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Special Issue on Data Science for Better Productivity

Corporate diversification, firm productivity and resource allocation decisions: The data envelopment analysis approach

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Pages 1002-1014 | Received 21 May 2018, Accepted 17 Dec 2018, Published online: 04 Apr 2019
 

Abstract

Corporate diversification has been an important research topic in the field of business administration. Although it is regarded as an essential strategy for firms, its relationship with firm performance seems inconclusive in the literature. To fill this gap, our study uses data envelopment analysis (DEA) to develop models that help diversified firms more accurately calculate productivity at both the firm and its business segment levels, and then reallocate resources among business segments in order to achieve better firm overall performance. We empirically test the models using a sample of U.S. public firms for a period of 2012–2016. The results show that in comparison with two conventional DEA models, our model provides more useful productivity expression for diversified firms, and that the model-suggested resource reallocation is linked to better firm performance.

Notes

1 The same procedure and weight selection could be applied to outputs as well.

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