161-180 of 269 Results


Machine Learning in Management  

Elizabeth Degefe, Krishna Savani, and Abhishek Sheetal

Although modern machine learning techniques were developed decades ago, management researchers have started using them only in the 2010s. Researchers in management have used machine learning techniques to analyze numeric data, most commonly relying on neural networks and decision trees; they have also used AI techniques to analyze text data to classify topics or model topics.


Managing Age Diversity in the Workplace  

Cody Cox, Richard Posthuma, Fabian Castro, and Eric Smith

Many researchers have noted the increasing age of the workforce, but less noted is that the workforce is also becoming more diverse in terms of age. Thus, as the workforce ages, the ability to manage age diversity will become increasingly important. Managing workers of different ages requires understanding the physiological, psychological, and motivational changes that accompany age, as well as how individuals of different ages interact in organizational contexts. With an increased awareness of the multidimensional nature of age, employers can consider useful adaptations to their human resource practices. Dispelling invalid age stereotypes may be accomplished through inclusive HR practices, the use of intergenerational interactions, and providing meaningful work to all employees.


Managing Conflict for Effective Leadership and Organizations  

Dean Tjosvold, Alfred S. H. Wong, and Nancy Yi Feng Chen

Leaders and employees deal with conflict as they collaborate in the everyday life of organizations and as they confront crises. Depending how they manage conflict, they can frustrate employees and provoke customer complaints but also stimulate their relationships and decision-making. The possibilities of constructive conflict are significant and documented, but the challenges to making conflict constructive are significant too. The practice of defining conflict as a win-lose battle has obscured ways of managing conflict constructively. Fortunately, researchers have developed concepts and findings that can help managers and employees manage conflict. A first step is developing a useful, unconfounded definition of conflict. Deutsch proposed that conflict occurs when there are incompatible activities. Team members are in conflict as they argue for different options for a decision. Deutsch also theorized that how people believe their goals are related very much affects their interaction, specifically their conflict management. They can conclude that their goals are cooperative (positively related), competitive (negatively related), or independent. People with cooperative goals believe that as one of them moves toward attaining goals, that helps others achieve their goals. In competition, people conclude that their goals are negatively related and only one can succeed in the interaction. In independence, one person ‘s success neither benefits nor harms the others’ success. Researchers have found that the nature of the cooperative or competitive relationship between protagonists has a profound impact on their mutual motivation to discuss conflicts constructively. Cooperative and competitive methods of handling conflict have consistent, powerful effects on constructive conflict. Team members with cooperative goals engage in open-minded discussions where they develop and express their opposing positions, including the ideas, reasons, and knowledge they use to support their positions. They also work to understand each other’s perspectives. They are then in a position to combine the best of each other’s ideas and create effective resolutions of conflict that they are both committed to implement. Teams that rely on cooperative, mutual benefit interaction ways of managing conflict and avoid competitive, win-lose ways been found to use conflict to promote high quality decisions, to stimulate learning, and to strengthen their work relationships. What has an impact on constructive conflict is not so much the occurrence, amount, or type of conflict but how leaders and employees approach and handle their conflicts, specifically, the extent to which their discussions are cooperative and open-minded.


Managing Surface-Level Diversity as a Business Imperative  

Jacqueline A. Gilbert

Organizational diversity is regarded positively, but haphazardly embraced. The absence of a cultural mandate at work (one which includes an emphasis on managing differences) can result in minority assimilation, and in either unintended bullying or in intentional abuse. Declining stock price, loss of goodwill, inability to recruit qualified candidates, and internal havoc marked by perpetuation of firm dysfunction may occur. These outcomes are especially alarming in the face of transformative population growth, in which minorities are predicted to become the demographic majority within the United States. Inattention to employee misconduct prevents firms from experiencing enhanced productivity. Encouraging civil behavior is thus essential to engendering camaraderie in a diverse workforce, in which incivilities, or micro-inequities, are disproportionately targeted at minority groups. Management modeling of appropriate behavior (and swift action toward perpetrators for non-compliance) are necessary to achieve human capital integration.


