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Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

Nowadays, the main problem of industries is the issue of environmental pollution. The green supply chain (GSC) is one of the processes that can be effective to consider this issue and its practices in all working processes in every organizations, so that the concept of GSC has been emerged with the acceleration of the government regulations and rules to achieve environmental standards and the increasing demands of consumers to supply green products. Therefore, the organizations should move toward the development of environmental activities in today’s turbulent world. In other words, the current organizations should consider making their supply chain more agile and green to survive in the competition arena or in other words, they should consider making agile the GSC. The necessity of considering this issue needs to identify the evaluating indicators of the agility of the GSC. This study aims to consider this issue.

With reviewing the research literature and having survey with the experts, totally 7 criteria and 37 sub-criteria were identified as the evaluating indicators of the agility of the GSC. The results from collecting research data and using the confirmatory-factor analysis suggest the suitability of the above-mentioned indicators.

The idea of the GSC is to remove or minimize the greenhouse, chemical/hazardous gases and waste throughout the supply chain. On one hand, the agility of the supply chain as an operational capability in quick response to the uncertain and turbulent markers not only improves the performance of the company but also leads to cost decrease and increase of the professional capabilities. Therefore, the organizations should step toward the development of the environmental activities in the today’s turbulent world. The importance of the issue of agility and considering the environment in the supply chain double the necessity of identification of the factors of agility of the GSC.

The present research considers the identification of the evaluating indicators of the agility of the GSC in industries.

This paper aims to illuminate the nuanced dynamics of green supply chain management (GSCM), specifically focusing on the intersections of supplier relationships, supplier governance and organizational agility. Recognizing a gap in the understanding of how these elements confluence to promote green purchasing, the paper uses a quantitative study on data collected from the Australian food industry. Advanced analysis techniques provide empirical evidence underscoring the pivotal roles these elements play, expanding on current GSCM literature within a resource-based view.

This study, based on a questionnaire sent to Australian food professionals, used higher-order reflective constructs to assess supplier relationships and governance. Data was analyzed using partial least squares structural equation modeling and Hayes PROCESS, considering factors like firm revenue and manager experience. Both the reliability of measures and mediation hypotheses were stringently validated using established guidelines.

The comprehensive study validated supplier governance's key influence on green purchasing and supplier relationships. Notably, organizational agility emerged as a crucial mediator, underscoring the interplay of these constructs. Concurrently, the reflective measurement model exhibited robust validity and reliability. Interestingly, demographic factors such as company size, revenue and managerial experience showed no discernible impact on green purchasing practices.

In the Australian food sector, supplier governance and relationships are pivotal for advancing green purchasing. This study emphasizes the value of organizational agility in amplifying these practices. Managers, when aligning with supplier relationships enhanced by communication and mutual aid, can foster robust green initiatives. Embracing these insights and the critical importance of supplier governance, managers can drive more sustainable, informed supply chain decisions in the industry.

In pursuit of understanding the relationship between supplier governance, supplier relationships and green purchasing, this research uniquely situates itself within the resource-based view (RBV) to reveal critical theoretical and practical implications. By focusing on the Australian food industry, the study spotlights the often-overlooked mediating role of organizational agility in linking supplier relationships with green purchasing efforts. In doing so, this research not only strengthens the argument for fortified supplier relationships – as a catalyst for enhancing agility and thereby green practices – but also re-contextualizes the RBV in a fresh light. This new perspective provides managers with an enriched model, emphasizing the imperative of solid supplier governance for sustainable, agile and green supply chain operations in the food domain.

Today's businesses are facing a world that is more complex, turbulent and unpredictable than in the past with increasing levels of environmental complexity. Rather than proposing environmental uncertainty as a mediator/moderator of the relationship between agility and performance as others have done, the authors offer an alternative view where supply chain agility is seen as mediating the relationship between environmental uncertainty and supply chain performance.

The authors propose that supply chain agility is a response to the effects of environmental uncertainty and, as such, environmental uncertainty should be seen as a driver of supply chain agility. Few studies test the direct relationship between uncertainty and supply chain performance, and none simultaneously test for agility's mediation and moderation effect between environmental uncertainty and agility.

The model was statistically assessed using partial-least-squares structural equation modeling (PLS/SEM) by analyzing survey data from manufacturing managers in 136 US firms. The study results did not indicate a significant relationship between environmental uncertainty and supply chain performance. However, the authors did find a significant positive relationship between agile manufacturing and supply chain performance using measures that were primarily operations-centered rather than financial. Additionally, the authors found that agile manufacturing fully mediates the relationship between environmental uncertainty and supply chain performance.

The authors’ model, though simple, provides a base for future research for them and other researchers who can incorporate other impacting variables into the model. The study results show that uncertainty can be a force for good and that utilizing agile manufacturing can be a new source of opportunity.

The purpose of this paper is to contribute to the existing knowledge system of lean supply chain management (LSCM), i.e. by using main path analysis, and the authors extract the main development track of LSCM. It is advantageous for relevant scholars to deepen their understanding of this academic field from a bibliometrics view to grasp the future directions better.

Structuring a citation network with the processed data set containing 866 papers and relevant information collected from Web of Science (WoS). Conducting review analyses aiming at the main paths that are extracted from the above citation network.

There are two different evolution paths in LSCM field, i.e. improving corporate sustainability performance through combining lean and green practices, and seeking the balance between lean and agility to structure leagile supply chain for specific industries. LSCM research studies mainly focus on five aspects: (1) establishment and development of LSCM theory; (2) structuration of lean supply chain; (3) research studies of the relationship between LSCM and corporate performance; (4) supply chain evaluation system; and (5) review and vista of LSCM field. The intersection of two knowledge evolute routes would be Industry 4.0, which is an integrated theory system combining lean, agility, green and other supply chain thinking.

