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The disruption caused by COVID-19 exhorts to reiterate the role of operations and supply chain management (OSCM) in achieving social sustainability. Therefore, the present study aims to develop a conceptual understanding of the OSCM ecosystem's role in enabling the world to accelerate towards social sustainability.

The study uses the integrative review method to achieve the stated objectives. The study first identifies the societal disruptions caused by COVID-19. Then based on dynamic capabilities (DC) theory, stakeholder theory and real-life examples, the study puts forward the stakeholder dynamic capabilities (SDC) view as an approach to overcome these social challenges.

Taking the SDC view, the study identified ten social challenges aggravated by the COVID-19. Response actions for OSCM have been proposed to mitigate these challenges.

The pandemic has brought new challenges to the OSCM to achieve social sustainability. Therefore, the study's proposed response actions aim to assist OSCM managers in leveraging their expertise to do good for society and create a better world. Moreover, the study also provides avenues for future research on the topic.

Based on the SDC view, the study attempts to conceptualise social sustainability for OSCM during a pandemic. The SDC view helps capture internal and external social challenges emerging due to COVID-19 and utilise firms' capabilities to overcome these challenges.

The purpose of this research is to (1) analyse the effect of customised on-demand 3DP on surgical flow time, its variability and clinical outcomes (2) provide a framework for hospitals to decide whether to invest in 3DP or to outsource.

The research design included interviews, workshops and field visits. Design science approach was used to analyse the impact of the 3D printing (3DP) interventions on specific outcomes and to develop frameworks for hospitals to invest in 3DP, which were validated through further interviews with stakeholders.

Evidence from this research shows that deploying customised on-demand 3DP can reduce surgical flow time and its variability while improving clinical outcomes. Such outcomes are obtained due to rapid development of the anatomical model and surgical guides along with precise cutting during surgery.

We outline multiple opportunities for research on supply chain design and performance assessment for surgical 3DP. Further empirical research is needed to validate the results.

The decision to implement 3DP in hospitals or to engage service providers will require careful analysis of complexity, demand, lead-time criticality and a hospital's own objectives. Hospitals can follow different paths in adopting 3DP for surgeries depending on their context.

The operations and supply chain management community has researched on-demand distributed manufacturing for multiple industries. To the best of our knowledge, this is the first paper on customised on-demand 3DP for surgeries.

Food supply chains (FSCs) are becoming increasingly complex and vulnerable to recall risks due to quality failures. Measures for supply chain risk management can minimize these recall risks. However, this responsibility must be shared by all stakeholders in the chain. This study aims to analyze the roles of different stakeholders in managing risks in the events of food recalls.

A systematic literature review was carried out, and 110 articles were explored to identify risk management actions and to link them to the role of stakeholders involved in FSC recall.

The study found that nine stakeholders were responsible for 25 hazard management actions related to food safety and traceability systems, regulatory and preventive measures, and control and response mechanisms for food recalls in the FSC.

This article contributes to the literature by proposing an explanatory map associating risk management actions to different stakeholders in food recall. The actions were grouped according to whether they were prevention actions to avoid a food recall or contention actions to limit the negative economic effects and maintain the health of the population.

The purpose of this paper is to investigate the impact of internal integration, external integration (EI), and supply chain risk management (SCRM) on manufacturing flexibility, and the moderating effect of SCRM on the relationships between internal and EI, respectively, and manufacturing flexibility.

Using hierarchical regression, data are analyzed from a sample of 343 manufacturing plants in Asia collected in 2013-2014 as part of the International Manufacturing Strategy Survey (IMSS VI).

Internal integration and SCRM have a direct effect on manufacturing flexibility. SCRM moderates the relationship between EI and flexibility.

Further research is needed to generalize beyond the flexibility performance of discrete manufacturing firms in Asia.

To benefit from EI and increase their flexibility performance, manufacturing firms need to implement different mechanisms of SCRM to prevent and deal with supply chain risks including those associated with supply chain integration.

This research contributes to the body of knowledge on the relationships between internal integration, EI, SCRM, and manufacturing flexibility.

The purpose of this paper is to identify challenges faced by industrial firms at different phases of adoption of 3D printing (3DP), and outline how 3DP service providers can help address these challenges.

Separate interview questionnaires for 3DP users and 3DP service providers were used to conduct semi-structured interviews.

