Supply chain management and Industry 4.0: conducting research in the digital age

The future of industry 4.0 and supply chain resilience after the COVID-19 pandemic: Empirical evidence from a Delphi study

The COVID-19 pandemic has caused major supply chain disruptions and unveiled the pressing need to improve supply chain resilience (SCRES). Industry 4.0 (I4.0) is a promising lever; however, its future in supply chain risk management (SCRM) is highly uncertain and largely unexplored. This paper aims to evaluate I4.0's potential to improve SCRES in a post-COVID-19 world. Based on current literature and multiple workshops, 13 future projections on potential I4.0 application areas in SCRM were developed. A two-round Delphi study among 64 SCRM experts with digital expertise was conducted to evaluate and discuss the projections regarding their probability of occurrence until 2030, their impact on SCRES, and their desirability. A fuzzy c-means algorithm was applied to cluster the projections based on the expert assessments. The expert evaluations led to three clusters on I4.0 application in SCRM: Four projections on generating data, increasing visibility, and building digital capabilities received considerable approval and are reliable to improve SCRES in 2030. Four projections enabling data sharing and processing were predominantly supported and demonstrated realization potential for 2030. Finally, five projections that require major supply network adaptations were deemed unlikely to improve SCRES in 2030. This paper answers several research calls by presenting empirical evidence on the pathway of I4.0 implementation in SCRM following the COVID-19 pandemic. Moreover, it evaluates a holistic set of technologies and indicates prioritization potentials to achieve SCRES improvements.

Embracing supply chain digitalization and unphysicalization to enhance supply chain performance: a conceptual framework

Purpose

The paper presents a research methodology that could be used to carry out a systematic literature review on the current state of the art of the technological development in the field of the digitalization and unphysicalization of supply chains (SCs). A three-dimensional conceptual framework focusing on the relationship between Digital Technologies (DTs), business processes and SC performance is presented. The study identifies the emerging practices and areas of SC management that could be positively affected by the implementation of DTs. With this in mind, the emerging practices have a high probability to be considered future best practices.

Design/methodology/approach

A systematic literature review was conducted on DTs in SC management. The methodology used aims to algorithmically and objectively standardize the information incorporated into thousands of scientific documents. Selected papers were analyzed to investigate the recent literature on SC digitalization and unphysicalization. A total of 87 DTs were selected to be analyzed and subsequently grouped into 11 macro-categories. 17 business processes linked to SC management are taken into account and 17 different impacts on SC management are presented. From a set of 1,585 papers, 5,060 emerging practices were collected and singularly summarized combining DT, business process and impact on SC performance.

Findings

A unique analytical perspective provided represents an important evolution when trying to organize the current literature on SC management. The widely used DTs in the practices and the most considered business processes and impacts are highlighted and described. The three-dimensional conceptual framework is graphically represented to allow for the emergence of the best combinations of DT, business process and impact on SC performance. These combinations suggest the most promising areas for the implementation of the emerging practices for SC digitalization and unphysicalization. Additional findings identify and define the most important contexts in which Big Data contributes to SC performance.

Originality/value

The research methodology used is offering progress through which to systemize the current practices as well as detect the potential of digitalization and unphysicalization under the three-dimensional conceptual framework. The paper provides a structured proposal for promising future research directions, assuming that the five research gaps as findings of this research could be the basis for prescriptions, as well as a future research agenda and theory development. Moreover, this research contributes to current managerial issues concerning SC management, referred to data and information management, efficiency and productivity of SC processes, market performance, SC relationship management and risk management in SC.

Supplier selection in the industry 4.0 era by using a fuzzy cognitive map and hesitant fuzzy linguistic VIKOR methodology

Organizations will be increasingly concerned about maintaining their positions in today's changing world, the high-tech era, and the emergence of innovative technologies because of the industrial revolutions. Everyone has come to believe that to survive and continue their constructive roles, they must achieve competitive advantages by working based on the trends. It is undeniable that the introduction of Industry 4.0 has had a significant impact on enterprises, organizations, and, of course, supply chains. In the meantime, selecting a supplier is one of the main strategic decisions of the organization because choosing the right supplier leads to increasing profitability, improving market competition, better accountability, enhancing product quality, and reducing costs. While the issue of supplier evaluation has been one of the interesting topics for researchers in recent decades, its development in the fourth supply chain generation needs further consideration. In this regard, current technologies in the fourth-generation industrial revolution, methods, and criteria used in previous studies based on industry 4.0 and before that are reviewed separately. By reviewing previous articles and experts' opinions, thirteen sub-criteria considering industry 4.0 have been identified for selecting suppliers in three categories, economic, environmental, and social. The weight of each criterion has been determined using a set of fuzzy cognitive maps (FCMs) and considering the centrality of criteria in the concept of communication networks. To prioritize the suppliers, the hesitant fuzzy linguistic term sets (HFLTS) VIKOR method has been used in hesitant fuzzy linguistic terms. Finally, a case study is introduced to illustrate the effectiveness and usefulness of our integrated methodology and prioritize its four suppliers.

