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Article

The arts have played a major role in the development of management theory, practice, and education; and artists’ competencies like creativity, inventiveness, aesthetic appreciation, and a design mindset are increasingly vital for individual and organizational success in a competitive global world. The arts have long been used in teaching to: (a) explore human nature and social structures; (b) facilitate cognitive, socioemotional, and behavioral growth; (c) translate theory into action; (d) provide opportunities for professional development; and (e) enhance individual and systemic creativity and capacities for change. Use of literature and films are curricular mainstays. A review of the history of the arts in management teaching and learning illustrates how the arts have expanded our ways of knowing and defining managerial and leadership effectiveness—and the competencies and training necessary for them. The scholarship of management teaching is large, primarily ‘how-to’ teaching designs and the assessments of them. There is a clear need to expand the research on how and why the arts are and can be used more effectively to educate professionals, enable business growth and new product development, facilitate collaboration and team building, and bring innovative solutions to complex ideas. Research priorities include: the systematic assessments of the state of arts-based management teaching and learning; explorations of stakeholder attitudes and of environmental forces contributing to current educational models and practices; analyses of the learning impact of various pedagogical methods and designs; examining the unique role of the arts in professional education and, especially, in teaching for effective action; mining critical research from education, psychology, creativity studies, and other relevant disciplines to strengthen management teaching and learning; and probing how to teach complex skills like innovative thinking and creativity. Research on new roles and uses for the arts provide a foundation for a creative revisiting of 21st-century management education and training.

Article

There are no clear definitions of entrepreneurship and art. It is therefore difficult to explain and theorize arts entrepreneurship education. Here, what artists think about these issues in the United States, India, and Mexico is explored. Suggestions made by artists were examined and included in the proposed arts entrepreneurship education theory. Artists stated that they do experience lack of business skills that arts entrepreneurship education can help them acquire. These business and aesthetic skill sets are needed to make a living as an artist. The Coleman Fellows Program provided an opportunity to test the arts entrepreneurship theory constructs being proposed. The results from these tests are included the article. The 2017 annual Strategic National Arts Alumni study reported that artists continue to suffer from several skill gaps. Of these, financial, business management, and entrepreneurship skills were identified as the main gaps that continue to plague artists. This is troubling because numerous educational and training efforts have been underway to address these and other skill gaps since at least the early 2000s. However, they have not closed these skill gaps. A modified arts entrepreneurship education theory is proposed in order to do so. Artists who acquire these skills should have a higher probability of success making a living practicing their art form. The article proposes three arts entrepreneurship education theory constructs, namely collaborative pedagogies utilizing the modules infusion method, entrepreneurial universities where these pedagogies can be tested and improved, and effectively managing the commodification of arts. Supporting evidence is provided for the three constructs, along with examples of the modules of entrepreneurship content for infusion. Implications and recommendations for future arts entrepreneurship education programs are provided and discussed.

Article

Corporate governance is a recent concept that encompasses the costs caused by managerial misbehavior. It is concerned with how organizations in general, and corporations in particular, produce value and how that value is distributed among the members of the corporation, its stakeholders. The interrelation of value production and value distribution links the ubiquitous technological aspect (the production of value) with the moral and ethical dimension (the distribution of value). Corporate governance is concerned with this link in general, but more specifically with the moral and ethical dimensions of distributing the generated value among the stakeholders. Value in firms is created by firm-specific investments, and the motivation and coordination of value-enhancing activities and investment is protected by the power concentrated at the pyramidal top of the organization. In modern companies, it is the CEO and the top management who decide how to create value and how to distribute it among the relevant stakeholders. Due to asymmetric information and the imperfect nature of markets and contracts, adverse selection and moral hazard problems occur, where delegated (selected) managers could act in their own interest at the costs of other relevant stakeholders. Corporate governance can be understood as a two-tailed concept. The first aspect is about identifying the (most) relevant stakeholder(s), separating theory and practice into two different and conflicting streams: the stakeholder value approach and the shareholder value approach. The second aspect of the concept is about providing and analyzing different mechanisms, reducing the costs induced by moral hazard and adverse selection effects, and balancing out the motivation and coordination problems of the relevant stakeholders. Corporate governance is an interdisciplinary concept encompassing academic fields such as finance, economics, accounting, law, taxation, and psychology, among others. As countries differ according to their institutions (i.e., legal and political systems, norms, and rules), firms differ according to their size, age, dominant shareholders, or industries. Thus, concepts in corporate governance differ along these dimensions as well. And while the underlying characteristics vary in time, continuously or as a result of an exogenous shock, concepts in corporate governance are dynamic and static, offering a challenging field of interest for academics, policymakers, and firm managers.

