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.
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.
Kathleen R. Allen
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.