21-40 of 268 Results

Article

Blame: Stakeholder Judgments That Impact Organizations and Entrepreneurs  

Varkey Titus and Izuchukwu Mbaraonye

Blame is a feature of everyday life, whether or not that blame is directed toward an individual for a willful act of moral transgression, an entrepreneur for taking reckless action that puts the venture and its employees at risk, or a company for the violation of some social norm. Blame identifies morally wrong behavior and has the power to pressure individuals to adhere to a set of norms. More broadly, blame is worthy of scholarly consideration because it is a reality for organizations and the individuals who lead them. Blame is multifaceted because it entails psychological, social, and legal issues. Historically, psychological theories of blame emphasized the rational and prescriptive—how blame attribution processes ought to occur to produce an accurate blame attribution, for example. Over time, psychological theories started to incorporate nonrational elements—such as how socially attractive the potentially blameworthy is, whether the blameworthy engage in “positive” or “negative” actions that are unrelated to the blameworthy act, and so forth. Blame becomes more complicated when it moves from a specific individual (e.g., an entrepreneur) to an aggregate group (a venture) or an abstract entity (a corporation). The aggregation of blame creates an apportionment problem in that it is unclear who within a group ought to be blamed. This complication is further illustrated in the court of law. For instance, courts in the United States have struggled to consistently judge cases of corporate criminal liability due, in part, to the difficulty of knowing how to assign blame to an abstract entity. Part of the challenge relates to establishing a criminal “state of mind” to a corporation, and the broader question whether a corporation can even have such a state of mind (or if that state of mind resides in its leaders, employees, etc.). Management research on blame is limited. Existing work examines blames-shifting tactics, such as scapegoating, wherein organizations place blame on specific organizational actors who may or may not have any direct connection to the blameworthy event. Importantly, blame attributions can flow both ways: employees may sometimes blame the broader organization, despite the employees’ involvement in the blameworthy act. Given the complexities of blame, entrepreneurs face unique blame-related challenges at different points of their venture’s life cycle. At early stages of the life cycle, blameworthy acts are unlikely to have significant societal impact, and attributions are relatively simple due to the minimal number of actors involved in the venture. As the venture grows, the impact of a blameworthy act grows in magnitude, as does the difficulty of accurately apportioning blame for the act among the numerous actors involved. If the venture eventually adopts a formal corporate structure, it also adopts corporate characteristics such as dispersed decision-making processes, a board of directors that are meant to provide some level of oversight, and so forth. This formal corporate structure introduces the challenge of establishing a “state of mind” for a blameworthy act. Ultimately, blame affects entrepreneurs, their ventures, and the corporations that eventually grow from them, and is worth further scholarly investigation.

Article

Board Interlocks and Diversification Strategies  

Christine Shropshire

The board of directors serves multiple corporate governance functions, including monitoring management, providing oversight on strategic issues, and linking the organization to the broader external environment. Researchers have become increasingly interested in board interlocks and how content transmitted via these linkages shapes firm outcomes, such as corporate structure and strategies. As influential mechanisms to manage environmental uncertainty and facilitate information exchange, Board interlocks are created by directors who are affiliated with more than one firm via employment or board service and allow the board to capture a diversity of strategic experiences. One critical corporate decision that may be influenced by interlocks and strategic diffusion is diversification (i.e., in which products and markets to compete). Directors draw on their own experiences with diversification strategies at other firms to help guide and manage ongoing strategic decision-making. There is broad scholarship on interlocks and the individuals who create them, with extant research reporting that some firms are more likely to imitate or learn from their interlock partners than others. Prior findings suggest that the conditions under which information is transmitted via interlock, such as an individual director’s experience with diversification strategies at other firms, may make that information more influential to the focal firm’s own strategic decision-making related to diversification. A more holistic framework captures factors related to the individual interlocking director, the board and firm overall and the context surrounding these linkages and relationships, helping to promote future research. Understanding the social context surrounding board interlocks offers opportunities to more deeply examine how these interconnections serve in pursuit of the board’s fundamental purpose of protecting shareholder investment from managerial self-interest. Overall, integrating multi-level factors will offer new insights into the influence of board interlocks on firm strategies on both sides of the partnership. Expanding knowledge of how inter-firm linkages transmit knowledge influential to board decision-making can also improve our understanding of board effectiveness and corporate governance.