Article

Vincenzo Butticè and Massimo G. Colombo

Fundraising has proved difficult for many entrepreneurs and ventures in the early stages of their businesses because of significant information asymmetries with investors and a lack of collateral. In an attempt to overcome such difficulties, since the early 2010s, some entrepreneurs have come to rely on the Internet in order to directly seek funding from the general public, or the “crowd.” The practice of collecting small amounts of capital from the “crowd” of Internet users is called crowdfunding. Crowdfunding research is a relative newcomer to the discipline of entrepreneurial finance. However, the availability of easy-to-access data, the diffusion of this funding channel among entrepreneurs, and increasing policy attention have made crowdfunding one of the most investigated areas of research in entrepreneurial finance. The literature has discussed crowdfunding as more than a simple mean of financing. Crowdfunding also allows entrepreneurs to develop a virtual community of followers, which provides a valuable source of information with which to test and improve early versions of innovative products. Moreover, crowdfunding represents a method of gaining information about market response to a given product and the size of demand for that product, and is a powerful marketing instrument that can be used to increase brand awareness and to promote the arts, social initiatives, and financial inclusion. However, crowdfunding also entails a number of pitfalls for entrepreneurs. In order to collect financial resources from the crowd, entrepreneurs are required to share sensitive information online. This includes information about the entrepreneurial initiative, the team, and the business model they are using. The provision of this information may facilitate product counterfeiting, or the appropriation of the value of the idea by other firms or entrepreneurs. Moreover, crowdfunding entails the risk of social stigma if the funding campaign results in a failure, because information about the performance of the crowdfunding campaign usually remains accessible online. Finally, crowdfunding entails additional challenges related to the management of the crowd of backers after the campaign, since several backers will be active providers of feedback and will interact with the entrepreneurs through direct communication. Despite these disadvantages crowdfunding has become a widely used funding source for entrepreneurs looking for financing for sustainable projects, creative initiatives, and innovative ideas.

Article

Frank Hoy

Family business is a multidisciplinary subject area of critical importance to practitioners. The global volume of family business owners and managers is enormous. The firms are significant components of national economies. Yet they are often underappreciated and have been under-represented in business and economic research. Scholars have the potential for contributing to the survival and prosperity of these firms. The boundaries of the field are ill-defined. Family business scholars are seeking recognition from their colleagues. Opportunities for future research are unlimited.

