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Talent compression is the labor market phenomenon where the average productivity differential between participants declines and has been used to explain the overall increase in competition within some professional sports markets. A finding that competitiveness is uniquely driven by talent compression is consistent with Rottenberg (1956), who argued that resource distribution is independent of factors that are invariant to labor productivity.

Rather than incorporate MLB team roster turnover as many of the past studies have done, we prefer to measure of all-star turnover in membership. Problematically, movement from an MLB team to an MLB team is limited by rule, finances and the fact that there are very few teams competing for player services. In contrast, All-Star membership is typically costlessly chosen by many millions of fans, league players and managers. In this way, All-Star voting should be invariant to many of the factors that affect movement from an MLB team to an MLB team.

In the end, we find that a close association between all-star turnover rates and the makeup of MLB’s labor pool.

The paper offers a new measure of player mobility.

The purpose of this paper is to examine the relationship between national diversity and team performance. Research on US teams involved in a task of low interdependence (baseball) is replicated with a Japanese sample to investigate possible cross‐national differences. The paper also presents a new quantitative measure of diversity.

This study uses quantitative research based on archival data. Regression modeling is applied to professional sports data from Japan. National diversity of teams is operationalized using a new approach to Blau's Index.

A negative relationship was found between national diversity and team performance in Japan. No significant results were found for age diversity. The results for national diversity are in contrast to research conducted on similar teams in the USA.

The findings provide evidence of cross‐national differences between US and Japanese teams. Findings are also directly applicable to managers in the growing field of international sports management and sports business.

Globalization has resulted in the internationalization of the professional sports industry. This paper is one of the first international studies of professional sports teams that span the East‐West divide, to provide insights on international team performances. Findings from this cross‐national comparison of US and Japanese teams contribute to organizational research by reinforcing the need to consider national context in diversity research. Educators will find that use of professional sports allows students to easily relate to the findings of the study. Managers are offered direct evidence that team dynamics related to diversity are different between US and Japanese teams.

The evidence is strong that the instability of teacher rosters in urban school settings has negative consequences for student learning, but our concern is with the opposite phenomenon: What is the value added to the organization when a school's teaching roster is stable over time? Our theory of teacher corps stability hinges on the claim that the stability of a teacher corps over time is a sine qua non that, under certain conditions, permits formation of the social capital needed to catalyze school effectiveness.

We test this claim using longitudinal data from 72 schools in a large, urban southwestern US school district. We first identified a subset of 47 schools with either chronic teacher turnover (high, stable turnover) or a stable teacher roster (low, stable turnover) via school-level HLM growth modeling techniques. These classifications were then used as a covariate in a series of HLM growth models investigating its relationship to growth in structural, relational and cognitive social capital over time.

Our findings sustain a claim of the importance of teacher corps stability. In our sample of urban schools, we found robust increases in the relational and cognitive dimensions of social capital over time in those schools with stable rosters. Furthermore, schools with chronic turnover were declining significantly in relational social capital, but no appreciable growth in structural social capital was found in either stable roster or chronic teacher turnover schools.

Given the nature of teacher corps stability and its relationship to key organizational outcomes, school leaders play a central role in realizing teacher corps stability within their school. A certain amount of this effort must necessarily be focused on retaining a stable corps of quality, happy, committed teachers. However, building social capital concerns the active engagement of all actors; thus, school leaders need to think beyond retention to how the teachers that remain can play larger leadership roles in this process.

Few studies have examined the positive benefits that can emerge in schools where the majority of teachers remain year after year. Collectively, the study findings suggest that teacher corps stability can provide fertile conditions for the development of social capital that has the potential to enhance school effectiveness and that its staff can leverage for school improvement.

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector. There are over 16,000 medical scientists (AIHW, 2019) in Australia responsible for carrying out pathology testing to help save the lives of thousands of patients every day. However, there are systemic shortages of medical scientists largely due to erratic rostering practices and workload issues. The purpose of this paper is to integrate evidence-based human resource management (EBHRM), the LAMP model and HR analytics to enhance line manager decision-making on rostering to support the wellbeing of medical scientists.