Article

Board Processes and Performance: The Impact of Directors’ Social and Human Capital  

Morten Huse

What do we know about actual board behavior and board performance? How can we develop our knowledge about board processes and board members’ capabilities? As a research field grows into maturity, we learn to see nuances, and the vocabulary used becomes richer and more detailed. However, the development of a consistent and nuanced language in research about board processes and performance is lagging behind. How have research streams and individual scholars influenced how we do research today, and why are these stories not included in most of the published literature reviews on this topic? What distinguishes research about boards and governance from various disciplines? How do we find research about board processes and board capital, and how has groundbreaking research on the human side of corporate governance developed? Groundbreaking research of Myles Mace was conducted more than half a decade ago, and we need to understand what has taken place after the seminal 1989 contribution of Zahra and Pearce. Research about actual board behavior and processes were not for decades published in leading management and strategy journals. Most published research about board processes and board capital is formulaic, leans on proxies rather than direct observation, and has only incremental if any practical contributions. A message is thus that we should strive for more groundbreaking studies that challenge existing knowledge and practice, including our research practice. A research agenda about board processes and board capital should be influenced by some of the following suggestions: • It should go beyond formulaic and incremental studies. We should challenge existing wisdom and practice and search for alternative ways of doing research. • It should include more processual studies rather than archival data studies using proxies. • We should learn from the scholars doing groundbreaking research before us. • We should learn by comparing experiences from various types of organizations. • We must include lessons and publications not found in leading English-language journals. • We should apply a sharing philosophy and a programmatic approach in which we as researchers contribute to developing future generations of scholars.

Article

Bootstrapping: Complementary Lines of Inquiry in Entrepreneurship  

Matthew Rutherford and Duygu Phillips

Bootstrapping is a term, a construct, and a paradigm that has attracted substantial attention from both popular press writers and scholarly researchers. In the scholarly community bootstrapping research is concerned, broadly, with studying the phenomenon of startups in resource poor environments. While this would describe virtually all startups, bootstrapping is most focused upon those resource-starved startups that elected to use only the resources existing internally to the firm or founder(s). That is, in bootstrapped firms, no financing has been attained from individuals or entities outside the firm. In practice, bootstrapping is understood as (a) launching a business with no external debt or equity, and (b) finding creative ways to manage a business launched with no external debt or equity. Most entrepreneurs bootstrap at founding. It is estimated that few (20%) take on external debt at startup; and far fewer (5%) launch with external equity. Examples of techniques employed because of the decision to bootstrap include using credit cards, drawing upon home equity and sweat equity, taking loans from family, and investing salary from one’s “day job.” There are fundamental reasons for this, both from a demand side and a supply side. From the demand side entrepreneurs, on average, are autonomous and therefore have a preference for control and a general aversion to external forms of capital, both debt and equity. On the supply side, because of extreme asymmetric information that exists between financiers and entrepreneurs, financiers often cannot accurately gauge the underlying quality of the entrepreneur/venture and are therefore reluctant to provide capital to them. With regard to outcomes of bootstrapping, though, the research is equivocal. Ceteris paribus, it appears that there is no significant difference in performance between bootstrappers and non-bootstrappers; however, contingencies likely exist. For example, non-bootstrappers are likely more prone to failure because they often take more risks. Therefore, while a few heavily financed ventures may achieve lofty success, many fail in dramatic fashion. By contrast, bootstrappers are often more cautious and therefore these firms demonstrate less variance in outcomes. Understanding of both antecedents and outcomes of bootstrapping has grown since the introduction of the construct in the late 1980s. Because of this expanded understanding, the construct has evolved from phenomenological roots to one more grounded in theory. That said, there remain ambiguities around bootstrapping, not the least of which is the existence of myriad definitions and resultant operationalizations. Partially because of these varied conceptualizations, the scholarship on bootstrapping has been somewhat fragmented and challenging to decipher. This fragmented accumulation has led to not only a literature with vivid applications and examples, but also one with little universal logic. This fact has made it somewhat difficult for a field to advance. However, insights from existing theory (e.g., signaling, cultural entrepreneurship) as well as the relatively recent development of closely related bases (e.g., effectuation, bricolage) can complement and advance bootstrapping by adding theoretical breadth and depth. When understood alongside these related lines of research in entrepreneurship, researchers are better equipped to create, catalog, and accumulate knowledge regarding bootstrapping. In turn, educators will be more effective in communicating how entrepreneurs are able to launch in resource poor environments, and ultimately achieve success.

