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This paper aims to model the mediating effects of facilitating conditions and innovativeness in the industrial Internet of Things (IIoT) and blockchain technology (BT) on manufacturing supply chain performance (MSCP).

Partial least square structural equation modelling was used to test the goodness of the model fit and hypotheses by using SmartPLS 3.3.3. Data was collected from 464 managers in Pakistan’s automotive industry through a stratified random sampling technique.

IIoT, BT, facilitating conditions and innovativeness significantly enhanced the MSCP. Therefore, the mediation between facilitating conditions and innovativeness to IIoT and BT adoption was significant in the MSCP.

The adoption of digital technology to improve the MSCP can assist companies in reducing the cost of complex procurement, production and distribution processes through secured and efficient operations. Furthermore, organisations must establish a conducive atmosphere that fosters experimentation, collaboration and resource allocation towards technological advancements to capitalise on the advantages of these technologies effectively.

This study developed a research model integrating IIoT technology, BT, facilitating conditions and innovativeness to determine the MSCP under the resource-based view theory. The outcome of this study could help organisations design a framework to improve supply chain performance by integrating innovativeness.

This paper aims to investigate how manufacturing firms behave to mitigate business risk during and post-COVID-19 coronavirus disease (COVID-19) on the global supply chain.

A systematic literature review for data mining was used to address the research objective. Multiple scientometric techniques (e.g. bibliometric, machine learning and social network analysis) were used to analyse the Lens.org, Web of Science and Scopus databases’ global supply chain risk mitigation data.

The findings show that the firms’ manufacturing supply chains used digitalisation technologies such as Blockchain, artificial intelligence (AI), 3D printing and machine learning to mitigate COVID-19. On the other hand, food security, government incentives and policies, health-care systems, energy and the circular economy require more research in the global supply chain.

Global supply chain managers were advised to use digitalisation technology to mitigate current and upcoming disruptions. The manufacturing supply chain has high uncertainty and unpredictable global pandemics. Manufacturing firms should consider adopting Blockchain technology, AI and machine learning to mitigate the epidemic risk and disruption.

This study found the publication trend of how manufacturing firms behave to mitigate the global supply chain disruptions during the global pandemic and business uncertainty. The findings have contributed to the supply chain risk mitigation literature and the solution framework.

Cold supply chain technology is critical for extending the shelf life of perishable leafy green vegetables. This study aims to investigate the concept of managing leafy green products using cold supply chain technology and visualise the findings.

Using expert interviews and data visualisation approaches, this study examines how organisations deal with the complexity of cold supply chain processes and networks. Thematic data analysis was conducted. Two types of software were used to accomplish the research objectives. The first software used AntConc version 3.5.8 with word frequency (N-gram) analysis, whereas the second software, VOSViewer offered co-occurrence network visualisation and cluster analysis.

The findings show that the appropriate design of cold chain technology is critical in ensuring the freshness and quality of leafy green vegetables. The primary goal of managing the complexity of the cold supply chain is to achieve product freshness and energy efficiency. Regardless of the importance of energy efficiency, cold supply chains require warehouse management solutions for transportation and storage.

This study found that proper design and selection of appropriate technology in the cold supply chain have driven the companies to improve the firms’ competitive advantage while delivering the best quality of perishable leafy green food products. In addition, the freshness, quality, safety, and health of leafy green vegetables will be determined by the company’s capacity to handle long-distance transportation and select the appropriate distribution channels and storage. Warehouse management system technology was found to be secondary compared to cold chain technology, although distribution and warehousing practices are critical for supply chain performance.

This study has established the conceptual indicators based on best practices and outcomes for the cold supply chain. This study argued that cold supply chain management and performance should be monitored independently. Furthermore, the theory of technological adoption can be expanded to include product nature as a driver. Finally, this study has established cold chain best practices based on a perishable supply chain perspective. The findings of this study can promote healthy foods to solve zero hunger and achieve sustainable development goals. Although this study demonstrates that technology improves supply chain practises, cold storage and logistics benefit the most from technological advancements. In contrast, non-cold supply chains benefit from technology-driven improvements in performance.

Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

This paper aims to review the literature on the relationship between the implementation and performance of 4.0 industrial revolution (IR) technologies and explores the extent to which the effects of several internal and external contingency factors on these relationships have been considered by the existing empirical studies.

To achieve its purposes, this study follows a systematic review of the literature and explores the published empirical research on implementation and performance links of 4.0 IR technologies and the effects of contingency factors on these links in mainly three main databases.

The findings of this study reveal that in general several contingency factors tend to have significant effects on the implementation and performance links of 4.0 IR in several contexts. This study also shows that the effects of these contingencies the effects of contingency factors on the implementation and performance links of 4.0 IR technologies are receiving growing attention from researchers and have been studied in different approaches but the moderation approach was the highest.

The review of the literature conducted in this study refers to those studies published mostly by three main databases (i.e. Scopus, Web of Sciences, and Science Direct), and only those papers published in English, and thus does not contain publications out of these restrictions.

This is one of the early literature review studies to explore and discuss the current state of research on the effects of contingency factors on the relationships between the implementation and performance of 4.0 IR technologies in the contexts of logistics and supply chain management.