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The purpose of this paper is to identify the role and main attributes of manufacturing companies which operate in virtual supply chains.

In order to identify the role and main attributes of manufacturing companies enabling to operate in a virtual supply chain, a three-step statistical analysis was employed, namely exploratory factor analysis, hierarchical cluster analysis and non-hierarchical clustering technique.

The findings show that virtual supply chain operations would not be supported by manufacturing companies offering highly customized products achieved by a unit production, developed in details and engineered to order. On the contrary, the large manufacturing companies of virtual supply chains report a high level of flexibility stemming from a wide scope of more standardized products offered to the market. The conducted study show that better ability of manufacturers supporting virtual supply chains is not industry specific.

The list of investigated attributes is not complete, and other characteristics of manufacturers in virtual supply chains should be identified. Another important shortcoming of the study is its quantitative character and generalization of the findings. Each “virtual” environment in supply chains may be unique and some of the compared characteristics may differ significantly. Therefore, the aforementioned attributes should be considered separately with a conscious focus on the environmental context. The quantitative study may be greatly enhanced by applying the case study approach, showing detailed solutions and practices, and thus making the study more valuable from the theoretical and managerial standpoints.

The conducted study showed that better ability of manufacturers to support virtual supply chains is not industry specific, since the branch of electronic products and electrical equipment and components was represented by an equal share of manufacturers, both in non-virtual and virtual clusters. Furthermore, in order to operate in virtual supply chains, managers should pay attention to the structure and range of products delivered to the market. The managers should also be aware that apart from considering cost and efficiency, operating in a virtual supply chain environment also requires quality of products and processes in order to manufacture and deliver a superior value for the customers.

Having recognized major groups of indicators demonstrating the level of ability of manufacturing companies to operate in a virtual supply chain, the attributes of three clusters of manufacturers possessing different bunch of features, significant for virtual supply chains, have been distinguished.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

Additive manufacturing (AM) involves the renewal of production systems and also has implications for firms’ supply chains. Innovations related to AM supply chains are, so far, insufficiently understood, but their success will require firms’ awareness of their systemic nature and their firm-specific implications. The purpose of this paper is to explore the supply chain innovations dealing with AM in business-to-business supply chains.

An exploratory qualitative research design is used. Interviews were conducted in 20 firms, workshops were organized to map AM-related processes and activities, and supply chain innovations were analyzed.

This study reveals practical changes in supply chains and requirements for AM-related supply chain innovations. While earlier research has centered on technology or firm-specific AM implementations, this study shows that fully leveraging AM will require innovations at the level of the supply chain, including innovations in business processes, technology and structure, as well as supportive changes in the business environment. These innovations occur in different parts of the AM supply chain and are emphasized differently within different firm types.

This research was conducted in one country in the context of the machine building and process industry with a limited data set, which limits the generalizability of the results. The results offer an analytical framework and identify new research avenues for exploring the innovations in partial or complete AM supply chains.

The results offer a framework to assess the current state and future needs in AM-related supply chain innovations. Practical ideas are proposed to enhance AM adoption throughout firms’ supply chains. These results are important to managers because they can help them position their firms and guide the activities and collaborations with other firms in the AM supply chain.

This study draws attention to the supply chain innovations required when firms adopt AM in their processes. The generic supply chain innovation framework is enhanced by adding the business context as a necessary component. Implementation of AM is shown to depend on the context both at the level of the supply chain and the firm’s unique role in the supply chain. The holistic view taken reveals that successful AM technology adoption requires broad involvement from different firms across the supply chain.

Extreme weather events are on the rise around the globe. Nevertheless, it is unclear how these extreme weather events have impacted the supply chain sustainability (SCS) framework. To this end, this paper aims to identify and analyze the aspects and criteria to enable manufacturing firms to navigate shifts toward SCS under extreme weather events.

The Best-Worst Method is deployed and extended with the entropy concept to obtain the degree of significance of the identified framework of aspects and criteria for SCS in the context of extreme weather events through the lens of managers in the manufacturing firms of a developing country-Nigeria.

The results show that extreme weather preparedness and economic aspects take center stage and are most critical for overcoming the risk of unsustainable patterns within manufacturing supply chains under extreme weather events in developing country.

This study advances the body of knowledge by identifying how extreme weather events have become a significant moderator of the SCS framework in manufacturing firms. This research will assist decision-makers in the manufacturing sector to position viable niche regimes to achieve SCS in the context of extreme weather events for expected performance gains.

The topic of Lean Six Sigma (LSS) implementation in a supply chain context is an emerging research stream comprising of diverse objectives and complex processes thereby presenting opportunities for further exploration and organizational process improvement. Thus, this study proposes an integrated multi-criteria decision-making methodology to determine what can facilitate the successful implementation of LSS as an organizational change strategy in the manufacturing supply chain.