Article

In the late 1990s, there was considerable interest in national differences in entrepreneurial activity. The Global Entrepreneurship Monitor (GEM) research program was developed to provide harmonized, cross-national measures of participation in business creation; business creation was considered a critical aspect of entrepreneurship. This information was considered important for understanding the national characteristics associated with business creation and its subsequent impact on economic growth. The initial effort involved 10 countries in 1999. By 2014 Adult Population Surveys (APS) had been completed 705 times in 104 countries and with six special samples; this involved 2.3 million individual interviews. While there have been changes in the administrative structure and the focus of the annual global reports, the most significant data collection procedures have been stable since 2002. The GEM APS data sets are currently the only harmonized cross-national comparisons of business creation and business ownership. Designed to provide estimates of the prevalence of both business creation and existing firms, they also allow estimates of the total number of business ventures. GEM data sets are publically available three years after completion, providing a unique resource for assessing factors affecting business creation and its subsequent role in economic growth. Systematic assessments by national experts in participating countries provide measures of the national entrepreneurial framework conditions, complementing a variety of established measures of national economic and political characteristics. There are three distinct features that characterize the GEM initiative: the unique organizational structure, the global reports summarizing annual assessments of entrepreneurial activity, and data sets assembled and made available for public use. The initial organizational structure, a collaborative arrangement among national teams, was replaced by membership in the Global Entrepreneurship Research Association (GERA) in 2004. The annual global reports emphasize comparisons among member countries, the annual national reports the country-specific situations. Both are designed to facilitate reality-based public policy. Data collection for the APS provides harmonized comparisons of business creation across countries and within-country time series. The APS data has made clear the substantial variation among countries, by a factor of 10; that national levels of participation are very stable over time; that business creation is much more prevalent in poorer countries; that all segments of society are active in business creation; and that business creation is an important catalyst for the processes that lead to economic growth. The National Expert Survey (NES) questionnaire data provides information about the nature of the entrepreneurial framework in the GEN countries. There is much to be learned about the relationships between national context, entrepreneurship, and economic growth. The unique information in the GEM data sets should continue to facilitate improved understanding of this important phenomenon.

Article

Entrepreneurship is a critical driver of economic health, industrial rejuvenation, social change, and technological progress. In an attempt to determine how to best support such an important component of society, researchers and practitioners alike continue to ask why some countries, regions, and cities have more entrepreneurship than others. Unfortunately, the answer is not clear. This question is addressed by focusing on location-based support or infrastructure for entrepreneurship. A framework based on a social systems perspective guides this examination by concentrating on three main categories of infrastructure: resource endowments, institutional arrangements, and proprietary functions. Work from the knowledge-based perspective of entrepreneurship, systems of innovation, entrepreneurial ecosystems, and resource dependence literatures is integrated into this framework.

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

Heather A. Haveman and Gillian Gualtieri

Research on institutional logics surveys systems of cultural elements (values, beliefs, and normative expectations) by which people, groups, and organizations make sense of and evaluate their everyday activities, and organize those activities in time and space. Although there were scattered mentions of this concept before 1990, this literature really began with the 1991 publication of a theory piece by Roger Friedland and Robert Alford. Since that time, it has become a large and diverse area of organizational research. Several books and thousands of papers and book chapters have been published on this topic, addressing institutional logics in sites as different as climate change proceedings of the United Nations, local banks in the United States, and business groups in Taiwan. Several intellectual precursors to institutional logics provide a detailed explanation of the concept and the theory surrounding it. These literatures developed over time within the broader framework of theory and empirical work in sociology, political science, and anthropology. Papers published in ten major sociology and management journals in the United States and Europe (between 1990 and 2015) provide analysis and help to identify trends in theoretical development and empirical findings. Evaluting these trends suggest three gentle corrections and potentially useful extensions to the literature help to guide future research: (1) limiting the definition of institutional logic to cultural-cognitive phenomena, rather than including material phenomena; (2) recognizing both “cold” (purely rational) cognition and “hot” (emotion-laden) cognition; and (3) developing and testing a theory (or multiple related theories), meaning a logically interconnected set of propositions concerning a delimited set of social phenomena, derived from assumptions about essential facts (axioms), that details causal mechanisms and yields empirically testable (falsifiable) hypotheses, by being more consistent about how we use concepts in theoretical statements; assessing the reliability and validity of our empirical measures; and conducting meta-analyses of the many inductive studies that have been published, to develop deductive theories.