Agility and digitalization: why strategic agility is a success factor for mastering digitalization – evidence from Industry 4.0 implementations across a supply chain

Purpose

This paper addresses the emergence of strategic agility as adaptive capability to face the need to adapt to a constantly changing environment. Special emphasis is paid to governance mechanisms as a microfoundation of dynamic capabilities, investigating the dynamics and outcome in regards to the digitalization of supply chains and its socio-economic relations of its members.

Design/methodology/approach

A multiple-case study method is applied to explain the impact of a digitalization initiative in the form of an I4.0 implementation in a supply chain context. Building on qualitative in-depth interviews of experts in managerial positions, 16 cases from the manufacturing industry involving an I4.0 implementation across the supply chain were analyzed. Based on a conceptual design science approach, the CIMO logic (context, intervention, mechanisms and outcome) framework is used to investigate the interplay between agility as a dynamic capability and governance mechanisms.

Findings

The studied cases demonstrate an intensification of synergistic combinations of inter-firm resources to manage digitalization across the supply chain (SC). With the implementation of I4.0, competitive advantage along the SC takes higher priority over the competitive advantage in the individual or dyadic perspective. Strategic agility as a dynamic capability to cope with and adapt to the changing environment is hereby crucial emphasizing relational SC governance (SCG) as essential as a microfoundation to adjust the structure and management of SCs. Relationships, which allow competitive advantage as a SC balance out traditional power mechanisms within the SC hierarchy. Trust, collaboration and flexibility, aligned with common incentives in generating competitive advantages enable the SCs to mitigate uncertainty and risk while preventing opportunistic behavior.

Practical implications

The study offers SCM managers in-depth insights into strategic agility and how to address the recent challenge of digitalization successfully. Identifying crucial dynamics within SCG mechanisms based on first-hand use cases, practical success factors for implementing I4.0 to optimize effectiveness and efficiency can be derived how to structure and manage future SCs.

Originality/value

This paper contributes to the first insights examining the implications of digitalization and the role of strategic agility as a capability to adapt. Investigating the microfoundation of governance within this capability, this research provides insights on the socio-economic level, while discussing specific mechanisms how relationships of SCs evolve proposing relevant insights for future research.

Logistics 4.0 in warehousing: a conceptual framework of influencing factors, benefits and barriers

Purpose

In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts.

Design/methodology/approach

Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter’s decision-making process.

Findings

Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company’s digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified.

Originality/value

This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers’ perspective, whereas little has been explored in warehousing from the adopters’ view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.

Towards a contingency theoretic perspective on technology pre-adoption in supply chain management

Purpose

Emerging technologies and the concept of Industry 4.0 are on the rise. Thus, available solutions for SCM get more complex and dynamic. Technology adoption is crucial for organizations competitiveness, but resources are limited. Therefore, this paper aims to gain insights into the successful management of technology pre-adoption in SCM.

Design/methodology/approach

In-depth polar case studies of technology pre-adoption initiatives in various industries were collected using an interview-based approach. Subsequently, the paper deploys transcript coding on the data to analyze information within and across the cases. Lastly, utilizing contingency theory, supply chain-specific influencing factors and corresponding management practices were identified.

Findings

The research reveals eight contingency dimensions and corresponding variables that influence the design of successful technology pre-adoption in SCM (e.g. complexity and criticality). Moreover, ten response variables were identified, referring to the pre-adoption process or organization. They systemize possible options when conducting technology pre-adoption initiatives.

Research limitations/implications

The paper contributes to research by systemizing potential influencing factors and responses of technology pre-adoption through an explorative, empirical study. The paper is limited by its qualitative approach and the number of case studies conducted.

Practical implications

The results provide supply chain managers a guideline for analyzing potential influences on the technology pre-adoption process and propositions how to manage pre-adoption accordingly.

Originality/value

This research is among the first to provide in-depth insights into technology pre-adoption from an organization's perspective considering supply chain-specific contingencies. Also, it introduces a new perspective on technology selection as a management process.