Managing Team Diversity in the Workplace  

Maartje Schouten, Jasmien Khattab, and Phoebe Pahng

The study of team diversity has generated a large amount of research because of the changing nature of workplaces as they become more diverse and work becomes more organized around teams. Team diversity describes the variation among team members in terms of any attribute in which individuals may differ. Examples are demographic background diversity, functional or educational diversity, and personality diversity. Diversity can be operationalized as categorical (variety), continuous (separation), or vertical (disparity). Initial research on team diversity was dominated by a main-effects approach that produced two main perspectives: social-categorization scholars suggested that diversity hurts team outcomes, as it decreases feelings of cohesion and increases dysfunctional conflict, whereas the information and decision-making perspective suggested that diversity helps team outcomes, as it makes more information available in the team to help with decision-making. In an effort to integrate these disparate insights, the categorization-elaboration model (CEM) proposed that team diversity can lead both to social categorization and to information elaboration on the basis of contextual factors that may give rise to either process. The CEM has received widespread support in research, but a number of questions about the processes through which diversity has an effect on team outcomes remain.


Managing Third Sector Organizations  

Alex Murdock and Stephen Barber

What is the state of what can be described as management in the third sector? At its heart, it discusses the long-held assertion that these organizations are reluctant to accept the need for ‘management’. After all, what makes third sector organizations different, by their own estimation, from their commercial equivalents is the deeply embedded concepts of mission and values together with a distinctly complex stakeholder environment. For all that, there are also “commercial” pressures and an instinct for survival. To serve the mission necessarily needs resources. And there is a perennial tension in high-level decision-making between delivery of the mission and maintaining solvency. Third-sector organizations, like any other, are innately concerned with their own sustainability. It is here that the analysis is located and there is an opportunity to examine the topic theoretically and empirically. By introducing the concept of the “Management See-Saw” to illustrate the competing drivers of values and commercialism before exploring these identified pressures through the lens of three real-life vignettes, it is possible to appreciate the current state of play. Given all this, it is important for modern organizations to be able to measure value and impact. From a managerial perspective, the reality needs to be acknowledged that this environment is complex and multi-layered. In drawing the strands together, the discussion concludes by illustrating the importance of leadership in the sector, which is a powerful indicator of effectiveness. Nevertheless, with a focus on management, the core contention is that management remains undervalued in the third sector. That said, commercial focus can increasingly be identified and the longer term trend is squarely in this direction.


Maritime Business: A Paradigm of Global Business  

Gelina Harlaftis and Ioannis Theotokas

Maritime business is a paradigm of a global business. Its importance cannot be underrated as 90% of the world’s trade is at the present day carried by sea. In fact, the vast majority of the goods that form our daily lives depend upon the shipping industry. As ships sail in the seas and oceans of the world, and as ports are nowadays hidden away and not part of the everyday life of people in port cities, much of the shipping business is invisible and remains so to the mainstream business and management literature. Maritime business since, at least, the early modern period has evolved as a main factor for the communication and formation of the international and eventually global markets. Research in maritime business has evolved around the formation and transformation of shipping markets, the evolution of shipping firms and ship management, the effect of technology at sea transport and on its productivity and freight rates, on trends of the nationality of world fleet, and its denationalization or “flagging out,” on seafaring labor and risk at sea. A shipping firm is the economic unit that uses the factors of production to produce and provide sea transport services. It serves the world trade system which was consolidated in the 19th century, and the formation and organization of shipping firms followed the type of cargoes that had to be carried: first, bulk commodities carried in huge quantities like raw materials and second manufactured and packaged goods. The first type of cargo has been served by the tramp/bulk shipping companies and the second type by the liner/container shipping companies. Technology has been a watershed in the formation and transformation of the shipping firm. Five periods can be distinguished in the last two centuries in the evolution of the shipping industry and the shipping firm according to transformation of shipping markets and the introduction of new technologies: (a) up to the 1820s, (b) from the 1830s to the 1870s, (c) from the 1880s to the 1930s, (d) from the 1940s to the 1970s, and (e) after the 1980s. Until the last third of the 20th century Europe dominated the world fleet to be gradually replaced by the Asian fleets in the 21st century. Maritime business, is increasingly losing its “nationality” and is becoming global despite the fact that in sections of it there are powerful shipping families connected with certain nations. Shipping has always been a high-risk business, which, despite the evolution in many aspects of its operation, remains dependent on the acts of nature as well as on the acts of people, as the recent revitalization of piracy reveals.


