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The study investigated the relationship between digital supply chain (DSC) and sustainable supply chain performance (SSCP) of small and medium-sized enterprises (SMEs) via the lens of supply chain integration (SCI) and information sharing (IS). This study concentrates more on the mediating role of SCI and IS in the link between DSC and SSCP that no research has mentioned before.

This research figures out how the DSC impacts the performance of the organization and the supply chain. By employing a carefully designed questionnaire to gather data, a quantitative methodology was employed. Managers at the senior and medium levels were the responders who were targeted. There are 467 valid replies gathered from the primary survey. The data results were used in the analysis using partial least squares structural equation modeling (PLS-SEM).

The findings imply that SCI’s function in the information-sharing process is crucial as it fosters cooperation, coordination and connectivity throughout the DSC. Furthermore, the study’s conclusions offer helpful information on how businesses might enhance supply chain performance through information exchange. Businesses are constantly concentrating on the role that the DSC plays as a catalyst for sustainable growth and are improving supply chain performance through SCI and information exchange.

This study highlights the gaps and unexplored themes in the existing literature, catalogs the DSC published in the main logistics journals and helps people recognize and appreciate this kind of work. It also has the potential to contribute to future research on SSCP. Moreover, the novelty research is further reinforced by the coverage of the newfound mechanism, where SCI and IS mediate the relationship between DSC and SSCP, directly and positively enhancing SSCP.

The purpose of this paper is to examine the role of digital supply chain (DSC) technologies in automotive supply chain resilience (SCR) practices to improve the supply chain performance (SC-Perf.) objectives of companies operating in the automotive industry. This study also compares the results of the associated SC-Perf objectives before and after the COVID-19 pandemic outbreak lockdown situation.

The authors undertook in-depth empirical research using a questionnaire survey to explore the performance of automotive supply chains. The sample for this study consisted of practitioners from supply chain entities such as automotive original equipment manufacturers, Tier-1 component manufacturers and lead logistics providers in Asia-Pacific (AP) emerging markets. Research questions, framework and hypotheses were developed using the literature review.

The research outcome from analysis of the data the authors collected from an emerging market context, specifically the automotive sector, emphasizes the role of DSC technologies and encourages the firm’s SCR practices which, in turn, supports the SC-Perf objectives. The DSC technologies competency moderates the SCR and SC-Perf objectives relation, and the moderation effect is higher for post-COVID-19 pandemic outbreak lockdown situation than at prior state.

The scope of the study is restricted to the automotive firms in the AP region. The data were collected from a representative sample of the population through a questionnaire survey. The small size of the sample incurs a certain level of subjectivity.

This research provides practical insights for practitioners and academicians on DSC technologies’ influence in SCR practices to improve the firm’s SC-Perf. This research shares the literature insights on use of DSC technologies across the sector to allow the automotive firm to reassess the existing operational practices.

The paper adds insights on introducing or implementing DSC technologies across AP automotive firms to increase the operations’ performance by improving SCR practices and sustainability.

Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion.

This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence.

The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain.

This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits.

This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

One of the fundamental objectives of adopting digital supply chain (DSC) is to uplift the performance of an organization. Although a wide variety of literature confirms the impact of DSC on performance, it is hard to explore as to which dimensions of the performance is affected by DSC and how much. This chapter undertakes discussion on the impact of DSC on the various organizational performance indicators. The chapter also denotes some major key performance indicators (KPIs) that organization can track to gauge the impact of DSC on performance. A brief discussion on the challenges related to the development, adoption, and continuation of KPIs is also appeared in the later part of the chapter. The chapter concludes by denoting that the utilization of digital technologies (DTs) such as artificial intelligence (AI), the Internet of Things (IoT), and complex analytics in DSC has prospects for enhancing the operational efficiency, transparency, and agility of a supply chain (SC). Organizations that adopt these DTs have experienced better demand forecasting, reduced time order fulfillment time, and higher levels of consumer satisfaction. Nonetheless, the successful use of DSC requires development and implantation of KPIs regularly.

A digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.

The study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.

Conducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.

In the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

The purpose of this paper is to present a conceptual model that defines the essential components shaping the new Digital Supply Chains (DSCs) through the implementation and acceleration of Industry 4.0.

The scope of the present work exposes a conceptual approach and review of the key literature from 1989 to 2019, concerning the evolution and transformation of the actors and constructs in logistics and Supply Chain Management (SCM) by means of examining different conceptual models and a state-of-the-art review of Industry 4.0’s concepts and elements, with a focus on digitization in supply chain (SC) processes. A detailed study of the constructs and components of SCM, as defined by their authors, resulted in the development of a referential and systematic model that fuses the inherent concepts and roles of SCM, with the new technological trends directed toward digitization, automation, and the increasing use of information and communication technologies across logistics global value chains.

