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Contradictory sustainability priorities and perspectives among supply chain actors in greening transportation can be challenging. Several of these contradictions can be described as paradoxes (i.e. interests that are logical in themselves, but become irrational when perceived together). The aim of this study is to increase the understanding of paradoxical tensions hampering the greening of transportation in transport buyer–supplier dyads.

A case study method targeting greening transportation in two transport buyer–supplier dyads was applied, followed by an analysis with a point-of-departure in paradox theory.

Tensions related to performing, belonging, learning and organizing paradoxes in greening transportation were identified. These tensions arise as a consequence of actions, perspectives and other tensions, within three identified loci in individual companies and in dyads.

By identifying examples of tensions through the lens of paradoxes in a particular setting, this study provides an increased understanding of why the transition toward green transportation goes slow, despite the high ambitions of involved actors. The suggested framework provides a novel contribution to the literature that further increases the understanding of tensions, by providing additional insights into where tensions arise and how actions, perspectives and tensions in one place of a locus spectrum can disseminate along that spectrum.

This study is original because it applies paradox theory and the four categories of performing, belonging, learning and organizing within the field of greening transportation, and in particular as a lens to study interactions between different actors.

Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification.

The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis.

The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks.

The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system.

Authorities have set up numerous security checkpoints during times of armed conflict to control the flow of commercial and humanitarian trucks into and out of areas of conflict. These security checkpoints have become highly utilized because of the complex security procedures and increased truck traffic, which significantly slow the delivery of relief aid. This paper aims to improve the process at security checkpoints by redesigning the current process to reduce processing time and relieve congestion at checkpoint entrance gates.

A decision-support tool (clearing function distribution model [CFDM]) is used to minimize the effects of security checkpoint congestion on the entire humanitarian supply network using a hybrid simulation-optimization approach. By using a business process simulation, the current and reengineered processes are both simulated, and the simulation output was used to estimate the clearing function (capacity as a function of the workload). For both the AS-IS and TO-BE models, key performance indicators such as distribution costs, backordering and process cycle time were used to compare the results of the CFDM tool. For this, the Kerem Abu Salem security checkpoint south of Gaza was used as a case study.

The comparison results demonstrate that the CFDM tool performs better when the output of the TO-BE clearing function is used.

The efforts will contribute to improving the planning of any humanitarian network experiencing congestion at security checkpoints by minimizing the impact of congestion on the delivery lead time of relief aid to the final destination.

The service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this understanding by developing a typology of service ecosystem dynamics that explains the varying interplay between change and stability within the service environment through distinct behavioral patterns exhibited by service ecosystems over time.

This study builds upon a systematic literature review of service ecosystems literature and uses system dynamics as a method theory to abductively analyze extant literature and develop a typology of service ecosystem dynamics.

The paper identifies three types of service ecosystem dynamics—behavioral patterns of service ecosystems—and explains how they unfold through self-adjustment processes and changes within different systemic leverage points. The typology of service ecosystem dynamics consists of (1) reproduction (i.e. stable behavioral pattern), (2) reconfiguration (i.e. unstable behavioral pattern) and (3) transition (i.e. disrupting, shifting behavioral pattern).

The typology enables practitioners to gain a deeper understanding of their service environment by discerning the behavioral patterns exhibited by the constituent service ecosystems. This, in turn, supports them in devising more effective strategies for navigating through it.

The paper provides a precise definition of service ecosystem dynamics and shows how the identified three types of dynamics can be used as a lens to empirically examine change and stability in the service environment. It also offers a set of research directions for tackling service research challenges.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

The purpose of this study is to examine various data sources to identify trends and themes in humanitarian supply chain management (HSCM) in the digital age.

In this study, various data sources such as published literature and social media content from Twitter, LinkedIn, blogs and forums are used to identify trending topics and themes on HSCM using topic modelling.

The study examined 33 published literature and more than 94,000 documents, including tweets and expert opinions, and identified eight themes related to HSCM in the digital age namely “Digital technology enabled global partnerships”, “Digital tech enabled sustainability”, “Digital tech enabled risk reduction for climate changes and uncertainties”, “Digital tech enabled preparedness, response and resilience”, “Digital tech enabled health system enhancement”, “Digital tech enabled food system enhancement”, “Digital tech enabled ethical process and systems” and “Digital tech enabled humanitarian logistics”. The study also proposed a framework of drivers, processes and impacts for each theme and directions for future research.

Previous research has predominantly relied on published literature to identify emerging themes and trends on a particular topic. This study is unique because it examines the ability of social media sources such as blogs, websites, forums and published literature to reveal evolving patterns and trends in HSCM in the digital age.

This work conducts a comprehensive analysis of how to incorporate resilience and sustainability into capacity expansion strategies for business-to-business (B2B) chemical supply chains. This study aims to guide both researchers and managers on ensuring profitability in B2B chemical supply chains while minimizing environmental impacts, complying with regulations and mitigating disruptions and risks.

A systematic literature review is conducted to analyze the interplay between sustainability and resilience in chemical B2B supply chains, specify the quantitative and qualitative methods used to tackle this challenge and identify the drivers and barriers concerning capacity expansion. In addition, a comprehensive conceptual framework is suggested to outline a compelling research agenda.

The findings emphasize the increasing importance of modeling and resolving decision-making challenges related to sustainable and resilient supply chains, particularly in capital-intensive chemical industries. Yet, there is no standardized strategy for addressing these challenges. The predominant solution methods are heuristic and metaheuristic, and the selection of performance metrics tends to be empirical and tailored to specific cases. The main barriers to achieving sustainability and resilience arise from resource limitations within the supply chain. Conversely, the key drivers of performance focus on enhancing efficiency, competitiveness, cost effectiveness and risk management.

This work offers practitioners a conceptual framework that synthesizes the knowledge and tackles the challenges of designing sustainable and resilient supply chains as well as managing their operations in the context of B2B chemical supply chains. Results provide a practical guide for navigating the complex interplay of sustainability, resilience and chemical supply chain expansion.

The key concepts and dimensions associated with capacity expansion planning for a resilient and sustainable chemical supply chain are identified through structured and comprehensive analyses of existing literature. A conceptual framework is proposed for delineating the intersections among sustainability, resilience and chemical supply chain expansions. This mapping endeavor aims to facilitate a future characterized by the deployment of a nexus of resilience and sustainability in chemical supply chains. To this end, a promising future research agenda is accordingly outlined.

In the Global North, affordable housing has evolved and thrived, and it is now gaining traction in the Global South, where governments have been vocal supporters of the concept. Therefore, this paper aims to investigate the important criteria for selecting affordable housing units in Ghana.

A quantitative research approach was used, and a survey was administered to the residents. The data was analysed using both descriptive and inferential statistics. The relative importance index technique was used to rank the important criteria, and the EFA technique was used to create a taxonomy system for the criteria.

The hierarchical ranking of the most significant criteria for selecting affordable housing includes community safety, waste management and access to good-quality education. Furthermore, the important criteria for selecting affordable housing are classified into two groups, namely, “sustainability criteria” and “housing demand and supply and social service provision”.

This study has implications for the real estate industry and construction stakeholders, as this will inform decision-making in terms of the design of affordable housing and the suitability of the location for the development.

These findings provide a baseline to support potential homeowners and tenants in their quest to select affordable housing. Furthermore, these findings will aid future longitudinal research into the indicators or criteria for selecting suitable locations for the development of low- and middle-income housing.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.