41-60 of 131 Results

Article

Rolv Petter Amdam

Executive education, defined as consisting of short, intensive, non-degree programs offered by university business schools to attract people who are in or close to top executive positions, is a vital part of modern management education. The rationale behind executive education is different from that of the degree programs in business schools. While business schools enroll students to degree programs based on previous exams, degrees, or entry tests, executive education typically recruits participants based on their positions—or expected positions—in the corporate hierarchy. While degree programs grade their students and award them degrees, executive education typically offers courses that do not have exams or lead to any degree. Executive education expanded rapidly in the United States and globally after Harvard Business School launched its Advanced Management Program in 1945. In 1970, around 50 university business schools in the United States and business schools in at least 43 countries offered intense executive education programs lasting from three to 18 weeks. During the 1970s, business schools that offered executive education organized themselves into an association, first in the United States and later globally. From the 1980s, executive education experienced competition from the corporate universities organized by corporations. This led the business schools to expand executive education in two directions: open programs that organized potential executives from a mixed group of companies, and tailor-made programs designed for individual companies. Despite being an essential part of the activities of business schools, few scholars have conducted research into executive education. Extant studies have been dominated by a focus on executive education in the context of the rigor-and-relevance debate that has accompanied the development of management education since the early 1990s. Other topics that are touched upon in research concern the content of courses, the appropriate pedagogical methods, and the effect of executive education on personal development. The situation paves the way for some exciting new research topics. Among these are the role of executive education in creating, maintaining, and changing the business elite, the effect of executive education on socializing participants for managerial positions, and women and executive education.

Article

Felice B. Klein, Kevin McSweeney, Cynthia E. Devers, Gerry McNamara, and Spenser Blosser

Scholars have devoted significant attention to understanding the determinants and consequences of executive compensation. Yet, one form of compensation, executive severance agreements, has flown under the radar. Severance agreements specify the expected payments and benefits promised executives, upon voluntary or involuntary termination. Although these agreements are popular among executives, critics continually question their worth. Yet severance agreements potentially offer three important (but less readily recognized) strategic benefits. First, severance agreements are viewed as a means of mitigating the potential risks associated with job changes; thus, they can serve as a recruitment tool to attract top executive talent. Second, because severance agreements guarantee executives previously specified compensation in the event of termination, they can help limit the downside risk naturally risk-averse executives face, facilitating executive-shareholder interest alignment. Third, severance agreements can aid in firm exit, as executives and directors are likely to be more open to termination, in the presence of adequate protection against the downside. Severance agreements can contain provisions for ten possible termination events. Three events refer to change in control (CIC), which occurs under a change in ownership. These are (1) CIC without termination, (2) CIC with termination without cause, and (3) CIC with termination for cause. Cause is generally defined by events such as felony, fraud, embezzlement, neglect of duties, or violation of noncompete provisions. Additional events include (4) voluntary retirement, (5) resignation without good reason, (6) voluntary termination for good reason, (7) involuntary termination without cause, (8) involuntary termination with cause, (9) death, and (10) disability. Voluntary retirement and resignation without good reason occurs when CEOs either retire or leave under their own volition, and voluntary termination with good reason occurs in response to changes in employment terms (e.g., relocation of headquarters). Involuntary termination refers to termination due to any reason not listed above and is often triggered by unsatisfactory performance. Although some prior work has addressed the antecedents, consequences, and moderators of severance, the findings from this literature remain unclear, as many of the results are mixed. Future severance scholars have the opportunity to further clarify these relationships by addressing how severance agreements can help firms attract, align the interests of, and facilitate the exit of executives.