Article

Bureaucracy to Postbureaucracy: The Consequences of Political Failures  

Mallory E. Compton and Kenneth J. Meier

Pathologies inherent in democratic political systems have consequences for bureaucracy, and they need to be examined. Limited in time, resources, and expertise, elected officials turn to bureaucratic institutions to carry out policy goals but all too often give public agencies too little support or too few resources to implement them effectively. In response to the challenges imposed by politics, public agencies have sought organizational solutions. Bureaucracies facing shortages of material resources, clear goals, representation of minority interests, or public trust have in recent decades adopted less hierarchical structures, exploited networks and privatization, and taken a representative role. In other words, the evolution of postbureaucratic governance institutions is in part a consequence of political incentives. Efforts to diagnose and resolve many of the shortcomings attributed to bureaucracy therefore require an accounting of the political processes shaping the context in which public managers and bureaucrats operate.

Article

Business Groups as an Organizational Model  

Asli M. Colpan and Alvaro Cuervo-Cazurra

Business groups are an organizational model in which collections of legally independent firms bounded together with formal and informal ties use collaborative arrangements to enhance their collective welfare. Among the different varieties of business groups, diversified business groups that exhibit unrelated product diversification under central control, and often containing chains of publicly listed firms, are the most-studied type in the management literature. The reason is that they challenge two traditionally held assumptions. First, broad and especially unrelated diversification have a negative impact on performance, and thus business groups should focus on a narrow scope of related businesses. Second, such diversification is only sustainable in emerging economies in which market and institutional underdevelopment are more common and where business groups can provide a solution to such imperfections. However, a historical perspective indicates that diversified business groups are a long-lived organizational model and are present in emerging and advanced economies, illustrating how business groups adapt to different market and institutional settings. This evolutionary approach also highlights the importance of going beyond diversification when studying business groups and redirecting studies toward the evolution of the group structure, their internal administrative mechanisms, and other strategic actions beyond diversification such as internationalization.

Article

Business History in International Business  

Teresa da Silva Lopes

Historical research on the multinational enterprise has long been important in international business studies. When the discipline of international business first developed in the late 1950s, historical evidence was frequently used to build generalizations and propose theories. However, over time, that tradition eroded, as the discipline moved toward using more quantitative and econometric reasoning. International business and business history share important commonalities, such as the topics they address. These include: multinational patterns of international trade and foreign investment; the boundaries and competitiveness of the multinational enterprise; changes in organizational strategy and structure of multinational enterprises and the connections between the two; coordination and management of the activities of the multinational enterprise; impact of multinationals on knowledge and capital flows in host countries; and investment, resilience, and survival in high-risk environments. Nonetheless, the approaches followed can be quite distinct. While both disciplines consider the firm and other institutional forms as the unit of analysis, the way context and the environment are integrated in the analysis, the methodologies followed, the types of comparative analysis carried out, the temporal dimensions adopted, and the way in which theory is used are quite distinct. There are possible ways forward for international business history to be more integrated and provide new dimensions in international business studies. These include using history as a generator of theory to understand phenomena such as the origins of competitiveness and as a way to uncover phenomena that can be fully understood only after the situation has occurred, such as the impact of entrepreneurship on economic development; as a way to check false claims that certain phenomena is new; and to inform discussions on complex phenomena and grand challenges such as globalization and deglobalization, investment in high risk environments, and climate change.