Mediation: Causal Mechanisms in Business and Management  

Patrick J. Rosopa, Phoebe Xoxakos, and Coleton King

Mediation refers to causation. Tests for mediation are common in business, management, and related fields. In the simplest mediation model, a researcher asserts that a treatment causes a mediator and that the mediator causes an outcome. For example, a practitioner might examine whether diversity training increases awareness of stereotypes, which, in turn, improves inclusive climate perceptions. Because mediation inferences are causal inferences, it is important to demonstrate that the cause actually precedes the effect, the cause and effect covary, and rival explanations for the causal effect can be ruled out. Although various experimental designs for testing mediation hypotheses are available, single randomized experiments and two randomized experiments provide the strongest evidence for inferring mediation compared with nonexperimental designs, where selection bias and a multitude of confounding variables can make causal interpretations difficult. In addition to experimental designs, traditional statistical approaches for testing mediation include causal steps, difference in coefficients, and product of coefficients. Of the traditional approaches, the causal steps method tends to have low statistical power; the product of coefficients method tends to provide adequate power. Bootstrapping can improve the performance of these tests for mediation. The general causal mediation framework offers a modern approach to testing for causal mechanisms. The general causal mediation framework is flexible. The treatment, mediator, and outcome can be categorical or continuous. The general framework not only incorporates experimental designs (e.g., single randomized experiments, two randomized experiments) but also allows for a variety of statistical models and complex functional forms.


Men, Masculinities, and Gender Relations  

Jeff Hearn and David Collinson

Even though gender and gender analysis are still often equated with women, men and masculinities are equally gendered. This applies throughout society, including within organizations. Following pioneering feminist scholarship on work and organizations, explicitly gendered studies on men and masculinities have increased since the 1980s. The need to include the gendered analysis of men and masculinities as part of gender studies of organizations, leadership, and management, is now widely recognized at least within gender research. Yet, this insight continues to be ignored or downplayed in mainstream work and even in some studies seen as “critical.” Indeed the vast majority of mainstream work on organizations still has either no gender analysis whatsoever or relies on a very simplistic and rather crude understanding of gender dynamics. Research on men and masculinities has been wide ranging and has raised important new issues about gendered dynamics in organizations, including cultures and countercultures on factory shopfloors; historical transformations of men and management in reproducing patriarchies; the relations of bureaucracy, men, and masculinities; management-labor relations as interrelations of masculinities; managerial and professional identity formation; managerial homosociality; and the interplay of diverse occupational masculinities. Research has revealed how structures, cultures, and practices of men and masculinities continue to persist and to dominate in many contemporary organizations. Having said this, the concepts of gender, of men and masculinities, and of organization have all been subject to complex and contradictory processes that entail both their explicit naming and their simultaneous deconstruction and critique. This is illustrated, respectively, in the intersectional construction of gender; the pressing need to name men as men in analysis of organizational dominance, but also deconstruct the category of men as provisional; and in the multiplication of organizational forms as, for example, interorganizational relations, net-organizations, and cyberorganizations. These contradictory historical and conceptual namings and deconstructions are especially important in the analysis of transnational organizations operating within the context of globalization, transnationalizations, production, reproduction, and trans(national) patriarchies. Within transnational organizations such as large gendered multinational enterprises, the taken-for-granted nature of transnational gendered hierarchies and cultures persists in management, maintained partly through commonalities across difference, gendered horizontal specializations, and controls. Transnational organizations are key sites for the production of a variety of developing forms of (transnational) business masculinities, some more individualistic, some marriage based, some nation based, some transcending nation. These masculinities have clear implications for gendered practices in private spheres, including the provision of domestic servicing often by Black and minority ethnic women. The growth of the knowledge economy brings further complications to these transnational patterns, through elaboration of techno-masculinities, and interactions of men, masculinities, and information and communication technologies. This is particularly relevant in the international financial sector, where constructions of men and masculinities are impacted by the gendering of capital and financial crisis, and gender regimes of financial institutions, as in men financiers’ risky behavior. Further studies are needed addressing the “gender-neutral” hegemony of organizations, leaderships, and managements, especially in transnational arenas, and organizations subject to changing technologies. Other key research issues concern analysis of neglected intersectionalities, including intersectional privileges, male/masculine/men’s bodies, and the taken-for-granted category of “men” in and around organizations.


