Disseminating Strategic Orientation of Machine Learning Along the Supply Chain

Abstract

This study explores why and how the focal firm disseminates its strategic orientation of machine learning (SOML) within its supply chain to affect the SOMLs of its suppliers and buyers, and how the operational efficiency (OE) of the focal firm and its supply chain partners moderates these relationships. Drawing upon inter-organizational learning theory and using data from 2351 publicly listed firms in China over the period 2013–2020, we construct a panel data set to test the effects of the focal firm’s SOML on the SOMLs of its suppliers and buyers and the contingent effects of the focal firm’s OE and partners’ OE. Our results show that the focal firm’s SOML can strengthen suppliers’ SOML, but has an inverted U-shaped effect on buyers’ SOML. Further, we find that the focal firm’s OE can improve the effects of its own SOML on its suppliers’ SOML, while its partners’ OE hinders SOML dissemination from the focal firm to its suppliers and buyers. These results provide important theoretical contributions and managerial implications in regard to firms’ machine learning strategy, supply chain management, and operations management.