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This study aims to identify service quality dimensions for logistics service providers (LSPs) and to examine their relationships with customer satisfaction and customer loyalty.

Service quality dimensions are identified from vast literature review. Customers who take services from LSPs were surveyed to collect data on basis of developed survey instrument. Structural Equation Modelling (SEM) is applied to test the proposed research hypotheses.

The study shows that all the five service quality constructs, i.e. “Operational Quality”, “Resource Quality”, “Information Quality”, “Personnel Contact Quality” and “Customization and Innovation Quality” have direct relationship with customer satisfaction. They also have indirect relationship with customer loyalty, implying the full mediation of customer satisfaction.

The results of the study suggest that the logistics service quality (LSQ) can be measured multi-dimensionally. It provides clear implications to LSPs for improvement of service quality. The present research work is expected to be useful for both, logistics service providers and the customer organizations, which take services from LSPs. LSPs can develop strategies to improve their service quality on basis of findings from this study.

The present research will help in extending the existing literature on service quality in context to LSPs.

This research aims to investigate the relationship between knowledge capabilities, engagement capabilities, operational capabilities and sustainable supply chain flexibility in the steel production industry. In addition, it seeks to understand how these elements contribute toward achieving a net-zero supply chain, under the moderation of industry dynamism.

In total, 371 people have responded to the self-administered survey that the authors developed. The nonresponse bias analysis was carried out before diving into fundamental assumptions, such as homoscedasticity and normality. The data's reliability and construct validity were assessed by using confirmatory factor analysis. The hypothesized conclusions were supported by subsequent regression outputs, strengthening the body of existing academic research.

The research's empirical results highlight the positive relationship among knowledge capabilities, operational capabilities, sustainable supply chain flexibility and net-zero supply chain, particularly under the influence of industry dynamism. Information obtained from the steel production industry corroborates these findings. Moderation role of industry dynamism in the relationship between operational capabilities, engagement capability and sustainable supply chain flexibility was found significant.

This conceptual framework clarifies how knowledge capability, dynamic capabilities and the flexibility of a sustainable supply chain interact. It highlights how these factors collectively work together to attain a sustainable supply chain with net-zero environmental impact.

Supply chain (SC) and knowledge management (KM) have been studied; still, there is a need to understand how KM can be used for SC resilience and improving the firm’s performance. The purpose of the paper is to study and analyze SC resilience strategies based on KM processes to enhance SC performance considering six SC strategies: SC reengineering, collaboration, SC innovation, SC integration, SC agility and SC risk management.

By adopting the dynamic capability theory, the empirical research is conducted on a sample of 312 Indian micro, small to medium enterprises. To evaluate 312 samples, the structural equation modeling approach is adopted.

The study found a is a positive relationship between SC reengineering, SC collaboration, SC integration, SC agility, SC risk management and KM. Nevertheless, the relationship between SC innovation and KM is not significant. This study also found the mediating effect of KM on SC performance, and the results shows that SC reengineering, SC collaboration, SC agility and SC risk management are having complementary mediation, while SC innovation and SC integration did not show any mediation.

This is the only research that integrates resilience strategies and KM for improving SC performance. Using KM, SC reengineering will improve SC performance by enhancing readiness and recovery strategies to avoid SC disruption. KM will improve SC collaboration. It will enhance the SC process’ overall visibility, transparency and so on. Agility leads to increased speed, visibility and flexibility, which aids in dealing with uncertainty in the environment. SCRM entails investments and additional resources (such as equipment and labor) to navigate uncertainty and risks in the SC and improve SC performance.

Food supply chain resilience is a critical aspect in ensuring the continuous and reliable flow of food, particularly in the face of disruptions. This study aims to address specific gaps in the existing literature by conducting a bibliometric analysis. The primary objective is to identify key areas of concern and lacunae related to disruptions and resilience within the food supply chain. The study also strives to contribute to the field by developing a comprehensive framework that evaluates the factors influencing resilience. Furthermore, the research intends to propose effective strategies for mitigating and recovering from disruptions, emphasizing the urgency of these measures in light of identified gaps in the current body of literature.

To achieve these objectives, the authors extracted the most relevant papers from Scopus and Web of Science (WoS) databases. The analysis parameters included a comprehensive review of current food supply chain practices and an exploration of trending research topics, such as sustainability, adaptability, circular economy and agility. Notably, the study recognized the pervasive impact of COVID-19 on food supply chain disruptions, with a high occurrence in the literature. Using advanced analytics tools like VOSviewer and Biblioshiny, the research delved into the role of modern technologies, including Industry 4.0, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML) and blockchain in addressing disruptions and enhancing resilience.

