Evaluating the impact of socialization tactics, so.. (SocialiseME)
Evaluating the impact of socialization tactics, social networks and demographic similarity on newcomers’ organizational socialization and performance in a longitudinal cross-industry data sample
Start date: Apr 1, 2014,
End date: Mar 31, 2018
Organisational socialisation, or how we “acquire the social knowledge and skills necessary to assume an organisational role”, is now more relevant than ever due to current socio-economic trends that have repercussions on individuals, organisations and the overall society. The 2008 Great Recession put the cost-structures of EU organisations under great stress, and failure in newcomer socialisation hinders organisations and firms due to the inability of incoming talent to perform at high levels, and to the costs associated with turnover and additional recruitment. My first objective is thus to evaluate the effectiveness of socialisation tactics in different industries and job tasks. Second, in the flat, interdependent organisations that characterise the current workplace, networks are critical in determining success. Thus, I will evaluate the development of newcomer social networks and their relationship to their performance. Results will allow workers to self-access their career and socialisation trajectory through a tool based on my scientific findings, in order to achieve higher individual performance, job satisfaction and well-being. Third, employees now transition into organisations that are highly diverse due to the increasing cross-country mobility and immigration in the EU. It then becomes relevant to evaluate the impact of demographic differences between newcomers, supervisors and colleagues on socialisation effectiveness. Socialising diverse newcomers more efficiently will foster organisational performance and prevent social discrimination by ensuring a smooth integration of individuals of different cultural origins into the workplace. To attain my research objectives I will test a new theoretical framework using statistical estimation methods on two separate large longitudinal datasets, based on survey data from the Apprentissage of French Master Grande Ecole students and archival data on the performance of professional basketball players (1985-2012).
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