The International Journal of Logistics Management

To explore the role of human resources (HR), specifically ability, motivation and opportunity practices (AMO) framework and supply chain orientation top management support (SCO-TMS), in driving the dynamic capabilities of the Triple-A (agility, adaptability and alignment), which help to overcome the challenges faced by global supply chains (SC). A survey is answered by managers from different functions in a sample of 287 manufacturing plants (three manufacturing sectors) and 14 countries (nine developed and five developing). The database is analyzed by PLS-SEM. In-sample and out-of-sample model predictive capacity is assessed by PLSPredict and CVPAT. A multigroup analysis (MGA) has been done to assess the possible influence of the countries’ economic development context in the model. This research confirms significant positive relationships between AMO and SCO-TMS and AAA capabilities, with SCO-TMS showing a stronger relationship. This highlights the importance of HR aspects (AMO and SCO-TMS) as drivers of Triple-A SC, and particularly the importance of top management’s strategic vision to support SCO and develop collaborative relationships with suppliers and customers. The wide multi-country/multi-sector sample, reinforced by a good model’s in-sample and out-of-sample predictive capacity, makes these results more reliable and generalizable to other settings than other research in the field. Managers are encouraged to develop AMO practices and SCO-TMS (focusing on SCO-TMS as the main lever) to enhance Triple-A SC capabilities. The analysis of the country’s economic development context still encourages the use of SCO-TMS as the main lever since its effect is higher than that of AMO. This knowledge is crucial to improving the allocation of limited resources toward developing appropriate capabilities. Following the DCV and ROT perspectives, this research pioneers the analysis of HR practices (AMO) and SCO-TMS as antecedents of the Triple-A SC capabilities, making relevant contributions to the knowledge on the drivers of these relevant dynamic capabilities, an area with limited prior research.

Despite being a fundamental concept, the field of supply chain management (SCM) exhibits a significant lack of consensus regarding the definition of supply chain flows (SCFLOWS). Additionally, there has been an over-reliance on three flows – material, information and finance – while various other flows crucial to SCM performance have been overlooked. Hence, the purpose of this study is twofold: (1) to explore the multi-dimensional nature of SCFLOWS and (2) to identify additional flows beyond the commonly acknowledged ones that are vital for SCM performance. This study employs various qualitative methods as part of the abduction process. The methods include in-depth interviews with logistics professionals, a Delphi study involving SCM scholars and a focus group comprising airline industry practitioners. Seven SCFLOWS dimensions are identified and presented as SCFLOWS framework. Also, two additional flows, i.e. human and capital equipment, are proposed as vital to SCM performance. This is the first study to introduce SCFLOWS framework to achieve consensus in the field. By introducing two additional flows, it proposes extending the SCFLOWS boundary to include various flows overlooked previously but pertinent to SCM performance. The SCFLOWS framework serves as a systematic guide to validate additional flows and represents an important step towards building SCM theory.

Although electric vehicles (EVs) offer promising solutions for reducing transport emissions, several obstacles hinder their adoption, and supply chain (SC) stakeholders must systematically identify and address these challenges. Prior research has explored barriers to EV adoption but lacks a global focus on last-mile delivery (LMD). Our study aims to fill this gap, providing a foundation for future research and aiding organizational shifts towards sustainable transportation. Our study identifies 21 critical barriers to EV deployment in LMDs, validated through a quantitative survey involving 157 SC experts. The survey data are analysed using Exploratory Factor Analysis (EFA), which identifies four distinct dimensions encapsulating the identified barriers. Based on consultations with five experts, the Analytical Hierarchy Process (AHP) ranks these dimensions and individual impediments globally. The study finds “Energy and Infrastructure Barriers” and “Financial and Resource Barriers” to be the most significant hindrances. Noteworthy individual barriers include the absence of fast-charging stations, insufficient electricity provision and the need for investment in Power Grid upgrades. This research contributes to the existing literature by offering a robust methodology for classifying and ranking EV adoption barriers through EFA and AHP. It thus provides a globally applicable framework for stakeholders to devise targeted strategies for overcoming these barriers.

Current catch documentation and traceability practices in the Philippines are paper-based. However, with technological advancements, a shift toward electronic documentation has become a global trend to combat illegal, unreported and unregulated (IUU) fishing. This study aims to determine the factors influencing fishers' preference for a mobile traceability platform and identify the challenges in achieving a digital tuna supply chain in Davao Region, Philippines. A survey of 178 tuna fishers was conducted in select sites in Davao Region using a semi-structured questionnaire. Factors influencing fishers' preference for a mobile traceability platform were identified using logistic regression. Results revealed that one-third of the fishers (34.5%) preferred a mobile traceability platform. Membership in organizations and higher educational attainment increased the preference for a mobile traceability platform. Meanwhile, respondents' knowledge was associated with a preference for paper-based traceability. This association between knowledge and preference was in the context of catch recording performed by government agencies and fisherfolk associations in landing sites. Intensified support aimed at increasing the fishers' literacy and access to technological devices, including the internet and smartphones, is emphasized to provide them with the basic requirements for participating in mobile traceability systems. Moreover, several challenges in implementing digital traceability beyond fisherfolk were identified. This study amplifies the need for infrastructure and legislation to support the implementation of a digital tuna supply chain and eliminate IUU fishing.

Artificial intelligence (AI) usage improves e-commerce logistics efficiency. However, many actors can play significant roles, such as supply chain consistency (SCC), last-mile logistics (LML) performance and collaboration and coordination among logistics firms. This study aims to assess how SCC and LML performance mediate and collaboration and coordination moderate the relationship between AI usage and logistics efficiency. A structured questionnaire was used to collect the data. A total of 245 valid responses were received from Indian e-commerce businesses. The data were then analysed using AMOS v25 and structural equational modelling using SPSS for regression, PROCESS macro for mediation and moderated mediation analysis. The findings show that AI usage independently impacts logistics efficiency, with SCC and last-mile delivery performance as mediating variables. Collaboration and coordination among logistic firms are also critical moderators in enhancing AI’s efficacy in logistic operations. The study findings suggest the integration of AI into logistic operations and provide implications to managers on the urgency of fostering a collaborative and synchronised environment to utilise the full potential of AI in e-commerce businesses. This study not only contributes to the field of logistics theory by presenting empirical data on the various ramifications of AI but also offers practical guidance for logistics firms, particularly those operating in developing economies, on how to strategically employ AI to enhance operational efficiency and attain a competitive advantage in the era of e-commerce logistics in the digital age.