Article

Business Models and Usage of Technology: A New Perspective on Business Model Design  

Neva Bojovic and Vincent Mangematin

Companies need business models to profit from innovation and technology. However, the success of a certain technology depends on whether and how it is used. Usage is important not only as an indicator of technology adoption, but also as a way for companies to design business models—as a way to create and capture value from technology. Usage is inscribed by the designers in the technology, but users in their ongoing practice can alter the designers’ intentions, which sometimes leads to innovation. Users can also combine different technologies in practice to accomplish a specific usage. In essence, usage is constitutive of technology and its value. Technology usage-based business modeling is a way to explore business modeling for technology that looks into how different technologies are integrated, either by users or platform actors, into solutions to address specific usage needs. To understand this notion of usage for business model design, one must first understand how value is created and captured from technology. At the same time, it is also important to know different streams of literature that have investigated technology usage: user-centered design, user innovation and lead users, form, function, affordances of technology, and the practice-based view. While usage-based business modeling has implications for all kinds of technologies, it is of particular importance for emerging, enabling, and embedding technologies, where the value of technology depends on the usage across multiple applications and connectedness between different users.

Article

Business Research Process  

James A. Muncy and Alice M. Muncy

Business research is conducted by both businesspeople, who have informational needs, and scholars, whose field of study is business. Though some of the specifics as to how research is conducted differs between scholarly research and applied research, the general process they follow is the same. Business research is conducted in five stages. The first stage is problem formation where the objectives of the research are established. The second stage is research design. In this stage, the researcher identifies the variables of interest and possible relationships among those variables, decides on the appropriate data source and measurement approach, and plans the sampling methodology. It is also within the research design stage that the role that time will play in the study is determined. The third stage is data collection. Researchers must decide whether to outsource the data collection process or collect the data themselves. Also, data quality issues must be addressed in the collection of the data. The fourth stage is data analysis. The data must be prepared and cleaned. Statistical packages or programs such as SAS, SPSS, STATA, and R are used to analyze quantitative data. In the cases of qualitative data, coding, artificial intelligence, and/or interpretive analysis is employed. The fifth stage is the presentation of results. In applied business research, the results are typically limited in their distribution and they must be addressed to the immediate problem at hand. In scholarly business research, the results are intended to be widely distributed through journals, books, and conferences. As a means of quality control, scholarly research usually goes through a double-blind review process before it is published.

Article

Career Development and Organizational Support  

Melinde Coetzee

The complexity of modern careers requires personal agency in managing career development and employability capital as personal resources for career success. Individuals’ employability capital also serves as a valuable resource for the sustainable performance of organizations. Individuals’ ability to proactively engage in career self-management behaviors through the use of a comprehensive range of self-regulatory capabilities, known as career metacapacities, contributes to their employability capital. Organizational career development supports initiatives that consider individuals’ proactivity in light of conditions that influence their motivational states, and availability of personal resources helps organizations benefit from individuals who bring information, knowledge, capacities, and relationship networks (i.e., employability capital) into their work that ultimately contribute to the organization’s capability to sustain performance in uncertain, highly competitive business markets. Career development support practices should embrace the individualization of modern-day careers, the need for whole-life management, and the multiple meanings that career success has for individuals.

