Sustainable supply chain management under big data: a bibliometric analysis

Mapping sustainable supply chain innovation: A comprehensive bibliometric analysis

This comprehensive bibliometric study investigates Sustainable Supply Chain Innovation (SSCI) research, examining its evolution, identifying key contributors, and unveiling emerging trends. Analyzing 1158 English-language SSCI articles using the robust Scopus dataset exposes noteworthy journals, authors, institutions, and global contributions. The findings suggest a consistent increase in research output since 1999, with a notable surge in the past decade. Network analysis and density-based spatial clustering identified six SSCI research clusters: Sustainability and Responsibility in Business, Navigating Innovation and Disruption, Sustainable Business Strategies, Environmental Sustainability and Innovation, Sustainable Food Systems and Environmental Impact, and Sustainable Business Dynamics. These clusters highlight the diverse nature of the evolving Sustainability and Supply Chain Management (SCM) field, contributing to a thorough understanding of the SSCI research landscape and emphasizing interconnections between sustainability and SCM themes, potentially leading to more comprehensive theoretical models. Furthermore, this understanding aids businesses in anticipating emerging trends and implementing optimal practices in SSCI. Moreover, recognizing active institutions and global contributors provides practical insights for fostering strategic collaborations.

Linking big data, sustainable supply chain management and corporate performance: the moderating role of circular economy thinking

Purpose

This paper aims to assess how big data–driven supply chain management (BDSCM) influences sustainable supply chain management (SSCM) to achieve sustainable corporate performance (SCP) for small and medium-sized enterprises (SMEs) in an emerging economy such as Vietnam, besides exploring whether Circular Economy Thinking Application (CETA) moderates the relationship between BDSCM and SSCM.

Design/methodology/approach

This study collected survey data from 495 SMEs in the food supply chain sector. It employed the PLS-SEM (Partial Least-Squares Structural Equation Modeling) technique to evaluate the hypothesized relationships.

Findings

This study found that BDSCM positively, directly and indirectly, impacted SCP. SSCM partially mediated the correlation between BDSCM and SCP. Additionally, CETA moderated the relationship between BDSCM and SSCM. CETA had a direct and positive effect on SSCM.

Originality/value

The insights into how BDSCM influences SSCM to achieve SCP for SMEs in the food value chain in an emerging economy like Vietnam provides an original value. Moreover, the novelty of this study is further reinforced by the coverage of the newfound mechanism, where CETA moderates the relationship between BDSCM and SSCM, directly and positively enhancing SSCM. These contributions could interest business practitioners and academics.

Exploring trade-offs between basic and advanced sustainable supply chain practices among consumer electronics: a social media analytics approach

Purpose

This study explores the sustainable supply chain trade-offs in the electronics industry.

Design/methodology/approach

The study employs a social media analytics approach and analyses Twitter posts from August 2017 to December 2021. Thematic analysis is applied to discover the pattern in sustainable supply chain trade-offs based on the consumers' perceptions. In addition, a chi-square test was used to measure whether a relationship exists between product groups and sustainable supply chain perceptions.

Findings

The results indicate that environmental practices are the most frequent topic among consumers on social media. Further, although basic sustainable supply chain practices are prioritised in the environmental aspect, advanced sustainable supply chain practices take precedence over basic ones in the social dimension. The result from the chi-square independence test reveals that there is no significant relationship between different products and perceptions of consumers except for economically advanced sustainable supply chain practices.

Practical implications

The main implications of the present study are to offer a fast and efficient method to marketers and companies for discovering customer perceptions. In a way, they can identify where the quality of practices needs to improve in their supply chains to gain customer satisfaction. Additionally, the authors suggest industries declare their trade-off preferences between sustainable supply chain practices transparently.

Originality/value

The findings extend the abundance of sustainable supply chain literature by identifying the sustainable supply chain trade-offs among consumer electronics. Also, the reason for customers' dissatisfaction is provided. In the end, six propositions are presented based on the explorations.

Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis

Sustainable development emergent subfields have been rapidly evolving, and their popularity increased in recent years. Sustainable development is a broad concept having numerous sub-concepts including, but not limited to, circular economy, sustainability, renewable energy, green supply chain, reverse logistics, and waste management. This polymorphism makes decision-making in this field to be an abstruse task. In this perplexing circumstance, the presence of VUCA conditions makes decision-making even more challenging. By taking advantage of artificial intelligence tools and approaches, this paper aims to study with a concentration on sustainable development-related decision-making under VUCA phenomena elements using bibliometric and network analyses which can propose numerous novel insights into the most recent research trends in this area by analyzing the most influential and cited research articles, keywords, author collaboration network, institutions, and countries that finally provides results not previously fully comprehended or assessed by other studies on this topic. In this study, an extensive systematic literature review and bibliometric analysis are conducted using 534 research articles out of more than 3600. From the content analysis part, four clusters have been found. The decision parameters, presumptions, and research goal(s) for each model are pointed out too. The findings contribute to both conceptual and practical managerial aspects and provide a powerful roadmap for future research directions in this field, such as how real-life multidimensionality can be considered in sustainable development-related decision-making, or what are the effects of the VUCA in sustainable development considering the circular economy and waste management intersection.

Big data driven innovation for sustaining SME supply chain operation in post COVID-19 scenario: Moderating role of SME technology leadership

Due to the COVID-19 pandemic, there is an unprecedented crisis for businesses. The small and medium enterprises (SMEs) have been impacted even more, due to their limited resources. Extant literature has prescribed many treatments on how SMEs could survive in post COVID-19 situation, but studies did not analyse how big data driven innovation could improve supply chain management (SCM) process in the post COVID-19 pandemic under the moderating influence of SME technology leadership support. Thus, there is a research gap in this important domain. The aim of this study is to examine the impact of big data driven innovation and technology capability of the SME on its supply chain system. The study also investigates the moderating role of SME technology leadership support on SME performance in the post COVID-19 scenario. With the help of literature and resource-based view (RBV) and dynamic capability view (DCV) theory, a theoretical model has been developed conceptually. Later the model is validated using structural equation modelling (SEM) technique with 327 usable respondents from SMEs from India. The study found that both big data driven innovation and the techno-functional capability of SME impacts supply chain capability which in turn impacts the SME performance in the post COVID-19 scenario. The study also finds that there will be a moderating impact of SME technology leadership support on SME performance.

Digital Innovation, Data Analytics, and Supply Chain Resiliency: A Bibliometric-based Systematic Literature Review

In recent times, the literature has seen considerable growth in research at the intersection of digital innovation, data analytics, and supply chain resilience. While the number of studies on the topic has been burgeoning, due to the absence of a comprehensive literature review, it remains unclear what aspects of the subject have already been investigated and what are the avenues for impactful future research. Integrating bibliometric analysis with a systematic review approach, this paper offers the review of 262 articles at the nexus of innovative technologies, data analytics, and supply chain resiliency. The analysis uncovers the critical research clusters, the evolution of research over time, knowledge trajectories and methodological development in the area. Our thorough analysis enriches contemporary knowledge on the subject by consolidating the dispersed literature on the significance of innovative technologies, data analytics and supply chain resilience thereby recognizing major research clusters or domains and fruitful paths for future research. The review also helps improve practitioners' awareness of the recent research on the topic by recapping key findings of a large amount of literature in one place.

Examining the trend of humanitarian supply chain studies: pre, during and post COVID-19 pandemic

Purpose

This research aims to shed light on the trend of humanitarian supply chain (HSC) studies in the era of pre, during and post coronavirus disease 2019 (COVID-19) pandemic outbreaks. This study provides comprehensive bibliometric mapping published in the 21 top vintage sources globally providing detailed metadata on HSC articles. The manuscript objectives are threefold: to explore the documents that are published in the field of humanitarian logistics and supply chain; second, to identify details of articles in humanitarian logistics and supply chain and thirdly, to explore research the critical area published in the HSC in pre, during and post era of pandemic COVID-19.

Design/methodology/approach

This research adopts bibliometric analysis of HSC studies using the Biblioshiny, a shiny app for the Bibliometrix R package. The tool employed in this study decodes the data extracted from the Scopus database to various visualized forms. The review of the HSC studies in this research covers all related publications from 2006 to early 2022. The record of the article was scanned and refined accordingly.

