M59 - Personnel Economics: OtherReturn

With rising levels of work-related stress and its dramatic consequences, organizations are increasingly investing in finding solutions to promote employee well-being. As an effective approach to stress management, humour has begun to attract the attention of practitioners and researchers. This study proposes to look at humour as a further managerial tool to improve workplace relationships and associated positive outcomes. It examines how the humour style of supervisors and subordinates affects the leader-follower relationship. Specifically, the effects of humour style (dis)similarity on leader-employee exchanges are examined. Data were collected in 2022 from 128 supervisor-subordinate dyads (N = 53 supervisors; N = 128 subordinates) in an international organization headquartered in Switzerland. Our polynomial regression analysis reveals that leader-member exchange (LMX) is positively influenced by congruence in affiliative, self-enhancing and self-defeating humour. These findings contribute to the discussion on the impact of humour style similarity on workplace relationships and the importance of considering dyadic interactions.
Implications for Central European audience: The results suggest that leaders should take humour seriously and consider including it in their managerial toolkit to improve workplace relationships. It is important to differentiate between humour styles and their effects and apply them with respect to the situation and desired outcomes. Joking together improves LMX, which is why leaders should consider supporting their employees in humorous behaviour to strengthen bonds. Since leaders’ behaviour is perceived as a reference and considering the numerous positive effects of humour in organizations, leaders may practice humour at work more often to lead by example and integrate it into the group culture.

Family businesses are the lifeblood of the economic growth of the nations. However, a large gap exists about the application of machine-learning algorithms such as Random Forests (RF) to the quantification of patterns, drivers, and interactions in the succession process of family businesses. The primary aim and novelty of this study lie in the quantification of variable importance based on machine-learning algorithms, and the differences among the characteristics of family businesses, family employees, and family business owners (FBOs) for multivariate responses. For this reason, a field study was carried out in family businesses in Sivas and Ardahan provinces. The questionnaire form created by the researchers was used in this study. In this research, RF classification model was applied. RF classification models of 17 response variables were constructed as a function of 32 predictors.
Implications for Central European audience: Impacts of characteristics of FBOs, family businesses, and family employees on FBOs’ willingness to transfer to successors and preferences about the successor’s qualities were modelled. High-dimensional data were collected from 53 family business owners (FBOs) in two cities for a total of 49 variables. As a result, the domain of the FBOs’ characteristics was found to have a more profound impact on both FBO’s willingness to transfer to a successor and what successor’s qualities were most valued than did the domains of the family business and employee characteristics.