Article

Careless Responding and Insufficient Effort Responding  

Jason L. Huang and Zhonghao Wang

Careless responding, also known as insufficient effort responding, refers to survey/test respondents providing random, inattentive, or inconsistent answers to question items due to lack of effort in conforming to instructions, interpreting items, and/or providing accurate responses. Researchers often use these two terms interchangeably to describe deviant behaviors in survey/test responding that threaten data quality. Careless responding threatens the validity of research findings by bringing in random and systematic errors. Specifically, careless responding can reduce measurement reliability, while under specific circumstances it can also inflate the substantive relations between variables. Numerous factors can explain why careless responding happens (or does not happen), such as individual difference characteristics (e.g., conscientiousness), survey characteristics (e.g., survey length), and transient psychological states (e.g., positive and negative affect). To identify potential careless responding, researchers can use procedural detection methods and post hoc statistical methods. For example, researchers can insert detection items (e.g., infrequency items, instructed response items) into the questionnaire, monitor participants’ response time, and compute statistical indices, such as psychometric antonym/synonym, Mahalanobis distance, individual reliability, individual response variability, and model fit statistics. Application of multiple detection methods would be better able to capture careless responding given convergent evidence. Comparison of results based on data with and without careless respondents can help evaluate the degree to which the data are influenced by careless responding. To handle data contaminated by careless responding, researchers may choose to filter out identified careless respondents, recode careless responses as missing data, or include careless responding as a control variable in the analysis. To prevent careless responding, researchers have tried utilizing various deterrence methods developed from motivational and social interaction theories. These methods include giving warning, rewarding, or educational messages, proctoring the process of responding, and designing user-friendly surveys. Interest in careless responding has been growing not only in business and management but also in other related disciplines. Future research and practice on careless responding in the business and management areas can also benefit from findings in other related disciplines.

Article

Case Study Research: A State-of-the-Art Perspective  

Eric Volmar and Kathleen M. Eisenhardt

Theory building from case studies is a research strategy that combines grounded theory building with case studies. Its purpose is to develop novel, accurate, parsimonious, and robust theory that emerges from and is grounded in data. Case research is well-suited to address “big picture” theoretical gaps and dilemmas, particularly when existing theory is inadequate. Further, this research strategy is particularly useful for answering questions of “how” through its deep and longitudinal immersion in a focal phenomenon. The process of conducting case study research includes a thorough literature review to identify an appropriate and compelling research question, a rigorous study design that involves artful theoretical sampling, rich and complete data collection from multiple sources, and a creative yet systematic grounded theory building process to analyze the cases and build emergent theory about significant phenomena. Rigorous theory building case research is fundamentally centered on strong emergent theory with precise theoretical logic and robust grounding in empirical data. Not surprisingly then, theory building case research is disproportionately represented among the most highly cited and award-winning research.

Article

Categorization Theory  

Judith A. Clair and Mary M. Struzska-Tyamayev

Categorization, the process of placing or separating into classes or groups, is a socially meaningful process and has been studied across a variety of disciplines, including the organizational studies field. Organizational scholars have focused on implications of social categorization (classification of another person as part of a group in organizational life), self-categorization (identifying the self as part of a group or category), and, increasingly, categorization systems (the norms and structures shaping and legitimizing the categories themselves) for individuals, group functioning, and organizational outcomes. All three elements are interconnected, as how one categorizes the self is linked to how one is socially categorized by others in organizational life, while categorization systems used in organizations provide the context for this process. Categorization, in its various forms, plays a key role in diversity and inclusion dynamics within organizations, as it can have positive and negative consequences. Among the most discussed negative outcomes is the potential for categorization to serve as a precursor to interpersonal or systemic forms of bias in organizations. Once categorized, a person may experience stigmatization or work discrimination based on the category assigned. Categorization is associated with unique forms of bias; for instance, if one is perceived to be a-prototypical for a category (e.g., a poor fit), the person may resultingly experience social penalties or work-based negative consequences for not exemplifying the group’s core qualities well enough. In turn, this can generate negative personal and interpersonal effects at work and undermine organizational efforts to build inclusion. For instance, if one does not fit a “leader” prototype well enough, they may have a more difficult time claiming the role of leader. However, categorization also allows for the individual and organizational creation of meaning and understanding of the social world, group cohesion, interpersonal congruence, and ultimately the coordination and structuring of institutional diversity and inclusion efforts. There are many avenues for advancing understandings of categorization and its effects. In particular, opportunities are rich for studies that explore implications of a growing number of people with intersected, multiple, and/or non-normative categories at work and in organizations. The growth of more complex categories has implications at multiple levels of analysis—for people, group functioning, and organizations seeking to build a more inclusive workplace. Also, with the rise of artificial intelligence (AI) and computerization, categories drawn upon and the processes of categorization, and their implications, are intimately linked to nonhuman forces. There are ample opportunities for organizational research in this domain, a chance to explore and understand the subject beyond the bounds of traditional computing disciplines.