Organizational Trust in the Age of the Fourth Industrial Revolution: Shifts in the Nature, Production, and Targets of Trust

In this essay, we argue that the advent of the Fourth Industrial Revolution calls for a reexamination of trust patterns within and across organizations. We identify fundamental changes in terms of (1) what form organizational trust takes, (2) how it is produced, and (3) who needs to be trusted. First, and most broadly, trust is likely to become more impersonal and systemic. Trust between actors is increasingly substituted by trust in a system based on digital technology. Second, in terms of trust production modes, characteristic- and institution-based trust production will gain in importance. Third, despite the move toward system trust, there will nonetheless be a need to trust certain individuals; however, these trustees are no longer the counterparts to the interaction but rather third parties in charge of the technological systems and data. Thus, the focal targets of interpersonal trust are changing.

4.0 technologies in city logistics: an empirical investigation of contextual factors

Industry 4.0 technologies, originally developed in the manufacturing sector, can be purposefully implemented to improve City Logistics (CL) processes by automatizing some of their operational tasks and enabling real-time exchange of information, with the ultimate goal of providing better interconnection among the actors involved. This work aims to identify the main social and economic contextual drivers for investing in the application of Industry 4.0 technologies to urban logistics. To this end, a dataset based on the primary collection of 105 CL projects exploiting the main 4.0 technologies has been built. After that, a regression model has been completed including potential economic, strategic, and demographic determinants of investments in CL 4.0. According to the obtained outcomes, Gross Domestic Product, Foreign Direct Investments, Research and Development Expenditure, Employment Rate, and Number of Inhabitants are significant contextual factors for the adoption of Industry 4.0 technologies in last mile logistics. The study might support academicians to investigate novel application fields of Industry 4.0 technologies. Also, it can serve as a roadmap for orienting the investments of private organizations and public entities to promote CL innovation and digitalization. Moreover, Industry 4.0 technology providers might find this study interesting to uncover prospective business sectors and markets. Future research efforts will analyse the impacts of internal business factors on CL 4.0 and the satisfaction levels of urban logistics stakeholders.

Theorizing the impact of network characteristics on multitier sustainable supply chain governance: a power perspective

Purpose

While the literature on multitier supply chain management traditionally assumes that first-tier suppliers belong to the visible proportion of the supply base, intermediaries might limit focal firms' visible horizon already at this stage. High power asymmetries promoting centrality and complexity in the supply network are seen as a particular root cause that limits the impact of governance mechanisms for sustainability. To map the space for governance mechanisms in a network-sensitive context more comprehensively, the study analyzes supply network characteristics from a power perspective.

Design/methodology/approach

This research is conceptual. To better understand power imbalances and mutual dependencies from network centrality and complexity, network configurations were constructed drawing on resource dependence theory. These configurations allow deducing the impact of (non-)mediated governance mechanisms for a sustainable development in the supply network. An agenda to stimulate future empirical and model-based research is accordingly presented.

Findings

The research shows that those networks with densely interconnected first-tier suppliers promote network centrality and complexity, leading to an inverted U-shape relationship between the focal firm's exertion of coercive power and the sustainability performance in the supply network. The findings allow a more comprehensive theoretical grounding for mapping governance approaches in a network-sensitive context and provide insights on how to avoid negative effects from power asymmetries.

Practical implications

The findings suggest the need for accompanying, indirect governance mechanisms already at the stage of first-tier suppliers based on non-mediated forms of power, such as referent power, also promoting disintermediation. Purchasing companies may also consider using digital platform technologies that foster disintermediation, such as blockchain technology.

Originality/value

By studying intermediaries from a power and network perspective, the conceptualization adds to the discussion on governance in multitier sustainable supply chain networks in various industries. Furthermore, it contributes to the increasing efforts of middle-range theorizing in logistics and supply chain management. The results partially challenge previous assumptions on the moderating role of specific network characteristics.

Did COVID-19 change the rules of the game for supply chain resilience? The effects of learning culture and supplier trust

Purpose

This paper aims to clarify the effects of learning culture and trust on supply chain resilience (SCR) and to investigate their role specifically during COVID-19 pandemic to aid decision-makers. For this, a conceptual model proposing relations between variables was developed. The focal point of this research is to investigate the relationship between organizational learning culture (OLC) and SCR, and the mediating effect of supplier trust (ST) in the relationship before and during a pandemic.

Design/methodology/approach

This study relies on a unique dataset collected through two separate cross-sectional surveys corresponding to pre- and during-pandemic times that were conducted at the same time. The questionnaire was collected from 245 medium- to senior-level managers, to ensure a thorough understanding about the company’s inner workings and supply chain (SC). To test the proposed research model, the authors processed their data and model using lavaan package in R.

