a linear process from invention to market rather than a complex system. To understand how individuals in the technology commercialization system make strategic choices around outcomes, studies have been successful in identifying some units of analysis (the tech transfer office, the laboratory, the investment community, the entrepreneurship community); but they have been less effective at integrating the commercialization process, contexts, behaviors, and potential outcomes to explain the forces and reciprocal interactions that might alter those outcomes. The technology commercialization process that leads to new technology products and entrepreneurial ventures needs to be viewed as a complex adaptive system that operates under conditions of risk and uncertainty with nonlinear inputs and outputs such that the system is in a constant state of change and reorganization. There is no overall project manager managing tasks and relationships; therefore, the individuals in the system act independently and codependently. No single individual is aware of what is going on in any other part of the system at any point in time, and each individual has a different agenda with different metrics on which their performance is judged. What this means is that a small number of decision makers in the university commercialization system can have a disproportionate impact on the effectiveness and success of the entire system and its research outcomes. Critics of reductionist research propose that understanding complex adaptive systems, such as university technology commercialization, requires a different mode of thinking—systems thinking—which looks at the interrelationships and dependencies among all the parts of the system. Combined with real options reasoning, which enables resilience in the system to mitigate uncertainty and improve decision-making, it may hold the key to better understanding the complexity of the university technology commercialization process and why it has not been as effective as it could be.

Article

Nikolaus Franke and Christian Lüthje

Users of products and services, be they user firms or consumers, frequently develop innovations for their own benefit. Such user innovation is a long-existing phenomenon, but it has gained much momentum in the new millennium. The Internet has greatly facilitated connections between creative users, and at the same time cost-effective design and prototyping technologies are making it increasingly feasible for users to develop their own products and services. Users have been found to innovate mainly because they want solutions that best serve their own needs. In general, their innovation activities involve no expectations of monetary profit, being motivated rather by self-rewards (such as fun, positive feelings of altruism, signaling of competence to the community of peers). This explains why users are typically willing to share their innovations without requiring payment. A problem of user innovation is that, since the benefit that others could gain is an externality for users, they lack strong incentives to invest in the active diffusion of their innovations. The consequence of this “diffusion shortfall” is social welfare losses. There are several ways in which producers and service providers can help overcome these problems and benefit from the innovation potential of users at the same time. They can apply the lead user method to actively search for a small group of particularly highly motivated and qualified users, they can outsource product design work to their users via user design toolkits, and they can broadcast innovation challenges to an appropriate crowd of external problem solvers.

Article

Virtual work has become critical to competing in the global information economy for many organizations. Successfully working through technology across time and space, especially on collaborative tasks, however, remains challenging. Virtual work can lead to feelings of isolation, communication and coordination difficulties, and decreased innovation. Researchers attribute many of these challenges to a lack of common ground. Virtual worlds, one type of virtualization technology, offer a potentially promising solution. Despite initial interest, organizational adoption of virtual worlds has been slower than researchers and proponents expected. The challenges of virtual work, however, remain, and research has identified virtual world technology affordances that can support virtual collaboration. Virtual world features such as multi-user voice and chat, persistence, avatars, and three-dimensional environment afford, in particular, social actions associated with successful collaboration. This suggests that the greatest value virtual worlds may offer to organizations is their potential to support virtual collaboration. Organizational scholars increasingly use a technology affordance lens to examine how features of malleable communication technologies influence organizational behavior and outcomes. Technology affordances represent possibilities of action enabled by technology features or combinations of features. Particularly relevant to virtual world technology are social affordances—affordances of social mediating technologies that support users’ social and psychological needs. To be useful to organizations, there must be a match between virtual world technology affordances, organizational practices, and a technology frame or organizing vision. Recent studies suggest a growing appreciation of the influence of physical organizational spaces on individual and organizational outcomes and increasing awareness of the need for virtual intelligence in individuals. This appreciation provides a possible basis for an emerging organizing vision that, along with recent technology developments and societal comfort with virtual environments, may support wider organizational adoption of virtual worlds and other virtualization technologies.