Having achieved an exploration of the different conceptual frameworks, there is no compelling evidence of the existence of a conceptual SCM that incorporates the basic theoretical constructs and the new roles and elements of Industry 4.0. Therefore, the main components of Industry 4.0 and their impact on DSC Management are described, driving the proposal for a new conceptual model which addresses and accelerates a vision of the future of the interconnectivity between different DSCs, grouped in clusters in order to add value, through new forms of cooperation and digital integration.

This research explores the gap in the current SCM models leading into Industry 4.0. The proposed model provides a novel and comprehensive overview of the new concepts and components driving the nascent and current DSCs. This conceptual framework will further aid researchers in the exploration of knowledge regarding the variables and components presented, as well as the verification of the newly revealed roles and constructs to understand the new forms of cooperation and implementation of Industry 4.0 in digitalized SCs.

This study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.

The research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.

Four broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.

The proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.

The proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.

This research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

The rapid global changes we are witnessing pose a pressing challenge that necessitates reevaluating conventional supply chain practices. Consequently, the integration of digital technologies into supply chain operations, often referred to as digital supply chain (DSC), has emerged as a strategic shift that aims to empower organizations to proactively seize new opportunities rather than being caught off guard by unforeseen disruptions arising from economic volatility, global pandemics and regional conflicts. Thus, this study embraces a knowledge-centric approach to explore the direct and indirect impact of knowledge management, innovation and learning capabilities on DSC adoption in an emerging economy context. Furthermore, it aims to shed light on the moderating role of environmental dynamism in this intricate interplay.

Employing a cross-sectional survey, the research data were collected from 354 managers representing Egyptian manufacturing and service firms utilizing a structured questionnaire. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results unveiled that knowledge management capability (KMC) has the highest path coefficient value among all endogenous variables. It accounts for a significant portion of the variance in innovation and learning capabilities, which play pivotal roles in adopting DSC. Notably, learning capability appears to exert a more powerful influence on DSC adoption than innovation capability through direct and mediating effects. Furthermore, the findings underscore the moderating effect of environmental dynamism on the relationship between learning capability and DSC adoption. However, this moderating role is not observed in the link between innovation capability and DSC adoption.

There is a growing trend among firms to adopt DSC in response to significant environmental shifts. This study offers valuable insights for managers and policymakers, providing them with a deeper understanding of the DSC adoption process. The study’s findings assist in identifying crucial factors that boost DSC adoption and offer guidance on successfully leveraging digital technologies for managing supply chain practices. Moreover, the study offers stimulating directions for future DSC research directions.

The study contributes to the existing literature by expanding our understanding of the adoption of DSC by utilizing knowledge, innovation and learning capabilities within the context of emerging economies.

This paper aims to systematically review the literature on digital supply chain (DSC), big data (BD) and manufacturing lead time (MLT) in industrial companies.

This study provides a systematic review of the 99 research on this subject that was published between 2015 and 2022. Studies were found in the Scopus database. This review also identifies gaps in the literature, highlights conflicting results, examines prospective data sources for empirical researchers and offers suggestions for choosing promising research subjects in the future.

This study performed a thorough literature review to a developing field of inquiry in order to identify the impact of the digital supply chain, BD and manufacturing lean time, an area that has received little attention in the literature. Future pathways and ramifications are also offered based on the literature content search. The results showed that BD improves DSC performance through resilience and innovation of the DSC. MLT and DSC integration were found to be positively correlated, according to the results.

Although the production lead time is preferable to boost customer value and supply reliability, the long lead time hurts the DSC’s ability to compete. DSC integration also improves coordination and streamlines processes. The researchers suggest fostering organizational flexibility, information exchange to accomplish DSC integration and adaptable behaviors including responsiveness and alertness.

The Industry 4.0 phenomenon is bringing unprecedented disruptions for all traditional business models and hastening the need for a redesign and digitisation of activities. In this context, the literature concerning the digital supply chain (DSC) and its capabilities are in the early stages. To bridge this gap, the purpose of this paper is to propose a framework for digital supply chain capabilities (DSCCs).

This paper uses a narrative literature approach, based on the main Industry 4.0 elements, supply chain and the emerging literature concerning DSC disruptions, to build an integrative framework to shed light on DSCCs.

The study identifies seven basic capabilities that shape the DSCC framework and six main enabler technologies, derived from 13 propositions.

The proposed framework can bring valuable insights for future research development, although it has not been tested yet.

Managers, practitioners and all involved in the digitalisation phenomenon can utilise the framework as a starting point for other business digitalisation projects.

This study contributes to advancing the DSC literature, providing a well-articulated discussion and a framework regarding the capabilities, as well as 13 propositions that can generate valuable insights for other studies.