Findings

The findings show that OLC and ST have positive and significant effects on SCR. Furthermore, learning culture also triggers ST. Thus, it is ST that explained, as a mediator, the positive effects of OLC on SCR. All these findings are similar for both before and after the pandemic. A critical finding is about the effect of size (small vs. large) and ownership (local vs. multinational). The analysis suggests that during pandemic multinational companies and larger organizations exhibit higher SCR than their counterparts.

Research limitations/implications

First, responses to the questionnaire were collected from only one country. Cross-cultural comparisons can be made by collecting data from different countries in future research. Second, the data were obtained from companies operating in different sectors, with a majority in manufacturing. It is possible to obtain more specific findings by analyzing responses from a specific industry. Third, results of this study reflect responses of only SC and manufacturing managers, but other departments such as marketing or finance can also complement the findings. Finally, several other organizational variables may be factored in as moderators to enrich the conceptual model.

Practical implications

The authors believe that findings of this research will guide shareholders and managers to develop effective strategies in order to prevent SC disruptions during similar risk/shock scenarios.

Originality/value

Similar to earlier research, this study considers the importance of ST on SCR. But this study differs in analyzing the effects of OLC on SCR directly and in taking the mediating effect of ST into account. The authors test the strengths of these relationships individually before and during COVID-19 pandemic. Under pandemic conditions, the authors present empirical evidence on the effects of organizational learning and ST on SCR. In contrast to previous research on SCR, this study connotes the importance of an organization’s internal dynamic capabilities in developing resilience.

An ISM-MICMAC approach for analyzing dependencies among barriers of supply chain digitalization

Purpose

Supply chain digitalization (SCD) facilitates a competitive advantage and is equally challenging. A literature analysis reveals that research related to SCD is available, but analysis of key barriers and their interrelations for effective SCD is limited. This paper aims to identify and find out interrelationships among the key barriers affecting SCD in the electronic supply chain (SC).

Design/methodology/approach

Interpretive structural modeling (ISM) is used to identify the contextual relationship among the SCD barriers. The model is validated using MICMAC analysis.

Findings

The findings of this study have implications at both theoretical and practical levels. The proposed ISM model can help organizations analyze and interpret interrelationships among barriers to SCD. It can lead to better insights and understanding for minimizing the dominant barriers to effective SCD.

Originality/value

This study tries to bridge the gap in identifying and finding the interrelationships among the key barriers to effective SCD in an electronic SC. The result assists practicing managers and academicians in effective decision-making on the SCD process.

Effectiveness of English Online Learning Based on Deep Learning

With the popularization of the Internet lifestyle and the innovation of learning methods, more and more online learning systems have emerged, allowing users to study in the system anytime and anywhere. While providing convenience to users, online learning systems also bring troubles to users, who cannot quickly find the resources they are interested in from the huge amount of learning resources. In this paper, we apply deep learning to an English online learning platform and analyze learners and learning contents by clustering algorithm and association rules. Based on this, a content organization system is developed using genetic algorithms, which is applied to the case of this paper to provide learners with personalized learning content. With the hope that the system can be extended to other online learning platforms in the future, three data mining techniques were selected to solve the problems found in the English online learning platform, and we designed how these techniques should be applied to the online learning platform. The first technique is the cluster mining technique, which is used to analyze learners' profiles, classify learners in different categories, provide them with personalized learning content, and organize group learning. The second technique is association rules, which is used to analyze the correlation between learning contents. For the adaptive student-teacher knowledge migration strategy, the teacher model can guide the student model to track online and migrate the task-specific knowledge to the online tracking student model through the network parameters. Finally, a case study is selected and the above design is applied to this case study, and the results are analyzed in detail. The data mining technology is applied to the English online learning platform, and an innovative English learning content organization system is developed. It is hoped that the results of this study will have some practical value for promotion and provide an idea for the construction of the online learning platform, and it is also expected that the idea can improve the quality of online learning to a certain extent. Specifically, the online student model is adaptively updated by the teacher model parameters and the online student model parameters together.

Investigating social factors and their impact on value co-creation in supply chain ecosystems

Purpose

As coopetition often characterizes relationships in ecosystems, social factors are particularly important to ensure resilient and reliable relationships, therefore efficient collaboration, and a corresponding outcome. Social factors have so far only been considered as peripheral factors in the ecosystem literature. Thus, this study aims to analyse the current state of literature to provide initial insights into the impact of social factors on value co-creation in supply chain ecosystems.

Design/methodology/approach

A structured literature review was conducted. Eleven articles were identified which explicitly examined social factors in the context of supply chain ecosystems.

