Journal of Operations Management最新文献

Demand planning is informed by demand forecasts, service level requirements, replenishment constraints, and revenue projections. “Demand forecasts” differ from “demand plans” in that forecasts only represent the distribution (or the most likely value) of product demand. Motivated by common forecasting practices in industry, our research examines whether forecasters recognize this difference between demand forecasts and demand plans. Based on a lab experiment informed by data from two large FMCG companies, we found that forecasters factor service levels into their demand forecasts, even when they are clearly instructed to predict the most likely demand and incentivized to minimize the forecast error. We establish that this result holds for students and practitioners alike, and show that this behavior is driven by the service level information, and not some other anchor. We use data from a recent industry survey to support the external validity of our key findings.

A chasm is growing between the advanced technologies available for improving manufacturing operations and those effectively used in practice. The vision of Industry 4.0 is to mobilize industry to seek out these possibilities for improvement and to close the gap between opportunity and reality. However, when compared with more established improvement opportunities such as lean manufacturing, the digitalization of manufacturing lacks in both paradigmatic examples and an understanding of how to achieve the benefits. This lack is a complication of concern: Without an appropriate operations strategy to capture the value of digitalization, manufacturing companies will be unable to focus on technological investments and operational changes. To address this concern, operations management academics must develop new theory through active engagement in the practice of digitalization in manufacturing. This research presents a paradigmatic example, based on engaged scholarship, focused on effectively combining novel object-interactive and conventional manufacturing syntax for benefiting from digitalization in internal operations and the wider supply chain. The contribution to literature is a novel operations strategy—hybrid digital manufacturing—for capturing the value of Industry 4.0 technologies.

Business models designed to serve those at the “base of the pyramid” are an effective means to create employment and improve quality of life. However, the effect that poverty has on the performance of such businesses is not well-understood. We address this gap through the context of “mobile money,” an electronic currency ecosystem designed as a secure, reliable way for those at the base of the pyramid to store and transfer money. Using data from Kenya and Uganda, and instrumenting for potentially endogenous regressors, we examine the effect poverty has on operational decisions (inventory and price transparency) and market dimensions (network density and demand). Our results suggest that mobile money, as a base of the pyramid business model, is well-positioned to serve those in poverty up to a point, with demand increasing in poverty when the concentration of poverty is sufficiently low. However, our results indicate that, where poverty is more pervasive, inventory costs increase in poverty while per agent demand and agent network density both decrease. In short, the business case for mobile money degenerates in regions where it, arguably, is needed the most. We conclude with thoughts on how to buttress mobile money's business case in these high poverty settings.

The outbreak of the COVID-19 pandemic has disrupted supply chains and increased the uncertainties faced by firms. While firms are struggling to survive and recover from the pandemic, Chinese e-commerce platforms have demonstrated resilient supply chains. We develop a framework that investigates the impacts of integration between an e-commerce platform and suppliers on supply chain resilience and the moderating effect of the suppliers' product flexibility. An analysis of data from a Chinese e-commerce platform using operational indicators finds that integration between the e-commerce platform and suppliers in terms of information sharing, joint planning and logistics cooperation has positive impacts on supply chain resilience, while procurement automation has the opposite effect. Furthermore, product flexibility positively moderates the impacts of information sharing, joint planning and logistics cooperation. The results enhance current understandings of the factors that contribute to the development of supply chain resilience and reveal that the relationship between integration and resilience should be examined within a contingency framework. The findings also provide guidelines for managers taking measures to mitigate the negative influences of supply chain disruptions.

