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This study provides new insights into antecedents and outcomes of reverse logistics practices by examining green customer salience as the driver of reverse logistics practices and examining environmental performance and green firm reputation as the outcomes of reverse logistics practices.

A research model examining the proposed relationships was developed and tested using data from beverage manufacturers in Ghana. The model was analysed using partial least squares structural equation modelling.

This study confirmed that green customer salience drives reverse logistics practices. It was also revealed that reverse logistics directly enhances environmental performance, but not green firm reputation. Additionally, the effect of reverse logistics on green firm reputation was fully mediated through environmental performance.

To the best of the authors’ knowledge, no previous studies have empirically examined the relationship between green customer salience, reverse logistics, environmental performance and green firm reputation.

Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.

This study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.

The findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.

Given the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.

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.

This study aims to investigate the various systems in logistics industry of Pakistan through the lens of the World Bank's logistics performance indicators (LPI) and understand their impact on the China–Pakistan economic corridor (CPEC) that is a vital part of China's belt and road initiative (BRI).

In this study thematic analysis was performed on twenty-three semi-structured interviews with experts in Pakistan's logistics and supply chain sector to gain an in-depth insight into the logistics performance relative to CPEC.

A performance gap exists in the logistics systems in Pakistan, both for hard and soft infrastructure. The significant challenges are the inefficiencies of the government, minimal use of information and computing technology (ICT), and an incapable workforce. It is essential to be cognizant of the ground realities and amendments required in the existing policies and practices in light of the challenges faced and best practices adopted by developed and developing countries with good standing in logistics performance. This study will guide policymakers and practitioners for hard and soft logistics infrastructure improvement, which may benefit economic corridors in general and CPEC in particular.

This study contributes to the existing literature by highlighting the role of ICT in improving both soft and hard logistics infrastructure, which can lead to significant development of economic corridors. The study makes use of a case study of the CPEC to demonstrate the lack of ICT can hamper the growth of an economic corridor despite billions of dollars of investment in the hard infrastructure development projects.

This study aims to investigate and classify the hospital logistics key performance indicators (KPIs) using the context of public hospitals in remote areas.

The public hospitals in northern Thailand were selected for the case study. The questionnaire was developed and used to collect data from hospital logistics experts. Then, the analytic hierarchy process (AHP) method was used to evaluate the hospital logistics KPIs in each dimension.

This research found that the procurement management dimension is ranked highest. Information and technology management is the last rank in the hospital logistics KPIs used for public hospitals in remote areas.

The public hospitals located in northern Thailand were selected for the case study. Fuzzy multi-criteria decision-making methods can be used to reduce the vagueness of the values.

The results from this study can be a guideline for hospitals to improve the efficiency of their logistics operations.

The decision-makers in the hospital can use these results to improve the hospital’s logistics performance in the future, which could help increase the service level and the safety of the patients.

The hospital logistics KPIs were revised, and the crucial KPIs were prioritized for improving the hospital logistics using the AHP method.

The aim of this research is to underscore the pivotal role of warehouse management in the current turbulent global landscape exacerbated by the confluence of a health crisis and geopolitical instability in Europe. In today's interconnected global economy, the turbulence of the global supply chain causes a lack of its resilience among companies. Facing this critical crisis context, companies are refocusing on business processes and outsourcing support processes such as logistics. In this paper we have empirical and methodological objectives. Methodologically, we employ a qualitative research approach utilizing action research in a collaborative framework that involves academics and practitioners. The purpose of this methodology is to empirically investigate warehouse outsourcing as a solution for enhancing a company's performance and agility within the crisis context.

The authors’ action research based on case study approach is conducted through an immersion within the ALCL French multinational company located in Morocco. The authors mobilize the theory of constraints, which allows us to set up a process of identification and optimization of managerial constraints (Goldratt, 1990). The approach allows to set up a retroactive loop to increase the performance of the constraint.

The study shows that ALCL has a storage over-dimension constraint due to the decrease of physical flows caused by the global crisis. The results of action research protocol show that the optimization of warehousing constraint is achieved by the total outsourcing of the process.

The study provides new insights into how action research can improve management practices within companies and explore concrete solutions to the logistical challenges faced by businesses.

The purpose of this study is to identify the factors that create value for the customer in the area of e-commerce logistics and to verify whether these factors impact online retailers' performance through customer satisfaction and customer loyalty in a business to customer (B2C) area.

For the purpose of the study, a model of logistics value in e-commerce was introduced. The model was proposed based on the literature review. A total of 592 correctly filled questionnaires from telephone and web interviews [computer-assisted telephone interview (CATI) and computer-assisted web interview (CAWI)] were studied. The exploratory factor analysis (EFA) and structural equation modeling (SEM) were conducted in the study.

It was confirmed that four of five defined logistics value dimensions have positive impact on customer satisfaction. These dimensions are communication of delivery status, convenience of receipt, reception experience and convenience of return. The influence of speed of delivery on customer satisfaction was not confirmed. It was also confirmed that customer satisfaction has a positive impact on customer loyalty and that customer loyalty positively impacts online retailers' performance.

The study contributes to the current understanding of the influence of logistics factors on online retailers' performance through customer satisfaction and customer loyalty. There have been few studies that concern logistics value in e-commerce, with particular emphasis on above-mentioned relations. It is especially an important issue due to the fact that logistics can potentially lead to gain a competitive advantage in e-commerce.

This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an e-commerce company.

A case study approach is used to document the company’s experience, with interviews of key stakeholders and integration of obtained evidence with secondary data.

The paper presents an algorithm and a system to support a more efficient and smart management of reverse logistics based on a set of anticipatory actions, and continuous and automatic monitoring of returned goods. Improvements are described in terms of a number of key performance indicators.

The analysis and the developed system need further applications and validations in other organizational contexts. However, the research presents a roadmap and a research agenda for the reverse logistics transformation in Industry 4.0, by also providing new insights to design a multidimensional performance dashboard for reverse logistics.

The paper describes a replicable experience and provides checklists for implementing similar initiatives in the domain of reverse logistics, in the aim to increase the company’s performance along four key complementary dimensions, i.e. time savings, accuracy, completeness of data analysis and interpretation and cost efficiency.

The main novelty of the study stays in carrying out a classification of anomalies by type and product category, with related causes, and in proposing operational recommendations, including process monitoring and control indicators that can be included to design a reverse logistics performance dashboard.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

This study examines the relationship between trust, the investment model and logistics performance and the importance of commitment between companies in the supply chain. Furthermore, it analyzes satisfaction, quality of alternatives, investment size and commitment level, which are the constituent factors of the investment model, and reviews trust and logistics performance to ascertain their causal relationship.

The authors examined employees working in supply chain-related departments in Korean companies and further conducted an online survey for a month in January 2022 through the survey agency Entrust Survey, through which the authors distributed a total of 4,082 questionnaires and collected and used a total of 300 questionnaires for statistical analysis. The authors then validated the hypotheses using SPSS 18.0 and AMOS 18.0 using the structural equation modeling method.

The results showed that trust significantly and positively affects satisfaction levels in the relationship between companies in the supply chain. Trust can lower uncertainty in the transaction process between companies.

In this study, the investment model, which has been predominantly observed in the field of family psychology, was applied to business studies. In addition, the investment model was extended to enable its application to supply chain management research, thereby offering a distinctive research model from preceding studies.