Findings

The findings showed that in current research contributions, especially three social factors are considered crucial for value co-creation within supply chain ecosystems: trust, commitment and mindset. Moreover, researchers focus so far only on positive-affected social factors.

Research limitations/implications

The findings enable ecosystem orchestrators as well as actors to strengthen social factors in supply chain ecosystems. The cultivation and proactive consideration of social factors is crucial for efficient and effective collaboration and has a corollary effect on supply chain ecosystems value co-creation.

Originality/value

This paper extends the limited literature on social factors within supply chain ecosystems, notably from a strategic management perspective. The findings help scholars to understand why social factors do play a crucial role regarding the value co-creation in supply chain ecosystem and how specific social factors influence the overall business outcome. By raising awareness of the importance of social factors for all ecosystem actors, complementary cooperation in the ecosystem improves, which in turn has a positive impact on value co-creation.

Analysis of Directional Activities for Industry 4.0 in the Example of Poland and Germany

An analysis of directional activities in Poland and Germany towards the implementation of Industry 4.0 was carried out by comparing the common sustainable development features. The value of production sold along with the benefits of its implementation are presented. The transformation map was characterized along with development areas and potential directions of automation and robotization. Technological possibilities were assessed, considering the production of robots. The execution of activities aimed at implementing solutions in the field of Industry 4.0 in Poland was indicated. The key information gleaned in this study is the awareness of the implemented features proving the fulfillment of conditions relating to Industry 4.0. Action towards the sustainable replacement of machines that require repair or regeneration is significantly related to thinking towards rationalizing the actions taken and assessing the financial capabilities of companies so as not to lead to their collapse. The article presents original research on the characteristics of selected production companies in Poland and Germany striving for digital maturity and the results of our hypotheses. The key direction should be activities aimed at developing a coherent strategy, the proper selection and evaluation of managers, focusing on communication, and the pursuit of intelligent products by creating appropriate integration standards that facilitate the implementation of an innovative process generating modern technologies.

Robotic process automation in Maersk procurement–applicability of action principles and research opportunities

Purpose

The authors share a real-world case study of a multiple-year adoption process of robotic process automation (RPA) in procurement to add to the limited empirical research base on RPA in supply chain management. The Maersk case offers hard evidence of the value of RPA that can be used as a benchmark for decision-making in companies and as a basis for further research in key areas such as change management and behavioral aspects as well as return on investment on RPA and the need for RPA capability development.

Design/methodology/approach

Together with the co-author from Maersk, the authors cover a multiple year RPA program in procurements, to capture lessons learned and develop research questions for the future. The authors consider 39 generic action principles for RPA adoption in a specific procurement context.

Findings

The authors find RPA for procurement to be an enabler of strategic progress and of advancing the concept of triple values (enterprise, customer and employee) in a supply chain setting. The authors offer RPA adoption scoping guidance and show how, with growth and maturity of the program, conditions such as predictability of volume become less relevant as a scoping criterium. The authors also find that RPA augments work rather than replace staff. Maersk utilizes staff time freed up by automation to focus employees on more strategic priorities. The authors consider 39 generic action principles for RPA adoption in a procurement-specific context and develop additional action principles based upon the Maersk case.

Originality/value

The authors study both a unique and rich case to complement limited empirical research on RPA in procurement and supply chain management and the limited research into RPA past early stage adoptions. The authors address Hofmann et al.'s (2019) questions about the change management involved in RPA and consider generic RPA action principles from literature in this specific procurement setting. The authors extend those action principles and develop a rich set of research opportunities.

Digitalization and Future Agro-Food Supply Chain Management: A Literature-Based Implications

Achieving transition towards sustainable and resilient food systems is a critical issue on the current societal agenda. This study examined the potential contribution of digitalization of the food system to such transition by reviewing 76 relevant journal articles, indexed on the Scopus database, using the integrative literature review approach and descriptive content analysis with MAXQDA 2020 software. ‘Blockchain’ was the top hit among keywords and main concepts applied to the food system. The UK as a country and Europe as a continent were found to lead the scientific research on food system digitalization. Use of digital technologies such as blockchain, the Internet of Things, big-data analytics, artificial intelligence, and related information and communications technologies were identified as enablers. Traceability, sustainability, resilience to crises such as the COVID-19 pandemic, and reducing food waste were among the key benefit areas associated with digitalization for different food commodities. Challenges to practical applications related to infrastructure and cost, knowledge and skill, law and regulations, the nature of the technologies, and the nature of the food system were identified. Developing policies and regulations, supporting infrastructure development, and educating and training people could facilitate fuller digitalization of the food system.

