Causes and Consequences of Collective Turnover: A Meta-Analytic Review

Given growing interest in collective turnover (i.e., employee turnover at unit and organizational levels), the authors propose an organizing framework for its antecedents and consequences and test it using meta-analysis. Based on analysis of 694 effect sizes drawn from 82 studies, results generally support expected relationships across the 6 categories of collective turnover antecedents, with somewhat stronger and more consistent results for 2 categories: human resource management inducements/investments and job embeddedness signals. Turnover was negatively related to numerous performance outcomes, more strongly so for proximal rather than distal outcomes. Several theoretically grounded moderators help to explain average effect-size heterogeneity for both antecedents and consequences of turnover. Relationships generally did not vary according to turnover type (e.g., total or voluntary), although the relative absence of collective-level involuntary turnover studies is noted and remains an important avenue for future research

ILR Research in Progress 2011-12

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Research_in_Progress_2011_12.pdf: 46 downloads, before Oct. 1, 2020

Quality of Available Mates, Education and Intra-Household Bargaining Power

This paper further explores the role of sex ratios on spouses’ bargaining power, by focusing on educational attainment in order to capture the qualitative aspect of mate availability. Using Census and Current Population Survey data for U.S. metropolitan areas in year 2000, a quality sex ratio is constructed by education brackets to test the effect on the intra-household bargaining power of couples in the corresponding education bracket. We argue that a relative shortage of suitably educated women in the spouse’s potential marriage market increases wives’ bargaining power in the household while it lowers their husbands’. Additionally, we test the prediction that this bargaining power effect is greater as the assortative mating order by education increases. We consider a collective labor supply household model, in which each spouse’s labor supply is negatively related to their level of bargaining power. We find that higher relative shortage of comparably educated women in the couple’s metropolitan area reduces wives’ labor supply and increases their husbands’. Also, the labor supply impact is stronger for couples in higher education groups. No such effects are found for unmarried individuals, which is consistent with bargaining theory.Education, Intra-Household Bargaining Power, Labor Supply

A common rule for decision-making in animal collectives across species

A diversity of decision-making systems has been observed in animal collectives. In some species, choices depend on the differences of the numbers of animals that have chosen each of the available options, while in other species on the relative differences (a behavior known as Weber's law) or follow more complex rules. We here show that this diversity of decision systems corresponds to a single rule of decision-making in collectives. We first obtained a decision rule based on Bayesian estimation that uses the information provided by the behaviors of the other individuals to improve the estimation of the structure of the world. We then tested this rule in decision experiments using zebrafish (Danio rerio), and in existing rich datasets of argentine ants (Linepithema humile) and sticklebacks (Gasterosteus aculeatus), showing that a unified model across species can quantitatively explain the diversity of decision systems. Further, these results show that the different counting systems used by animals, including humans, can emerge from the common principle of using social information to make good decisions

An analytical framework to nowcast well-being using mobile phone data

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly "nowcast" the well-being and the socio-economic development of a territory

Being Different Yet Feeling Similar: The Influence Of Demographic Composition And Organizational Culture On Work Processes And Outcomes

Drawing from self-categorization theory, we tested hypotheses on the effects of an organization's demographic composition and cultural emphasis on work processes and outcomes. Using an organizational simulation, we found that the extent to which an organization emphasized individualistic or collectivistic values interacted with demographic composition to influence social interaction, conflict, productivity, and perceptions of creativity among 258 MBA students. Our findings suggest that the purported benefits of demographic diversity are more likely to emerge in organizations that, through their culture, make organizational membership salient and encourage people to categorize one another as having the organization's interests in common, rather than those that emphasize individualism and distinctiveness among members.(.)Managemen

When none of us perform better than all of us together: the role of analogical decision rules in groups

During social interactions, groups develop collective competencies that (ideally) should assist groups to outperform average standalone individual members (weak cognitive synergy) or the best performing member in the group (strong cognitive synergy). In two experimental studies we manipulate the type of decision rule used in group decision-making (identify the best vs. collaborative), and the way in which the decision rules are induced (direct vs. analogical) and we test the effect of these two manipulations on the emergence of strong and weak cognitive synergy. Our most important results indicate that an analogically induced decision rule (imitate-the-successful heuristic) in which groups have to identify the best member and build on his/her performance (take-the-best heuristic) is the most conducive for strong cognitive synergy. Our studies bring evidence for the role of analogy-making in groups as well as the role of fast-and-frugal heuristics for group decision-making

Will This Paper Increase Your h-index? Scientific Impact Prediction

Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with a growing body of literature focused on predicting the number of citations obtained by any given publication. The effectiveness of such predictions, however, is fundamentally limited by the power-law distribution of citations, whereby publications with few citations are extremely common and publications with many citations are relatively rare. Given this limitation, in this work we instead address a related question asked by many academic researchers in the course of writing a paper, namely: "Will this paper increase my h-index?" Using a real academic dataset with over 1.7 million authors, 2 million papers, and 8 million citation relationships from the premier online academic service ArnetMiner, we formalize a novel scientific impact prediction problem to examine several factors that can drive a paper to increase the primary author's h-index. We find that the researcher's authority on the publication topic and the venue in which the paper is published are crucial factors to the increase of the primary author's h-index, while the topic popularity and the co-authors' h-indices are of surprisingly little relevance. By leveraging relevant factors, we find a greater than 87.5% potential predictability for whether a paper will contribute to an author's h-index within five years. As a further experiment, we generate a self-prediction for this paper, estimating that there is a 76% probability that it will contribute to the h-index of the co-author with the highest current h-index in five years. We conclude that our findings on the quantification of scientific impact can help researchers to expand their influence and more effectively leverage their position of "standing on the shoulders of giants."Comment: Proc. of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15