Problem definition: Artificial intelligence (AI) is rapidly transforming the research and practice of supply chain management. Yet its impact depends on how effectively it is integrated with the theories, methods, and fundamental principles of operations management (OM), which must also evolve to account for the informational, incentive, and institutional changes brought by AI. The OM community has an important role and responsibility to lead in shaping not only how AI transforms supply chains but also how the supply chains that enable AI are designed to be sustainable, resilient, and equitable. Methodology/results: This vision statement organizes the discussion around five layers of the interaction between AI and supply chain management: intelligence, execution, strategy, human, and infrastructure. It synthesizes recent research and industry practice to show how AI enhances forecasting, planning, decision making, risk management, and human-machine collaboration and also examines the supply chains that support AI. Finally, it highlights persistent challenges in data quality, model integration, governance, and workforce adaptation. Managerial implications: Realizing AI's promise in supply chain management requires reliable data and infrastructure, integration of learning and optimization, transparent and explainable decision systems, and a long-term commitment to human-AI collaboration. Together, these elements form the foundation for resilient, adaptive, and trustworthy supply chains in the AI era.

The recent elimination of the United States de minimis exemption for import tariffs has been reported to have a significant impact on ultra-fresh fashion companies such as Shein and Temu. This article develops a game-theoretic model to investigate the impact of such tariffs. Specifically, we consider a model for a global ultra-fresh fashion supply chain with economies of scale under tariff hikes. Our model analysis reveals the following main insights. First, the ultra-fresh fashion firm would price in such a way to pass the entire import tariff onto customers in the tariff-imposing market, and tariff hikes in one market would reduce the firm’s product launch frequency and total product variety in all markets due to the supply chain scale economy effect. As a result, tariff hikes reduce the firm’s profit, with the loss amplified under greater supply chain scale economies. However, a higher demand from outside the tariff-imposing market helps soften the blow from tariff hikes, signifying the importance of the demand-side market diversification (a strategy termed as the “US Plus One” in this article). Moreover, we find that the firm would relocate its production for the tariff-imposing market if and only if the tariff rate exceeds a certain threshold, with supply chain scale economies serving as an “efficiency barrier” to counter-balance the supply-side production diversification. We also find numerically that the demand-side market diversification strategy can serve as a potential substitute for the supply-side production diversification strategy. Implications of tariff hikes for consumer surplus and the environment are further examined along with production relocation. Finally, we offer a general discussion regarding market competition and other relevant modeling considerations.

Over the past two decades, the foundational theory of inventory management has evolved to capture several complexities inherent in global supply chain operations. The impact of technology, firm-level collaborative practices, and more recently the explosion of data has added several dimensions to explore inventory management problems. Alongside, advances in management science has provided scholars with enhanced tool kits to study and analyze complexities inherent in these problems. In this chapter, we will discuss problems that arise at the confluence of (demand- or supply-side) information and incentives of firms. Our emphasis will be on highlighting models that capture the dynamic nature of information and incentives, and in particular, how they interact in the context of inventory management.

Using agile supply chains, fast fashion companies have been viewed as best practice examples in industries. Prior research focuses on how agility can equip such companies with strong sense-and-respond capabilities to identify and fulfill unpredictable customer demands. There is another powerful dimension of agility-the ability to create new products frequently-that has enabled recent market success of companies such as Shein and Temu, labeled by some industry press as ultra-fast fashion. These companies, relying on end-to-end digital technologies, have pushed this dimension of agility to unprecedentedly high levels, launching new products with great frequency and variety. The frequent product launches create freshness, stimulating latent demands of consumers and making these companies "ultra-fresh" fashion, a term we adopt in this paper. We seek to model this dimension of agility as an operational strategy for demand creation. Our model enables us to explore the effects through the lens of profit to the firm, consumer surplus, and environmental impact. Our analysis reveals that frequent product launches, high variety, and low prices-the three salient features of ultra-fresh fashion-are driven by both the product design agility and the customers' interest for product freshness. The ultrafresh strategy allows steady profit increase for the firm and benefits consumers in aggregate but may cause negative environmental impact if left unchecked.

JD.com utilizes advanced analytical techniques to strengthen its supply chain capability. The end-to-end inventory management model, intelligent risk management system and consumer-to-manufacturer system are implemented to attain agility, resilience and shared value. These efforts have led to significant revenue increases, cost savings, and value creation across the retail ecosystem, benefiting consumers and business partners.

