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This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.

At first, the authors measured the responsiveness of the Indian automobile supply chain, encompassing the top ten major automobile manufacturers, using both sentiment and conjoint analysis. Second, the authors used data envelopment analysis to identify the frontiers of their supply chain. The authors also measured the supply chain's efficiency, using the balance sheet. Further, the authors analyzed the “strategic fit” zone and discussed the results.

The results indicate that both the proposed methods yield similar outcomes in terms of strategic fitment.

The study outcomes facilitate measuring the strategic fit, thereby leveraging the resources available to align. The methodology proposed is both easy to use and practice. The methodology eases time and costs by eliminating hiring agencies to appraise the strategic fit. This valuable method to measure strategic fit can be considered feedback for strategic actions. This methodology could also be incorporated possibly as an operative measurement and control tool.

Data triangulation meaningfully enhances the accuracy and reliability of the analyses of strategic fit. Data triangulation leads to actionable insights relevant to top managers and strategic positioning of top managers within a supply chain.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

Used clothes supply chains are becoming increasingly complex, fragmented and less transparent due to rising volumes of discarded clothes and its dispersed reverse logistics operations across the Global North (GN) and Global South (GS). While it has a promising impact on circular economy and international trade growth, increasing exports of used clothes and overflowing landfills raise some negative concerns on its overall sustainability. This paper addresses the dichotomy that exists in terms of interpreting the sustainability credentials of used clothes supply chains.

A systematic literature review was carried out and 55 articles were examined to identify the triple bottom line (TBL) sustainability impacts of used clothes supply chains. TBL sustainability issues were identified, reflected through the lens of natural resource-based view and interpreted in the form of propositions.

The paper pinpoints seven TBL sustainability concerns and prescribes three sets of strategic resources required in glocal used clothes supply chains for mitigating these. These are (1) slowing the supply chain by tackling poor quality, overproduction and oversupply issues, (2) improving logistics/supply chain infrastructure and ecosystem collaboration and (2) embedding transparent environmental, social and governance (ESG) measures taken by both value chain actors and regulatory bodies, for embracing system-level sustainable development.

This is one of the first studies to analyse TBL sustainability of glocal north–south used clothes supply chains. The study is unique in terms of its scope and contribution to the sustainable supply chain literature.

The study provides an evaluation of the knowledge and skills importance covered in the degree of Logistics and Supply Chain Management (LSCM) as well as the knowledge and skills gap of graduates entry-level.

The study used both descriptive and exploratory research designs. The study adopted a self-administered questionnaire. The sample size is 41 logistics industry mid-managers of six organizations selected from the main operators of Sohar Port in Oman.

The findings reveal that logistics professionals agree on the importance of all the learner attributes, knowledge and cognitive skills, and general competencies identified in a university degree with a major in LSCM. Furthermore, the results identified moderate levels of gaps in five knowledge areas and six soft and hard skills of graduates at the entry level.

Further research can be built on this study findings by evaluating the perception of logistics and supply chain industry professionals in different global contexts and investigate the effectiveness of different training and educational programs in enhancing the knowledge and skills of logistics professionals in various regions.

This study may extend beyond Oman and have important implications for LSCM practices in other developing countries. Universities' management in developing countries can use this study findings to identify the key skills required by entry-level logistics professionals and incorporate them into their curricula to better prepare graduates for the workforce. In addition, the skills identified in our study, such as decision-making skills, managing stress, negotiation skills and critical thinking, are relevant to logistics professionals in other developing countries with similar socio-economic and industry characteristics.

Unlike the prior studies that focused on the mismatch between educational degrees and job requirements without considering study specializations and industry, this paper lays a nuanced understanding of the knowledge and skills gap associated with entry-level graduates of the logistics and supply chain industry. As such, the paper offers inputs for the LSCM academic degree related to knowledge and skills needed by logistics and supply chain industry.

This article aims to explore the concept of chain value of the public port system in Ecuador from the perspective of importing/exporting companies, analyzing how perceived value in the use of port services affects customer satisfaction and the intermediate links of the influence of trust and commitment on customer loyalty.

Relying on a survey of 634 Ecuadorian companies with experience in international trade as port users and a theoretical framework well-established in the literature on consumer behavior, the empirical study found evidence of a positive and significant relationship with the knowledge of chain effects.

The findings confirm the chain effect and reveal ways to maintain an ongoing satisfactory, trust and committed relationship with users, thereby ultimately gaining and maintaining their loyalty. The conclusions suggest how this postulate can help to close the gap referred to the effective management of port services, and point out that port managers should be concerned with a continuous in-depth understanding of the perceived value and its chain effects.

The authors add evidence of the use of the postulate of the chain of effects on these dimensions, whose applicability is very well established, tested and consensual for the doctrine in industrial marketing. In contrast, it is scarcely present in the port relationship with its users.

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.

The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.

The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.

The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.

This study reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

This study examines the effect of human and technological resource bundling on the financial and non-financial performance of third-party logistics (3PL) firms in India.

For achieving the research aim, 248 practitioners from India based 3PL firms were surveyed. The relationships between human and technology resources and firm performance were examined using structural equation modelling (SEM).

The results of empirical tests revealed that human and technological resources significantly enhance the performance of the 3PL firm. However, the firm's logistic capabilities related to track and trace, order management and final assembly do not mediate this relationship.

This study contributes by examining resource bundling in India's 3PL industry using empirical data and providing knowledge of the relationship between resources and business performance. It guides managers to consciously develop resource capabilities that influence firm performance.