Article

Citizen Science and Crowd Science  

Marion K. Poetz and Henry Sauermann

Citizen science and crowd science (CS) projects involve members of the public who participate in response to an open call and who can perform a broad range of research tasks. Scholars using the citizen science lens focus on the fact that many participants do not have formal scientific training, while scholars using the crowd science lens emphasize that participants are often recruited through an open call. CS projects have resulted in large-scale data sets, novel discoveries, and top-tier publications (i.e., scientific impact), but they can also have large societal and practical impacts by increasing the relevance of research or accomplishing other objectives such as science education and building awareness. The diverse landscape of CS projects reflects five underlying paradigms that capture different rationales for involving crowds and that require different organizational setups: crowd volume, broadcast search, user crowds, community production, and crowd wisdom. Within each CS project, the breadth of crowd involvement can be mapped along stages of the research process (e.g., formulating research questions, designing methods, collecting data). Within each stage, the depth of crowd involvement can be mapped with respect to four general types of contributions: activities, knowledge, resources, and decisions. Common challenges of CS projects relate to recruiting and engaging participants, organizational design, resource requirements, and ensuring the quality of contributions. Opportunities for future research include research on the costs and boundary conditions of CS as well as systematic assessments of different aspects of performance and how they relate to project characteristics. Future research should also investigate the role of artificial intelligence both as worker who can take over tasks from crowd members and as manager who can help organize CS activities.

Article

Cluster Evolution  

Nydia MacGregor and Tammy L. Madsen

A substantial volume of research in economic geography, organization theory, and strategy examines the geographic concentration of interconnected firms, industries, and institutions. Theoretical and empirical work has named a host of agglomeration advantages (and disadvantages) with much agreement on the significance of clusters for firms, innovation, and regional growth. The core assertion of this vein of research is that geographically concentrated factors of production create self-reinforcing benefits, yielding increasing returns over time. The types of externalities (or agglomeration economies) generally fall into four categories: specialized labor or inputs, knowledge spillovers, diversity of actors and activity, and localized competition. Arising from multiple sources, each of these externalities attracts new and established firms and skilled workers. Along with recent advancements in evolution economics, newer research embraces the idea that the agglomeration mechanisms that benefit clusters may evolve over time. While some have considered industry and cluster life-cycle approaches, the complex adaptive systems (CAS) theory provides a well-founded framework for developing a theory of cluster evolution for several reasons. In particular, the content and stages of complex adaptive systems directly connect with those of a cluster, comprising its multiple, evolving dimensions and their interplay over time. Importantly, this view emphasizes that the externalities associated with agglomeration may not have stable effects, and thus, what fosters advantage in a cluster will change as the cluster evolves. Furthermore, by including a cluster’s degree of resilience and ability for renewal, the CAS lens addresses two significant attributes absent from cyclical approaches. Related research in various disciplines may further contribute to our understanding of cluster evolution. Studies of regional resilience (usually focused on a specific spatial unit rather than its industrial sectors) may correspond to the reorganization phase associated with clusters viewed as complex adaptive systems. In a similar vein, examining the shifting temporal dynamics and development trajectories resulting from discontinuous shocks may explain a cluster’s emergence and ultimate long-term renewal. Finally, the strain of research examining the relationship between policy initiatives and cluster development remains sparse. To offer the greatest theoretical and empirical traction, future research should examine policy outcomes aligned with specific stages of cluster evolution and include the relevant levels and scope of analysis. In sum, there is ample opportunity to further explore the complexities and interactions among firms, industries, networks, and institutions evident across the whole of a cluster’s evolution.