In recent years, there has been an increasing trend in supply chains to employ a “control tower” approach to improve supply chain performance. One such strategy is customer-managed inventory (CMI) in which the customer (the downstream party) controls the inventory of the supplier (the upstream party). However, the optimal design of the inventory control policy and the required incentive structure for CMI has not been fully explored in the related literature. In this paper, we develop a two-echelon model consisting of a supplier and a customer that captures the interaction between both decision makers. Analysis of this model indicates that achieving the potential benefits of CMI requires suitable incentive mechanisms to be put in place. The two-echelon inventory system model, however, does not give closed-form solutions, which are required to generate an optimal solution to the inventory control and incentive problem. To address this challenge, we propose an approximate model, which decouples the two-echelon model into two newsvendor-type models with each party operating a single-echelon system. This approximate model requires the introduction of additional cost parameters so that the decoupled model captures the cost implications of supplier shortages in the original two-echelon model. By developing appropriate values for these cost parameters, the approximate model yields near optimal results. Analysis of the solution reveals important operational factors that determine which environments are conducive for CMI and conditions for Pareto improvement of all stakeholders. This paper was accepted by Jayashankar Swaminathan, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03658 .

Since the first case was identified, COVID-19 has spread to more than 200 countries. As of October 25, 2022, it had resulted in over 6 million deaths and 600 million confirmed cases. The rapid widespread of COVID-19 led to large-scale disruptions with major supply and demand shocks in supply chains, causing significant negative impacts on the global economy. The World Bank reported that the world GDP growth rate for 2020 was −3.27%, indicating the worst recession since 1961. First, the initial epidemic-control efforts blocked the flows of raw materials across the world, and limited labor movements by imposing temporary travel restrictions. As a result, many firms struggled with supply disruptions and labor shortages, setting off a chain reaction of disruption in global supply chains. Fortune (2020) reported that as of February 21, 2020, 94% of the Fortune 1000 companies had experienced supply-chain disruptions due to COVID-19.1 According to the Institute for Supply Management, almost 75% of companies reported supply-chain disruptions in some capacity due to coronavirus-related transportation restrictions.2 A survey conducted by the National Association of Manufacturers reported that 78.3% of manufacturers believed that COVID-19 had a significant negative influence on their financial performance, and 35.5% of them had experienced some type of supply chain disruptions.3 Second, the demand for essential personal-protective equipment increased dramatically because the virus was easily transmitted from person to person through air-borne droplets; accompanied by a drop in the need for other manufactured products (Nicola et al., 2020). For example, COVID-19 had caused a surge in the demand of face masks that were necessary to prevent infection among frontline workers (who were directly exposed to the virus when treating infected patients or conducting nucleic acid tests) and individuals in public places. China was the main producer of masks at the start of the crisis, accounting for approximately half of world production. In January 2020, China could produce 20 million masks per day, which was insufficient to equip even just healthcare workers in China. As a result of extensive efforts by the government and companies, Chinese production increased six-fold and reached 116 million masks per day by the end of February, 2020. But even this was insufficient to meet its own demand, and China imported a large quantity of masks. Similarly, Germany also experienced very limited availability of face masks in the spring of 2020. To increase the supply of face masks, the German government contracted with hundreds of companies and introduced a series of incentives to encourage local, non-medical manufacturers to temporarily transform to produce masks. More generally, demand patterns for supplies of all types became less predictable from the beginning of pandemic. Significant changes on the demand side included quick shifts of buying patterns (from physical stores to online stores) and rapid shifts of product mix (e.g., decline in office equipment to be used on site, but increases in appliances for home-office use). Compared with previous pandemics, COVID-19 has affected supply chains more durably and globally. As this special issue approaches publication, the COVID-19 pandemic has lasted for over 3 years. The extended duration of this external shock has been sufficient to permanently change the behavior of supply-chain partners (Poelman et al., 2021). These changes have encouraged firms to demonstrate an innovative bent, leading to structural process changes in a variety of industries. For example, demand for in-person restaurant dining decreased, whereas demand for take-away foods greatly increased, though by 2022, this pattern had begun to reverse. Under this change, firms needed to explore new ways of organizing their supply chains with respect to factors like product diversity and cooperation with more partners in the supply chains. This made it possible to define products and services to benefit quickly from pandemic-related opportunities (van der Vegt et al., 2015). The COVID-19 pandemic has also affected global supply chains as economic integration interacted with travel restrictions and worldwide lockdowns (Nikolopoulos et al., 2021) to create unprecedented challenges for enterprises to respond