Torsten Biemann

Size Does Matter: How Varying Group Sizes in a Sample Affect the Most Common Measures of Group Diversity

Work group diversity can be conceptualized in different ways (i.e., variety, separation, and disparity), and the appropriate operationalization of a diversity dimension depends on which of these diversity types researchers have in mind. Based on prior work on the measurement of the different types of diversity, we show that the most common diversity indexes (i.e., Blau’s index, Teachman’s index, standard deviation, mean Euclidean distance [MED], Gini coefficient, and coefficient of variation) are systematically biased whenever they are used in field studies in which the overall sample comprises groups of varying sizes. Using simulated data, we illustrate this bias inherent in all of the common diversity measures. This bias can lead to erroneous conclusions concerning the impact of group size and the relationship between group diversity and group outcomes. We offer bias-corrected formulas and suggest that diversity researchers henceforth use these adjusted versions when investigating the effects of group diversity in organizational settings.

What makes them move abroad? Reviewing and exploring differences between self-initiated and assigned expatriation

Only in recent years have self-initiated expatriates (SIEs) been distinguished from assigned expatriates (AEs). But there is still a lack of empirically based comparative results. Statistical analysis, performed on data from 193 expatriates (NAE = 67; NSIE = 126), indicates that self-initiated foreign work experience is significantly more likely to be chosen by women and those having lower job levels. Furthermore, boundaryless and protean career orientation only partially predicted which career path is chosen. SIEs have higher organizational mobility preferences, but do not differ from AEs in their boundaryless mindset and protean career attitude. Implications of these findings for research in expatriation are discussed.

Do Economic Globalization and Industry Growth Destabilize Careers? An Analysis of Career Complexity and Career Patterns Over Time

We analyze the impact of economic globalization and industry growth on the complexity of early work careers in Germany. We conceptualize complexity as the absolute number of employer changes, the regularity in the order of job changes, and the variability of the durations spent in different employment states. Results from empirical analyses based on the German Life History Study (N = 5453) show only a small increase in the complexity of work careers over the last decades, but there was a shift in the prevalence of different career patterns. This suggests that effects of globalization might be counteracted or modified by other social changes that affected work careers in Germany during the last 60 years. In particular, we consider the possible impact of educational expansion, labor market restructuring, and women’s increased employment. We find no evidence that industry-specific economic globalization impacts the complexity of work careers, but we find a U-shaped relationship between industry growth and career complexity. Careers are slightly more complex in industries with high or low industry growth. We conclude that, while there has been a shift in career patterns over time, the impact of globalization on career stability is possibly overestimated.

Career patterns of top management team members in five countries: an optimal matching analysis

This paper introduces optimal matching analysis (OMA) to the field of top management research. With this method, we develop six career patterns of top management team (TMT) members from five countries based on their international experience, organizational tenure and professional experience. The results provide strong support for the significance of these patterns, since each country (Denmark, Germany, Japan, the United Kingdom and the United States) shows one to four predominant career patterns of their managers and the occurrence of these patterns also differs significantly between the fields of activity within the TMT (chairperson, head of a division, primary activities and support activities).

A taxonomy of internationally mobile managers

Research on expatriates indicates that substantial differences exist within internationally active employees. Several typologies of expatriates have been suggested to account for this diverseness. However, empirical evidence on the accuracy of these classification schemes is scarce. On the basis of these research efforts, we introduce a data-based taxonomy of internationally mobile managers. By means of sequence analysis, we derive four career patterns from the curriculi vitae of 202 German managers. These patterns are built on the dimensions mobility and duration of the stays abroad. We further show that these patterns differ with regard to various individual and organizational variables. On the basis of these findings, we argue that expatriation career management practices and responsibilities need to be differentiated.Research on expatriates indicates that substantial differences exist within internationally active employees. Several typologies of expatriates have been suggested to account for this diverseness. However, empirical evidence on the accuracy of these classification schemes is scarce. On the basis of these research efforts, we introduce a data-based taxonomy of internationally mobile managers. By means of sequence analysis, we derive four career patterns from the curriculi vitae of 202 German managers. These patterns are built on the dimensions mobility and duration of the stays abroad. We further show that these patterns differ with regard to various individual and organizational variables. On the basis of these findings, we argue that expatriation career management practices and responsibilities need to be differentiated.