Mentoring Research Through the Years: A Brief Review  

S. Gayle Baugh

Mentoring relationships involve a more experienced individual who provides support for the career and personal development of a less experienced coworker. The focus of mentoring research has evolved over the years. Early on, investigators were interested in learning about the outcomes of the mentoring relationship for the protégé, who is the primary beneficiary of the relationship. Risks for the protégé were not acknowledged in the initial research on mentoring relationships. There were questions about how individuals identify appropriate mentoring partners and about the course of the relationship. Attention then turned to the motivations and potential benefits to the mentor, the other party in the relationship. However, scholars recognized that while there were positive outcomes from serving as a mentor, there were also costs associated with the role. Given that so much empirical focus was on the benefits of voluntary developmental relationships, scholars became interested in more formal, organizationally controlled approaches to encouraging mentoring relationships. However, mentoring relationships are not uniformly positive and beneficial to the parties so engaged. Just as would be the case in any relationship, there is a “dark side” to mentoring relationships that has emerged as the focus of empirical attention. Finally, the influence of diversity of the mentoring participants has been explored. That exploration has largely focused on gender issues, with limited attention devoted toward ethnicity. With the advent of greater diversity in the workforce in the United States and elsewhere, diversity represents an area ripe for investigation. Overall, despite the wealth of research on mentoring relationships, there are questions that remain under-researched or unexplored in each of the areas of research.


Mergers and Acquisitions  

Paulina Junni and Satu Teerikangas

There are many types of mergers and acquisitions (M&A), be they a minority acquisition to explore a potential high growth emerging market, a takeover of a financially distressed firm with the aim of turning it around, or a private equity firm seeking short- to medium-term returns. The terms “merger” and “acquisition” are often used interchangeably, even though they have distinct denotations: In an acquisition, the acquirer purchases the majority of the shares (over 50%) of another company (the “target”) or parts of it (e.g., a business unit or a division). In a merger, a new company is formed in which the merging parties share broadly equal ownership. The term “merger” is often used strategically by acquirers to alleviate fears and send out a message of friendly combination to employees. In terms of transaction numbers, the majority of M&A transactions are acquisitions, whereas mega-merger deals gain media attention owing to transaction size. While M&A motives, acquirer types, and dynamics differ, most M&A share the aim of generating value from the transaction in some form. Yet a prevalent dilemma in the M&A practice and literature is that M&A often fail to deliver the envisioned benefits. Reasons for negative acquirer performance stem from overestimating potential synergies and paying high premiums for targets pre-deal. Another problem lies in securing post-deal value creation. Post-deal challenges relate to optimal integration speed, the degree of integration, change, or integration management, communication, resource and knowledge sharing, employee motivation and turnover, and cultural integration. Researchers are calling for more research on how pre-deal processes such as target evaluation and negotiations influence M&A performance. A closer look at this literature, though, highlights several controversies. First, the literature often lacks precision when it comes to defining M&A. We call for future research to be explicit concerning the type of merger or acquisition transaction, and the organizational contexts of the acquiring and target firms. Second, we are still lacking robust and unified frameworks that explain M&A occurrence and performance. One of the reasons for this is that the literature on M&A has developed in different disciplines, focusing on either pre- or post-deal aspects. This has resulted in a “silo” effect with a limited understanding about the combined effects of financial, strategic, organizational, and cultural factors in the pre- and post-deal phases on M&A performance. Third, M&A studies have failed to critically scrutinize the M&A phenomenon, including aspects such as power, politics, and managerial drivers. Fourth, scholars have tended to focus on single, isolated M&A. We call for future research on M&A programs and M&A as part of broader corporate strategies. Finally, the study of M&A has suffered from a managerial bias, with insufficient attention paid to the rank and file, such as engineers, or marketing or administrative employees. We therefore call for future research that takes a broader view on actors involved in M&A, placing a greater emphasis on individuals’ roles and practices.