Findings

A multi perspectives of HSC studies were explored, discussed and identified. The bibliometric analysis findings offer significant information on the current and future trend publications in the area of humanitarian logistics and supply chain. Additionally, it also provides significant information on the highly cited documents in humanitarian logistics and supply chain studies, most productive contributors, keywords analysis findings, most productive countries and sources, network analysis data on co-occurrence network and themes mapping information in the field of humanitarian logistics supply chain before and after pandemic COVID-19.

Research limitations/implications

A multi-perspective of HSC studies was explored only within the online Scopus database. It excludes other articles published in other databases. Future research could explore related articles published in other recognized databases.

Practical implications

Practitioners can use multi perspectives findings from pre, during and post-pandemic COVID-19 issues discussed in this paper to get new insight and perception of the issue to facilitate their current and future operation and strategy.

Originality/value

To the best of the researchers’ knowledge, this is the first bibliometric study to analyze the trend of HSC studies using Biblioshiny focusing on pre, during and post COVID-19 pandemic. The review highlights annual publication trends, most productive authors, most cited papers, most productive countries, most productive institutions and most productive sources, which leads to a number of future research agendas for future studies.

Theoretical Perspectives on Sustainable Supply Chain Management and Digital Transformation: A Literature Review and a Conceptual Framework

In an era where environmental and social pressures on companies are increasing, sustainable supply chain management is essential for the efficient operation and survivability of the organizations (members of the chain). Digital transformation and the adoption of new technologies could support the development of sustainable strategies, as they support supply chain processes, decrease operational costs, enable control and monitoring of operations and support green practices. The purpose of this paper is to explore the relationship between sustainable supply chain management and digital transformation through the adoption of specific technologies (Blockchain technology, big data analytics, internet of things). It aims at theory building and the development of a conceptual framework, enabling the explanation of under which circumstances the above combination could lead to the development of sustainable performances. It also aims to examine how companies can increase their competitive advantage and/or increase their business performance, contributing both to academics and practitioners. After conducting a literature review analysis, a significant gap was detected. There are a few studies providing theoretical approaches to examining all three pillars of sustainability, while at the same time analyzing the impact of big data analytics, internet of things and blockchain technology on the development of sustainable supply chains. Aiming to address this gap, this paper primarily conducts a literature review, identifies definitions and theories used to explain the different pillars of flexibility, and examines the effect of different technologies. It then develops a theoretical conceptual framework, which could enable both academics and practitioners to examine the impact of the adoption of different technologies on sustainable supply chain management. The findings of this research reveal that digital transformation plays an important role to companies, as the combination of different technologies may lead to the development of significant capabilities, increasing sustainable performances and enabling the development of sustainable strategies, which can improve companies’ position in the market.

Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework

In the face of global competition, competitive enterprises should pursue sustainable development, and strengthen their supply chain resilience to cope with risks at any time. In addition, big data analysis has been successfully applied in a variety of fields. However, the method has not been applied to improve supply chain resilience in order to reduce sustainable supply chain risks. An approach for enhancing the capabilities of big data analytics must be developed to enhance supply chain resilience, and mitigate sustainable supply chain risks. In this study, a decision framework that integrates two-stage House of Quality and multicriteria decision-making was constructed. By applying this framework, enterprise decision-makers can identify big data analytics that improve supply chain resilience, and resilience indicators that reduce sustainable supply chain risks. A case study of one of China’s largest relay manufacturers is presented to demonstrate the practicability of the framework. The results showed that the key sustainable supply chain risks are risks regarding the IT infrastructure and information system efficiency, customer supply disruptions, transport disruptions, natural disasters, and government instability. To reduce risk in sustainable supply chains, enterprises must improve the key resilience indicators ‘financial capability’, ‘flexibility’, ‘corporate culture’, ‘information sharing’, and ‘robustness’. Moreover, to increase supply chain resilience, the following most important big data analysis enablers should be considered: ‘capital investment’, ‘building big data sharing mechanism and visualisation’, and ‘strengthening big data infrastructures to support platforms and systems’. This decision framework helps companies prioritise big data analysis enablers to mitigate sustainable supply chain risks in manufacturing organisations by strengthening supply chain resilience. The identified priorities will benefit companies that are using big data strategies and pursuing supply chain resilience initiatives. In addition, the results of this study show the direction of creating a fruitful combination of big data technologies and supply chain resilience to effectively mitigate sustainable risks. Despite the limited enterprise resources, management decision-makers can determine where big data analysis enablers can be most cost-effectively improved to promote risk resilience of sustainable supply chains; this ensures the efficient implementation of effective big data strategies.