Article

Competitive Dynamics in Strategic Management  

Claudio Giachetti and Giovanni Battista Dagnino

Competitive dynamics inquiry originates from a sequence of attacks and counterattacks among firms in an industry. Firms attack and respond to attacks of rivals in order to strengthen or defend their competitive position within their competitive space. Competitive dynamics research is thus centered on the analysis of how the firm’s actions affect rivals’ reactions and performance. Actually, the nature of competitive dynamics research is the open recognition that firm strategies are “dynamic”: Strategic actions initiated by one firm may trigger a series of actions among rival firms. The new competitive environment in many industries has generated the inception of furious competition, emphasizing flexibility, speed, and innovation in response to fast-changing technological and institutional conditions and temporary competitive advantages. The key constructs and the intellectual roots of competitive dynamics (i.e., Schumpeter’s theory of creative destruction and industrial organization economics and related oligopoly theories) offer some practical examples of industry and firm cases where competitive dynamics have found their main applications. The relevant underpinnings of the awareness–motivation–capability (AMC) framework provide an integrative model of the key behavioral drivers that shape a competitive actions and responses framework (i.e., the factors influencing the firm’s awareness of the context; the factors inducing or impeding the motivation of firms to respond to competitors’ action; and the capability-based factors affecting the firm’s ability to undertake actions), the three key attributes (i.e., the specific actions of firms in the industry, the firm’s competitive interdependence, and the antecedents and performance implications of firms’ competitive actions and reactions), and the three main levels of analysis used in competitive dynamics literature (i.e., action-level studies, business-level studies, and corporate-level studies). Some insights regarding the relationship between dynamic competition and the sources of temporary competitive advantage, coopetition dynamics, as well as the kind of accelerated competition epitomizing early 21st-century digital dynamics settings update the traditional competitive dynamics flavor, as they are connected with firms’ strategic interaction and the pursuit of temporary advantages.

Article

Constructs and Measures in Stakeholder Management Research  

James Mattingly and Nicholas Bailey

Stakeholder strategies, or firms’ approaches to stakeholder management, may have a significant impact on firms’ long-term prosperity and, thereby, on their life chances, as established in the stakeholder view of the firm. A systematic literature review surveyed the contemporary body of quantitative empirical research that has examined firm-level activities relevant to stakeholder management, corporate social responsibility, and corporate social performance, because these three constructs are often conflated in literature. A search uncovered 99 articles published in 22 journals during the 10-year period from 2010 to 2019. Most studies employed databases reporting environmental, social, and governance (ESG) ratings, originally created for use in socially responsible investing and corporate risk assessment, but others employed content analysis of texts and primary surveys. Examination revealed a key difference in the scoring of data, in that some studies aggregated numerous indicators into a single composite index to indicate levels of stakeholder management, and other studies scored more articulated constructs. Articulated constructs provided richer observations, including governance and structural arrangements most likely to provide both stakeholder benefits and protections. Also observed were constraining influences of managerial and market myopia, sustaining influences from resilience and complexity frameworks, and recognition that contextual variables are contingencies having impact in recognizing the efficacy of stakeholder management strategies.

