Knowledge that Transforms

Social media marketing has been relentlessly developed and integrated into firm operations. On social media platforms, firms rely on a combination of verbal and visual elements to communicate with consumers and attract their attention. The present research investigates how the semantic relationship between text and image information affects consumer engagement (forwards and comments). Leveraging a large-scale dataset of firm-generated messages, we use deep learning, large language models, and topic models to quantify each text–image message with a theorized two-dimensional text–image incongruency (relevancy and expectancy). Relevancy is how closely the information aligns with the main message. Expectancy is how predictable or surprising the information is based on what people expect, which concerns long-term affective and cognitive memories about one's past and present experiences. We find that the interaction of relevancy and expectancy, two distinct dimensions at the cognitive level, is a crucial antecedent of consumer engagement on social media. High-relevancy–high-expectancy (HRHE) content and low-relevancy–low-expectancy (LRLE) content are the most effective strategies, whereas high-relevancy–low-expectancy (HRLE) and low-relevancy–high-expectancy (LRHE) contents do not work so well. Furthermore, this paper also uncovers the distinct nature of consumer engagement forms in social media settings, including forwards and comments. In particular, HRHE offers the exclusive benefit of boosting forwards while the two strategies are equally effective in eliciting comments. This research derives several important operational implications of consumer engagement and social media marketing by addressing the importance of multi-dimensional text–image incongruency and contributes to the literature on operations management and marketing interface.

Consumers taking prescription drugs have limited ability to ascertain drug quality before taking the drug. After drug use, however, consumers frequently report their personal experiences with prescription drugs on one of the world's largest medical websites: WebMD. Drug reviews on WebMD are a potentially rich source of free-form text that can be utilized to inform firms, consumers, researchers, and the Food and Drug Administration (FDA) about the quality and safety of prescription drugs. Additionally, because men and women communicate in starkly different ways, the gender of the reviewer may play a key role in drug reviews signaling drug quality problems. We examine if drug review textual sentiment is associated with the hazard of a serious drug recall and whether this relationship varies depending on the gender of the reviewer. We analyze textual sentiment on drug reviews from WebMD along with 13 years of drug recall data using several hazard models. We find that the more negative the drug review sentiment, the greater the hazard of a serious recall on that drug. This relationship is completely explained by drug reviews written by females; reviews written by males have no explanatory power. Our findings are confirmed by numerous robustness checks. In post-hoc analysis, we explore possible mechanisms by comparing female and male adverse events on the recalled drugs in our study. Our contributions to gender diversity and drug quality literature leads to implications for the FDA, WebMD, and firms that manufacture prescription drugs.

We apply heterogeneous-agent proximal policy optimization (HAPPO), a multi-agent deep reinforcement learning (MADRL) algorithm, to the decentralized multi-echelon inventory management problems in both a serial supply chain and a supply chain network. We also examine whether the upfront-only information-sharing mechanism used in MADRL helps alleviate the bullwhip effect. Our results show that policies constructed by HAPPO achieve lower overall costs than policies constructed by single-agent deep reinforcement learning and other heuristic policies. Also, the application of HAPPO results in a less significant bullwhip effect than policies constructed by single-agent deep reinforcement learning where information is not shared among actors. Somewhat surprisingly, compared to using the overall costs of the system as a minimization target for each actor, HAPPO achieves lower overall costs when the minimization target for each actor is a combination of its own costs and the overall costs of the system. Our results provide a new perspective on the benefit of information sharing inside the supply chain that helps alleviate the bullwhip effect and improve the overall performance of the system. Upfront information sharing and action coordination in model training among actors is essential, with the former even more essential, for improving a supply chain's overall performance when applying MADRL. Neither actors being fully self-interested nor actors being fully system-focused leads to the best practical performance of policies learned and constructed by MADRL. Our results also verify MADRL's potential in solving various multi-echelon inventory management problems with complex supply chain structures and in non-stationary market environments.

Diversity, equity, and inclusion (DEI) has been gaining attention in operations and supply chain management (OSCM) research but is often narrowly framed and dominated by instrumental logic. We offer three lenses that potentially broaden the scope of this scholarship: justice, paradox, and dialectical. The justice logic frames DEI as primarily a moral concern of inequality in firms and supply chains. It goes against an instrumental, performance-driven approach to establishing DEI in OSCM. To understand the persistence of tensions in DEI implementation, we present a paradox lens and link it to OSCM through four major types of organizational paradoxes: performing, organizing, learning, and belonging. We employ a dialectical perspective to resolve these tensions and combine instrumental and justice logics to explore how the latter can help firms realize DEI's (often unfulfilled) performance potential. OSCM scholars are well placed to use justice, paradox, and dialectical lenses to assess pathways for realizing DEI's transformative potential through modeling, decision support, and empirical research. Such research can help managers pursue objectives that conflict with or go beyond instrumental DEI, thus contributing to substantive DEI implementation.