Article

Over the last three decades, service-learning has become a well-known experiential learning pedagogy in both management education and higher education more broadly. This popularity is observed in the increasing number of peer-reviewed publications on service-learning in management and business education journals, and on management education topics within higher education journals focused on civic engagement and community-based teaching and learning. In this field of study, it is known that service-learning can result in positive outcomes for students, faculty, and community members. In particular, for students, positive results are related to mastery of course content and group process skills like teamwork and communication, leadership, and diversity awareness. Despite the rise in scholarship, service-learning instructors still face several challenges in the area of best practice standards, fostering deep and cohesive partnerships, and managing institutional pressures that disincentivize engaged teaching practices. With constantly evolving challenges in management education, continued research is needed to understand a variety of service-learning facets such as platforms (face-to-face, hybrid, and virtual learning), populations (graduate vs. undergraduate populations and adult vs. traditional college-age learners), measurement (how to assess university-community partnerships and faculty instruction), and which institutional policies and procedures can enable and reward community-engaged teaching and learning approach.

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

Keith Murnighan* and Dora Lau

Group faultlines are hypothetical dividing lines that may split a group into subgroups based on one or more attributes. An example of a strong faultline is a group of two young female Asians and two senior male Caucasians. Members’ alignment of age, sex, and ethnicity facilitates the formation of two homogeneous subgroups. On the other hand, when a group consists of a young female Asian, a young male Caucasian, a senior female Caucasian, and a senior male Asian, the group faultline is considered weak because subgroups, regardless of how they are formed, are diverse. As a relatively new form of group compositional pattern, the group faultline is associated with subgroup formation, and these subgroups, rather than the whole group, can easily become the focus of attention. When members strive to obtain more resources and protect their subgroups, between-subgroup conflict, behavioral disintegration, lack of trust, lack of willingness to share information, and communication challenges are likely. As a result, group performance is often negatively affected, and sometimes groups may even be dissolved. These results were repeatedly found in studies of experimental groups, ad-hoc project groups, organizational teams, top management teams, global virtual teams, family businesses, international joint ventures, and strategic alliances.

Article

In such a complex and well-researched domain as decision support systems (DSS), with a long history of authors making insightful contributions since the 1960’s, it is critical for researchers, especially those less experienced, to have a broad knowledge of the seminal work that has been carried out by prior generations of researchers. This can serve to avoid proposing research questions which have been considered many times before, without having consideration for the answers which have been put forward by previous scholars, thereby reinventing the wheel or “rediscovering” findings about the life of organizations that have been presented long before. The study of human and managerial decision-making is also characterized by considerable depth and seminal research going back to the beginning of the 20th century, across a variety of fields of research including psychology, social psychology, sociology or indeed operations research. Inasmuch as decision-making and decision support are inextricably linked, it is essential for researchers in DSS to be very familiar with both stream of research in their full diversity so they are able to understand both what activity is being supported and how to analyze requirements for developing decision support artefacts. In addition, whilst the area of decision support has sometimes been characterized by technology-based hype, it is critical to recognize that only a clear focus on the thinking and actions of managers can provide decisive directions for research on their decision support needs. In this article, we consider first the characteristics of human cognition, before concentrating on the decision-making needs of managers and the lessons that can be derived for the development of DSS.

Article

Elisabeth Anna Guenther, Anne Laure Humbert, and Elisabeth Kristina Kelan

Gender research goes beyond adding sex as an independent, explanatory category. To conduct gender research in the field of business and management, therefore, it is important to apply a more sophisticated understanding of gender that resonates with contemporary gender theory. This entails taking the social construction of gender and its implications for research into consideration. Seeing gender as a social construct means that the perception of “women” and “men,” of “femininity/ties” and “masculinity/ties,” is the outcome of an embodied social practice. Gender research is commonly sensitive to notions of how power is reproduced and challenges concepts such as “hegemonic masculinity” and “heteronormativity.” The first highlights power relations between gender groups, as well as the different types of existing masculinities. The latter emphasizes the pressure to rely on a binary concept of “women” and “men” and how this is related to heterosexuality, desire, and the body. Gender research needs to avoid the pitfalls of a narrow, essentialist concept of “women” and “men” that draws on this binary understanding of gender. It is also important to notice that not all women (or men) share the same experiences. The critique of Black feminists and scholars from the global South promoted the idea of intersectionality and postcolonialism within gender research. Intersectionality addresses the entanglement of gender with other social categories, such as age, class, disability, race, or religion, while postcolonial approaches criticize the neglect of theory and methodology originating in the global South and question the prevalence of concepts from the global North. Various insights from gender theory inform business and management research in various ways. Concepts such as the “gendered organization” or “inequality regime” can be seen as substantial contributions of gender theory to organization theory. Analyzing different forms of masculinities and exploring ways in which gender is undone within organizations (or whether a supposedly gender-neutral organization promotes a masculine norm) can offer thought-provoking insights into organizational processes. Embracing queer theory, intersectionality, and postcolonial approaches in designing research allows for a broader image of the complex social reality. Altogether management studies benefit from sound, theoretically well-grounded gender research.

