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  Improving workplace climate in large corporations: A clustered randomized intervention

Alan, S., Corekcioglu, G., & Sutter, M. (2021). Improving workplace climate in large corporations: A clustered randomized intervention.

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 Urheber:
Alan, Sule, Autor
Corekcioglu, Gozde, Autor
Sutter, Matthias1, Autor           
Affiliations:
1Max Planck Institute for Research on Collective Goods, Max Planck Society, ou_2173688              

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Schlagwörter: Workplace climate, relational dynamics, leadership quality, RCT
 JEL: C93 - Field Experiments
 JEL: M14 - Corporate Culture; Diversity; Social Responsibility
 JEL: M53 - Training
 Zusammenfassung: We evaluate the impact of a training program aimed at improving the relational atmosphere in the workplace. The program encourages prosocial behavior and the use of professional language, focusing primarily on leaders' behavior and leader-subordinate interactions. We implement this program using a clustered randomized design involving over 3000 headquarters employees of 20 large corporations in Turkey. We evaluate the program with respect to employee separation, pro and antisocial behavior, the prevalence of support networks, and perceived workplace climate. We find that treated firms have a lower likelihood of employee separation, fewer employees lacking professional and personal help, and denser, less segregated support networks. We also find that employees in treated corporations are less inclined to engage in toxic competition, exhibit higher reciprocity toward each other, and report higher workplace satisfaction and a more collegial environment. The program's success in improving leader-subordinate relationships emerges
as a likely mechanism to explain these results. Treated subordinates report higher professionalism and empathy in their leaders and are more likely to consider their leaders as professional support providers.

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 Datum: 2022-07-012021-09-14
 Publikationsstatus: Online veröffentlicht
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 Ort, Verlag, Ausgabe: Bonn : Max Planck Institute for Research on Collective Goods, Discussion Paper No. 2021/17
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