This article describes the rapid upward march to research excellence of the Operations Management Department in the Naveen Jindal School of Management from 1996 to 2023. It reflects along the way on the internal strategy, as well as the institutional and external contributing factors that led to its phenomenal growth.

Prior research has documented that a firm's disclosure of corporate social responsibility (CSR) makes it a more attractive business partner, boosting its sales. The authors extend this finding to business-to-business (B2B) firms. Using a regulatory change in China as a quasi-natural experiment, they demonstrate that a firm's disclosure of its CSR lowers by 2.1% the firm's dependence (for sales revenue) on its major customers but raises by 3.7% its dependence (for purchases) on its major suppliers. They further show that the firm's production efficiency (marketing efficiency) is a mechanism underlying the effect of CSR disclosure on dependence on major customers (suppliers). Next, they demonstrate that the CSR report's emphasis on the firm's supply chain partners weakens (strengthens) the effect on dependence on major customers (suppliers). The findings contribute to the multidisciplinary evidence on the B2B value of CSR disclosure, and the operations and marketing literature streams on determinants of supply-chain dependence.

Forced labour poses a significant challenge within global supply chains, yet traditional compliance-based governance based on auditing has proven to be ineffective in addressing this issue. Non-government organizations and worker rights organizations can serve as crucial allies in supporting and safeguarding workers by assuming the role of a 'social intermediary' (SI) between supply chain firms and workers. However, these external organizations often hold limited power within these supply chains. In our paper, we examine the sources of power that SIs can cultivate and utilize to lead successful interventions against forced labour in supply chains. Through a comparative case study involving three SIs and their collaborative efforts with a global seafood brand, we explore various forms of non-mediated power and their underlying origins. By establishing these connections, we shed light on the effectiveness (or lack thereof) of interventions against forced labour. Our research makes three contributions. First, we contribute to ongoing research on forced labour in supply chains by emphasizing the constructive role that SIs can play to protect vulnerable workers. Second, we address a critical gap in the existing literature concerning power of SIs in supply chain relations. More specifically, we specify sources and types of non-mediated power that SI can leverage to design effective interventions against forced labour. Third, by comparing unique data on two worker groups vulnerable to forced labour – vessel workers and workers in seafood processing – we provide much-needed insights into how working conditions in non-factory settings can still be regulated.

The supply chain risk management literature differentiates between disruption risk that arises from supply disruptions to normal activities and recurrent risk that arises from problems in coordinating supply and demand in the absence of disruptions. Over the past decades, significant research has been carried out to better understand supply chain resilience, that is, the ability of a supply chain to mitigate disruptions. Supply chain efficiency, that is, the ability to mitigate recurrent risks in the absence of disruptions has been studied even longer. But only recently have the topics of efficiency and resilience been coupled in the supply chain literature. In this literature review, we focus on the intersection of supply chain resilience and supply chain efficiency. We provide a thematic overview of literature streams according to the structure of the underlying supply chains. We identify various gaps in the current literature including areas in multi-echelon and multi-product supply chain research. Furthermore, we consider dual-purpose and dedicated levers for building resilience. Dual-purpose levers are resources that are able to promote efficiency in a supply chain while enhancing resilience in expectation. By contrast, dedicated resilience levers are resources that are able to guarantee the resilience of a supply chain in the face of particular disruptions without benefiting the supply chain in the absence of disruptions. We call for more research to better understand the value of dual-purpose and dedicated resilience levers to overall supply chain performance.

We describe the state of supplier diversity efforts by large corporations from an international perspective. We examine data for the companies in the 2020 and 2022 Fortune Global 500 and find that corporate definitions of diversity are dynamic and vary across regions. Furthermore, while supplier diversity efforts are not yet widespread, these initiatives are increasingly common, especially in the form of references to diversity in companies’ supplier codes of conduct. Companies in North America and in certain economic sectors, such as the financial and healthcare sectors, are more likely to have such efforts in place. Based on our data, companies that report on their internal diversity and companies that have other forms of supplier sustainability initiatives are also more likely to have supplier diversity initiatives. We argue further that supplier diversity efforts will follow a trajectory similar to other supplier sustainability efforts. Finally, we suggest possible avenues for future research on supplier diversity.

Restaurants have traditionally operated offline only, but the growth of food delivery platforms has prompted a shift toward online sales. In practice, consumers who share digital coupons offered by the platforms (e.g. Uber Eats and Meituan) in social networks (e.g. Facebook, Twitter, and WeChat) will be rewarded for the social traffic, which effectively attracts many restaurants to open online store. However, this also leads to intensified competition with the restaurant's physical (offline) store. In this article, we formulate the restaurant's tradeoffs among platform traffic benefits, consumers’ heterogeneous utility, and the platform's commission in the online selling decision. Interestingly, we find that the increased platform traffic may be harmful to the restaurant, and even the entire channel system. The platform offering high subsidies may trap restaurants in a pricing dilemma. We also find that restaurants’ online selling will induce a negative externality due to online/offline order congestion, but it will not qualitatively change the main findings.