Article

A geographic information system (GIS) is a system designed to capture, store, organize, and present spatial data, which is referenced to locations on the Earth. Locational information is of value for a wide range of human activities for decision-making relating to these activities. As spatial data is relatively complex, GIS represents a challenging computer application that has developed later than some other forms of computer systems. GIS uses spatial data for a region of the Earth; such regional data are of interest to a wide range of users whose activities take place in that region, and so many users in otherwise disconnected domains share spatial data. The availability and cost of spatial data are important drivers of GIS use, and the sourcing and integration of spatial data are continuing research concerns. GIS use now spans a wide range of disciplines, and the diversity created is one of the obstacles to a well-integrated research field. Location analysis is the use of GIS for general-purpose analysis to determine the preferred geographic placement of human activities. Location analytics uses spatial data and quantitative spatial models to support decision-making, including location analysis. The growth of location analytics reflects the increasing amounts of data now available owing to new data collection technologies such as drones and because of the massive amounts of data collected by the use of mobile devices like smartphones. Location analytics allow many valuable new services that play an important role in new developments such as smart cities. Location analytics techniques potentially allow the tracking of individuals, and this raises many ethical questions, however useful the service provided; therefore, issues related to privacy are of increasing concern to researchers.

Article

Carol T. Kulik and Belinda Rae

The “glass ceiling” metaphor represents the frustration experienced by women in the 1980s and 1990s who entered the workforce in large numbers following equal opportunity legislation that gave them greater access to education and employment. After initial success in attaining lower management positions, the women found their career progress slowing as they reached higher levels of their organizations. A formal definition of the glass ceiling specifies that a female disadvantage in promotion should accelerate at the highest levels of the organization, and researchers adopting this formal definition have found mixed evidence for glass ceilings across organizations and across countries. Researchers who have expanded the glass ceiling definition to encompass racial minorities have similarly found mixed results. However, these mixed results do not detract from the metaphor’s value in highlighting the stereotype-based practices that embed discrimination deep within organizational structures and understanding why women continue to be underrepresented in senior organizational roles around the world. In particular, researchers investigating the glass ceiling have identified a variety of obstacles (including glass cliffs, glass walls, and glass doors) that create a more complete understanding of the barriers that women experience in their careers. As organizations offer shorter job ladders and less job security, the career patterns of both women and men are exhibiting more downward, lateral, and static movement. In this career context, the glass ceiling may no longer be the ideal metaphor to represent the obstacles that women are most likely to encounter.

Article

Clara Kulich and Michelle K. Ryan

A wealth of research has previously shown that gender stereotypes and discrimination keep women from climbing the corporate ladder. However, women who do break through the “glass ceiling” are likely to face new barriers. Research on the glass cliff phenomenon shows that, when women reach positions of power, they tend to do so in circumstances of crisis and instability. A number of archival, experimental, and qualitative studies have demonstrated that women are more likely to rise in the professional hierarchy in difficult, and for these women, potentially harmful, situations. For example, compared to their male peers, women are seen as more desirable for managerial or political leadership positions in times of instability and crises, or following scandals. Such appointments expose women to a higher risk of failure, criticism, and psychological distress, thus a danger of falling off an “invisible” cliff.