Article

Robert J. David, Pamela S. Tolbert, and Johnny Boghossian

Institutional theory is a prominent perspective in contemporary organizational research. It encompasses a large, diverse body of theoretical and empirical work connected by a common emphasis on cultural understandings and shared expectations. Institutional theory is often used to explain the adoption and spread of formal organizational structures, including written policies, standard practices, and new forms of organization. Tracing its roots to the writings of Max Weber on legitimacy and authority, the perspective originated in the 1950s and 1960s with the work of Talcott Parsons, Philip Selznick, and Alvin Gouldner on organization–environment relations. It subsequently underwent a “cognitive turn” in the 1970s, with an emphasis on taken-for-granted habits and assumptions, and became commonly known as “neo-institutionalism” in organizational studies. Recently, work based on the perspective has shifted from a focus on processes involved in producing isomorphism to a focus on institutional change, exemplified by studies of the emergence of new laws and regulations, products, services, and occupations. The expansion of the theoretical framework has contributed to its long-term vitality, though a number of challenges to its development remain, including resolving inconsistencies in the different models of decision-making and action (homo economicus vs. homo sociologicus) that underpin institutional analysis and improving our understanding of the intersection of socio-cultural forces and entrepreneurial agency.

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

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

During the last decade, qualitative comparative analysis (QCA) has become an increasingly popular research approach in the management and business literature. As an approach, QCA consists of both a set of analytical techniques and a conceptual perspective, and the origins of QCA as an analytical technique lie outside the management and business literature. In the 1980s, Charles Ragin, a sociologist and political scientist, developed a systematic, comparative methodology as an alternative to qualitative, case-oriented approaches and to quantitative, variable-oriented approaches. Whereas the analytical technique of QCA was developed outside the management literature, the conceptual perspective underlying QCA has a long history in the management literature, in particular in the form of contingency and configurational theory that have played an important role in management theories since the late 1960s. Until the 2000s, management researchers only sporadically used QCA as an analytical technique. Between 2007 and 2008, a series of seminal articles in leading management journals laid the conceptual, methodological, and empirical foundations for QCA as a promising research approach in business and management. These articles led to a “first” wave of QCA research in management. During the first wave—occurring between approximately 2008 and 2014—researchers successfully published QCA-based studies in leading management journals and triggered important methodological debates, ultimately leading to a revival of the configurational perspective in the management literature. Following the first wave, a “second” wave—between 2014 and 2018—saw a rapid increase in QCA publications across several subfields in management research, the development of methodological applications of QCA, and an expansion of scholarly debates around the nature, opportunities, and future of QCA as a research approach. The second wave of QCA research in business and management concluded with researchers’ taking stock of the plethora of empirical studies using QCA for identifying best practice guidelines and advocating for the rise of a “neo-configurational” perspective, a perspective drawing on set-theoretic logic, causal complexity, and counterfactual analysis. Nowadays, QCA is an established approach in some research areas (e.g., organization theory, strategic management) and is diffusing into several adjacent areas (e.g., entrepreneurship, marketing, and accounting), a situation that promises new opportunities for advancing the analytical technique of QCA as well as configurational thinking and theorizing in the business and management literature. To advance the analytical foundations of QCA, researchers may, for example, advance robustness tests for QCA or focus on issues of endogeneity and omitted variables in QCA. To advance the conceptual foundations of QCA, researchers may, for example, clarify the links between configurational theory and related theoretical perspectives, such as systems theory or complexity theory, or develop theories on the temporal dynamics of configurations and configurational change. Ultimately, after a decade of growing use and interest in QCA and given the unique strengths of this approach for addressing questions relevant to management research, QCA will continue to influence research in business and management.