Meta-Analysis as a Business Research Method  

Alexander D. Stajkovic and Kayla S. Stajkovic

Mounting complexity in the world, coupled with new discoveries and more journal space to publish the findings, have spurred research on a host of topics in just about every discipline of social science. Research forays have also generated unprecedented disagreements. For many topics, empirical findings exist but results are mixed: some show positive relationships, some show negative relationships, and some show no statistically significant relationship. How, then, do researchers go about discovering systematic variation across studies to understand and predict forces that impinge on human functioning? Historically, qualitative literature reviews were performed in conjunction with the counting of statistically significant effects. This approach fails to consider effect magnitudes and sample sizes, and thus its conclusions can be misleading. A more precise way to reach conclusions from research literature is via meta-analysis, defined as a set of statistical procedures that enable researchers to derive quantitative estimates of average and moderator effects across available studies. Since its introduction in 1976, meta-analysis has developed into an authoritative source of information for ascertaining the generalizability of research findings. Thus, it is perhaps not surprising that meta-analyses in the field of management garner, on average, three times as many citations as single studies. A framework for conducting meta-analysis explains why it should be used, outlines what it has yielded to society, and introduces the reader to a fundamental conception and a misconception. More specifics follow about data collection and study selection criteria and implications of publication bias. How to convert estimates from individual studies to a common scale to be able to average them, what to consider in choosing a meta-analytic method, how to compare the procedures, and what information to include when reporting results are presented next. The article concludes with a discussion of nuances and limitations, and suggestions for future research and practice. Science builds knowledge cumulatively from numerous studies, which, more often than not, differ in their characteristics (e.g., research design, participants, setting, sample size). Some findings are in concert and some are not. Through its quantitative foundations, conjoint with theory-guiding hypotheses, meta-analysis offers statistical means of analyzing disparate research designs and conflicting results and discovering consistencies in a seemingly inconsistent literature. Research conclusions reached by a theory-driven, well-conducted meta-analysis are almost certainly more accurate and reliable than those from any single study.


Meta-Analytic Structural Equation Modeling  

Mike W.-L. Cheung

Meta-analysis and structural equation modeling (SEM) are two popular statistical models in the social, behavioral, and management sciences. Meta-analysis summarizes research findings to provide an estimate of the average effect and its heterogeneity. When there is moderate to high heterogeneity, moderators such as study characteristics may be used to explain the heterogeneity in the data. On the other hand, SEM includes several special cases, including the general linear model, path model, and confirmatory factor analytic model. SEM allows researchers to test hypothetical models with empirical data. Meta-analytic structural equation modeling (MASEM) is a statistical approach combining the advantages of both meta-analysis and SEM for fitting structural equation models on a pool of correlation matrices. There are usually two stages in the analyses. In the first stage of analysis, a pool of correlation matrices is combined to form an average correlation matrix. In the second stage of analysis, proposed structural equation models are tested against the average correlation matrix. MASEM enables researchers to synthesize researching findings using SEM as the research tool in primary studies. There are several popular approaches to conduct MASEM, including the univariate-r, generalized least squares, two-stage SEM (TSSEM), and one-stage MASEM (OSMASEM). MASEM helps to answer the following key research questions: (a) Are the correlation matrices homogeneous? (b) Do the proposed models fit the data? (c) Are there moderators that can be used to explain the heterogeneity of the correlation matrices? The MASEM framework has also been expanded to analyze large datasets or big data with or without the raw data.


