Although it has been argued that leader-member exchange (LMX) is a phenomenon that develops over time, the existing LMX literature is largely cross-sectional in nature. Yet, there is a great need for unraveling how LMX develops over time. To address this issue in the LMX literature, we examine the relationships of LMX with 2 variables known for changing over time: job performance and justice perceptions. On the basis of current empirical findings, a simulation deductively shows that LMX develops over time, but differently in early stages versus more mature stages. Our findings also indicate that performance and justice trends affect LMX. Implications for LMX theory and for longitudinal research on LMX, performance, and justice are discussed. (PsycINFO Database Record

Using data collected from 620 health care and senior services customer-contact employees and their employer, we investigated the chain of relationships between work–family balance, job anxiety, turnover intentions, and voluntary turnover. Results showed that work–family balance was related to job anxiety, turnover intentions, and actual, subsequent voluntary turnover. The relationship between work–family balance and turnover intentions was fully mediated by job anxiety. The findings indicate that work–family balance affects organizationally relevant employee psychological outcomes (i.e., job anxiety and turnover intentions) and is a predictor of voluntary turnover. The study further highlights three stages at which hospitality and health care managers and supervisors may intervene to reduce the likelihood of voluntary turnover, namely, to help employees maintain their work and family balance, to correct imbalances, and to restructure or otherwise change work duties if an employee intends to leave.

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Understanding measurement model specification is especially important for hospitality research due to its cross-disciplinary nature and the prevalence of measures used in the field which are often central to the formative versus reflective debate (e.g., SERVQUAL, socioeconomic status). The current study contributes to this topic by providing empirically based prescriptive advice to drive better measurement model specification. Specifically, the decision-making procedures developed by this study can complement theoretical reasons for a model choice as well as help determine a correct model choice when theories are equivocal or non-existent. This study combines actual and simulated data to show that model fit statistics alone cannot determine which model specification is correct, but also that a correct measurement model will generate more accurate predictions within a model which in turn will offer more accurate managerial recommendations.