Article

Nydia MacGregor and Tammy L. Madsen

Regulatory shocks, either by imposing regulations or easing them (deregulation), yield abrupt and fundamental changes to the institutional rules governing competition and, in turn, the opportunity sets available to firms. Formally, a regulatory shock occurs when jurisdictions replace one regulatory system for another. General forms of regulation include economic and social regulation but recent work offers a more fine-grained classification based on the content of regulations: regulation for competition, regulation of cap and trade, regulation by information, and soft law or experimental governance. These categories shed light on the types of rules and policies that change at the moment of a regulatory shock. As a result, they advance our understanding of the nature, scope, magnitude, and consequences of transformative shifts in rules systems governing industries. In addition to differences in the content of reforms, the assorted forms of regulatory change vary in the extent to which they disrupt an industry’s state of equilibrium or semi-equilibrium. These differences contribute to diverse temporal patterns or dynamics, an area ripe for further study. For example, a regulatory shock to an industry may be followed by rapid adjustment and, in turn, a new equilibrium state. Alternatively, the effects of a regulatory shock may be more enduring, contributing to ongoing dynamics and prolonging an industry’s convergence to new equilibrium state. As such, regulatory shocks can both stimulate ongoing heterogeneity or promote coherence within and among industries, sectors, organizational fields, and nation states. It follows that examining the content, scope, and magnitude of regulatory shocks is key to understanding their impact. Since conforming to industry regulation (deregulation) increases economic returns, firms attempt to align their policies and behaviors with the institutional rules governing an industry. Thus, regulatory shocks stimulate the evaluation of strategic choices and, in turn, impact the competitive positions of firms and the composition of industries. Following a shock, at least two generic cohorts of firms emerge: incumbents, which are firms that operated in the industry before the change, and entrants, which start up after the change. To sustain a position, entrants must build capabilities from scratch whereas incumbents must replace or modify the practices they developed in the prior regulatory era. Not surprisingly, the ensuing competitive dynamics strongly influence the distribution of profits observed in an industry and the duration of firms’ profit advantages. Our review highlights some of the prominent areas of research inquiry regarding regulatory shocks but many areas remain underexplored. Future work may benefit by considering regulatory shocks as embedded in a self-reinforcing system rather than simply an exogenous inflection in an industry’s evolutionary trajectory. Opportunities also exist for studying how the interplay of industry actors with actors external to an industry (political, social) affects the temporal and competitive consequences of regulatory shocks.

Article

Entrepreneurial activity is facilitated by the ties that connect founders and their venture to a broader network of actors. This insight on the value of social capital has been enriched by a large body of research that builds on core concepts of network content, governance, and structure. Network content refers to the resources, information and social support that is exchanged or flows between actors. Governance encompasses the mechanisms that organize and regulate the exchange. Network structure refers to broader patterns created from the relationships between actors. With these building blocks, key findings that have emerged over 30 years of research can be organized into two domains: how networks influence entrepreneurial outcomes and how networks develop over the entrepreneurial process. Core findings regarding the performance consequences of social capital underscore its benefits while identifying limitations due to decreasing returns to growing and maintaining a large network or to contingencies tied to the stage of the venture’s growth. Our understanding of the sources of network evolution and the resulting patterns have also developed significantly. As a motor of network change, scholars have emphasized the goal-oriented behavior of the entrepreneur, but recognize social relationships also engender mutual concern, obligation, and emotional attachment. From a focus on founder and founding team ties to start-up, small firm networks, the literature now spans multiple levels and accounts for contextual variation between industries and institutional environments. Advances within each of these domains of inquiry have led to rich insights and greater conceptual complexity. Future research opportunities will arise that leverage cross-fertilization of the process and performance research streams.