Micro-Foundations of Institutional Logic Shifts: Entrepreneurial Action in Response to Crises  

Trenton Alma Williams

Institutional logics shape how actors interpret and organize their environment. Institutional logics include society’s structural, normative, and symbolic influences that provide organizations and individuals with norms, values, assumptions, and rules that guide decision-making and action. While institutional logics influence individuals and organizations, they do not exist/form in a vacuum, but rather are instantiated in the practices and patterned behaviors of actors who act as carriers of logics in specific contexts. Given the dynamic interaction between institutional logics and individual/organizational actors, research has begun to explore the micro-level processes that influence institutional logic changes to help explain how and why those who are shaped by an institution enact changes in the very context in which they are embedded. Thus, the formation and changing of institutional logics involve precipitating action—which can include entrepreneurial action. Entrepreneurial action—especially in moments of crisis (e.g., when there is a disruptive event, natural disaster, or external feature that disturbs the status quo), can function as a micro-foundation for institutional logic shifts. An entrepreneurship model of dominant logic shifts therefore reveals how crises induce sensemaking activities that can influence shifts in how actor’s see the world, which in turn motivates the pursuit of entrepreneurial opportunities. Significant disruptions, such as environmental jolts, have a triggering effect in enabling individuals to problematize previously held beliefs and logics, allowing them to temporarily “step out of” status quo institutional logics. With prior beliefs and logics problematized, individual decision-makers become open to seeing new interpretations of their surroundings as it is and as it could be. Therefore, actors shift their dominant way of seeing the world (e.g., dominant logic) and then enact this new logic through ventures that, ultimately, can shift and alter institutional-level logics. Therefore, an entrepreneurship model of dominant logic shifts serves as an explanation for how broader institutional logics may shift as a result of the interaction between entrepreneurial action and the environment following a major disruption.


Minority Employees’ Ethnic Identity in the Workplace  

Nasima M. H. Carrim

With an increase in the number of diverse groups of individuals (including ethnic minorities) entering organizations, managing diversity in the 21st-century workplace has become imperative. The workplace provides employees with opportunities to work interactively with others in diverse situations and to express their identities, including ethnic identity. Despite Western-based organizations’ adoption of strategies such as affirmative action in an effort to integrate diverse employees into their workplaces, members of ethnic minority groups may still experience great difficulties in obtaining instrumental and social support in these organizations. While some minorities may not outwardly manifest their ethnicity, in the majority of cases, ethnic identity forms a core identity of many individuals and employees do not leave this identity at the doorstep of the organization. In some countries, ethnic minorities have refused to assimilate into the majority workplace culture, and have maintained strong ethnic identities. By outwardly expressing their identities, ethnic minority employees face discrimination, stereotyping and micro-aggressive behaviors within the workplace, and in the majority of cases are relegated to dead-end lower level posts and face barriers to their career advancement. Also, having strong ethnic identities results in a conflict between minorities ethnic identities and the workplace culture. This is especially apparent in terms of religious beliefs and values. Embracing ethnic identity of migrants into organizational cultures is especially challenging for organizations these days, as many immigrants are highly skilled professionals that enter western corporations. They experience discrimination and not receiving support in order to advance their careers.


Missing Data in Research  

Hettie A. Richardson and Marcia J. Simmering

Nonresponse and the missing data that it produces are ubiquitous in survey research, but they are also present in archival and other forms of research. Nonresponse and missing data can be especially problematic in organizational contexts where the risks of providing personal or organizational data might be perceived as (or actually) greater than in public opinion contexts. Moreover, nonresponse and missing data are presenting new challenges with the advent of online and mobile survey technology. When observational units (e.g., individuals, teams, organizations) do not provide some or all of the information sought by a researcher and the reasons for nonresponse are systematically related to the survey topic, nonresponse bias can result and the research community may draw faulty conclusions. Due to concerns about nonresponse bias, scholars have spent several decades seeking to understand why participants choose not to respond to certain items and entire surveys, and how best to avoid nonresponse through actions such as improved study design, the use of incentives, and follow-up initiatives. At the same time, researchers recognize that it is virtually impossible to avoid nonresponse and missing data altogether, and as such, in any given study there will likely be a need to diagnose patterns of missingness and their potential for bias. There will likewise be a need to statistically deal with missing data by employing post hoc mechanisms that maximize the sample available for hypothesis testing and minimize the extent to which missing data obscures the underlying true characteristics of the dataset. In this connection, a large body of programmatic research supports maximum likelihood (ML) and multiple imputation (MI) as useful data replacement procedures; although in some situations, it might be reasonable to use simpler procedures instead. Despite strong support for these statistical techniques, organizational scholars have yet to embrace them. Instead they tend to rely on approaches such as listwise deletion that do not preserve underlying data characteristics, reduce the sample available for statistical analysis, and in some cases, actually exacerbate the potential problems associated with missing data. Although there are certainly remaining questions that can be addressed about missing data techniques, these techniques are also well understood and validated. There remains, however, a strong need for exploration into the nature, causes, and extent of nonresponse in various organizational contexts, such when using online and mobile surveys. Such research could play a useful role in helping researchers avoid nonresponse in organizational settings, as well as extend insight about how best and when to apply validated missing data techniques.


