Can Global Sourcing Strategy Predict Stock Returns?

Nitish Jain () and Di (Andrew) Wu ()
Additional contact information
Nitish Jain: London Business School, London NW1 4SA, United Kingdom
Di (Andrew) Wu: Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109

Manufacturing & Service Operations Management, 2023, vol. 25, issue 4, 1357-1375

Abstract: Problem definition : Whereas firms are increasingly relying on sourcing globally as a key constituent of their supply chain strategy, there is no empirical evidence on whether investors of these firms adequately reflect firms’ global sourcing strategy (GSS) in their stock-valuation process. In this paper, we empirically test whether stock market participants are efficient in doing so. Methodology/results : Using the empirical asset-pricing framework, we find that information concerning firms’ GSS strongly predicts their future stock returns. We compile a transaction-level imports database for U.S.-listed firms and construct measures for five widely studied GSS aspects in the operations management literature: the extent of global sourcing, supplier relationship strength, supplier concentration, sourcing lead time, and sourcing countries’ logistical efficiency. For each measure, we examine returns of a zero-cost investment strategy of buying from the highest and selling from the lowest quintile of that measure. Collectively, these investment strategies yield an average annual four-factor alpha of 6%–9.6% (6%–13.9%) with value (equal)-weighted portfolios. Their return predictability is incremental over other operations- and cost arbitrage–motivated predictors, such as inventory turnover, cash conversion cycle, and gross profitability; is persistent across different supply chain positions; and is robust to alternate risk models, subsamples, and empirical specifications. Together, our results indicate that the GSS measures embody independent information about firms’ future profitability, and this information is mispriced by market participants, leading to predictable returns. In accordance with this mechanism, we find that the GSS measures strongly predict both firms’ future earnings and the surprise in market reactions around the earnings announcement days. Managerial implications : The robust return predictability of our GSS measures suggests that investors are not fully incorporating GSS-related information in their stock valuation frameworks. Therefore, our results call for greater investor education on global sourcing and better dissemination of global-sourcing information so as to mitigate valuation inefficiency.

Keywords: global sourcing strategies; asset pricing; empirical operations management (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/msom.2023.1189 (application/pdf)

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:inm:ormsom:v:25:y:2023:i:4:p:1357-1375

Access Statistics for this article

More articles in Manufacturing & Service Operations Management from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().