Abstract
Purpose – There is a lack of studies investigating the role of the structural configuration of social capital – more specifically, structural holes – for employees' individual learning. The objective of this paper is to address this gap in the literature, ultimately enhancing understanding of the link between the structural configuration of social capital and individual learning.
Design/methodology/approach – An online questionnaire survey was administered to employees affiliated to 22 pharmacies in Sweden to gather attributional and relational data on the individual level. Social network analysis techniques were used to describe salient structural characteristics of individuals' social capital. The impact of social capital on individual learning was explored through ordinal logistic regression models based on maximum likelihood estimations.
Findings – The presence of structural holes initially increases the degree of individual learning, then reaches a maximum and begins to gradually decrease.
Practical implications – The results of the study provide valuable input for the development and management of networks within firms, in order to improve learning and innovation. In addition, given the close proximity between learning, as conceptualized in this study, and other job attitudes, human resource management practices in general could benefit greatly from the results.
Originality/value – In this paper, the authors focus on the structural configuration of social capital, more specifically structural holes, and its inter-relationship with learning. Although prior literature has analyzed various beneficial effects of social capital, this study is the first of its kind to investigate the role of the structural configuration of the social capital for employees' individual learning.
Lingua originale | English |
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pagine (da-a) | 576-591 |
Numero di pagine | 16 |
Rivista | Journal of Knowledge Management |
Volume | 16 |
DOI | |
Stato di pubblicazione | Pubblicato - 2012 |
Pubblicato esternamente | Sì |
Keywords
- learning
- networks