Moral Disengagement and Organizations  

Catherine Hessick

One does not need to look extensively to find examples of organizations behaving unethically in today’s society. With the passage of whistleblower laws and the increased attention to ethical behavior in recent years, many businesses focus on training in order to reduce unwanted behavior. Despite organizations transitioning to more engaging, substantial ethical training programs for their employees, unethical behavior still remains. Moral disengagement, in part, could be the reason. Moral disengagement is when an individual deliberately deactivates their moral self-regulations, allowing the individual to commit unethical acts without shame or guilt. Moral disengagement has eight mechanisms: moral justification, euphemistic labeling, advantageous comparison, displacement of responsibility, diffusion of responsibility, distortion of the consequences, dehumanization, and attribution of blame. Each of these mechanisms offers insight into why and how moral disengagement operates within individuals. Because an individual’s reasoning can fall into either a single mechanism or a combination of them, measurement tools commonly place each mechanism as a dimension of moral disengagement. Doing so allows the researcher to examine the construct and its relationships more accurately. The research investigating unethical behavior in organizations is substantial. However, moral disengagement is an antecedent to unethical behavior and not necessarily an unethical act itself. Previous research on moral disengagement often lies within psychology, military science, sociology, and other nonbusiness fields. With the depths of moral disengagement in the workplace still unexplored, scholars have opportunities to contribute research that can help organizations understand moral disengagement, improve ethical training, and potentially curtail employees’ unethical behavior.


Moral Emotion and Intuition in Organizations  

Armin Pircher Verdorfer, Martin Fladerer, and Clarissa Zwarg

While traditional approaches have described ethical decision-making in organizations mainly as being the result of rational deliberative thought, a steadily growing body of research indicates that moral decision-making is strongly influenced by moral intuitions and emotions. The moral intuition approach typically has two aspects: the process through which moral intuitions emerge and their content. With regard to the process, moral intuitions represent fast, automatic, evaluative reactions that are emotionally charged. An important tenet of moral intuition research refers to the primacy of intuition—the notion that moral intuitions generally drive moral decision-making. Accordingly, moral intuitions are described as starting points for rational reflection processes that follow later. On this basis, it has also been argued that the interplay of moral intuition and deliberation is malleable. Specifically, the well-formed moral intuitions of experts are thought to differ from the naive moral intuitions of novices. With increasing experience and reflection about the moral issues in one’s experiences, deliberation increasingly enables individuals to shift between intuitions and reasoning and to monitor, test, weigh, and reject both intuitions and reasons. The content of moral intuition refers to the foundations of morality, which are the underlying moral domain, specifying what individuals view as morally right or wrong. The most commonly referenced account in this field, Moral Foundations Theory (MFT), argues that moral intuitions are a function of evolutionarily developed, innate predispositions to master multiple social problems that interact with social and cultural influences. These predispositions, or moral foundations, include care, fairness, loyalty, authority, and sanctity. While empirical work on the role of moral intuition in organizations is still at an early stage, several areas have been identified that may particularly benefit from integrating moral intuition process and content. For instance, the moral intuition perspective can aid the understanding and prevention of processes through which unethical behaviors and practices, such as corruption, may be justified and normalized in organizations. Furthermore, the moral intuition perspective is increasingly used to study the moral leadership process, most notably the link between leader moral foundations and moral leader behaviors, as well as the role of (mis)fit between leader and follower moral foundations. Moral emotions are an inherent element of the moral intuition process and refer to the welfare of others and the promotion of a functioning society. It is thought that individuals experience moral emotions when they or others have violated moral standards. These emotions build the motivational force for moral action and are often placed in five clusters: other‐praising (e.g., gratitude), other‐suffering (e.g., sympathy), other‐condemning (e.g., contempt), self‐condemning (e.g., guilt), and self-approving (e.g., moral pride) moral emotions.


