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The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

The purpose of this study is to examine the impact of sustainable supply chain management (SSCM) practices on both competitive advantage (CA) and organizational performance (OP) in the manufacturing sector in Ethiopia.

Data for the study were collected from a sample of 221 manufacturing companies operating in the four manufacturing groups/sectors in Ethiopia. In addition, data analysis was performed using the partial least squares method, which is a variance-based Structural Equation Modeling approach in the Smart-PLS software version (SmartPLS 4.0).

Based on the statistical analysis of the collected data, it demonstrates that SSCM has a significant and positive impact on both competitive advantage and organizational performance. Furthermore, statistical findings offer proof of the clear connection between competitive advantage and organizational performance. Moreover, competitive advantage indirectly mediates the relationship between SSCM and OP.

The primary limitation of this research is its reliance on a cross-sectional design. The generalizability of the findings obtained from the present study may be hindered. The variable under investigation in this research assessed organizational performance, a concept that is widely acknowledged to be extremely dynamic.

The study provides managers and researchers with valuable information on Sustainable Supply Chain Management strategies and how they influence competitive advantage and organizational performance in commercial and industrial environments.

This paper adds to the body of knowledge by providing new data and empirical insights into the relationship between SSCM practices and the performance of manufacturing companies in Ethiopia.

Just transition is a fundamental concept for supply chain management but neither discipline pays attention to the other and little is known about how supply chains can be orchestrated as socioecological systems to manage these transitions. Building from a wide range of just transition examples, this paper explores just transition to understand how to move beyond instrumental supply chain practices to supply chains functioning in harmony with the planet and its people.

Building from a systematic review of 72 papers, the paper identifies just transition examples while interpreting them through the theoretical lens of supply chain management, providing valuable insights to help research and practice understand how to achieve low-carbon economies through supply chain management in environmentally and socially just ways.

The paper defines, elaborates, and extends the just transition construct by developing a transition taxonomy with two key dimensions. The purpose dimension (profit or shared outcomes) and the governance dimension (government-/industry-led versus civil society-involved), generating four transition archetypes. Most transitions projects are framed around the Euro- and US-centric, capitalist standards of development, leading to coloniality as well as economic and cultural depletion of communities. Framing just transition in accordance with context-specific plural values, the paper provides an alternative perspective to the extractive transition concept. This can guide supply chain management to decarbonise economies and societies by considering the rights of nature, communities and individuals.

Introducing just transition into the supply chain management domain, this paper unifies the various conceptualisations of just transition into a holistic understanding, providing a new foundation for supply chain management research.

This study aims to holistically explore the intersection of sustainable supply chain management, carbon accounting and life cycle assessment (LCA). The purpose of this study is to derive state-of-the-art knowledge of this landscape and use it to build a structured research agenda that can help to further develop this field.

Seventy-eight distinct contributions, identified through a rigorous, transparent and replicable search protocol, are analyzed through a systematic literature review. Additionally, bibliometric information on the studies is extracted from the Scopus database and visualized through the use of VOSViewer and RStudio.

This study outlines the current state-of-the-art knowledge across three spheres of supply chain management, synthesizing the extant literature into several nascent themes – namely, the significance of Scope 3 emissions; how LCA can be integrated into carbon accounting and sustainability disclosures, the differences between countries and industries in terms of carbon emissions and policies for a concerted effort toward carbon reduction.

Several practical implications can be drawn from the research for both practitioners and policymakers. The research provides a comprehensive, bird’s eye view on the discrepancies between different industries and countries in terms of carbon emissions, along with how carbon accounting should move toward strategic and predictive adoption.

The results show that adopting life cycle thinking can contribute to more transparent monitoring of carbon emissions in supply chains; however, its use in sustainability reporting needs to become more widespread, encompassing not only the carbon footprints of products and services but also the organization as a whole.

Using bibliographic and critical qualitative analyses, this study reviews the literature on LCA in sustainable supply chain management and carbon accounting. To the best of the authors’ knowledge, this review is the first attempt to synthesize this relevant and rapidly growing nexus between the three literature streams mentioned above.

This study examines the direct and indirect effects of social capital on supply chain performance via supply chain quality integration (SCQI), which refers to integrating supply chain partners from the perspective of quality management. It also examines the moderating role of environmental uncertainty in the link between social capital and SCQI and determines the conditional indirect effect of social capital on supply chain performance via SCQI.

Data were collected using a time-lagged research design through a self-administered survey of supply chain professionals in manufacturing firms in Pakistan. Hayes’ PROCESS Macro was used to test the hypotheses.

The results show a positive relationship between social capital and supply chain performance. SCQI partially mediates the relationship between social capital and supply chain performance. Environmental uncertainty significantly moderates that relationship in such a way that firms that operate under high environmental uncertainty are more likely to use their social capital to develop SCQI than firms that operate under low environmental uncertainty.