to changes in demand and supply, employee shortages, and lack of access to financial capital. These long lasting, structural, and global supply-chain impacts have led enterprises to increase responsiveness and resilience (2Rs) via management mechanisms and technological innovations. Based on the media reports and literature review, such innovative measures include cross-enterprise cooperation (e.g., Unilever and Terra Drone), government-enterprise cooperation (e.g., Hubei Provincial Government and JD Logistics), adjustments to manufacturing activities (e.g., BYD, Foxconn, Pernod Ricard, and Bauer shifted their production to face masks/shields), as well as the adoption of digital technologies (e.g., JD Logistics, New HAVI). This 2R emphasis represents a major departure from the usual emphasis on cost reduction (Caunhye et al., 2016). Observing that some companies have performed well in responding quickly to changes in demand and supply, and flexibly to disruptions, we seek to learn from the innovative practices and experiences of that have yielded success in dealing with this large-scale disruption. What were the key lessons learned in terms of selecting suppliers and managing supplier/customer relationships, designing global supply networks, and adopting new digital technologies and big data analytics? What were the long-term impacts of COVID-19 on the structures of global supply chains and the strategic positioning of major supply chain players? This special issue focuses on uncovering the key success factors and lessons from these innovative practices. We aimed to gain deeper understanding of how the adoption of technological innovations, business model innovations, and innovations in collaboration mechanisms and methods of operations improvement/optimization have helped companies enhance 2Rs in supply chains. To frame this special issue, we define some key concepts and briefly review some literature published in leading operations management journals focusing on supply chain responsiveness, supply chain resilience, supply chain integration, and big data analytics. To address disruptions and demand shocks, a great deal of emphasis has been placed in research on strategies to enhance the 2Rs in supply chains (Hendricks et al., 2009). Responsiveness is defined as the ability of a supply chain to respond purposefully within an appropriate timeframe to customer requests or supply changes in the marketplace (Shekarian et al., 2020). Generally speaking, responsiveness to changes in demand and supply is reflected in multiple aspects (Williams et al., 2013), including volume flexibility, variety flexibility, product/service modification flexibility, new product flexibility, and so on. According to Singh and Sharma (2014), a responsive supply chain could ensure a reduction in lead time, the right service quality, the right service quantity, and the on-time response to requirements of customers. Roh et al. (2014) asserted that the goal of a responsive supply chain design is to provide customers with the right product at the right place in the right length of time. The recent literature and practice show that effective measures to improve the responsiveness of supply chains include signing flexible contracts with suppliers, forecasting the trend of future demand and supply, conducting multi-source procurement, making centralized decision-making, and investing in digital technologies. Resilience is defined as the ability to mitigate the negative effects, rapidly accommodate, and react to a supply chain disruption (Kim et al., 2015). Wieland and Durach (2021) stated that resilience does not just relate to the ability of a system to bounce back after a disruptive event but also to the capacity to adapt and transform. Combining these perspectives, resilience generally refers to the ability to absorb or cushion against damage or loss, as well as the ability to rapidly recover from a disruption (Hora & Klassen, 2013). Thus, resilience is dynamic instead of static, which is considered as a fundamental attribute that supply chains need to adopt for maintaining stable growth in the face of external disruptions (Essuman et al., 2020) such as the COVID-19 pandemic. Supply chain resilience consists of multiple constituent elements, including stability, agility, robustness, collaboration, redundancy, centralization, visibility, and information sharing (Hosseini et al., 2019). Tukamuhabwa et al. (2015) emphasized the importance of building collaborative relationships in improving supply chain resilience. Other measures include maintaining slack resources, adopting a flexible production strategy, and building a risk-management infrastructure (Ambulkar et al., 2015; Modi & Mishra, 2011). Although 2Rs are the key attributes for enterprises to improve supply chain performance, there is limited research on how to develop responsive and resilient strategies to deal with long-lasting, structural, and global impacts. Previous studies mainly focused on normal situations, in which supply chain integration and big data analytics are the bases of building 2Rs supply chains. Supply chain integration is the ability to integrate all activities among a company's internal functions and external partners (supplier, distributor, retailer, etc.), until the finished product arrives at the end customer (Zhao et al., 2013). From the perspective of collaborative partners, supply chain integration could be divided by horizontal strategies and vertical strategies (Mesquita & Lazzarini, 2008), while the vertical integration is further divided by integration with suppliers (also known as upstream integration) and integration with customers (also known as downstream integration). In the era of Industry 4.0, supply chain integration consists of three dimensions: process and activity integration, technology and system integration, and organizational relationship linkages (Tiwari, 2020). A recent editorial in JOM (Browning, 2020) discussed related aspects of organizational and process integration. In recent