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Human Resource Management Contributions to Knowledge Sharing for a Sustainability-Oriented Performance: A Mixed Methods Approach.

Authors :
Muñoz-Pascual, Lucía
Galende, Jesús
Curado, Carla
Source :
Sustainability (2071-1050); Jan2020, Vol. 12 Issue 1, p161-161, 1p
Publication Year :
2020

Abstract

This research examines how internal and external Human Resource Management (HRM) contributes to Knowledge Sharing (KS) in order to reach Sustainability-Oriented Performance. This paper uses a mixed methods approach to report on the main antecedents of KS for Sustainability-Oriented Performance. There are many antecedents of KS both inside and outside organizations that are as yet unidentified. This research applies two complex statistical techniques, namely, structural equation modeling (SEM) (Study 1) and fuzzy-set Qualitative Comparative Analysis (fsQCA) (Study 2). First, SEM is used to determine the antecedents of KS for Sustainability-Oriented Performance: Affective Commitment (AC) (an internal dimension of HRM) and a collaboration-oriented Human Resource Management system (CHRMS) (an external dimension of HRM). Second, three multi-group SEMs are used to determine whether a manager's characteristics (age and gender) and firm size moderate the relationship between KS and its antecedents. Finally, an fsQCA is conducted to identify alternative configurations that lead either to KS or to its absence. The sample comprises data from an online survey of 367 certified innovative Portuguese small and medium enterprises (SMEs). The SEM results show that a collaboration-oriented HRM system always has a positive effect on KS for Sustainability-Oriented Performance. In addition, if the manager is a young man working in a small firm, their AC positively affects KS. There are alternative configurations that lead to the presence or absence of KS. There is, therefore, empirical evidence for the moderating effects of the manager's age and gender, and firm size. Our study offers improved new HRM configurations and results when compared to the sole use of traditional quantitative statistical methods. The results are consistent and conclusive. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20711050
Volume :
12
Issue :
1
Database :
Complementary Index
Journal :
Sustainability (2071-1050)
Publication Type :
Academic Journal
Accession number :
141387829
Full Text :
https://doi.org/10.3390/su12010161