The proposed methodology based on Decision-Making Trial and Evaluation Laboratory and hierarchical Evaluation Based on Distance to Average Solution is employed to ascertain the relative importance and priorities of an identified framework of factors with the aid of opinions of managers in the Nigerian plastics industry.

The results show a high significance of institution-based factors (e.g. government regulations) and present relevant implications to the policymakers as well as the managers and practitioners of the plastics manufacturing industry.

This study indicates a possible pathway to accurately evaluate a framework of critical factors to integrate and institutionalize LSS in the manufacturing supply chain for organizational performance improvement.

The purpose of this paper is to investigate the differences and similarities between the manufacturing and services sectors in order to develop a methodology that can provide the opportunity for the transfer of best practice between the two sectors. This paper aims to describe an audit methodology capable of yielding objective comparisons of supply chain integration performance that can assist practitioners and academics to transfer learned solutions.

A robust, site-based, multi-method supply chain diagnostic for detecting manufacturing supply chain system uncertainty was amended for the service sector in order to yield objective comparisons of the (normalised) supply chain integration performances of 119 organisations.

The research confirms the value of using a lens enabled by the uncertainty circle model (UCM) for generating meaningful comparative supply chain performances. The research found that services do not always exhibit unique attributes which effectively bar manufacturing-based supply chain best practice from being adopted within the service sector.

Combining the UCM and Quick Scan Audit Methodology approach has the potential to assist the spread of proven good practice across both sectors. The framework provides realistic and repeatable performance vectors, capable of aligning estimates of value stream health status even when comparing supply chains with differing objectives, configurations, and performance goals.

The purpose of this paper is to identify a classification scheme which represents the variation in business and supply chain performance of supply chains in Indian manufacturing industry. Classification is done by presenting an empirical taxonomy of clusters representing supply chains in Indian manufacturing industry based on variation in supply chain excellence index (SCEI) and business performance index (BPI).

The clustering of supply chains in Indian manufacturing industry is done by considering BPI and SCEI as clustering variables, which were found by using survey responses and results of a prior empirical study which was carried out in Indian manufacturing industry. The cluster analysis is performed by using Ward’s agglomerative hierarchical clustering followed by using K-means clustering algorithm to establish final set of clusters.

It was found that supply chains in Indian manufacturing industries can be clustered in four major clusters which are named as strategic, celebrity, capable and undeveloped cluster. The characteristics of these clusters reveal some major characteristics of supply chains in Indian manufacturing industry.

The research work presented in this paper takes a novel way to introduce the clusters of supply chains in Indian manufacturing industry. The researchers who are seeking patterns in large data sets of manufacturing companies of Indian industry will be benefitted by using the proposed clusters. While practitioners who are seeking to move their supply chain one step ahead will also reap the benefits of the paper by seeking the characteristics of particular cluster.

Additive manufacturing has been described as converting supply chains into demand chains. By focusing on metal additive manufacturing as a contemporary technology causing ongoing disruption to the supply chain, the purpose of this paper is to describe and discuss how incumbent firms act during an ongoing, transformational disruption of their supply chain.

Interviews and secondary data, along with seminars attracting approximately 600 individuals operating in metal additive manufacturing, form the empirical basis for this paper.

The findings of this paper indicate how disruption occurs at multiple positions in the supply chain. Episodic positions as conceptualised in this paper refer to how parties challenged by disruption attempt to reach normality while speeding the transformational disruption.

This paper contributes to previous research by theorising about episodic positions in light of a supply chain disruption. The empirical data are unique in how they capture supply chain change at the time of disruption and illustrate disruptive, transformational change to supply chains. The paper interlinks research on disruption from the innovation and supply chain literature, with contributions to both.

The emergence of new manufacturing technologies, spurred by intense competition, will lead to dramatically new products and processes. New management systems, organizational structures, and decision‐making methods will also emerge as complements to new products and processes. This paper attempts to investigate technologies, systems and paradigms for the effective management of networked enterprise (supply chain networks), especially long supply chains. In doing so, the paper presents not only an exhaustive literature review to identify the complexities, gaps and challenges associated with long supply chains but also the emerging enabling technologies to support these gaps and challenges.

The approach takes the form of an interview of industrials, researchers and a literature review.

“Competition in the future will not be between individual enterprises but between competing supply chains.” Business opportunities are captured by groups of enterprises in the same enterprise network. This is due to the global competition that forces enterprises to focus on their core competences.

The paper presents a vision of the future technical issues relating to long supply chains and an insight into the future scientific and industrial advances required to meet future market and public demands.

This research work highlights the research issues and discusses the key enabling features, which will need to evolve and be perfected in industry in the future manufacturing networked enterprises and especially long manufacturing supply chains.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.