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions.

Integrating Industry 4.0 and circular economy: a review

Purpose

Industry 4.0 and circular economy are the two major areas in the current manufacturing industry. However, the adoption and implementation of Industry 4.0 and circular economy worldwide are still in the nascent stage of development. To address this gap, the purpose of this article is to conduct a systematic literature review on integrating Industry 4.0 and circular economy. Further, identify the research gaps and provide the future scope of work in this area.

Design/methodology/approach

Content-based analysis was adopted for reviewing the research articles and proposed a transition framework that comprises of four categories, namely, (1) Transition from Industry 3.0 to Industry 4.0 and integration with circular economy; (2) Adoption of combined factors and different issues; (3) Implementation possibilities such as front-end technologies, integration capabilities and redesigning strategies; (4) Current challenges. The proposed study reviewed a total of 204 articles published from 2000 to 2020 based on these categories.

Findings

The article presents a systematic literature review of the last two decades that integrates Industry 4.0 and circular economy concepts. Findings revealed that very few studies considered the adoption and implementation issues of Industry 4.0 and circular economy. Moreover, it was found that Industry 4.0 technologies including digitalization, real-time monitoring and decision-making capabilities played a significant role in circular economy implementation. The major elements are discussed through the analysis of the transition and integration framework. The study further revealed that a limited number of developing countries like India have taken preliminary initiatives toward Industry 4.0 and circular economy implementation.

Research limitations/implications

The study proposes a transition and integration framework that identifies adoption and implementation issues and challenges. This framework will help researchers and practitioners in implementation of Industry 4.0 and circular economy.

Originality/value

Reviews of articles indicated that there are very few studies on integrating Industry 4.0 and circular economy. Moreover, there are very few articles addressing adoption and implementation issues such as legal, ethical, operational and demographic issues, which may be used to monitor the organization's performance and productivity.

Industry 4.0, Disaster Risk Management and Infrastructure Resilience: A Systematic Review and Bibliometric Analysis

The fourth industrial era, known as ‘Industry 4.0’ (I4.0), aided and abetted by the digital revolution, has attracted increasing attention among scholars and practitioners in the last decade. The adoption of I4.0 principles in Disaster Risk Management (DRM) research and associated industry practices is particularly notable, although its origins, impacts and potential are not well understood. In response to this knowledge gap, this paper conducts a systematic literature review and bibliometric analysis of the application and contribution of I4.0 in DRM. The systematic literature review identified 144 relevant articles and then employed descriptive and content analysis of a focused set of 70 articles published between 2011 and 2021. The results of this review trace the growing trend for adoption of I4.0 tools and techniques in disaster management, and in parallel their influence in resilient infrastructure and digital construction fields. The results are used to identify six dominant clusters of research activity: big data analytics, Internet of Things, prefabrication and modularization, robotics and cyber-physical systems. The research in each cluster is then mapped to the priorities of the Sendai framework for DRR, highlighting the ways it can support this international agenda. Finally, this paper identifies gaps within the literature and discusses possible future research directions for the combination of I4.0 and DRM.

The Nexus between Big Data and Sustainability: An Analysis of Current Trends and Developments

With the development of technological innovations, Big Data is transforming the socio-economic world, impacting almost every organization and person. The transformations associated with the development of Big Data have important consequences for the sustainability of organizations, regions, and the society as a whole, and as such, they have been specifically addressed by the academic literature focusing on sustainability. Despite its importance, and perhaps because of its rapid emergence, there is a lack of studies dealing with the analysis of this body of literature and its trends. The current research attempts to fill this gap. The study develops a bibliometric and visualization analysis of the literature on the nexus between Big Data and Sustainability. The research analyzes 726 documents on this topic, published until the end of 2020, in the Web of Science Core Collection database through the VOSviewer software. The results indicate the main trends and developments on the topic related to the most cited papers, authors, publications, institutions, and countries. The visualized frameworks, structures and trends are useful for both researchers and practitioners, as they can help them understand the current situation, issues to consider, and main developments on the topic.