Artificial Intelligence Applications for Industry 4.0: A Literature-Based Study

Artificial intelligence (AI) contributes to the recent developments in Industry 4.0. Industries are focusing on improving product consistency, productivity and reducing operating costs, and they want to achieve this with the collaborative partnership between robotics and people. In smart industries, hyperconnected manufacturing processes depend on different machines that interact using AI automation systems by capturing and interpreting all data types. Smart platforms of automation can play a decisive role in transforming modern production. AI provides appropriate information to take decision-making and alert people of possible malfunctions. Industries will use AI to process data transmitted from the Internet of things (IoT) devices and connected machines based on their desire to integrate them into their equipment. It provides companies with the ability to track their entire end-to-end activities and processes fully. This literature review-based paper aims to brief the vital role of AI in successfully implementing Industry 4.0. Accordingly, the research objectives are crafted to facilitate researchers, practitioners, students and industry professionals in this paper. First, it discusses the significant technological features and traits of AI, critical for Industry 4.0. Second, this paper identifies the significant advancements and various challenges enabling the implementation of AI for Industry 4.0. Finally, the paper identifies and discusses significant applications of AI for Industry 4.0. With an extensive review-based exploration, we see that the advantages of AI are widespread and the need for stakeholders in understanding the kind of automation platform they require in the new manufacturing order. Furthermore, this technology seeks correlations to avoid errors and eventually to anticipate them. Thus, AI technology is gradually accomplishing various goals of Industry 4.0.

The implications of Industry 4.0 on supply chains amid the COVID-19 pandemic: a systematic review

Background: COVID-19 has caused significant disruptions in supply chains. It has increased the demand for products and decreased the supply of raw materials. This has interrupted many production processes. The emerging technologies of Industry 4.0 have the potential to streamline supply chains by improving time-sensitive customized solutions during this emergency. Purpose: This research examines the effects of the epidemic on supply chains and how these effects are reduced through Industry 4.0 technology. Design/methodology/approach: An extensive literature review using the "Preferred Reporting Items for Systematic Review and Meta-Analysis" method was carried out on the impact of the COVID-19 pandemic on supply chains and Industry 4.0 technologies. The study was undertaken by selecting keywords validated by experts and a search was conducted in the Scopus, ProQuest, and Google Scholar databases. Publications from the leading journals on these topics were selected. The bibliographical search resulted in 1484 articles followed by multiple layers of filtering. Finally, the most pertinent articles were selected for reviewing, and a total of 53 articles were analysed. Findings: This study discusses the impact of COVID-19 on the supply chain and how the emerging technologies of Industry 4.0 can help manufacturers to ease the impact. These technologies will enhance the production system through the automation and optimization of production flow convergence, enabling efficiencies and improvements among the suppliers, manufacturers, and consumers in the COVID-19 situation. Originality/value: The study summarizes the impact of the COVID-19 on supply chains and shows the potential of Industry 4.0 technologies to lessen the impact on manufacturing supply chains. This is valuable information for policymakers and practitioners so that they can get insights and take necessary actions.

An analysis of Industry 4.0 implementation-variables by using SAP-LAP and e-IRP approach

Purpose

In today’s uncertain business environment, Industry 4.0 is regarded as a viable strategic plan for addressing a wide range of manufacturing-related challenges. However, it appears that its level of adoption varies across many countries. In the case of a developing economy like India, practitioners are still in the early stages of implementation. The implementation of Industry 4.0 appears to be complex, and it must be investigated holistically in order to gain a better understanding of it. Therefore, an attempt has been made to examine the Industry 4.0 implementation for the Indian manufacturing organization in a detailed way by analyzing the complexities of relevant variables.

Design/methodology/approach

SAP-LAP (situation-actor-process and learning-action-performance) and an efficient interpretive ranking process (e-IRP) were used to analyze the various variables influencing Industry 4.0 implementation. The variables were identified, as per SAP-LAP, through a thorough review of the literature and based on the perspectives of various experts. The e-IRP has been used to prioritize the selected elements (i.e. actors with respect to processes and actions with respect to performance) of SAP-LAP.

Findings

This study ranked five stakeholders according to their priority in Industry 4.0 implementation: government policymakers, industry associations, research and academic institutions, manufacturers and customers. In addition, the study also prioritized important actions that need to be taken by these stakeholders.

Practical implications

The results of this study would be useful in identifying and managing the various actors and actions related to Industry 4.0 implementation. Accordingly, their prioritized sequence would be useful to the practitioners in preparing the well-defined and comprehensive strategic roadmap for Industry 4.0.