Article

Alexander Bolinger and Mark Bolinger

There is currently great enthusiasm for entrepreneurship education and the economic benefits that entrepreneurial activity can generate for individuals, organizations, and communities. Beyond economic outcomes, however, there is a variety of social and emotional costs and benefits of engaging in entrepreneurship that may not be evident to students nor emphasized in entrepreneurship courses. The socioemotional costs of entrepreneurship are consequential: on the one hand, entrepreneurs who pour their time and energy into new ventures can incur costs (e.g., ruptured personal and professional relationships, decreased life satisfaction and well-being, or strong negative reactions such as grief) that can often be as or more personally disruptive and enduring than economic costs. On the other hand, the social and emotional benefits of an entrepreneurial lifestyle are often cited as intrinsically satisfying and as primary motivations for initiating and sustaining entrepreneurial activity. The socioemotional aspects of entrepreneurship are often poorly understood by students, but highlighting these hidden dimensions of entrepreneurial activity can inform their understanding and actions as prospective entrepreneurs. For instance, entrepreneurial passion, the experience of positive emotions as a function of engaging in activities that fulfill one’s entrepreneurial identity, and social capital, whereby entrepreneurs build meaningful relationships with co-owners, customers, suppliers, and other stakeholders, are two specific socioemotional benefits of entrepreneurship. There are also several potential socioemotional costs of entrepreneurial activity. For instance, entrepreneurship can involve negative emotional responses such as grief and lost identity from failure. Even when an entrepreneur does not fail, the stress of entrepreneurial activity can lead to sleep deprivation and disruptions to both personal and professional connections. Then, entrepreneurs can identify so closely and feel so invested that they experience counterproductive forms of obsessive passion that consume their identities and impair their well-being.

Article

Briance Mascarenhas and Megan Mascarenhas

A strategic group is defined as a set of firms within an industry pursuing a similar strategy. The strategic group concept emerged with much promise over 40 years ago. Research on strategic groups over time in a broad variety of settings has sought to clarify their theoretical and empirical properties. These research findings are gradually being translated into practical managerial guidance, so that the strategic group concept can be understood, operationalized, and used productively by managers. Two main approaches exist for identifying strategic groups—a ground-up approach, using disaggregated data, and a top-down, using cognition. Once identified, managerial insights can be derived from clarifying a strategic group’s profile. Firm membership in a group helps to uncover immediate and more distant types of competitors. Group profitability differences reveal the more rewarding and less attractive areas within an industry, as well as identify the lower-return groups from where firm exits are likely to occur. Group dynamics reflect competitive and cooperative behavior within and between groups. Several promising areas for future research on strategic groups to improve understanding and practice of strategy.

Article

In the early 1990s business creation was receiving a great deal of attention after it was clear that new firms were a major source of job creation. There was not, however, reliable data on the prevalence of persons participating in firm creation, what they would do to implement new ventures, or the proportion of start-up efforts that became profitable businesses. This hiatus led to the development of longitudinal studies of the entrepreneurial process; 14 projects have now been implemented in 12 countries. The Panel Study of Entrepreneurial Dynamics (PSED) protocol was designed to provide estimates of the prevalence of individuals involved in business creation and the presence of pre-profit, start-up ventures; data on the major activities undertaken to implement a new firm; and track the proportion that completed the transition from start-up to profitable new firm. A number of challenges were involved in implementing the research program, including the development of efficient procedures for identifying representative samples of nascent entrepreneurs and criteria for determining the dates of entry into the start-up process, the transition to a profitable business, and disengagement from the initiative. Data collection is a three-stage process. The initial stage is identifying nascent entrepreneurs in a representative sample of adults. The second are detailed interviews on the start-up team and activity related to creating a new venture. The third stage is follow-up interviews completed to determine the outcome of the start-up efforts. A large number of scholars have been involved in development of the interviews and the PSED data sets have considerable information on the perspectives, activities, and strategies of those involved in the start-up process. Since the initial data sets were made available 15 years ago, there has been considerable research utilizing PSED data sets. One major finding, however, is that the firm creation process is much more diverse and complicated than had been expected. There are substantial research opportunities to be explored. A review of the major features of the PSED protocol and a summary of the existing data sets provides background that will facilitate additional analysis of the firm creation process. Four data sets (Australia, Sweden, and U.S. PSED I & II) are now in the public domain. Critical features of the start-up process have been consolidated and harmonized in a five-cohort, four country data set which is also available.

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.