Ageing and work motivation: A task-level perspective

Purpose – The paper aims to establish the position that discrete work tasks, rather than entire jobs, are the most useful level of analysis of age differences in work motivation.Design/methodology/approach – A total of 189 workers (aged 18‐65 years) from production and office jobs in the building industry completed a survey on personal and job resources, overall and task‐specific motivation, and job satisfaction.Findings – Age was positively associated with motivation for generativity‐related, but not growth‐related tasks. Personal and job resources were positively and differentially related to task‐specific motivation.Research limitations/implications – Building on the notion of age‐specific constellations of high and low‐motivation tasks, the findings inspire research into age‐related changes in work motivation. The authors studied only two task types; a more comprehensive task set will in future studies yield deeper insights into motivational regulation. Working with other industry sectors will enhance...

The impact of international experience on objective and subjective career success in early careers

There is an ongoing debate in the literature on the long-term impact of international work experience on future career success. In this longitudinal study based on university graduates, we compare expatriates (n = 159), repatriates (n = 395) and domestic employees (n = 2697) with regard to their objective and subjective career success during the first five years of their careers. Results from propensity score matching and ordinary least-squares regressions show that expatriates and repatriates have a higher objective career success in terms of monthly wages. We further find a higher subjective career success for expatriates and male repatriates.

Analyzing Sequence Data Optimal Matching in Management Research

In this article we discuss optimal matching (OM), an invaluable yet underutilized tool in the analysis of sequence data. Initially developed in biology to identify and study patterns in DNA sequences, OM subsequently migrated over to sociology, where it has been used to examine career patterns in life course research. It involves the computation of the number of insertions, deletions, and substitutions of sequence elements that are needed to transform one sequence into another and the costs associated with such transformations. The goal is to identify similarities across sequences, which can then be used for pattern identification. Along with a discussion of the logic underlying OM analysis, we provide an illustration of its use in the examination of careers of deans at U.S. business schools. In addition, we use Monte Carlo simulation to compare OM and cluster analysis and highlight the superiority of OM analysis in the analysis of sequence data. Also discussed are recent methodological advances that have been made in OM and our recommendations and guidelines for future applications of OM in management research.

The role of risk propensity in predicting self-employment.

This study aims to untangle the role of risk propensity as a predictor of self-employment entry and self-employment survival. More specifically, it examines whether the potentially positive effect of risk propensity on the decision to become self-employed turns curvilinear when it comes to the survival of the business. Building on a longitudinal sample of 4,973 individuals from the German Socio-Economic Panel, we used event history analyses to evaluate the influence of risk propensity on self-employment over a 7-year time period. Results indicated that whereas high levels of risk propensity positively predicted the decision to become self-employed, the relationship between risk propensity and self-employment survival followed an inverted U-shaped curve.

A TRANSITION-ORIENTED APPROACH TO OPTIMAL MATCHING

Optimal matching (OM) is a method that assesses sequence similarity. It was originally developed to study protein and DNA sequences and was later transferred to the social sciences where it was applied accordingly. However, there is an ongoing debate on the adequacy of its use in the social sciences, as a superficial transfer might not respond to the significant differences between typical sequences in biological and social settings. In this paper, I elaborate on these differences and introduce a distinction between two sequence types—namely, common ancestors and unfolding processes. While the first sequence type is typically found in biological settings (e.g., DNA sequences), the latter applies to most sequences studied in the social sciences (e.g., careers). Based on this distinction, I present a new way of coding sequences as an extension to conventional OM analyses and demonstrate its usefulness in simulated and empirical examples. The paper concludes with a discussion of this new approach and its integration into previous extensions of OM.