years, under the influence of economic globalization, supply chains have been transformed. Since globalization has become pervasive, suppliers have pursued global markets, and most companies source extensively from global suppliers (Cohen & Lee, 2020). This has led to an increase in outsourcing activities and a corresponding decline in vertical integration of supply chains. As a result, supply chain networks have become flatter and more complex, composed of different organizations dispersed across multiple tiers and different geographies, and extended beyond a single country's boundaries (Choi & Hong, 2002). Global supply chains are characterized by focal firms that distribute across multiple countries, locate production facilities abroad, or source from offshore suppliers. Munir et al. (2020) showed that integration in the global supply chain could increase companies' resilience in making flexible deliveries and the number of products. Big data refers to data that arrive at a high volume and velocity with considerable variation, while analytics refers to the ability to gain insights from data via statistics, learning, optimization, or other techniques. The applications of big data and analytics are closely interlinked to enable firms to make better decisions. Hence, prior literature has typically discussed them together as big data analytics, which allows the use of advanced computing techniques, strategies and architectures to store, extract, and analyze multi-source, heterogeneous data to support decisions, and has been commonly used in operations management (Wamba et al., 2015). In the era of economic globalization, supply chain management has become extremely complex, with large-scale and online decision-making challenges emerging (Yang et al., 2021), for example, the joint decision-making between proactive planning and reactive operations in the forms of demand forecasting, production planning, inventory management, supply allocation, transportation, and distribution. It is no longer efficient to rely on traditional analytics methods. Many firms have been exploring how to take big data analytics to promote lean and agile activities in supply chain management (Baruffaldi et al., 2019). Existing studies have shown that applications of digital technologies can help improve supply chain performance by enhancing visibility and reducing supply chain risks (Govindan et al., 2018). The digitalization of supply chains produces large volumes of data, which is regarded as a new kind of resource and has the potential to create value and enhance competitiveness. Singh and El-Kassar (2019) proposed that digital technologies have transformed traditional supply chain management into a more data-driven approach, which requires a much higher level of big data analytics capabilities compared to traditional supply chain management. Following the call for papers, the submission of 114 manuscripts, and the review and revision process, seven articles were selected for this special issue that contribute to our understanding of the impact of COVID-19 on supply chains and its effect on addressing the 2Rs. In "Strengthening supply chain resilience during COVID-19: A case study of JD.com" (Shen & Sun, 2023), the authors used quantitative operational data obtained from JD.com4 to analyze the impact of the pandemic on supply chain resilience. They described the challenging scenarios that retailing supply chains experienced in China and the practical response of JD.com over the course of the pandemic the pandemic. JD.com was observed to respond well to the exceptional demand and severe logistical disruptions caused by COVID-19 in China based on its highly integrated supply chain structure (including both process and activity integration and technology and system integration) and comprehensive digital technologies. In particular, the existing, intelligent platforms and delivery procedures were modified slightly but promptly to deal with specific disruptions. The joint efforts of multiple firms, the government, and the entire Chinese society contributed to surmounting the challenges. The experience of JD.com contributes to understanding of the value of investing in operational flexibility and beyond-supply-chain collaboration given the possibility of large-scale supply chain disruptions such as the COVID-19 outbreak. In "Breaking out of the pandemic: How can firms match internal competence with external resources to shape operational resilience?" (Li et al., 2023), the authors explored how firms sought to effectively combine internal competence with external resources from the supply chain network to improve operational flexibility and stability during the COVID-19 pandemic. The internal flexibility refers to product diversity, the internal stability refers to operational efficiency, the external flexibility refers to structural holes, and the external stability refers to network centrality. Drawing upon matching theory, the authors provided an internal-external combinative perspective to explain operational mechanisms underlying different matchings. Based on the empirical results of 2994 unique firms and 5293 observations, they found that more heterogeneous combinations between internal (external) flexibility and external (internal) stability may result in a complementary effect that enhances operational resilience, whereas more homogeneous combinations between internal flexibility (or stability) and external flexibility (or stability) may have a substitutive effect that reduces operational resilience. With the COVID-19 pandemic having had a significant impact on supply chains, government initiatives have played a central role in managing the crisis. In "The impact of governmental COVID-19 measures on manufacturers' stock market valuations: The role of labor intensity and operational slack" (Chen et al., 2023), the authors investigated the impact of the Chinese government's Level I emergency-response policy (Ge et al., 2020) on manufacturers' stock-market values, and the role of