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Logistics service provider (LSP) selection involves multiple criteria, alternatives and decision makers. Group decision-making involves vagueness and uncertainty. This paper aims to propose a novel fuzzy method for assessing and selecting agile, resilient and sustainable LSP, taking care of the inconsistency and uncertainty in subjective group ratings.

Eighteen agile, resilient, operational, economic, environmental and social sustainability criteria were identified from the literature and discussion with experts. Interval-valued Fermatean fuzzy (IVFF) sets are more flexible and accurate for handling complex uncertainty, impreciseness and inconsistency in group ratings. The IVFF PIvot Pairwise RElative Criteria Importance Assessment Simplified (IVFF-PIPRECIAS) and IVFF weighted aggregated sum product assessment (IVFF-WASPAS) methods are applied to determine criteria weights and LSP evaluation, respectively.

Collaboration and partnership, range of services, capacity flexibility, geographic coverage, cost of service and environmental safeguard are found to have a greater influence on the LSP selection, as per this study. The LSP (L3) with the highest score (0.949) is the best agile, resilient and sustainable LSP in the manufacturing industry.

Hybrid IVFF-based PIPRECIAS and WASPAS methods are proposed for the selection of agile, resilient and sustainable LSP in the manufacturing industry.

The model can help supply chain managers in the manufacturing industry to easily adopt the hybrid model for agile, resilient and sustainable LSP selection.

The paper also contributes to the social sustainability of logistics workers.

To the best of the authors’ knowledge, IVFF-PIPRECIAS and IVFF-WASPAS methods are applied for the first time to select the best agile, resilient and sustainable LSP in a developing economy context.

Logistics and supply chain management (L&SCM) scholars and practitioners have devoted extensive efforts to advancing green logistics practices (GLPs), yet the intersection between the two domains in relation to the topic remains underexplored. To accelerate GLPs’ development amid the escalating climate crisis, this research examines this intersection by comparing the responsiveness of academia and practice to the call for green logistics over time.

To compare between academia and practice, we combined a systematic literature review on the development of GLPs in L&SCM journals (N = 122) with a content analysis of annual and sustainability reports published by the four major global logistics service providers (LSPs: DHL, DB Schenker, UPS and FedEx; N = 156) over the past three decades.

This research reveals that all the GLPs covered in the L&SCM literature have already been applied and reported by practitioners, both consistently and over a significant period of time. Academic progress, in turn, is delayed by slow-paced empirical methods, elevated research quality standards, prolonged funding and recruitment processes, and extended peer-review intervals. Further, a tendency toward reactive knowledge creation rather than proactive knowledge transfer is evident, obscuring the role of L&SCM scholars in steering the industry’s green advancement.

Recommendations are offered to L&SCM authors, editors, reviewers and university departments to advance pracademic endeavors in green logistics research and increase its responsiveness to global events.

This is one of the first studies to scrutinize the intersection between academia and practice on the evolution of GLPs. The revealed gaps prompted us to suggest a transformative paradigm for academia-practice collaborations targeting the L&SCM discipline at large, combining a bold proactive research stream aimed at knowledge transfer with a more traditional reactive stream aimed at knowledge creation.

The purpose of this paper is to investigate the role of performance measurement systems (PMS) within the context of digital servitization (DS), especially in collaborations involving multiple actors. The paper adopts a bottom-up ecosystem perspective to gain insights into how companies can effectively manage the complexities of digital transformation in the servitization domain.

This research draws upon a longitudinal case study within the wine and spirit supply chain. It focuses on a logistics company, “GR”, which has promoted a DS strategy to offer advanced services and enhance the competitiveness of the entire ecosystem.

The study offers valuable insights into the evolution of PMS roles throughout the DS journey, promoting cooperation, coordination, collaboration and control among ecosystem actors, thereby facilitating the development of a DS strategy.

The study is focused on a logistics company with unique capabilities and networks. Future research should include a broader range of contexts. Furthermore, our analysis focuses on the initial stages of ecosystem emergence, particularly the initiation and momentum phases. Further research should explore how DS impacts organizations in the following ecosystem phases.

This research offers valuable insights for managers, particularly in the development of DS strategy. It underscores the significance of PMS as key facilitators in crafting DS strategy and in the broader ecosystem evolution. The findings demonstrate that PMS is instrumental across different phases of the servitization process, improving aspects such as performance monitoring, resource allocation, collaboration and communication. Moreover, this study emphasizes the importance for small and medium-sized enterprises manufacturers and logistics firms to build and nurture collaborative relationships with various supply chain stakeholders to successfully implement a servitization strategy. In the wine industry, embracing a multiactor perspective is crucial. The delivery of advanced services necessitates a wide spectrum of knowledge and skills on one hand, and adaptability and flexibility in developing relationships on the other.

The study contributes to the literature on management accounting by exploring the role of PMS in DS. It reveals that PMS acts as a fundamental enabler, promoting seamless coordination and collaboration among various actors involved in DS. This sheds light on the transformative potential of PMS in creating a collaborative environment, where multiple organizations work together to offer value-added services.

This paper aims to review the literature on the relationship between the implementation and performance of 4.0 industrial revolution (IR) technologies and explores the extent to which the effects of several internal and external contingency factors on these relationships have been considered by the existing empirical studies.