Article

Jawad Syed and Memoona Tariq

Diversity management refers to organizational policies and practices aimed at recruiting, retaining, and managing employees of diverse backgrounds and identities, while creating a culture in which everybody is equally enabled to perform and achieve organizational and personal objectives. In a globalized world, there is a need for contextual and transnational approaches to utilize the benefits that global diversity may bring as well as the challenges that organizations may face in managing a diverse workforce. In particular, it is important to take into account how diversity is theorized and managed in non-Western contexts, for example in BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) and Muslim-majority countries. The literature confirms the need for organizational efforts to be focused on engaging with and managing a heterogeneous workplace in ways that not only yield sustainable competitive advantage but also are contextually and socially responsible. Organizations today are expected to take positive action, beyond legal compliance, to ensure equal access, employment and promotion opportunities, and also to ensure that diversity programs make use of employee differences, and contribute to local as well as global communities.

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

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

Corporate governance is a central issue in business and economics. However, governance in financial institutions is more complicated than in other fields because of the nature of financial services and instruments. Financial organizations are similar to other businesses in terms of their purposes of establishment, but confidence in management and complex risk structures are more important in financial organizations than in other businesses. In financial institutions, there are various areas in which problems arise that are related to corporate governance, including the agency problem and stakeholder protection. The importance of good governance for sound performance of financial institutions was reconfirmed during the 2008 financial crisis, raising the need to understand the agency problems and the efficiency of various corporate governance mechanisms in mitigating them. International organizations, such as the Organisation for Economic Co-operation and Development, the Basel Committee, the International Finance Corporation, and the International Organization of Securities Commissions, have been working with regulators and policy makers to improve corporate governance practices both in nonfinancial and financial institutions. Corporate governance, especially in financial institutions, is essential in guaranteeing a sound financial system, capital markets, and sustainable economic growth. Governance weaknesses at financial institutions can result in the transmission of problems across the finance sector and the economy. Consequently, the effectiveness of governance mechanisms of financial institutions and capital markets after financial crises had significant importance in a period that witnessed an intensive discussion of corporate governance issues with new regulations and the related academic works.

Article

Tracking with Japan’s macroeconomic fortunes since World War II, global interest in Japanese management practices emerged in the 1950s with the start of Japan’s “miracle economy,” soared in the 1980s as Japanese industrial exports threatened manufacturers around the world, and declined after 1990 as Japan’s growth stalled. Japanese techniques, especially in labor and production management, fascinated Western scholars and practitioners in their striking divergence from U.S. and European conventions and their apparent advantages in creating harmonious, highly productive workplaces. Two reductive approaches to the origins of Japan’s distinctive management methods―one asserting they were the organic outgrowth of Japan’s unique cultural heritage, the other stressing Japan’s proficiency at emulating and adapting American models—came to dominate the academic and popular literature. As historical analysis reveals, however, such stylized interpretations distort the complex evolution of Japanese industrial management over the past century and shed little light on the current debates over the potential convergence of Japanese practices and American management norms. Key features of the Japanese model of labor management—“permanent” employment, seniority-based wages and promotions, and enterprise unions—developed between the late 1800s and the 1950s from the contentious interaction of workers, managers, and government bureaucrats. The distinctive “Japanese Employment System” that emerged reflected both employers’ priorities (for low labor turnover and the affirmation of managerial authority in the workplace) and labor’s demands (for employment security and respect as full members of the firm). Since 1990, despite the widespread perception that Japanese labor management is inefficient and inflexible by international standards, many time-honored practices have endured, as Japanese corporations have pursued adaptive, incremental change rather than precipitous convergence toward a more market-oriented American model. The distinguishing elements of Japanese production management—the “lean production” system and just-in-time manufacturing pioneered in Toyota factories, innovative quality-control practices—also evolved slowly over the first century of Japanese industrialization. Imported management paradigms (especially Frederick Taylor’s scientific management) had a profound long-term impact on Japanese shop-floor methods, but Japanese managers were creative in adapting American practices to Japan’s realities and humanizing the rigid structures of Taylorism. Japanese production management techniques were widely diffused internationally from the 1980s, but innovation has slowed in Japanese manufacturing in recent decades and Japanese firms have struggled to keep pace with latest management advances from the United States and Europe. In sum, the histories of Japanese labor and production management cannot be reduced to simple narratives of cultural determinism, slavish imitation, or inevitable convergence. Additional research on Japanese practices in a wide range of firms, industries, sectors, regions, and historical periods is warranted to further nuance our understanding of the complex evolution, diverse forms, and contingent future of Japanese management.

