The impacts of industry environment on software insourcing, outsourcing, and buying
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 11 May 2022
Issue publication date: 21 June 2022
Abstract
Purpose
Nowadays, an increasing number of firms choose to develop proprietary software, instead of buying packaged software. What factors will affect different types of software investments? According to the environment-strategy alignment research, environment should be an influential factor. However, environment's role has received scarce attention in the literature. The authors' study addresses this research gap by investigating how industry environment affects different types of software investments. The study identifies three types of software investments (software insourcing, outsourcing, and buying) and examines how the characteristics of the industry environment (including industry munificence, dynamism, and concentration) influence each software investment.
Design/methodology/approach
The generalized least squares (GLS) model and the ordinary least squares with panel-corrected standard errors (OLS-PCSE) model are applied to test the hypotheses, based on industry-level panel data from the US Bureau of Economic Analysis (BEA).
Findings
The analysis shows that industry munificence, dynamism, and concentration have different impacts on software insourcing, outsourcing, and buying, respectively.
Originality/value
This study classifies software investment into three types – software insourcing, outsourcing, and buying and investigates how the industry environment affects them. The findings suggest that research should distinguish among software insourcing, outsourcing, and buying due to their different characteristics.
Keywords
Acknowledgements
Funding: This research was supported by the National Natural Science Foundation of China (No. 71572180).
Citation
Liu, X., Qu, W.G. and Pinsonneault, A. (2022), "The impacts of industry environment on software insourcing, outsourcing, and buying", Industrial Management & Data Systems, Vol. 122 No. 7, pp. 1541-1559. https://doi.org/10.1108/IMDS-08-2021-0511
Publisher
:Emerald Publishing Limited
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