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This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.

A multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.

Study results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.

This is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.

In the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.

For diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.

Testing of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.

Viewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.

As well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.

This paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

Omni-channel shopping affords consumers a variety of delivery options to receive products based on their preferred times and locations. By considering consumers' contributions (physical, social and attentive efforts) in co-creating delivery services, this study investigates their preferences for parcel delivery.

A scenario-based questionnaire survey is conducted for data collection in Singapore (n = 483). Furthermore, a multinomial logistic regression is performed to assess consumers' choice mode of delivery among five alternatives, that is attended home delivery, unattended home delivery, automated self-collection locker, attended pickup point and click-and-collect.

Compared to attended home delivery, consumers who choose the alternatives are found to be more willing to contribute physical effort but less interested in responding attentively to informational updates. Efforts required for social interactions discourage consumers from choosing attended deliveries, prompting unattended alternatives (e.g. home delivery and self-collection) as more attractive choices. Additionally, socio-demographic factors and product value also influence consumers' preferences.

This study contributes to the literature by integrating the theoretical concept of consumer logistics into omni-channel studies, providing a new approach to examining consumers' channel behaviour. With detailed profiling that links product value and consumers' socio-demographics to their choice mode of delivery, the authors create practical insight into the optimal design of omni-channel distribution systems that best harness consumers' voluntary contributions.

This study explores the factors that characterize the logistics service quality (LSQ) of cross-border e-commerce and identifies the different relationships between these factors with respect to customer satisfaction.

The study applied a two-stage mixed-methods design. The first stage (Stage 1) was a qualitative study of 3,000 reviews from the Amazon China e-commerce platform. The second stage (Stage 2) included a quantitative study that analyzed survey data from 590 Chinese cross-border e-commerce customers using the Kano model.

Stage 1 involved developing a conceptual framework for the LSQ of cross-border e-commerce, including six dimensions: timeliness, safety, reliability, economy, personnel contact quality and information quality. In Stage 2, the study found that only reliability and personnel contact quality indicators are linearly related to customer satisfaction. Timeliness and the safety of packaging greatly contribute to customer satisfaction, but do not cause dissatisfaction when unfulfilled. Economics and information quality indicators, and the safety of goods, are basic requirements that tend to provoke customer dissatisfaction when unmet, but do not increase customer satisfaction when they are met.

This study is one of the first to construct a conceptual model of LSQ that applies to cross-border e-commerce and to identify the instrumental nature of various LSQ attributes and their impact on improved customer satisfaction.

Africa has been identified as an area where higher mortality happens due to un-accessibility to health care, drugs and other health facilities. Nigeria, as one of the African countries, is not excluded from such difficulties. This study aims to examine the determinants of efficient last-mile delivery at selected health facilities and the Kaduna State Health Supplies Management Agency (KADSHMA).

The study sourced data from KADSHMA and the health facilities’ staff, with a total of 261 observations used. Likewise, the respondents were picked from warehouses of each health facility and KADSHMA. The data was analysed using the partial least square structural equation modelling analysis to estimate the relationship among the variables of the study.

The study’s findings revealed that all five variables of the study (i.e. determinants) were significantly affecting the efficient last-mile delivery. Four constructs (delivery cost [DC], delivery time [DT], mode of delivery [MD] and facilities technology [FT]) have shown a positive and significant association with efficient last-mile delivery, whereas one variable (product mix [PM]) indicated a negative and significant association with efficient last-mile delivery. The study concludes that DC, DT, MD, FT and PM played significant roles in efficient last-mile delivery.

The study provides that specific means of transportation should always be on standby to transport health supplies. Time schedules should always be prepared and adhered to when transporting health supplies to the facilities, and each facility should network with robust technology to ease communication in terms of order and order planning. Additionally, facilities should try as much as possible to reduce the varieties of products when ordering health supplies, as it will increase the efficiency of the delivery.

To the best of the authors’ knowledge, this study is the first of its kind that considered these five variables (DC, DT, MD, FT and PM) with impact on the last-mile delivery in one model, especially in the Nigerian case. This is a great contribution to knowledge, more importantly, to the last-mile delivery of the health sector. The result confirmed the importance of these determinants (DC, DT, FT and PM) of last-mile delivery efficiency in saving lives.

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 presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Crowd logistics is a rising phenomenon in last-mile delivery that integrates technological applications and sources a large number of participants to do logistical activities, achieving sustainable shipping in urban environments. However, up until now, there has been limited literature in this field. This research aims to investigate the extrinsic and intrinsic factors that impact the participative behaviour of driver-partners in crowd logistics.

An integrated model is developed based on motivation theory, incorporating attitude as a contributor to both extrinsic and intrinsic motivations. A questionnaire was constructed and distributed to collect data from 303 respondents who are existing or potential driver-partners in Vietnam.

Our findings confirm (1) the influence of monetary rewards on extrinsic motivation and (2) the power of self-efficacy, trust and sense of belonging on intrinsic motivation. Further, we find that attitude positively impacts extrinsic motivation, whereas there is no effect between attitude and intrinsic motivation. Both extrinsic and intrinsic motivations are demonstrated to significantly influence driver-partners' participative intentions. Additionally, a positive association is found between extrinsic and intrinsic motivations.

Findings from this study theoretically enrich the literature on crowd logistics, especially on the supply side, and empirically contribute to implications that are valuable to crowd logistics firms on driver-partner recruitment and business strategy development.

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.