manufacturers' operational slack on adding resilience. Specifically, through an event study of 1357 Chinese manufacturing companies listed on the Shenzhen Stock Exchange, the authors found that the government's emergency-response policy triggered a statistically significant positive reaction from the stock market for manufacturers. However, the authors also found negative impacts on stock market values for manufacturers in labor-intensive industries because of the labor immobility triggered by the Level I measures. In addition, this article identified the positive role of operational slack in the form of financial slack and excess inventory in helping to maintain operations and business continuity, mitigate risks caused by the labor mobility restrictions, and improve supply chain resilience, which identifies operational slack as a supply chain resilience strategy to mitigate pandemic-related risks. When the COVID-19 pandemic broke out, the medical-product industry faced unprecedented demand shocks for personal protective equipment, including face masks, face shields, disinfectants, and gowns. Companies from various industries responded to the urgent need for these potentially life-saving products by adopting ad hoc supply chains in an exceptionally short time. In "Realizing supply chain agility under time pressure: Ad hoc supply chains during the COVID-19 pandemic" (Müller et al., 2023), the authors explored the use by 34 German companies of ad hoc supply chains to produce personal protective equipment. From these cases, the authors developed an emergent theoretical model of ad hoc supply chains around enablers of supply chain agility such as dynamic capabilities (the ability to integrate, build, and reconfigure internal and external competences to address rapidly scenario changes), entrepreneurial orientation (proactiveness, risk-taking, innovativeness, autonomy, and competitive aggressiveness), and temporary orientation (speedy action in a limited time). To cope with the COVID-19 crisis, many firms allowed their employees to work from home (WFH). In "Working from home and firm resilience to the COVID-19 pandemic" (Ge et al., 2023), the authors examined whether a firm's WFH capacity increased its resilience. The authors put forward and tested a unique data set that combines listed firms' financial data, epidemiological data, and online job postings data from China. They found that imposing COVID-19 anti-contagion policies on firms and their suppliers or customers significantly increased their operating revenue volatility, slowed their recovery, and had repercussions on their supply chains. WFH enhanced firms' resistance capacity by reducing the effect of COVID-19 on their operating revenue volatility and disruptions to their supply chain partners; however, it also decreased their recovery capacity by extending the time taken to return to normal. Firm attributes, along with workers' occupations, education, and experience, impacted the effect of WFH on firm resilience. This article enhances our understanding of shock transmission across supply chains and identifies WFH as a source of firm resilience. In "Developing supply chain resilience through integration: An empirical study on an e-commerce platform" (Qi et al., 2023), the authors developed a framework that described the impact on supply chain resilience of process and activity integration between an e-commerce platform and suppliers. An analysis of data from a Chinese e-commerce platform found that integration between the e-commerce platform and suppliers in terms of information sharing, joint planning, and logistics cooperation had positive impact on supply chain resilience, while procurement automation had the opposite effect. Manufacturing flexibility positively moderated the impact of information sharing, joint planning, and logistics cooperation. The results contribute to understanding of the factors that encourage the development of supply chain resilience, suggesting that the relationship between integration and resilience is best examined within a contingency framework. There is ongoing debate about whether a firm should develop a concentrated supply chain, with the literature reporting both benefits and drawbacks. In "Opportunities or constraints? A network embeddedness perspective on the role of supply chain concentration during the pandemic" (Jiang et al., 2023), the authors examined this puzzle. Drawing on the interdependence perspective, the authors investigated how customer and supplier concentration affected supply chain resilience during the disruption and recovery stages of the pandemic, where customer concentration refers to the extent to which a firm's sales are dependent on a few major customers, and supplier concentration refers to the extent to which a firm's purchases are from a few major suppliers. The analysis of 26,488 firm-quarter observations from 2366 Chinese-listed manufacturing firms revealed that concentration can be both detrimental and beneficial, contingent on the exchange role and the crisis stage. To be specific, customer concentration accentuated the downside of firm productivity in the disruption stage but facilitated productivity restoration in the recovery stage, while supplier concentration had no significant impact on productivity in the disruption stage but hindered firm productivity from bouncing back in the recovery stage. The guest editorial team (Xiang Li, Xiande Zhao, Hau L. Lee, and Chris Voss) would like to thank the co-editors-in-chief of the Journal of Operations Management, Suzanne de Treville and Tyson Browning, for their support. The authors would also like to acknowledge all of the many reviewers and associate editors for their extensive reviews and expert advice on the large number of articles submitted to this special issue. This work was supported by the National Natural Science Foundation of China (Nos. 71931001, 71722007). The research of Prof. Zhao was partially suported by the Major Program of National Social Science Foundation of China (22&ZD082).

