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This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

Ineffective management inventory of medical products such as blood and vaccines can create severe repercussions for hospitals, clinics or medical enterprises, such as surgery delays and postponements. Inventory sharing is a form of horizontal collaboration that can provide solutions to key actors of the healthcare supply chain (HSC), yet no prior study reviewed this topic.

This study conducts a systematic literature review of thirty-nine inventory-sharing studies in the context of HSCs published from 2012 until early 2022. The descriptive and thematic analyses include chronological distribution, geographical location, comparison between developed/developing regions, stakeholder and incident analysis.

Thematic analysis classified inventory sharing among five product supply chains (blood, medical supplies, medicines, vaccines and generic medical products). Benefits include shortage reduction, cost minimisation, and wastage mitigation. Barriers include (1) IT infrastructure, (2) social systems, (3) cost and (4) supply chain operations. Perishable inventory policies include Fresher-First (FF), Last-Expire-First-Out (LEFO), First-In-First-Out (FIFO) and First-Expire-First-Out (FEFO). The analysis also showed differences between developed and developing countries. The study identifies several future research opportunities that include (1) product utilisation rate, (2) cost reductions, (3) shortage mitigation and (4) waste reduction.

No prior study has systematically reviewed inventory sharing in HSCs to reveal benefits, barriers, patterns and gaps in the current literature. It makes five propositions and develops a research model to guide future research. The study concludes with theoretical and managerial implications.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

The Indian pharmaceutical industry has contributed significantly to global healthcare by securing superior-quality, inexpensive and reachable medicines worldwide. However, supply chain management (SCM) has been challenging due to constantly shifting requirements for short lifecycles of products, the convergence of industry and changeable realities on the ground. This study aims to identify, assess and prioritize the strengths, weaknesses and opportunities of the pharmaceutical SCM environment in India.

The paper employs a Strength, Weakness, Opportunity, Threat (SWOT) analysis and recognizes strategies to utilize the advantages of the strengths and opportunities, rectify weaknesses and resolve threats.

A variety of strategies that could have a positive effect on the Indian pharmaceutical business are presented. Findings and suggested strategies can significantly advance knowledge, enhance understanding and contribute to the growth of a successful SCM for the Indian pharmaceutical sector.

This paper would act as a roadmap to greater comprehension of the market leaders and market leaders' operating climate. The findings from this study will offer academic scholars and business practitioners deeper insights into the environment of SCM.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

The aim is to analyze the European eco-management because the global warming has become a topical issue impacting the whole world. Individual countries are trying to minimize all the catalysts of global warming, such as carbon emissions. This paper addresses this issue and analyzes the performance of European eco-management for the purpose of future energy investments being environmentally.

This paper develops a fuzzy decision-making model to study the performance indicators of selected countries based on EMAS III standard. It employs interval type-2 fuzzy DEMATEL to evaluate the performance factors and TOPSIS methodology to assess five selected European countries' performance in relation to eco-friendly, emission and renewable energy.

Eco-friendly energy plays the most critical role in this respect followed by emissions and renewable energy which constitute significant factors. The novelty of this study is identifying significant criteria regarding environmental and energy efficiency of investments and making performance assessments of European countries with a new fuzzy decision-making model. Both expert opinions and datasets are used for the analysis. This paper supports previous research about energy efficiency investments in Europe.

The innovative feature of this study is identifying significant criteria regarding environmental and energy efficiency of investments and assessing the performance of European countries with a new fuzzy decision-making model. The fact that the analysis only concerns the European region is an important limitation. In future analyses, other groups of countries can be examined. Innovations can be made regarding the method applied. In this context, analyses can be done utilizing different fuzzy numbers. Finally, the importance of the criteria can be calculated with other methods such as SWARA.

The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments is done in this manuscript.

Analysis of European eco-management performance was done for environmentally friendly and efficient energy investments. A fuzzy decision-making model is constructed. The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments.

This study aims to thoroughly examine and understand the relationship between working capital management (WCM) and the sustainable financial performance (FP) in the context of the New Zealand companies listed on stock exchange.

This study has applied various regression techniques to examine WCM and the sustainable FP relationship. The data set period is from 2009 to 2019. The results are robust upon various layers of robustness parameters. The system-generalized method of moments is applied for managing endogeneity issue.

The research reveals compelling evidence of a meaningful connection between WCM and sustainable FP indicators. The study specifically highlights the significant negative associations between the cash conversion cycle, average collection period and average age of inventory with the firm’s sustainable FP. Through robust analyses and various parameter adjustments, the study ensures the credibility and reliability of its conclusions, further reinforcing the impact of WCM on the financial health of New Zealand-listed firms.

This study provides future directions for researchers to explore the dynamic relationship between WCM and a firm sustainable FP because it is still a demanding and challenging area. Future research may care to explore the optimal way to reduce the cash conversion cycle, average collection period and average age of inventory for New Zealand firms. The current study does provide insights to NZ financial managers, which is useful for improving sustainable FP by efficiently managing WCM.

WCM is problematic and constitutes a notable challenge; it requires further research, especially in small economies such as New Zealand. Hence, it is an updated and fresh attempt based on a larger data set to measure the empirical relationship between WCM and the sustainable performance of New Zealand-listed firms. Furthermore, the current study uses dynamic panel data estimation techniques in addition to multiple regression techniques.