(Multi)Collinearity in Behavioral Sciences Research  

Dev K. Dalal

A statistical challenge many researchers face is collinearity (also known as multicollinearity). Collinearity refers to a situation in which predictors - independent variables, covariates, etc. - are linearly related to each other and typically are related strongly enough as to negatively impact one’s statistical analyses, results, and/or substantive interpretations. Collinearity can impact the results of general linear models (e.g., ordinary least squares regression, structural equation modeling) or generalized linear models (e.g., binary logistic regression; Poisson regression). Collinearity can cause (a) estimation/convergence challenges (particularly with iterative estimation methods), (b) inflated standard errors, as well as (c) biased, unstable, and/or uninterpretable parameter estimates. Due to the issues in the results, substantive interpretation of models with collinearity can be inaccurate, sometimes in significant ways (e.g., nonsignificant predictors that are in fact significantly related to the outcome). In standard linear models, researchers can make use of variance inflation factor (VIF) or tolerance (Tol) indices to detect potential collinearity. Although zero-order correlations may be useful for detecting collinearity in rare instances, most researchers will want to use VIF or Tol to capture the potential for collinearity resulting from linear combinations of predictors. For statistical models that use iterative estimation (e.g., generalized linear models), researchers can turn to condition indices. Researchers can address collinearity issues in a myriad of ways. This includes basing models on well-developed a priori theoretical propositions to avoid including empirically or conceptually redundant variables in one’s model—this includes the careful and theoretically appropriate consideration of control variables. In addition, researchers can use data reduction techniques to aggregate correlated covariates (e.g., principal components analysis or exploratory factor analysis), and/or use well-constructed and well-validated measurements so as to ensure that measurement of key variables are not related due to construct overlaps.


Multicultural Identities at Work  

Yih-Teen Lee and Nana Yaa Gyamfi

Cultural identity, a specific form of social identity that refers to a person’s degree of identification and sense of belonging to a specific cultural group, has been extensively examined as a kind of social identity over the past decades, especially in the fields of migration, cross-cultural psychology, and applied international management. Meanwhile, exposure to settings with different cultures typically triggers a process of acculturation, enabling individuals to develop multicultural identities, whereby people see things from multiple cultural groups’ perspectives, feel at one with the cultural groups, and act according to the norms of those cultural groups. Individual organizational members serve as the conduit by which culture influences and is influenced by organizational life. There exist various forms of multicultural identities with different psychological and behavioral implications on individuals. In terms of plurality, to date, extant studies accumulated extensive knowledge on biculturalism, which focuses on individuals having two distinct cultural identities and how these identities intersect and influence the individual. Beyond biculturalism obtained through birth, ancestry, or immersive foreign experience, individuals may become multicultural by being simultaneously immersed in more than two cultures: a situation common among children of immigrants (i.e., second-generation immigrants), children raised in multicultural households, third culture individuals who spend their formative years outside their passport country, and individuals living within multicultural societies. A key to understanding multicultural identities is how these multiple identities are structured within individuals. Scholars largely agree that the structural pattern of identities affects the outcomes and degree of synergy among multiple identities. Widely accepted modes of structuring multiple identities include relative strength of identities involved and how multiple identities relate to each other. Scholars have built on these lines of thinking to examine specific forms of multicultural identities and their outcomes. Furthermore, research indicates that multiculturals possess unique identity resources relevant to organizational life, including cognitive strengths, relational capital and belonging, and leadership-related competencies. Although there is evidence for responsiveness of multicultural identity to situational cues, there are also strong arguments made in favor of the agency of individuals over their multiple identities. The foregoing notwithstanding, individuals with multicultural identities must balance their agentic enactments of identity with societal requirements of legitimacy. In particular, business organizations play a vital role in providing identity workspaces and other enabling factors which legitimize multicultural identities. Additionally, business organizations play the role of balancing power, status and other dynamics between multicultural and non-multicultural members.