The research reveals a significant impact of the COVID-19 pandemic on food supply chain disruptions, underscoring the critical need for strategies to bolster resilience. Notably, the study identifies the pivotal role of modern technologies (Industry 4.0, IoT, AI, ML and blockchain) in mitigating disruptions and enhancing resilience in the food supply chain. The bibliometric analysis conducted through VOSviewer and Biblioshiny provides valuable insights into research trends and focal areas within the literature.

The observed importance of Industry 4.0, IoT, AI, ML and blockchain implies a practical need for integrating these technologies into food supply chain operations. Moreover, the paper discusses strategies for reducing the impact caused by disruptions, providing practical guidance for resilience planning in food supply chains. Researchers can leverage the findings to direct future efforts toward areas with identified gaps and opportunities, fostering advancements in the field and offering practical insights for real-world applications.

By amalgamating insights from bibliometric analysis and the developed framework, this study contributes to a holistic understanding of the challenges and opportunities in fortifying the resilience of the food supply chain. The identified factors and strategies offer valuable insights for researchers and practitioners seeking to address disruptions in food supply chains. The study’s unique contribution lies in bridging theoretical perspectives with practical applications, enhancing the relevance of business-to-business/industrial supply chain theories.

Sustainable supply chain management (SSCM) concepts have received immense attention in the recent past in both academia and industries. Especially, manufacturing industries in developing countries realize the importance of adopting sustainability concepts in their supply chain. The SSCM adoption has not been to the same level across different manufacturing sectors and hence a single implementation framework will not have the same effect across sectors. This paper aims to compare the adoption level of 25 SSCM practices across three major manufacturing sectors, namely, automobile, electronics and textile, in an emerging economy, India.

A questionnaire-based data collection technique is used to obtain adoption levels of each of the identified SSCM practices on a five-point Likert-type scale with “1” representing not considering presently to “5” indicating successful implementation. Second, a hypothesis is framed and tested to compare the adoption levels across sectors using a one-way single-factor ANOVA followed by a post hoc test by Tukey’s test.

The results derived suggest that though the industries across different sectors are in the course of adopting SSCM practices, the level of adoption is found to be not the same. The textile sector has adopted the least, and the electronic sector edges ahead of the automobile sector in terms of successful transformation to SSCM.

This study focuses on the differences and similarities in the adoption of policies in the automobile, electronics and textile sectors using statistical data analysis tools. A total of 25 individual practices are identified from existing literature and classified into six groups, namely, management, supplier, collaboration, design, internal and society, based on their similarities. Based on a detailed questionnaire survey with industrial experts in relevant fields as respondents, the adoption levels of practices are rated individually and categorically.

This study aims to investigate the synergy between supply chain flexibility and sustainable supply chain management in the manufacturing industry. The study also investigates the roles of leadership practice, knowledge management practice and digital quality management practice in promoting supply chain flexibility that leads to sustainable supply operations from a practice-based perspective.

The authors developed a self-administered questionnaire and distributed it amongst manufacturing executives in India. Data were collected from 347 executives. Before moving on to assumptions, such as constant variance and normality, we have analysed them to check for possible nonresponse bias. Confirmatory factor analysis was employed to check the data’s reliability and consistency. PLS-SEM was used to validate the constructs and verify the hypotheses.

The findings indicate that knowledge practice and digital quality management practice, augmented by effective leadership practice, are positively associated with supply chain flexibility in the manufacturing sector. Further, the findings indicate a positive relationship between flexibility and supply chain sustainability.

The novelty of this study lies in the developed framework, wherein the authors attempted to rope in both flexibility and sustainability measures. The findings bridge a gap in the literature, especially in the context of the manufacturing industry, by demonstrating how leadership, KNP and DQMP collectively influence SCF and, ultimately, supply chain sustainability.

This paper presents a systematic literature review of the various aspects of reverse logistics (RL) and closed-loop supply chains (CLSC) in implementing and achieving circular economy (CE) motives. CE is identified as a method of embracing imperishability into the economic structure, helping shift from a linear to a condition leading to ecological and social benefits.

Systematic literature was used to review a total of 80 peer-reviewed articles are included in the study and covers different concepts related to the implementation of CE, such as cost-saving, network design, sustainable RL, waste management and extended producer responsibility.

The findings reveal that the research in the domain is in a growing phase, and in recent years, a lot of attention has been given by researchers across the globe. However, further research is required in crucial areas for the adoption of CE, such as retail reverse logistics, pharmaceutical industries and resource recycling industry.

The study discusses the business needs and solutions for industries. Key enablers and barriers are listed along with the main activities involved in each sector in CLSC. Managers can design a pathway to decide which lever to use to overcome a particular challenge.

The work contributes theoretically by developing research themes in RL and CLSC practices applied to CE. It also provides theoretical and practical implications of the study, which can be used as a signboard for further research.

Increased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.

In this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.

The identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.

In addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.