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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.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

To investigate the influence of logistics and transportation workers’ perceptions of their management’s simultaneous safety and operations focus (or lack thereof) on related worker safety and operational perceptions and behaviors.

This multi-method research consisted of two studies. Study 1 aimed to establish correlational relationships by evaluating the impact of individual-level worker perceptions of operationally focused routines (as a moderator) on the relationship between worker perceptions of safety-related routines and workers’ self-reported safety and in-role operational behaviors using a survey. Study 2 aimed to establish causal relationships by evaluating the same conceptual relationships in a behavioral-type experiment utilizing vehicle simulators. After receiving one of four pre-task briefings, participants completed a driving task scenario in a driving simulator.

In Study 1, the relationship between perceived safety focus and safety behavior/in-role operational behavior was strengthened at higher levels of perceived operations focus. In Study 2, participants who received the balanced pre-task briefing committed significantly fewer safety violations than the other 3 treatment groups. However, in-role driving deviations were not impacted as hypothesized.

This research is conducted at the individual (worker) level of analysis to capture the little-known perspectives of logistics and transportation workers and explore the influence of balanced safety and operational routines from a more micro perspective, thus contributing to a deeper understanding of how balanced routines might influence worker behavior when conducting dynamic tasks to ensure safe, effective outcomes.

This study aims to identify the main challenges to achieving humanitarian logistics in the context of United Nations peace missions in sub-Saharan Africa and to present suggestions for overcoming the logistical gaps encountered.

The methodological approach of the work focuses on the comparative case study of the United Nations Mission in South Sudan, the United Nations Multidimensional Integrated Stabilisation Mission in the Central African Republic and The United Nations Organisation Stabilisation Mission in the Democratic Republic of Congo from 2014 to 2021. The approach combined a systematic literature review with the authors’ empirical experience as participant observers in each mission, combining theory and practice.

As a result, six common challenges were identified for carrying out humanitarian logistics in the three peace missions. Each challenge revealed a logistical gap for which an appropriate solution was suggested based on the best practices found in the case study of each mission.

This paper presents limitations when addressing the logistical analysis based on only three countries under the UN mission as a case study, as well as conceiving that certain flaws in the system, in the observed period, are already in the process of correction with the adoption of the 2016–2021 strategy by the UN Global Logistic Cluster. The authors suggest that further studies can be carried out by expanding the number of cases or using countries where other bodies (AU, NATO or EU) work.

To the best of the authors’ knowledge, this study is the first comparative case study of humanitarian logistics on the three principal missions of the UN conducted by academics and practitioners.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

Conflict and violence are the main drivers of globally escalating humanitarian needs. Local grassroots initiatives are pivotal in distributing humanitarian supplies in the acute response phase until more established humanitarian aid organizations can enter. Nevertheless, scant research exists regarding the role of grassroots associations in providing humanitarian assistance during a military conflict. The purpose of this paper is to understand the role of grassroots associations and identify important themes for effective operations.

This paper adopts a case-study approach of three Ukrainian grassroots associations that began operating in the immediate days of the full-scale invasion of Ukraine. The findings are based on analyzing primary sources, including interviews with Ukrainian volunteers, and are supported by secondary sources.

Grassroots associations have local contacts and a contextual understanding of population needs and can respond more rapidly and effectively than large intergovernmental agencies. Four critical themes regarding the operations of grassroots associations emerged: information management, inventory management, coordination and performance measurement. Grassroots humanitarian response operations during conflict are challenged by personal security risks, the unpredictability of unsolicited supplies, emerging volunteer roles, dynamic transportation routes and shifting demands.

Grassroots responses are central to humanitarian responses during the acute phase of a military conflict. By examining the operations of grassroots associations in the early months of the 2022 war in Ukraine, the authors provide a unique perspective on humanitarian logistics. Nonetheless, more inclusive models of humanitarian responses are needed to harness the capacities and resilience of grassroots operations in practice.

The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.