Subsidiary autonomy and subsidiary performance: A meta-analysis
Jose-Mauricio Galli Geleilate,
Daniel S. Andrews and
Stav Fainshmidt
Journal of World Business, 2020, vol. 55, issue 4
Abstract:
Although research shows that subsidiary decision-making autonomy may improve subsidiary performance in some contexts, the conditions under which autonomy is beneficial to subsidiary performance remain unclear. Accordingly, we review the literature and develop an initial framework of possible contingencies to the autonomy-performance relationship. We then meta-analyze 94 studies encompassing 23,337 foreign subsidiaries and identify moderators of the performance outcomes of autonomy related to institutional and industry contexts and to the headquarters-subsidiary relationship. We discuss the implications of these moderation patterns for subsidiary management research and propose a theory-based roadmap for future research on the outcomes of subsidiary autonomy.
Keywords: Subsidiary autonomy; Subsidiary performance; Meta-analysis; Subsidiary management; Contingency theory (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1090951618308642
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:worbus:v:55:y:2020:i:4:s1090951618308642
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/620401/bibliographic
http://www.elsevier. ... 620401/bibliographic
DOI: 10.1016/j.jwb.2019.101049
Access Statistics for this article
Journal of World Business is currently edited by David Collings and Jonathan Doh
More articles in Journal of World Business from Elsevier
Bibliographic data for series maintained by Catherine Liu ().