The data set collected from WoS cannot contain all the research studies about LSCM is the main research limitation. Sustainability, as represented by environmental performance, will continue to be a major pursuit of this field. Integrating LSCM in Industry 4.0 will be the next hotspot in LSCM field.

Providing the main research contents and common methods of LSCM field. It is conducive to deepening the understanding of relevant practitioners and scholars to LSCM field from a dynamic perspective.

To the best of the authors’ knowledge, it is the first time to reveal the knowledge diffuse trajectories of LSCM under different view with main path analysis. This study is unique that it provides a new view to understand the field of LSCM.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Supply chain agility (SCA) is the primary strategy for reducing impacts and quick recovery when supply chains experience a disruption risk, such as the COVID-19 pandemic. This study will investigate how SCA can be achieved through supply chain information sharing (SCIS) under the different dependence relationships (DR) with suppliers or customers. The purpose of this paper is to investigate this issue.

Based on information process and resource dependency theories, this study constructs and empirically tests a proposed model of the relationships amongst the three dimensions of SCIS and the two areas of SCA and the contingency effects of two types of DR on those relationships. Using a dataset collected from 400 manufacturers in China, the authors tested this theoretical model using multi-group and structural path analysis.

The results of the structural path and multi-group analyses show that (1) all dimensions of SCIS are positively correlated with both areas of SCA and (2) dependence on the supplier and dependence on the customer have completely different impacts on the relationship between SCIS and SCA.

This study can improve the understanding of the multidimensional concepts of SCIS and SCA and relationships between them under two different DR conditions in the Chinese manufacturing setting. It contributes to IS and the SCA literature and provides theoretically driven and empirical explanations for the diverse dynamics between the dependence on the supplier and customer.

This paper aims to explore the divergences and commitments between the lean, agile, resilient and green paradigms while investigating the effect of paradigms' practices within supply chain attributes.

A conceptual model with lean, agile, resilient and green practices and supply chain management attributes is proposed. Causal diagrams were used to represent the relationships between paradigm practices and supply chain attributes. The four diagrams were aggregated to build the conceptual model.

The conceptual model allows for the identification of synergies and divergences resulting from the paradigms practices implementation. The synergies between paradigms are related to “information frequency” and “integration level” increasing as well as reduction of “production lead time” and “transportation lead time”. However, other supply chain attributes such as “capacity surplus”, “inventory level” and “replenishment frequency” are affected in opposite directions by some paradigms creating divergences.

The model relationships were established using an anecdotal approach derived from the literature review, reflecting only a partial view of supply chain dynamics. More research related to other supply chain attributes and/or paradigm practices, and validation of the proposed relationships is suggested.

The proposed model can be the basis for further research in lean, agile, resilient and green paradigms, contributing to a more sustainable and competitive lean supply chain with the necessary agility toward a quick response, resiliency to disruptions, and harmonization with the ecologic and environmental aspects.

To the authors' knowledge this paper is the first to provide an understanding about the tradeoffs among lean, agile, resilient and green supply chain paradigms.

The current study examines the impact of big data analytics capabilities (BDAC) on supply chain performances of the manufacturing firms. Based on the underpinning of resource-based view (RBV) theory, the current study will highlight the significance of BDAC on green dynamic capabilities (GDC), supply chain agility (SCA) and green competitive advantage (GCA). Furthermore, the study examines the moderating effect of supply chain innovativeness (SCI) on the relationship between GCA and firm performance (FP).

Online survey method was employed for the data collection from the 331 managers employed in Pakistan Stock Exchange (PSX)-listed manufacturing firms. The hypothesized model was tested using partial least squares structural equation modeling (PLS-SEM) technique.

The study results indicate that BDAC has a positive influence on both GDC and SCA, leading to enhanced GCA. Furthermore, the results demonstrate that GCA significantly and positively impacts FP, and the relationship between them is positively moderated by SCI.

This study developed a novel theoretical perspective based on RBV theory and provided empirical evidence that manufacturing firms' performances are significantly influenced by BDAC, GDC and SCA. The study results provide valuable practical implications top management regarding the effectiveness of BDAC and SCA in the supply chain. The findings further highlight the significance of SCI strengthening relationship between GCA and FP.

The purpose of this paper is to present green supply chain, resilient supply chain, agile supply chain, cold supply chain and lean supply chain (GRACL SC) procedures based on a detailed perspective, analyzing subjects in the past 19 years with a systematic literature review (SLR) of the papers reported from 2000 to 2019, and offering information and guidelines for further studies.

This research is based on 17 keywords in the title and topic of the articles and collects data from Web of Science (WOS) databases and objectively chooses 1,190 articles and performs meta-data analyses. Tables and statistical reports are based on the following three filters: publication year, authors and document type. At least, 39 publications from the ISI WOS has been examined for presenting information of categorization of the conducted research with regard to the content analysis, comprising the conceptual development and obstacles, cooperation with the supply chain elements, as well as mathematical and other optimization models.

Finally, this study answered three main questions in the research and demonstrates that the majority studies in the green supply chain (GSC) and a minimum number of studies on the cold supply chain have been conducted and 27 factors are chosen to achieve the 2000 to 2019 GRACL SCM model which robust and fit for Iranian food industries. The model shows that the agile, resilient and lean supply chain have direct effect on GSC and it can be said that all 27 groups which are selected for the final model of this research can be the main groups in the supply chain.

This paper was actually conducted by authors who reported it. To prevent plagiarized, redoubled efforts have been made and actually this paper is based on SLR methodology and the results are real and the researcher discusses the results appropriately. This investigation can have a positive impact within the field of expanding supply chain flexibility and lessening squander within the Iranian generation framework.