Problem definition: The paper focuses on an innovative bank-intermediated trade finance contract, which we call dynamic trade finance (DTF, under which banks dynamically adjust loan interest rates as an order passes through different steps in the trade process). We examine the value of DTF, the impact of process uncertainties, and the associated information frictions on this value and the strategic interaction between DTF and FinTech. Academic/practical relevance: As more than 30% of global trade involves bank-intermediated trade finance, examining contract innovation in trade finance (DTF) and its strategic interaction with FinTech is of practical importance. Also, analyzing trade finance in the presence of process dynamics and information frictions complements the existing academic literature. Methodology: We construct a parsimonious model of a supply chain process consisting of two steps. The duration of each step is uncertain, and the process may fail at either step. Information delay may also occur when verifying the process passing a step. The seller borrows from a bank to finance this two-step process either through uniform financing (the interest rate remains constant throughout the process) or DTF (the interest rates are adjusted according to a precommitted schedule as the process passes each step). When lending, the bank faces a regulatory capital requirement (the bank is required to hold capital reserve when issuing risky loans) or information asymmetry (the seller/borrower possesses more accurate information about the trade process than the bank). Results: The value of DTF lies in its ability to reduce transactional deadweight loss (under the regulatory capital requirement) and screening (separate high-quality borrowers from the low-quality ones under information asymmetry). This value is greater for more reliable or lengthier trade processes, yet DTF’s ability to screen is stronger when the process is less reliable. The severity of information delay hurts the value of DTF convexly. FinTech that expedites information transmission and verification and enables automatic execution complements DTF, and those that segment customers more efficiently could substitute DTF. Managerial implications: Our results shed light on how the underlying trade process dynamics and the type of information frictions involved affect the optimal deployment of contract innovations (DTF) and FinTech in trade finance.

