Resource Orchestration and Firm Profitability: Uncovering Recipes for Success in the US Manufacturing Industry
Purpose – Developing and implementing strategies to maximize profitability is a fundamental challenge facing manufacturers. The complexity of orchestrating resources in practice has been overlooked in the operations field and it is now necessary to go beyond the direct effects of individual resources and uncover different resource configurations that maximize profitability. Design/methodology/approach – Drawing on a sample of US manufacturing firms, multiple regression analysis (MRA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) are performed to examine the effects of resource orchestration on firm profitability over time. By comparing the findings between analyses, the study represents a move away from examining the net effects of resource levers on performance alone. Findings – The findings characterize the resource conditions for manufacturers’ high performance, and also for absence of high performance. Pension and retirement expense is a core resource condition with R&D and SG&A as consistent peripheral conditions for profitability. Moreover, although workforce size was found to have a significant negative effect under MRA, this plays a role in manufacturers’ performance as a peripheral resource condition under fsQCA. Originality/value – Accounting for different resource deployment configurations, this study deepens knowledge of resource orchestration and presents findings that enable manufacturers to maximize profitability. An empirical contribution is offered by the introduction of a new method for examining manufacturing strategy configurations: fsQCA.
Citation : Hughes, P., Hodgkinson, I.R., Elliott, K. and Hughes, M., Resource Orchestration and Firm Profitability: Uncovering Recipes for Success in the US Manufacturing Industry. International Journal of Operations and Production Management,
ISSN : 0144-3577
Research Institute : Centre for Enterprise and Innovation (CEI)
Peer Reviewed : Yes