Article

Hypothesis testing is an approach to statistical inference that is routinely taught and used. It is based on a simple idea: develop some relevant speculation about the population of individuals or things under study and determine whether data provide reasonably strong empirical evidence that the hypothesis is wrong. Consider, for example, two approaches to advertising a product. A study might be conducted to determine whether it is reasonable to assume that both approaches are equally effective. A Type I error is rejecting this speculation when in fact it is true. A Type II error is failing to reject when the speculation is false. A common practice is to test hypotheses with the type I error probability set to 0.05 and to declare that there is a statistically significant result if the hypothesis is rejected. There are various concerns about, limitations to, and criticisms of this approach. One criticism is the use of the term significant. Consider the goal of comparing the means of two populations of individuals. Saying that a result is significant suggests that the difference between the means is large and important. But in the context of hypothesis testing it merely means that there is empirical evidence that the means are not equal. Situations can and do arise where a result is declared significant, but the difference between the means is trivial and unimportant. Indeed, the goal of testing the hypothesis that two means are equal has been criticized based on the argument that surely the means differ at some decimal place. A simple way of dealing with this issue is to reformulate the goal. Rather than testing for equality, determine whether it is reasonable to make a decision about which group has the larger mean. The components of hypothesis-testing techniques can be used to address this issue with the understanding that the goal of testing some hypothesis has been replaced by the goal of determining whether a decision can be made about which group has the larger mean. Another aspect of hypothesis testing that has seen considerable criticism is the notion of a p-value. Suppose some hypothesis is rejected with the Type I error probability set to 0.05. This leaves open the issue of whether the hypothesis would be rejected with Type I error probability set to 0.025 or 0.01. A p-value is the smallest Type I error probability for which the hypothesis is rejected. When comparing means, a p-value reflects the strength of the empirical evidence that a decision can be made about which has the larger mean. A concern about p-values is that they are often misinterpreted. For example, a small p-value does not necessarily mean that a large or important difference exists. Another common mistake is to conclude that if the p-value is close to zero, there is a high probability of rejecting the hypothesis again if the study is replicated. The probability of rejecting again is a function of the extent that the hypothesis is not true, among other things. Because a p-value does not directly reflect the extent the hypothesis is false, it does not provide a good indication of whether a second study will provide evidence to reject it. Confidence intervals are closely related to hypothesis-testing methods. Basically, they are intervals that contain unknown quantities with some specified probability. For example, a goal might be to compute an interval that contains the difference between two population means with probability 0.95. Confidence intervals can be used to determine whether some hypothesis should be rejected. Clearly, confidence intervals provide useful information not provided by testing hypotheses and computing a p-value. But an argument for a p-value is that it provides a perspective on the strength of the empirical evidence that a decision can be made about the relative magnitude of the parameters of interest. For example, to what extent is it reasonable to decide whether the first of two groups has the larger mean? Even if a compelling argument can be made that p-values should be completely abandoned in favor of confidence intervals, there are situations where p-values provide a convenient way of developing reasonably accurate confidence intervals. Another argument against p-values is that because they are misinterpreted by some, they should not be used. But if this argument is accepted, it follows that confidence intervals should be abandoned because they are often misinterpreted as well. Classic hypothesis-testing methods for comparing means and studying associations assume sampling is from a normal distribution. A fundamental issue is whether nonnormality can be a source of practical concern. Based on hundreds of papers published during the last 50 years, the answer is an unequivocal Yes. Granted, there are situations where nonnormality is not a practical concern, but nonnormality can have a substantial negative impact on both Type I and Type II errors. Fortunately, there is a vast literature describing how to deal with known concerns. Results based solely on some hypothesis-testing approach have clear implications about methods aimed at computing confidence intervals. Nonnormal distributions that tend to generate outliers are one source for concern. There are effective methods for dealing with outliers, but technically sound techniques are not obvious based on standard training. Skewed distributions are another concern. The combination of what are called bootstrap methods and robust estimators provides techniques that are particularly effective for dealing with nonnormality and outliers. Classic methods for comparing means and studying associations also assume homoscedasticity. When comparing means, this means that groups are assumed to have the same amount of variance even when the means of the groups differ. Violating this assumption can have serious negative consequences in terms of both Type I and Type II errors, particularly when the normality assumption is violated as well. There is vast literature describing how to deal with this issue in a technically sound manner.