This chapter summarizes the last 8 years of collaborative research of a global group of scholars on supply chain management and especially on how companies are dealing with uncertainties and disruptions. Starting with analyzing the factors that drive changes in global supply chain designs, this chapter describes how companies are coping with new types of disruptions such as trade conflicts, natural disasters, and pandemics. Commonly suggested resilience strategies like reshoring or regionalization are de-mystified and discussed based on first-level insights from interviews and survey data. Moreover, we analyzed how companies have handled different types of disruption and the underlying efficiency-resilience trade-offs. The chapter then outlines the different types of complexity and obstacles to supply chain resilience that companies have to overcome based on their individual product characteristics, market environment, and supply chain setup. Finally, the need for measuring resilience is outlined and proposed resilience metrics are discussed.

The COVID-19 pandemic has not only caused unprecedented disruptions of global supply chains but also exposed unfair supply chain practices including unfair pricing, unfair trade, and unfair pay. Despite these unfair incidents, we observe that new industry initiatives have been developed to address various supply chain fairness issues. In this chapter, we discuss the notion of supply chain fairness as well as its strategic values and historical movements. We further outline the challenges of putting fairness to practice and various research opportunities in this area.

Recent research has documented that companies are pursuing a variety of strategies to enhance supply-chain resilience. This paper examines how managers actually think about resilience strategies, and then analyzes the relationship between operations, supply-chain characteristics, and the implemented strategies. We define a "Triple-P" framework that matches resilience strategies to supply-chain archetypes by examining Product, Partnership, and Process complexity based on interviews of senior supply-chain executives. These interviews revealed two major influencers of resilience strategy, that is, Homogeneity of internal supply-chain processes and Integration with other actors in their end-to-end supply chains. We found that the supply chains have different resilience requirements, have different ways to achieve resilience (which we conceptualize as "bespoke supply-chain resilience"), and face different obstacles to resilience. This study aims at initiating a dialogue between supply-chain scholars and practitioners to support more research for developing an effective supply-chain resilience strategy.

Morris Cohen et al. find that while managers generally understand the basics of supply chain resilience, putting them to work remains challenging. Drawing on interviews with executives, they describe these challenges and share their recommendations for how to overcome them.

(1) Problem Definition: Agricultural innovation can help farmers improve their productivity, reduce their environmental impact, and address the challenges associated with ever-changing soil, weather, and market conditions. Promoting innovation often requires government support as a way to incentivize producers to experiment with (and then eventually adopt) cutting-edge practices. We investigate the effectiveness of a number of policy instruments, i.e., taxes and subsidies, in terms of their impact on the adoption of innovative production methods, producers' profits, consumer surplus, and return on government expenditure.(2) Academic/Practical Relevance: We contribute to the existing literature by investigating not only the policy maker's role in encouraging innovation but also the role of consumer preferences and learning-by-doing benefits of new production methods.(3) Methodology: Our setting features producers with access to traditional and innovative production methods and consumers that have a higher valuation for the output of the innovative method. We develop a model to analyze producers' decisions of whether to experiment with a new production method when facing uncertainty about their production yield as well as the benefits associated with learning-by-doing.(4) Results: Our findings indicate that using only taxes encourages experimentation with new production methods but decreases social welfare. Utilizing only subsidies outperforms policies that involve both taxes and subsidies in achieving higher social welfare but the converse is true in achieving a higher experimentation rate. We show that zero-expenditure policies result in a decline in social welfare unless producers face financial barriers when making the costly transition to new methods.(5) Managerial Implications: The insights we generate can help policy makers design policies to achieve specific objectives, e.g., target experimentation/adoption rates. We illustrate their applicability by conducting a numerical study using data on conventional and organic egg production in Denmark. The study generates concrete policy recommendations to achieve the organic production goal set by the Danish government.

Problem definition: Difficulties in healthcare delivery in developing economies arise from poor road infrastructure of rural communities, where the bulk of the population resides. Although motorcycles are an effective means for delivering healthcare products, governments in developing economies lack expertise in proper maintenance, resulting in frequent vehicle breakdowns. Riders for Health, a nonprofit social enterprise (SE), has developed specialized capabilities that enable significant enhancements in vehicle maintenance. Riders for Health has engaged with the governments and provided its services using different contracting approaches. However, the effect of such practice on improving vehicle availability—the main social mission of Riders for Health—is not well understood. Academic/practical relevance: This paper presents one of the first rigorous analyses of how SEs achieve their goals through innovations in operations. Our analysis highlights the relationship between a social mission objective and a service contract choice, contrasting it with the choice by a profit-maximizing organization traditionally assumed in the service contracting literature in operations management. Methodology: We construct and analyze a stylized model that combines the elements of reliability theory and contract theory, explicitly accounting for the SE’s social mission in her objective function. Results: We find that the “total solution” approach of providing all aspects of vehicle maintenance, including fleet ownership, is a preferred choice for an SE that prioritizes improving vehicle availability; by contrast, an organization that focuses on profit maximization would find this approach less attractive. Moreover, we show that the total solution approach induces the SE to exert more efforts on failure prevention and repair lead time reduction in equilibrium. Our analysis also suggests that the SE could further improve vehicle availability by the total solution approach if it manages a large fleet that consists of vehicles with high resale values. Managerial implications: Our findings provide theoretical support for Riders for Health’s recent move toward the total solution approach as it expands its service into wider rural areas in many countries. The insights obtained from our analysis offer actionable guidelines to other SEs operating in developing economies.