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The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

This study examines the relationship between economic policy uncertainty (EPU) and managers' ex ante strategic choice on firms’ fixed and variable costs structure, i.e. cost rigidity and the moderating effect of government contracts and political connections.

Using a sample of 4,162 US firms during 2003–2019 and EPU measure from Baker et al. (2016), the authors examine the association between EPU and cost rigidity using multivariate regression analysis. The authors also examine the moderating effects of government customers and political connections using the subsampling method.

This study finds that increases in EPU leads to higher cost rigidity, suggesting that managers tend to look ahead and make an ex ante commitment to invest more in fixed costs to avoid congestion costs in anticipation of future product demand during EPU. The study also finds that the presence of government customers and political connections moderates the need for adopting greater cost rigidity.

This study measures firms' cost rigidity based on archival data. Future studies could utilize managers' cost structure choices using firms' internal management cost structure forecasts data to measure cost rigidity to examine the relationship between cost rigidity and EPU.

This study demonstrates that managers tend to make a proactive commitment to invest in fixed inputs when facing demand uncertainty from EPU to avoid congestion costs. This study also highlights the value of having government contracts and political connections by demonstrating that managers are less concerned about the congestion costs, hence weakening the impact of EPU on cost rigidity when they have government as major customers and/or political connections.

This study extends the management accounting literature by documenting that cost rigidity is related to EPU and that the relationship between cost rigidity and EPU also depends on whether the firm has government as major customers and/or political connections or not.

This study aims to develop a moderated mediation model to explain the practices of supply base management and how they can achieve innovation performance, and the authors explore the boundary conditions of this implementation mechanism.

The authors used the bootstrap procedure to conduct empirical tests on 328 Chinese manufacturers to verify the proposed model.

The results showed that supplier innovation focus, supply-base structuring and long-term relationship focus have a positive impact on innovation performance through supplier innovativeness, and the mediation performs differently under technology and demand uncertainty.

The authors only focused on innovation performance, and it does not explore the links between supply base management and other performance outcomes. This study involves part of the supply network which is easier to manage, i.e. supply base. The authors ignored the importance of other members in supply network. Finally, the data obtained in this study belong to the cross-sectional data during the same period but it accomplishes the research aim well.

The focal firm needs to improve their supply base composition, establish permeable organizational boundaries, and build long-term strategic partnerships characterized by equality and trust with suppliers to stimulate supply base members to make innovative contributions.

This study complements the implementation path of manufacturers around innovation, emphasizing multidimensional characteristics of supply base management. And this study clarifies the mechanism and boundary conditions between supply base management and innovation performance.

The study examines how the liquid assets holdings among non-financial Indian firms vary due to tightening monetary policy and increasing macroeconomic uncertainty.

The authors analyze 5,640 firms for the period 2011–2021. The authors first estimate India’s monetary policy shocks by decomposing the exogenous shocks from the systematic component of monetary policy changes. The authors then examine the effects of the estimated monetary policy shocks and a range of macroeconomic and policy uncertainty indicators on companies’ cash and bank balances to asset ratios using two-step system generalized method of moments (GMM) estimators.

The authors find that monetary policy shocks cause the cross-sectional variances for the firms’ liquidity holdings to increase. In anticipation of macroeconomic volatility, companies respond to these shocks after taking into account all the firm-level information to minimize the opportunity costs of holding extra cash or too few cash balances that can hamper firms’ operations. Furthermore, compared to other shocks, the contribution of inflation-induced shocks is predicted to be the largest in the cross-sectional deviation of the firm’s cash holdings. The authors also find that low-growth, older and financially constrained firms observe lesser heterogeneity in their cash holdings as they tend to hold cash as a precautionary buffer.

The authors’ approach to the analysis is unique in many ways. To address potential transmission bias, the authors use nowcasts and forecasts of real gross domestic product (GDP) growth and inflation to generate a series of exogenous monetary policy shocks for identifying unanticipated changes in short-term interest rates. Subsequently, the authors estimate how these shocks affect the cross-sectional deviation of liquid assets. For estimating the effects of macroeconomic uncertainty on corporate cash demand, the authors utilize a range of proxies for uncertainty. Unlike previous attempts, the authors offer evidence for a developing and fast-emerging economy.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

The growing focus on socially responsible supply chain management (SRSCM) has made it crucial to extend corporate social responsibility (CSR) to upstream suppliers. Drawing on resource dependence theory, this study aims to examine how supplier dependence upon socially responsible buyers impacts suppliers' CSR performance and how this relationship is moderated by network prominence and demand uncertainty.

The proposed hypotheses are tested using regression analysis with Heckman's two-stage model and a dyadic supply chain dataset constructed based on publicly traded Chinese firms between 2008 and 2016. This time window is selected due to a one-year lag of the dependent variable and the change in evaluation methods of the database providing CSR performance in 2018.