The study has practical implications for managers who seek to implement SCQI practices using social capital. Leveraging social capital across the supply chain fosters strong connections and a quality-oriented approach across the supply chain, and improves overall performance. Managers can use the power of social capital to navigate environmental uncertainty.

This study’s originality lies in its drawing on the dynamic capability theory and contingency theory and integrating the dispersed scholarly work on social capital, SCQI, and supply chain performance under the boundary condition of environmental uncertainty.

Previous literature reviews mainly focus on green supply chain, however, there is surprisingly little effort made in the systematic literature review to focus on a specific function of green supply chain, i.e. green procurement (GP). Regarding research methodology, most reviews are qualitative and inductive generalizations. Quantitative methods such as bibliometrics have started to be applied in recent years. This paper responds to this trend by counting the largest amount of literature with 238 articles in the last 24 years from 2000 to 2023 to visually analyze different theoretical perspectives and research topics into a comprehensive framework and identify future research directions and opportunities in the GP field.

Based on CiteSpace and in-depth content analysis, this paper attempts to visually analyze 238 valid papers to identify key literature and analyze the evolution of research hot spots and frontier development trends.

Combined with the visualization results and the content analysis of key references, we identify key literature and examine the evolution of research hotspots and frontier development trends. The bibliometric analysis mainly includes knowledge mapping to identify key themes, co-occurrence and clustering analysis of keywords, cooperation networks in researchers' countries. An overall GP research model is presented and our research suggests future avenues for GP research, such as low carbon, digitalization, servitization and ecosystem perspectives.

Firstly, in terms of time and volume of literature, we have counted the most comprehensive and up-to-date literature in the field of GP research, which is conducive to further expanding and enriching GP research. Secondly, this study clearly describes the theoretical evolution of GP research from bilateral and multilateral to ecosystem perspectives, and constructs a new and comprehensive research framework of “driver-practice-outcome”. Thirdly, based on the bibliometric analysis results, our research suggests future avenues for GP research, such as low-carbon, digitalization, servitization, and ecosystem perspectives, which can contribute to expanding our understanding of GP development.

The purpose of this paper is to show the benefits of bridging the gap between supply chain management (SCM) and political philosophy to challenge the underlying assumptions about SCM concepts and open doors to novel theory building.

A thought experiment is conducted to illustrate how the two philosophers Niccolò Machiavelli and Jürgen Habermas would tackle sustainability issues in coffee supply chains from a research perspective. The thought experiment is carried out using data from 30 semi-structured interviews with actors from the coffee industry. Supplementing the thought experiment with empirical insights allows for a deeper understanding of supply chain dynamics and how these are impacted by the application of the philosophical viewpoints.

The research stresses the importance of SCM scholars being aware of the underlying assumptions of their research, as these have a remarkable impact on theory building. A combination of empirical insights and philosophical understandings makes it possible to reflect on the underlying concepts of SCM, providing suggestions for reimagining SCM.

The contribution of the research is twofold. First, the paper presents an original view on SCM, as the thought experiment is introduced as an approach to better understand SCM concepts. By challenging the underlying assumptions with political philosophy, researchers will be better equipped to address grand challenges in the twenty-first century. Second, this is exemplified by the case study of the coffee supply chain, which provides the reader with insight into the dynamics of supply chains with prevalent power differences.

Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.

This research offers clarity regarding process supply chain integration through two deliverables: (1) developing six constructs (both integrative mechanisms and integrative practices for internal, customer, and supplier integration); and (2) empirically testing a theoretically grounded supply chain process model using three distinct datasets (internal, customer, and supplier integration).

The construct development procedure involved a continuous improvement cycle for identifying 1,450 items previously used to measure internal, customer, and/or supplier integration constructs; classifying the items into one of six categories; and refining the instruments based on pilot data and peer feedback. Three surveys (targeted key informants based on their specialized knowledge on internal, customer, or supplier integration) were disseminated for evaluating the measurement instruments and testing the theoretically grounded supply chain management process models, by performing the Covariance-Based Structural Equation Modeling (CB-SEM) analysis technique.

The findings revealed consistencies across all three dimensions of supply chain integration where integrative mechanisms and integrative practices are distinct constructs; integrative mechanisms make it possible for integrative practices and supply chain orientation to occur in a supply chain company; and integrative practices and supply chain orientation improve business performance.

Our study contributes to answering how process-oriented supply chain management occurs, responding to calls for research in the supply chain management discipline and advancing theory development around supply chain integration. The theoretical and managerial contributions of developing six constructs and testing three supply chain management process models relate to identifying the specific aspects of supply chain integration that improves business performance. The three tested models also reveal both direct and mediating effects of integrative practices and supply chain orientation, which contributes to the practical understanding of effective supply chain management implementation.

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.