Showing papers in "Journal of Operations Management in 2020"

TL;DR: Wang et al. as mentioned in this paper studied the relationship among GSCM pressures, practices, and performance under the moderating effect of quick response (QR) technology, and established several results.

TL;DR: In this paper, the authors investigate how supplier degree centrality influences the generation of supplier-supplier innovations and the extent to which this relationship is moderated by the structural embeddedness of firms in the supply network.

TL;DR: In this article, the authors investigated the impact of customers' digital banking adoption on hidden defection, in which customers purchase financial products from competing banks instead of their primary banks, and they developed an analytical model to provide insights into the effects of digital banking adopts while taking customers' multi-homing behaviors into consideration.

TL;DR: In this paper, Choi et al. presented a survey of the work of the Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts, USA.

TL;DR: In this paper, the stock market reaction to CSE appointments is not significantly different from zero, but stock market reacts more or less positively under certain firm-and industry-specific conditions.

TL;DR: In this paper, the authors examined the longitudinal impact of service mix on cost efficiency in U.S. acute care general hospitals and found that as the level of a hospital's specialization increases, hospital cost efficiency should improve at a decreasing rate.

TL;DR: In this paper, the authors analyze 140 NPD projects that were executed by a contract R&D organization in the aerospace industry and find that buyer participation lowers the buyer's and the supplier's perceptions of project success for buyer-as-supplier multiplexity.

TL;DR: The forecasting approach developed in this paper incorporates transaction-level data, such as purchase and return timestamps, and predicts future return quantities using a two-step “predict–aggregate” process and demonstrates significant forecasting error reduction over benchmark models constructed from common industry practice and existing literature.

TL;DR: This work finds that relational and cognitive embeddedness factors support team learning, which in turn supports the implementation of complex endovascular treatment techniques by a multidisciplinary aortic treatment group.