Multinational corporations have benefited tremendously from free trade in the past few decades. However, the dynamism of international relations, paired with the global recession, has rekindled the debate over frictionless trade. In this study, we examine how trade friction, created by tariff trade barriers, affects the operational performance of domestic firms which source from the affected countries. We also investigate how various supply chain characteristics and strategies can moderate the impact of such trade friction. Motivated by the 2018 U.S.–China trade war, we conducted a difference-in-difference analysis to examine the impact of trade tariffs on performance indicators of U.S. firms with direct supplier connections in China. Specifically, we found that U.S. firms with direct supply partners (i.e., first-tier suppliers) in China had a worse performance than the U.S. firms without direct supply partners in China in terms of inventory (i.e., days of supply) and profitability (return-on-assets). We further found that the negative impacts were more severe for firms with a higher degree of outsourcing, and horizontal and spatial supply base complexity. We discuss the implications for international operations management, supply chain networks, supply risk management, and provide suggestions to supply chain practitioners and trade policymakers.

Surge pricing has been used to coordinate supply and demand in the ride-sharing industry, but its causal effects on driver behavior remain unclear. This motivates us to examine how surge pricing causally affects driver earnings and labor supply by leveraging a unique quasi-experiment, in which a leading ride-sharing company in China introduced surge pricing in two cities at different times. Using a difference-in-differences design with the causal forest method, we find that surge pricing led to increases in drivers' weekly revenue. Decomposing the weekly revenue into “intensive margin” and “extensive margin” factors, we discover two countervailing effects at play: a cherry-picking effect and a competition effect, and the daily revenue decreased because the latter dominated. Consequently, the increased weekly revenue can be explained by the extensive margin: drivers worked on more days to compensate for the decreased daily revenue, a result consistent with the income targeting behavior. Finally, we examine heterogeneous treatment effects across drivers, and find that surge pricing enticed more part-time drivers to flood the market and crowd out full-time drivers, and that the increase in the drivers' weekly revenue was primarily driven by part-time drivers. Therefore, the benefit of surge pricing was unevenly distributed across drivers.

In this article, we characterize the relationship between spatial pricing and capacity based on distributed service design (DSD) decisions in a two-sided sharing economy platform. We leverage theoretical tenets on two-sided markets and on spatial pricing and capacity management in the sharing economy to inform a set of empirical and simulation models. Empirically, we use data on 156,520 observations of dynamic pricing and capacity distribution within Uber's San Francisco region. Estimation of a spatial econometric model reveals that the number of active drivers in neighboring zones negatively impacts the price in focal zones. Simultaneously, we find that spatial proximity is a significant factor in determining the distribution of prices when service demand levels are sufficiently high. We leverage this simultaneity finding to advance the literature on the sharing economy by incorporating operational considerations such as distributed capacity into service design. We link these econometric results with profit and welfare using a simulation that tests a variety of DSD pricing strategies under varying elasticity and revenue-sharing conditions. Our findings offer guidance to firms managing two-sided sharing economy platforms on tracking demand- and supply side price elasticity levels as well as revenue sharing spread when seeking to maximize profit, welfare, or both.

This study examines the effect of direct equity ownership (DO) a buyer holds in its supplier on financial performance and operations of the supplier and buyer. Based on a sample of US buyer–supplier pairs from 1982 to 2017, we find that DO benefits buyer performance, but not supplier performance. The results support the view that DO mainly provides greater control for the buyer. Furthermore, we find that the performance effects of DO are moderated by firm characteristics that engender dependence. The beneficial influence of DO on a buyer's performance is more pronounced when the buyer is more innovative or operates in a more competitive environment. Our examination of the effects of DO on the operations of suppliers and buyers finds that suppliers in buyer–supplier relationships (BSRs) with higher DO invest more in relationship-specific assets (R&D), provide more trade credits, and have lower gross profit margins. Buyers in BSRs with higher DO receive more trade credits and have lower cost of goods sold when the purchases of the buyer from the supplier make up a high proportion of the buyer's cost of goods sold. Overall, these results suggest that DO primarily benefits the buyer at the expense of the supplier, a finding that is consistent with the effects of bargaining and control power of the buyer. We discuss the implications of these findings for practitioners and for extensions to both relational and resource dependence theories.