Animal roles in organizations: A framework for exploring organizational human–animal relations

Despite the growing body of research on human–animal studies in various disciplines, attempts to systematically include animals in organization studies have been limited. In this article, we build on organizational role theory and propose a typology of five roles of animals in human organizations (i.e., animals as commodities, clients, co-workers, companions, and acquaintances) as a framework for analyzing organizational human–animal relations. The identified roles emerge as distinct categories that illuminate the varying degrees of agency afforded to animals in certain organizational settings and the extent to which human work is focused on animals. Lastly, we outline how advancing scholarly perspectives on animals in organizations requires going beyond anthropocentric and anthropomorphic perspectives and suggest various avenues for future research

Evolution of professionals' careers upon graduation in STEM and occupational turnover over time: Patterns, diversity characteristics, career success, and self-employment

While STEM occupational turnover constitutes a major concern for society given the importance of innovation and technology in today's global economy, it also represents an opportunity to achieve career sustainability for individuals. There is ample research on the reasons why students drop out from STEM education, but evidence on STEM professionals' career patterns and on correlates of occupational turnover after graduation is scarce. Drawing on the sustainable careers framework, the current study examines how STEM graduates' careers evolve over time, revealing diverse patterns of occupational turnover and the relationships of such career patterns with work diversity characteristics in terms of sex and ethnic minority status, career success, and self-employment. Using longitudinal data from 1512 STEM graduates over 10 years, results of an optimal matching analysis demonstrate six career patterns that can be distinguished into three continuity (STEM, part-STEM, non-STEM) and three change (hybrid, boomerang, dropout) sustainable career patterns. We find differences in sex, but not in ethnic minority status, across career patterns. Further, professionals who change from STEM occupations to non-STEM occupations show higher objective career success and are more often self-employed than those following a continuous STEM career pattern. Theoretical and practical implications of these findings are discussed

The emergence of similar personalities in similar occupations

Personality research suggests that individuals tend to develop more homogeneous—or similar—personalities within, rather than between, occupations due to attraction and selection, attrition, and socialization effects. We expand this perspective using a distance‐based methodological approach that relates similarities between combinations of individuals' personality traits to similarities between their occupations. Leveraging German panel data tracing individuals' careers from 2005 to 2017, we test how attraction and selection, attrition, and socialization effects contribute to the emergence of similar personalities in similar occupations over time. Our results reveal that individuals with more similar Big Five personality traits join more similar occupations, whereas those with personalities less similar to those of other occupational incumbents are more likely to leave the occupation. Moreover, individuals staying in more similar occupations develop more similar personalities. These findings enhance our understanding of the intricate interplay between individuals' personalities and occupations, providing evidence that similar personality traits emerge not only within the same occupation but also between similar occupations over time

Navigating the boomerang mobility process: A conceptual framework and agenda for future research

What happens when people leave an organization but return to it later? Expanding the dominant organizational and HRM perspectives on boomerang employment, we advocate for a career transition approach that incorporates an individual focus. We define the boomerang mobility process as a series of career transitions, starting with the exit transition from the original employer, and ending with the boomerang transition when that employee returns to that original employer. We offer a comprehensive conceptual model of the boomerang mobility process, including its antecedents, mediating processes, outcomes, and boundary conditions. By providing insights into the organizational and individual considerations that may influence employees' decision to rejoin an organization, this conceptual model expands the career mobility scholarship and offers a more nuanced understanding of individuals' career development.</p

A career ecosystem perspective on societal and organizational characteristics and careers to the top in higher education

The context in which careers develop is attracting increasing scholarly attention. Building on career ecosystem theory, we examine how societal and organizational actors within career ecosystems influence the development of careers. In our study of university leaders in 60 countries, we find that career trajectories are more similar within than across countries and that the overall organizational context relates to the similarity of career trajectories within the career ecosystem. We identify six distinct career patterns to the top of organizations within the ecosystem of higher education (e.g., ‘university president’ or ‘rector’). Furthermore, we identify several societal and organizational characteristics that are related to the prevalence of specific career patterns. Key findings include that academic leaders' careers tend to follow career patterns within the same organization in countries with low power distance, low labour market flexibility and low meritocracy, as well as in universities with less research focus. Our findings add to the literature on career ecosystems and advance the understanding of career paths to the top of organizations, using the case of academic careers

Optimal matching analysis in career research: A review and some best-practice recommendations

Optimal matching is a method for the analysis of sequential data. It allows researchers to detect patterns in career sequences or in trajectories of vocational development. After giving a brief introduction to the method, we review the present literature on careers and vocational development to show where optimal matching analysis has already been employed. We then conduct Monte Carlo simulations of data with varying parameters for sequence length and sample size. Based on the results from these simulation studies, we recommend which properties data sets should have for an optimal matching analysis. We also provide guidelines on how to code sequences, discuss how to deal with missing values, and show which cost settings and clustering algorithms deliver the best results for data sets with specific properties