Technology and Innovation Management

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.

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.

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.

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.

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Business and Management. Please check back later for the full article.

Scientific advance and innovation are major sources of economic growth and are crucial for making social and environmental development sustainable. A critical question is if private enterprises invest sufficiently in research and development and, if not, to what degree and how governments should engage in the support of science 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 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 the impact on social inclusion and the natural environment. An emerging topic is the extent to which national perspectives continue to be relevant in a globalizing learning economy facing multiple global complex challenges, including the issue of global warming. Scholars point to a movement toward transformative innovation policy and global knowledge sharing as a response to current challenges.

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.

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.

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.