Originality/value

This study has adopted qualitative and quantitative approaches for identifying and prioritizing different variables of Industry 4.0 implementation. This, in turn, helps the stakeholder to comprehend the concept of Industry 4.0 in a much simpler way.

Supply chain resilience for managing the ripple effect in Industry 4.0 for green product diffusion

Purpose

The purpose of this paper is to examine (1) how the recovery speed using promotional investment and (2) distributed production using additive manufacturing (AM) improve the resilience of the supply chain to manage any disruptions in the diffusion of green products.

Design/methodology/approach

The environmental performance, service level performance and economic performance are the measures of interest. These measures are studied through the integration of inventory and production planning (I&PP) of the reverse logistics system and consumer behavior using Bass (1969) model of diffusion of innovation under the paradigm of Industry 4.0 architecture. The Taguchi experimental design framework was used for the simulation analysis.

Findings

The adoption patterns based on the Bass model in conjunction with recovery speed and production on AM during the disruption period suggest that there exist tradeoff decisions between various combinations of information-sharing and I&PP policies.

Practical implications

The extensive sensitivity analyses provide real-time support for managerial decisions. Besides the potentials of Industry 4.0 capabilities, the present research suggests paying close attention to the recovery speed in conjunction with the inventory management system.

Social implications

The integration of consumers' behavior (Bass model) to digital technologies is an additional contribution of the present research toward sustainability issues from the social perspective.

Originality/value

Previous research studies have discussed resilience to manage the ripple effect. However, none of them have addressed the changing scope of resilience to manage the ripple effect caused by the disruption in the diffusion of green products in a reverse logistics setup.

Analysis of enablers for the digitalization of supply chain using an interpretive structural modelling approach

Purpose

Over the years, technology development has rationalized supply chain processes. The demand economy is disrupting every sector causing the supply chain to be more innovative than ever before. The digitalization of the supply chain fulfils this demand. Several technologies such as blockchain, big data analytics, 3D printing, Internet of things (IoT), artificial intelligence (AI), augmented reality (AR), etc. have been innovated in recent years, which expedite the digitalization of the supply chain. The paper aims to analyse the applicability of these technological enablers in the digital transformation of the supply chain and to present an interpretive structural modelling (ISM) model, which presents a sequence in which enablers can be implemented in a sequential manner.

Design/methodology/approach

This paper employed the ISM approach to propose a various levelled model for the enablers of the digital supply chain. The enablers are also classified graphically based on their driving and dependence powers using matrix multiplication cross-impact applied to classification (MICMAC) analysis.

Findings

The study indicates that the enablers “big data analytics”, “IoT”, “blockchain” and “AI” are the most powerful enablers for the digitalization of the supply chain and actualizing these enablers should be a topmost concern for organizations, which want to exploit new opportunities created by these technologies.

Practical implications

This study presents a systematic approach to adopt new technologies for performing various supply chain activities and assists the policymakers better organize their assets and execution endeavours towards digitalization of the supply chain.

Originality/value

This is one of the initial research studies, which has analysed the enablers for the digitalization supply chain using the ISM approach.

Reacting to the COVID-19 pandemic through digital connectivity with customers: the Italian experience

The COVID-19 has deeply impacted the firm’s competitiveness because of the restrictions that limited the relationships with existing and new customers. The pandemic has pushed firms to rely on digital technologies to redefine business processes as well as customer relationships and marketing strategies. The digital technological portfolio firms may rely on to face the COVID-19 related challenges spanning from the established web-based technologies to the more recent Industry 4.0 tools related to the fourth industrial revolution. In this regard, the paper aims at exploring which digital technologies allowed firms to positively react to the pandemic to overcome their constraints in managing the market relationships. Based on an original qualitative analysis on 26 Italian SMEs carried out during the first Italian lockdown in 2020, the paper identifies three strategies in the use of digital technologies to support customer relationship management and market expansion. It emerges specifically the strategic importance of web-based technologies (videoconferencing, CRM and e-commerce) to support firm competition and performance through customer interactions and digital experience, advancing the literature on firms’ reaction strategies during turbulent and crisis times.

A holistic model for Global Industry 4.0 readiness assessment

Purpose

Transformation to Industry 4.0 has become crucial for nations, and a coherent transformation strategy requires a comprehensive picture of current status and future vision. This study presents a comprehensive model for readiness assessment of nations based on rigorous analysis of several global indices and academic Industry 4.0 literature.

Design/methodology/approach

A holistic approach is taken considering overall socioeconomic development along with industrial innovation and seven readiness dimensions: enabling environment, human resource, infrastructure, ecological sustainability, innovation capability, cybersecurity and consumers. The indicators used for evaluation are standard metrics for which data are collected from reputed sources such as World Bank, United Nations Educational Scientific and Cultural Organization (UNESCO), World Economic Forum (WEF) and International Organization for Standardization (ISO), and hence internationally acceptable.