Off-office audit of natural resource assets and water pollution: a quasi-natural experiment in China

Purpose

The purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.

Design/methodology/approach

This study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.

Findings

The implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.

Practical implications

These findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.

Originality/value

This study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

Worldwide Research on Socio-Hydrology: A Bibliometric Analysis

The technical and scientific analysis regarding studies of the water surface or groundwater has increasingly taken on a great social impact, which has led to the creation of the term socio-hydrology. Since decision making has a greater weight, considering the social perspective, its study has become more important in the past 20 years. This article aims to carry out a bibliometric analysis related to socio-hydrology using the Scopus database and the application of VOSviewer software for the evaluation of the intellectual structure of socio-hydrology, its conceptual evolution, and its tendencies. The methodology considers (i) search criteria of the research field, (ii) search and document selection, (iii) software and data extraction, and (iv) analysis of results and trends. The results show us the term socio-hydrology as a new scientific discipline that has traces in the Scopus database in the past two decades. However, its application stems from recognising ancestral knowledge alongside other forms of knowledge. Socio-hydrology practice requires participatory models, where the community has a great influence, and for the most part, it guarantees results for the common good. The trend of this topic is growing and open to the criteria of sustainability.

Research Trends in Career Success: A Bibliometric Review

The purpose of this article is to provide an overview of academic research on professional success, using the bibliometric analysis to understand the evolution of this field between the years 1990 and 2020. The information was obtained from the publications indexed in the Scopus database, under a rigorous bibliometric process that comprises five parts: (i) criteria search of the field, (ii) selection of database and documents, (iii) inclusion and selection criteria, (iv) software and data selection, and (v) analysis and results. The results show professional success as a scientific discipline in full exponential growth, which allows us to consider the main contributions of authors, institutions, and international contributions, as well as to consider the main themes that have shaped the intellectual structure of the subject through their visualization using bibliometric maps of co-citation and co-occurrence, which combined showed eight main lines of research. The results obtained allowed us to identify patterns of convergence and divergence in various topics, which allows obtaining current and diverse information on the state of the research field’s art.

Applying Industry 4.0 technologies in the COVID–19 sustainable chains

Purpose

The purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0 technological innovations that interact between the real and virtual worlds and that are applied in the sustainable supply chain process; 2) to contribute to the identification of the opportunities, the challenges and the gaps that will support the new research study developments and 3) to analyze the impact of the Industry 4.0 technologies as facilitators of the sustainable supply chain performance in the midst of the Coronavirus (COVID-19).

Design/methodology/approach

This research is performed through a bibliographic review in the electronic databases of the Emerald Insight, the Scopus and the Web of Science, considering the main scientific publications on the subject.

Findings

The bibliographic search results in 526 articles, followed by two sequential filters for deleting the duplicate articles (resulting in 487 articles) and for selecting the most relevant articles (resulting in 150 articles).

Practical implications

This article identifies the opportunities and the challenges focused on the emerging Industry 4.0 theme. The opportunities can contribute to the sustainable performance of the supply chains and their territories. The Industry 4.0 can also generate challenges like the social inequalities related to the position of the man in the labor market by replacing the human workforce with the machines. Therefore, the man-machine relationship in the Industry 4.0 era is analyzed as a gap in the literature. Therefore, as a way to fill this gap, the authors of this article suggest the exploration of the research focused on the Society 5.0. Also known as “super-smart society,” this recent theme appeared in Japan in April 2016. According to Fukuda (2020), in addition to the focus on the technological development, the Society 5.0 also aims at the quality of life and the social challenge resolutions.

Originality/value

This article contributes to the analysis of the Industry 4.0 technologies as facilitators in the sustainable supply chain performance. It addresses the impacts of the Industry 4.0 technologies applied to the supply chains in the midst of the COVID-19 pandemic, and it analyzes the research gaps and limitations found in the literature. The result of this study can add value and stimulate new research studies related to the application of the Industry 4.0 technologies as facilitators in the supply chain sustainable performance. It can encourage the studies related to the COVID-19 impacts on the sustainable supply chains, and it can promote the research development on the relationship among the man, the machine and the labor in the Fourth Industrial Revolution.