The empirical results indicate that supplier dependence upon socially responsible buyers is positively associated with suppliers' CSR performance. However, this positive relationship is attenuated when suppliers occupy a prominent position in the network or when they face high demand uncertainty.

This study extends knowledge about the role of relationship dependence in implementing SRSCM by highlighting its positive impact on suppliers' CSR. Thus, this study contributes to the buyer–supplier relationship literature and the power and relationship dependence literature. This study further advances the understanding of the factors that influence suppliers' behavior by exploring the moderating roles of network prominence and demand uncertainty. The results have several practical implications for managers and policymakers.

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

This research aims to investigate how manufacturing flexibility can address the challenges of an ever-changing and unpredictable business environment in Bangladesh’s labor-intensive ready-made garment (RMG) industry, which is underserved and situated in a developing country.

Using Partial Least Square Structural Equation Modeling, this study empirically evaluated the relationships between manufacturing flexibility, environmental uncertainty and firm performance. The analysis utilized 320 survey responses from potential RMG experts, representing 95 organizations.

The study achieved a decision-making model for implementing manufacturing flexibility in the RMG industry of Bangladesh with acceptable model fit criterion. The research pinpointed that workforce flexibility plays the maximum mediating among different types of manufacturing in coping with demand and supply uncertainty in the RMG sector.

The study made valuable contributions to theoretical and practical knowledge in the context of manufacturing flexibility in Bangladesh’s RMG and other underserved labor-intensive sectors in developing economies. It suggests that managers should shift from defensive and risky business strategies to more aggressive and proactive approaches by utilizing workforce flexibility resources adaptively to enhance manufacturing capabilities and align with dynamic market demand. Additionally, the study offers recommendations for future research to build upon its findings.

This study is unique in its approach because it presents a decision model for implementing manufacturing flexibility in a labor-intensive industry in a developing economy, specifically the RMG industry in Bangladesh, whereas previous research has primarily focused on high-tech industries in developed economies.

This study aims to examine the value of the call option contract in hedging the risks in the supply chain. The decentralized supply chain without call option contract is first studied as the criterion model for evaluations. This paper addresses several questions: What will be the optimal manufacturer’s production quantity, retailer’s ordering and pricing policies in the presence of random demand and random yield by applying the downconversion approach? How will the call option contract influence the optimal decisions for the members of the supply chain? Can the risk from randomness be divided among the members in the supply chain through the call option contract?

This paper considers a two-level decentralized supply chain under random yield and random demand in which the manufacturer takes advantage of the downconversion approach with two scenarios, with and without option contract. To the best of the authors’ knowledge, no article or study uses the downconversion approach in a supply chain regarding random yield and random demand. Furthermore, the paper considers pricing with option contract in the supply chain, which makes this article stands out significantly from other articles in the literature.

This study shows that the downconversion approach would reduce the risk caused by the random yield, which appears to be the appropriate method for the environmental goal of the supply chains. Moreover, adopting a call option contract can increase flexibility and mitigate risks, resulting in more expected members’ profits.

To simplify the model, the authors assume one manufacturer and one retailer, so extending the model to consider multiple retailers instead of one retailer and inventory sharing between them would be interesting. Considering the option and exercise prices as decision variables would be important future research topics. Put option and bidirectional option contracts could be investigated in the future. Another extension is modeling asymmetry of information in supply chain.

This paper provides managerial insights on dealing with both demand and yield risks in a manufacturer–retailer supply chain. The manufacturer has a random yield production and produces two types of vertical products: low-end and high-end. To reduce waste caused by the random yield, the manufacturer uses a downconversion approach in which low-end products are made by converting the defective high-end products. The manufacturer purchased a shortage of high-end products from the secondary market (i.e. emergency sourcing). High-end products are sold through the retailer, and low-end products are sold directly by the manufacturer. The customer demand for high-end products in the end market is random and depends on the selling price, and the customer demand for the low-end products in the secondary market is independent and random. The retailer contracts the manufacturer with the call option to obtain high-end products to meet a random demand; in fact, by using the call option contract, the authors try to balance the risks between two members. Two scenarios of with and without call option contract are proposed. After the high-end product demand is observed, the retailer would exercise the option order quantity in the call option contract scenario and then place an instant order with the manufacturer if necessary. In each scenario, the manufacturer and the retailer make their decisions simultaneously (static game) to determine the retailer’s optimal ordering and pricing policies and the optimal production quantity of the manufacturer (Nash equilibrium) by maximizing their expected profits. Finally, the impact of the model parameters on the supply chain is expressed through numerical examples. The numerical analysis shows that the call option contract provides greater profit than the wholesale price contract.