Findings

The formulated model is used to evaluate Industry 4.0 readiness of 126 economies that account for 98.25% of world’s gross national income. Observations show poor scores of most economies on innovation capability and cybersecurity dimension as compared to other 5 dimensions. In 75% countries, I4.0 readiness score is below 0.5 on a scale of 0–1(completely ready), highest being 0.65 for Denmark.

Originality/value

A systematic literature review revealed lack of assessment models discussing a nation's current status or readiness for Industry 4.0. This academic study is first of its kind.

Do network capabilities improve corporate financial performance? Evidence from financial supply chains

Purpose

The purpose of this study is to bridge the gap in the literature on supply chain finance (SCF) by exploring the relationship between network capabilities and corporate financial performance (CFP) in financial supply chains (FSCs).

Design/methodology/approach

The authors collect panel data and adopt regression analysis to analyse the joint investment activities among 1359 manufacturing firms and 289 financial service providers in China to explore how network capabilities, both network power and network centrality, improve CFP in the FSCs.

Findings

Under the FSCs environments, network centrality (i.e. eigenvector centrality, closeness centrality and betweenness centrality) raises CFP (ROA, ROE and Tobin's Q) and network power (node degree, clustering coefficient) also improves CFP. However, node strength from the network power stream has a negative effect on Tobin's Q, indicating that when the partner of a firm has an extremely strong influence in FSCs; this weakens the bargaining ability and flexibility of the focal firm, thus reducing its long-term financial performance.

Practical implications

The joint investment activities among supply chain partners and financial service providers help managers understand the advanced financing solutions generated by internal and external network organisations as well as be aware of network capabilities' impact on CFP in FSCs.

Originality/value

This study answers the call for more empirical research on SCF to provide a broader sample to examine financial supply chain management. This is one of the earliest studies to shed light on a new perspective – how network capabilities improve CFP in the FSCs.

Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries

There has been an increased interest among scholars to investigate supply chain resilience (SCRes) in manufacturing and service operations during emerging situations. Grounded in the SCRes theory, this study provides insights into the impact of the COVID-19 outbreak on the automobile and airline supply chain. Both the short and long-term response strategies adopted by the two supply chains are assessed, using a combination of qualitative and quantitative techniques in three distinct phases. In phase one, we use a sequential mixed-method for resilience evaluation, integrating Time-to-Recovery (TTR) and Financial Impact (FI) analysis. In phase two, we conduct an empirical survey involving 145 firms to evaluate the short-term SCRes response strategies. In the third phase, we conduct semi-structured interviews with supply chain executives both from the automobile and airline industries to understand the long-term SCRes response strategies. Our findings indicate that: (i) the automobile industry perceived that the best strategies to mitigate risks related to COVID-19, were to develop localized supply sources and use advanced industry 4.0 (I4.0) technologies. (ii) The airline industry on the other hand, perceived that the immediate need was to get ready for business continuity challenges posed by COVID-19, by defining their operations both at the airports and within the flights. (iii) Importantly, both the sectors perceived Big Data Analytics (BDA) to play a significant role by providing real-time information on various supply chain activities to overcome the challenges posed by COVID-19. (iv) Cooperation among supply chain stakeholders is perceived, as needed to overcome the challenges of the pandemic, and to accelerate the use of digital technologies.

Local Extremes of Selected Industry 4.0 Indicators in the European Space—Structure for Autonomous Systems

In the past, the social and economic impacts of industrial revolutions have been clearly identified. The current Fourth Industrial Revolution (Industry 4.0) is characterized by robotization, digitization, and automation. This will transform the production processes, but also the services or financial markets. Specific groups of people and activities may be replaced by new information technologies. Changes represent an extreme risk of economic instability and social change. The authors described available published sources and selected a group of indicators related to Industry 4.0. The indicators were divided into five groups and summarized by negative or positive impact. The indicators were analyzed by precedence analysis. Extremes in the geographical dislocation of factor values were found. Furthermore, spatial dependencies in the distribution of these extremes were found by calculating multiple (long) precedencies. European countries were classified according to individual groups of indicators. The results were compared with the real values of the indicators. The indicated extremes and their distribution will allow to predict changes in the behavior of the population given by changes in the socio-economic environment. The behavior of the population can be described by the behavior of autonomous systems on selected infrastructure. The paper presents research related to the creation of a multiagent model for the prediction of spatial changes in population distribution induced by Industry 4.0.