Article

Immigrant entrepreneurs are different, and they are everywhere. They can be unambiguously distinguished from entrepreneurs without a migration background. They operate under distinct conditions and respond to unique opportunities and challenges. They have specific motivational, economic, and social resources at their disposal, for example, ethnic solidarity and international networks. Their knowledge of languages and cultures, as well as the high pressure to integrate themselves into a new society, can be factors that stimulate entrepreneurship and innovation. It is hard to find countries with no immigrant entrepreneurs. In many places like the United States, Canada, or South East Asia, they play a substantial economic role. The ubiquity, dynamism, and significance of immigrant entrepreneurs has led to a spate of research projects since the 1990s, especially by economic sociologists and ethnologists, but also by management scholars and historians. On the basis of their work, the article distinguishes six different ideal types of immigrant entrepreneurs, even though these categories are neither clear-cut nor mutually exclusive. Necessity entrepreneurs react to blocked careers in other areas and often set up small, precarious businesses, out of which in exceptional cases more viable companies emerge. Diaspora merchants are part of commercial networks of people with the same ethnic background who live in foreign countries and trade with each other. Transnational entrepreneurs are not necessarily part of networks and do not always engage in mercantile activities. This category also encompasses individual actors and industrial activities. They are characterized by the ability to mobilize resources in several countries and facilitate activities between different countries. Middleman minorities stand between the majority society and third parties, often minorities. They fill niches that are left by indigenous businesses, which consider these areas as unattractive. Entrepreneurs in ethnic enclave economies live and work with their co-ethnics in neighborhoods defined by their group. Their main function is to cater to their own communities, often with ethnic products such as food or publications from their countries of origin. Refugee entrepreneurs leave their home country involuntarily, often driven out by violence and expropriation. In most cases their emigration is unprepared. Starting conditions in the country of destination are unfavorable. Conversely, the pressure for social integration is pronounced and can act as an impulse for self-employment. There are, however, cases in which refugees are consciously patronized or even summoned by the governments of the receiving countries, turning them into a highly privileged group.

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

Yao Sun and Ann Majchrzak

Starting from early 21st century, companies increasingly use open innovation challenges to generate creative solutions to business problems. This revolution in business models and management strategy reflects the evolution supported by new technology. Employing this new strategic model, companies seek to innovate in a wide variety of areas, such as clothes designs, photography solutions, business plans, and film production. Contrary to closed innovation through which companies develop creative ideas internally, innovation challenges are catalyzed by socioeconomic changes such as the rapid advancement of information technologies, increased labor division, as well as ever-expanding globalization. Going hand in hand are trends such as outsourcing, occurring in parallel in the management area, which makes companies more agile and flexible. Multifaceted and multidimensional, open innovation challenges consist of various activities such as inbound innovation (acquiring and sourcing), outbound innovation (selling and revealing), or a compound mix of these two forms. It also pertains to complementary assets, absorptive capacity, organizational exploration, and exploitation. In an attempt to determine how to best support such an important component of society, scholars and practitioners continue to pursue effective innovation challenge architecture (the art or practice that guides participants’ interactions and exchange) that allows open collaboration among the crowd, as well as an approach for incorporating such architecture into technological platforms in order to improve the crowd’s creativity. This issue is addressed by focusing on existing research that delineates various types of effective architecture of innovation challenges. A theory-based framework guides this examination, and work from various scholarly perspectives of innovation challenges, knowledge management, motivated knowledge sharing, and crowdsourcing are 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.