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A recent cross-cultural study suggests employees may be classified, based on their scores on a measure of work ethic, into three profiles labeled as "live to work," "work to live," and "work as a necessary evil." The present study assesses whether these profiles were stable before and after an extended lockdown that forced employees to work from home for 2 years because of the COVID-19 pandemic. To assess our core research question, we conducted a longitudinal study with employees of a company in the financial sector, collecting data in two waves: February 2020 ( n = 692) and June 2022 ( n = 598). Tests of profile similarity indicated a robust structural and configural equivalence of the profiles before and after the lockdown. As expected, the prolonged pandemic-based lockdown had a significant effect on the proportion of individuals in each profile. Implications for leading and managing in a post-pandemic workforce are presented and discussed. JEL CLASSIFICATION: M12

This study utilized the social relations model (SRM) to examine the influence of interpersonal perceptions on team processes and outcomes. We hypothesized that the three components of the SRM (assimilation, consensus, and unique relations) would yield differential relationships with group process outcomes. We proposed that unique relations in members' perceptions of group members, perceptual relationships specific to particular dyads within a focal group, would be a source of negativity within teams' outcomes. Participants were undergraduates who worked in small groups for assignments for the duration of one semester; each member rated themselves and their teammates on five individual-level characteristics. Hypotheses about unique relations were supported. This component of the SRM model was positively related to conflict and negatively related to cohesion, showing the greatest relative importance among the three SRM components in predicting team process and outcomes.

This present study examined the factors associated with organizational commitment among blue-collar workers. Previous work in this area suggests that, among blue-collar employees, commitment should be more closely related to extrinsic rewards (e.g., pay satisfaction) than to intrinsic factors. In order to test this hypothesis, sixty-four public service employees in a waste, water, and sanitation department completed a questionnaire designed to measure organizational commitment and perceptions of extrinsic and intrinsic factors related to their jobs. The results indicated that the following were positively and significantly related to commitment: promotion satisfaction, job characteristics, communication, leadership satisfaction, job satisfaction, extrinsic exchange, intrinsic exchange, extrinsic rewards, and intrinsic rewards. Contrary to expectations, pay satisfaction did not correlate significantly with commitment. Both intrinsic and extrinsic rewards were equally predictive of commitment; this contradicts the contention that extrinsic rewards are more important determinants of blue-collar commitment. These findings are noteworthy because they suggest that intrinsic rewards are important for public service employees, members of a relatively understudied population.

For nearly three decades, the predominant approach to modeling the latent structure of multitrait–multimethod (MTMM) data in organizational research has involved confirmatory factor analysis (CFA). Despite the frequency with which CFA is used to model MTMM data, commonly used CFA models may produce ambiguous or even erroneous results. This article examines the potential of generalizability theory (G-theory) methods for modeling MTMM data and makes such methods more accessible to organizational researchers. Although G-theory methods have existed for more than half a century, the research literature has yet to provide a clear description and integration of latent models implied by univariate and multivariate G-theory with MTMM data, notions of construct validity, and CFA. To help fill this void, the authors first provide a jargon-free overview of the univariate and multivariate G-theory models and analytically demonstrate linkages between their parameters (variance and covariance components), elements of the MTMM matrices, indices of convergent and discriminant validity, and CFA. The authors conclude with a discussion and empirical illustration of a G-theory-based modeling process that helps clarify the use of G-theory methods for modeling MTMM data.

Three major reviews of the assessment center (AC) construct-validity literature have disagreed as to the most appropriate analytic model for AC postexercise dimension ratings. We report a Monte Carlo study addressing the following questions: (a) To what extent does the "true" model (i.e., the model that generated the data) actually appear to fit the data well? (b) To what extent can a model appear to fit the data well even though it is the wrong model? and (c) Is model fit actually a useful empirical criterion for judging which model is most likely the population model? Results suggest that "true" models may not always appear as the best fitting models, whereas "false" models sometimes appear to offer better fit than the true models. Implications for the study of AC construct validity are discussed.

The goal of the present study is twofold. First, we take a person-centered approach to individual differences in work ethic. Here, we focus on the identification and stability of profiles of work ethic dimensions across individuals from two relatively diverse samples. Second, we examine the extent to which work ethic profile membership influences which characteristics of an ideal coworker are viewed as most important. To assess our hypotheses, we used a diverse US-based sample of 2440 as well as a sample of 692 employees in sales-related positions in the financial sector in Mexico. Results from a series of latent profile analyses (LPAs) clearly support the idea that from the combination of scores on the seven dimensions of work ethic, clear and reliable profiles emerge and were generalizable across samples. The three profiles were identified as "Live to Work," "Work to Live," and "Work as a Necessary Evil." Significant differences were found in 5 of 11 desired attributes of an ideal coworker between the employees in the three emerging profiles. Also, in line with our hypotheses, results show that employees belonging to the profile with the highest scores on the core dimensions of the work ethic construct reported that the top desired characteristic in an ideal peer is the hard worker attribute.

Emergent states are team-level attributes that reflect team members' collective attitudes, values, cognitions, and motivations and influence team effectiveness. When measuring emergent states (e.g., cohesion, conflict, satisfaction), researchers frequently collect ratings from individual group members and aggregate them to the team level. After aggregating to the team level, researchers typically focus on mean differences across teams and ignore variability within teams. Rather than focusing on the mean level of emergent states, this study draws on recent advances in multilevel theory and describes an approach for examining the specific patterns of dispersion (i.e., disagreement) across five emergent states. Our findings suggest that teams reliably demonstrate different patterns of rating dispersion that are consistent with existing theoretical frameworks and typologies of dispersion, yet have not previously been empirically demonstrated. We also present evidence that the different patterns of dispersion in emergent states are significantly related to key team outcomes, even after controlling for the mean levels of those emergent states. These findings underscore the importance of exploring additional forms of team-level constructs and highlight ways of extending our understanding of group-level phenomena.

Management researchers often use consensus-based composition models to examine the antecedents and effects of higher-level constructs. Typically, researchers present three indices, rwg, ICC(1), and ICC(2), to demonstrate agreement and consistency among lower-level units when justifying aggregation. Nevertheless, researchers debate what values for these indices are sufficient. This study examines the distributional characteristics of ICCs and rwg values from three sources: the multilevel literature, a large multinational sample of student teams, and a large sample of randomly generated "pseudo teams." Our results support existing cutoff criteria for ICCs but suggest that generally accepted values for rwg may, under certain circumstances, reflect pseudo-agreement (i.e., agreement observed among two raters not attributable to the same target). Thus, when there is minimal between-group variance (i.e., low ICCs), it is difficult to determine whether high rwg values reflect agreement or pseudo-agreement. Based on these findings, we provide recommendations to help researchers interpret aggregation indices.