To achieve its purposes, this study follows a systematic review of the literature and explores the published empirical research on implementation and performance links of 4.0 IR technologies and the effects of contingency factors on these links in mainly three main databases.

The findings of this study reveal that in general several contingency factors tend to have significant effects on the implementation and performance links of 4.0 IR in several contexts. This study also shows that the effects of these contingencies the effects of contingency factors on the implementation and performance links of 4.0 IR technologies are receiving growing attention from researchers and have been studied in different approaches but the moderation approach was the highest.

The review of the literature conducted in this study refers to those studies published mostly by three main databases (i.e. Scopus, Web of Sciences, and Science Direct), and only those papers published in English, and thus does not contain publications out of these restrictions.

This is one of the early literature review studies to explore and discuss the current state of research on the effects of contingency factors on the relationships between the implementation and performance of 4.0 IR technologies in the contexts of logistics and supply chain management.

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.

Due to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.

In this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.

Competitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.

The findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.

This study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

In the existing era, international trade is boosted by maritime freight movement. The academicians and Government are concerned about environmental contamination caused by maritime goods that transit global growth and development. Digital technologies like blockchain help the maritime freight business to stay competitive in the digital age. This study aims to illuminate blockchain technology (BCT) adoption aspects to alleviate early industry adoption restrictions.

This study adopts a two-stage approach comprising of structural equation modeling (SEM) with artificial neural networks (ANN) to analyze critical factors influencing the adoption of BCT in the sustainable maritime freight industry.

The SEM findings from this study illustrate that social, organizational, technological and infrastructual and institutional factors affect BCT execution. Furthermore, the ANN technique uses the SEM data to determine that sustainability enabled digital freight training (S3), initial investment cost (O5) and trust over digital technology (G1) are the most essential blockchain deployment factors.

The hybrid approach aims to help decision-makers and policymakers examine their organizational blockchain adoption goals to construct sustainable, efficient and effective maritime freight transportation.

This study aimed to identify and assess the barriers to implementing modular construction systems (MCS) in developing country's architecture, engineering and construction (AEC) industry, targeting built environment professionals from Nigeria and South Africa.

The study adopted a quantitative research method, using a structured questionnaire to seek the opinions of the professionals on the identified categories of barriers.

Results indicated that all identified categories of barriers were statistically significant using a one-sample t-test at p = 0.05 significance level which indicates they are critical towards the implementation of MCS in developing countries. Assessment of the opinion of the professionals using the Kruskal–Wallis scale showed that they hold similar views on the barriers to the adoption of MCS. Pearson correlation shows a high correlation coefficient amongst the barrier categories and an acceptable level of significance (p = 0.05).

This study is limited to two significant African countries (Nigeria and South Africa) selected based on the gross domestic product (GDP). Further studies can consider developing countries outside Africa and investigate broader respondents.

The study provides implications on the barriers affecting MCS in developing countries for the academia, industry and government to have an insight into the barriers and make informed decisions and policies.

The research satisfies the need to study the barriers affecting the MCS in developing countries that can mitigate housing deficits. This innovative construction method has been adopted and implemented in developed countries, and the result has been positive.

Extreme weather events are on the rise around the globe. Nevertheless, it is unclear how these extreme weather events have impacted the supply chain sustainability (SCS) framework. To this end, this paper aims to identify and analyze the aspects and criteria to enable manufacturing firms to navigate shifts toward SCS under extreme weather events.

The Best-Worst Method is deployed and extended with the entropy concept to obtain the degree of significance of the identified framework of aspects and criteria for SCS in the context of extreme weather events through the lens of managers in the manufacturing firms of a developing country-Nigeria.

The results show that extreme weather preparedness and economic aspects take center stage and are most critical for overcoming the risk of unsustainable patterns within manufacturing supply chains under extreme weather events in developing country.

This study advances the body of knowledge by identifying how extreme weather events have become a significant moderator of the SCS framework in manufacturing firms. This research will assist decision-makers in the manufacturing sector to position viable niche regimes to achieve SCS in the context of extreme weather events for expected performance gains.

The digital evolution of production and logistics systems requires seamless integration of various functions. Cyber-physical systems (CPS) can streamline operations, reduce costs and optimise freight transport dynamics. Therefore, CPS adoption is essential to transform existing logistics infrastructure by connecting logistical equipment to cyberspace. This research addresses the critical issue of low CPS adoption in logistics. By analysing the barriers, the study proposes effective strategies to increase CPS integration significantly.

This study used the technology-organisation-environment (TOE) framework and identified 18 barriers to CPS adoption in freight logistics. The barriers were then analysed using the fuzzy data-driven multi-criteria decision-making (MCDM) method, i.e. fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL).

The computational analysis of the proposed framework shows that “the complexity of CPS and lagged data-driven logistics infrastructure” (T₁) is a major technological inhibitor to CPS adoption. The “high cost of CPS technology” (O₈) and a “lack of top management support” (O₃) are the top causal inhibitors at the organisational level. “Lack of data governance and regulatory framework” (E₂) is the main environmental inhibitor.

The causal mapping of the TOE-based barriers helps policymakers and logisticians to develop strategies or follow recommended adoption strategies to improve CPS adoption in logistics.

This study is a pioneering effort to unveil the adoption barriers of CPS in the freight logistics industry and suggest strategies for fostering adoption. This research could provide valuable insights for logistics organisations to support CPS-driven logistics modernisation.