Using a qualitative methodological approach, the authors conducted 21 semi-structured interviews with managers/directors and nine focus groups with 53 medical scientists, making a total 74 participants from four large public hospitals in Australia.

Across four health services, manual systems of rostering and management decisions do not meet the requirements of the enterprise agreement (EA) and impact negatively on the wellbeing of medical scientists in pathology services. The authors found no evidence of the systematic approach of the organisations and line managers to implement the LAMP model to understand the root causes of rostering challenges and negative impact on employees. Moreover, there was no evidence of sophisticated use of HR analytics or EBHRM to support line managers' decision-making regarding mitigation of rostering related challenges such as absenteeism and employee turnover.

The authors contribute to HRM theory by integrating EBHRM, the LAMP model (Boudreau and Ramstad, 2007) and HR analytics to inform line management decision-making. The authors advance understandings of how EBHRM incorporating the LAMP model and HR analytics can provide a systematic and robust process for line managers to make informed decisions underpinned by data.

The purpose of this paper is to empirically investigate the interactive effect of turnover and task interdependence on performance in work teams. Based on pervious research, the authors contend that turnover will have a negative effect on team performance and this effect will be more pronounced as teams perform highly interdependent tasks.

Using longitudinal data from the National Football League (NFL), the authors empirically examine the effect of player turnover on NFL team performance (i.e. wins and losses in the subsequent year), and the difference in team performance based on the high/low task interdependence of the work team.

Findings suggest a negative impact of turnover on organizational performance, regardless of the interdependent nature of work team tasks. In addition, the negative influence of turnover is enhanced by the task interdependence within a team.

This is one of the few studies that examine task interdependence as a moderating variable of the turnover – team performance relationship. More specifically, by examining an industry with high team member turnover (i.e. The NFL), the findings from this study give practicing managers a guide as to which work teams managers should attempt to minimize turnover.

There appear to be many paradoxes within the management of the growing call centre sector. The purpose of this paper is to consider one of these paradoxes, the extensive recruitment and training regimes in workplaces that are faced with very high levels of turnover.

This research is of a single worksite, a call centre of a public utilities company. The research method was non‐participant observation over a seven‐month period coupled with ten interviews with key personnel.

It was found that the organisation was able to offset the costs of training and recruitment through internal transfers within the larger organisation.

It is a single site study, hence, while of substantial depth the findings are not generalisable. More broad based research is required in the area.

A useful source of information for practitioners in call centres, as well as researchers in the area of recruitment, training and call centres.

This paper provides a valuable insight into an area of call centres that has not been adequately investigated; that of recruitment and training employees for emotional labour.

The Chinese Professional Baseball League (CPBL) experienced a rapid decline in attendance after the mid 1990s. In this study, market demand analysis is used to discover the causes of variation in CPBL attendance from 1990 to 2008. The ordinary least squares (OLS) is employed for model estimation. From this model, empirical evidence reveals that a homogenous sport substitute, Taiwan Major League (TML), the Major League Baseball (MLB) effect and game-fixing scandals in CPBL negatively influence CPBL attendance. Additionally, real income is found to negatively affect CPBL attendance, making CPBL games an inferior product. The proposed model accounts for approximately 91% of variation in CPBL attendance between 1990 and 2008.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.

Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.

Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.

Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.

Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

The purpose of this paper is to illustrate the effect of controllability on compensation of Major League Baseball.

The sample consists of Major League Baseball players who have publicly published compensations figures and who have actively played in the Major Leagues. All data used in the study are publicly available. Multiple regression is employed to test the relationship between player's performance and starting salary of the next season.

The paper proposes that strikeouts, bases on balls, and home runs are relatively controllable for both hitters and pitchers because these performance measures are essentially independent of other teammates' performance.

The distinctness of professional baseball players by nature may constrain the generalization of this paper. It is recommended that further interpretation of the effects of controllability on compensation for other high‐interdependency organizations should be made with caution.

It is suggested that managers in low‐interdependency organizations should make a stronger linkage between subordinates' controllable performance and their compensation. If the compensation plan is designed to maximize the subordinates' reward for performing a controllable task, they will be motivated to expend greater effort on it.

This article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.

A literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.

Findings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.

Given the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.

This article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.