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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

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

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

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

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.