The key 3DP adoption challenges are as follows: creating a business case; difficulty in using different materials; optimising the process for specific parts; lack of “plug and play” solutions offered by equipment manufacturers; limited availability of training and educational support; poor end product quality; machine breakdowns; and high cost of maintenance and spare components. Using the theoretical lens of the technology acceptance model, results show a lack of ease of use and technological turbulence impact companies’ decisions to adopt 3DP. 3DP service providers can indeed attempt to alleviate the above challenges faced by customers through providing multiple 3DP services across different stages of adoption.

Future research should examine the role of 3DP equipment manufacturers and design and modeling software solutions providers in improving adoption and how 3DP equipment manufacturers could develop into more integrated service providers as the technology advances.

Service providers can help customers transition to 3DP and should develop a portfolio of services that fits different phases of adoption.

The paper outlines how 3DP service providers can help address customer challenges in adoption of 3DP across different stages of adoption.

The purpose of this paper is to assess the impact of additive manufacturing (AM) implementation on aircraft supply chain (SC) networks. Additive and conventional manufacturing spare part inventory control systems are studied and compared, revealing insights into SC performance.

A leading global commercial airline’s SC network data are used to model the research problem. A system dynamics simulation approach is followed, drawing out insights for managers.

A significant improvement in SC efficiency is observed through the implementation of AM, rendering it a worthwhile investment for global SCs. AM helps to balance inventory levels, and increase responsiveness while decreasing disruptions and carbon emissions in the supply networks.

The paper offers guidance on the adaption of AM in aircraft SCs and AM’s impact on spare part inventory systems.

The study provides robust evidence for making critical managerial decisions on SC re-design driven by a new and disruptive technology. Next-generation SC and logistics will replace the current demand for fulfilling material products by AM machines.

The purpose of this paper is to identify various risk drivers which affect a food processing supply chain and to create a map of how those risk drivers propagate risks through the supply chain and impact important performance measures.

This study involves experts from food processing companies to elucidate the contextual relationships among the risk drivers and between risk drivers and performance measures. This is used to quantify the relationships and to determine the indirect and overall relationships applying Fuzzy Interpretive Structural Modeling.

Three categories of risk drivers which Indian food processing companies need to pay maximum attention to minimize risks are identified. These are supplier dependency and contracting, supplier variability, visibility and traceability and manufacturing disruptions. Analysis shows that collaborating with suppliers and logistics service providers, developing mutually beneficial contracts with them while ensuring that adequate technology investments are made can significantly mitigate risks and consequently improve margins and lead to revenue growth.

This study has been carried out with experts from large food processing companies in India, and hence, the results cannot be generalized across other types of food processing companies.

The proposed methodology can help understand the interrelationships between supply chain risks and between those risks and performance measures. Thus, it can help a food processing company to create business cases for specific supply chain risk mitigation projects.

This study is one of the earliest to create a comprehensive risk propagation map for food processing companies which helps in quantifying the impact the risk drivers have on each other and on performance measures.

The purpose of the paper is to develop a conceptual framework for improving the effectiveness of risk management in supply networks following a critical literature review.

A critical review of 91 scholarly journal articles published between 2000 and 2018 supports the development of an integrated conceptual framework.

The findings emphasize that supply chain integration (SCI) can have both a positive and negative impact on the effectiveness of risk management in supply networks. It is possible to have a positive effect when SCI can be used to develop competencies in joint risk planning within the organization and with wider supply network members and, in turn, to develop collaborative risk management capabilities. Supply network characteristics can influence whether and the extent to which SCI has a positive or negative impact on risk management effectiveness.

The conceptual framework can be used to empirically assess the role of SCI for effective risk management. Dynamic evaluation of the effectiveness of risk management and potential redesign of the supply network by considering other contingent factors are some future research avenues.

There is a need for developing specific competencies in risk planning within organizations and joint risk planning with supply network members which, in turn, can help develop collaborative risk management capabilities to improve the effectiveness of risk management in supply networks. Network characteristics will influence whether and the extent to which SCI results in the effectiveness of risk management.

Moving beyond recent (systematic) reviews on supply chain risk management, this study develops a novel conceptual framework interlinking SCI and the effectiveness of risk management while considering network characteristics.

The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics.

Content analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products.

There is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains. Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain. Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions.

The findings need to be validated through further empirical research and modeling. There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products. Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information. Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars.

The findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose. To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort.

This paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research.