Article

Content and Text Analysis Methods for Organizational Research  

Rhonda K. Reger and Paula A. Kincaid

Content analysis is to words (and other unstructured data) as statistics is to numbers (also called structured data)—an umbrella term encompassing a range of analytic techniques. Content analyses range from purely qualitative analyses, often used in grounded theorizing and case-based research to reduce interview data into theoretically meaningful categories, to highly quantitative analyses that use concept dictionaries to convert words and phrases into numerical tables for further quantitative analysis. Common specialized types of qualitative content analysis include methods associated with grounded theorizing, narrative analysis, discourse analysis, rhetorical analysis, semiotic analysis, interpretative phenomenological analysis, and conversation analysis. Major quantitative content analyses include dictionary-based approaches, topic modeling, and natural language processing. Though specific steps for specific types of content analysis vary, a prototypical content analysis requires eight steps beginning with defining coding units and ending with assessing the trustworthiness, reliability, and validity of the overall coding. Furthermore, while most content analysis evaluates textual data, some studies also analyze visual data such as gestures, videos and pictures, and verbal data such as tone. Content analysis has several advantages over other data collection and analysis methods. Content analysis provides a flexible set of tools that are suitable for many research questions where quantitative data are unavailable. Many forms of content analysis provide a replicable methodology to access individual and collective structures and processes. Moreover, content analysis of documents and videos that organizational actors produce in the normal course of their work provides unobtrusive ways to study sociocognitive concepts and processes in context, and thus avoids some of the most serious concerns associated with other commonly used methods. Content analysis requires significant researcher judgment such that inadvertent biasing of results is a common concern. On balance, content analysis is a promising activity for the rigorous exploration of many important but difficult-to-study issues that are not easily studied via other methods. For these reasons, content analysis is burgeoning in business and management research as researchers seek to study complex and subtle phenomena.

Article

Control Variables in Management Research  

Guclu Atinc and Marcia J. Simmering

The use of control variables to improve inferences about statistical relationships in data is ubiquitous in management research. In both the micro- and macro-subfields of management, control variables are included to remove confounding variance and provide researchers with an enhanced ability to interpret findings. Scholars have explored the theoretical underpinnings and statistical effects of including control variables in a variety of statistical analyses. Further, a robust literature surrounding the best practices for their use and reporting exists. Specifically, researchers have been directed to report more detailed information in manuscripts regarding the theoretical rationale for the use of control variables, their measurement, and their inclusion in statistical analysis. Moreover, recent research indicates the value of removing control variables in many cases. Although there is evidence that articles recommending best practices for control variables use are increasingly being cited, there is also still a lag in researchers following recommendations. Finally, there are avenues for valuable future research on control variables.

Article

Coopetition  

Michael Dowling

Ray Noorda, the former CEO of Novell Inc., first coined the term “coopetition” in 1992 to describe a common phenomenon in the computer industry: cooperation between competitors. This phenomenon is inconsistent with classical economic and business theory going as far back as Adam Smith, who viewed the production system as based on a separation between suppliers and buyers. Micro-economists have traditionally viewed the firm as buying raw materials and components from suppliers, producing finished goods, and selling those goods in competition with other firms to a different set of firms or consumers. However, starting in the 1990s, research on forms of cooperative relationships between competitors became very common. The most common types are (a) competing firms engaging in horizontal alliances along the same level of the value chain and (b) vertical cooperation along different levels of the value chain between suppliers and firms in the focal industry or between customers and firms. In the last 25 years, there has been a great increase in research on coopetition. In a systematic literature review conducted in 2014, one researcher found over 130 academic articles in more than 80 academic publications published since 1996. The majority of the research to date has been qualitative, with many cases studied conducted. A number of special issues in academic journals have been devoted to the topic in general or to special topics concerning coopetition. The Strategic Management Journal organized a special issue in 2018 on the interplay of competition and cooperation, and a number of workshops have been held on coopetition strategy and innovation.