Purpose

While Industry 4.0 draws on a technology-centered approach, Industry 5.0 emphasizes resilience, sustainability, and human-centricity as key components of value chains supported by technological advancements (Golovianko et al. 2023). One guiding principle of Industry 5.0 is to capture the value of new technologies while prioritizing humans' well-being, where technology should serve humans, rather than the other way around (Kolade and Owoseni 2022). The purpose of this study is to examine the impact of individual human linguistic differences in goal-oriented visual search tasks which is typical for technology assisted production settings. This would support an enhanced understanding of human factor issues on operations performance in production and logistics settings, paving the way for human-centric workplace and process design with superior performance as a win-win-objective (Casla et al. 2019, Lu et al. 2022).

Methodology

We conduct an online experiment with two groups of participants. One group learned German as the first native written language and the second group learned Japanese. Both groups perform three goal-oriented visual search tasks with low, medium, and high visual clutter (stimuli). In our visual search tasks, participants are asked to select one correct shelf location among nine shelve locations. Repeating each trial twice, we arrive at 2 (observation groups) x 3 (stimuli) x 2 (repetitions) equaling 12 trials in total where we add 6 neutral trials and 6 empty trials where participants see a fixation cross. We collect information about the time required to select the correct field and the error rate when selecting one field. Time to select and the probability of error are our two dependent variables.

Findings

The linguistic relativity hypothesis proposes that the language we speak affect the way we think. We expect interesting findings when comparing participants involved in reading different script systems, such as alphabetic German versus logographic Japanese scripts. Representatives of alphabetic scripts are known for using analytical models of cognitive processes, concentrating on objects and their characteristics, while representatives of logographic scripts process information more holistically.

Originality

Previous research has reached wide consensus that a human-centric design of production operations systems is crucial, encompassing social, physical, and cognitive human factors (Loske et al., 2024; Klumpp, 2018). Relative to the literature on cognitive human factors and executed tasks, e.g., performance improvements through learning by doing, differences in cognitive processing stemming from a particular culture have received little attention in the production and operations management literature. Our study proposes that culture-specific mental functioning is important to consider in an Industry 5.0 environment in order to achieve process improvements and human well-being at the same time in production and logistics operations.

References

Casla et al. (2019).

Golovianko et al. (2023).

Klumpp (2018).

Kolade & Owoseni (2022).

Loske et al. (2024).

Lu et al., (2022).

Port decarbonization is an important part of worldwide efforts to combat climate change and move to a more sustainable economy. This study investigates how port decarbonization measures directly support the creation of green employment, therefore benefiting both environmental sustainability, economic growth and social welfare.

Ports emit considerable amounts of greenhouse gases mainly as they rely on fossil fuels for cargo handling and transportation. The move to decarbonization at ports entails implementing green technology such as electrification, renewable energy integration, and enhanced emission control methods (Botana Lagarón et al., 2022). Implementing these technologies cuts emissions and generates new employment possibilities in renewable energy generation, energy efficiency management, and environmental monitoring (Alamoush et al., 2023).

The requirement for specialized personnel to develop, install, and maintain new technologies and infrastructures contributes to generate green jobs. For example, the use of cold ironing at ports needs the installation and maintenance by electrical engineers and technicians (Bosich et al., 2023). Furthermore, ports that invest in green hydrogen production for fuel transition help to create jobs in the hydrogen sector (Pivetta et al., 2022). Additionally, incorporating renewable energy sources, such as solar and wind power, into port operations, creates jobs in the installation and maintenance of these systems. Ports that shift to electric cars and equipment need trained personnel in electric mobility technology (Issa Zadeh et al., 2023). Innovations such as digital twins and simulation technologies improve the efficiency of port operations while lowering their carbon impact, creating jobs in the technology industry (Wu et al., 2022).

Case studies show that ports that implement sustainable practices have effectively decreased their carbon footprint while fostering economic growth and job creation (Botana Lagarón et al., 2022). Decarbonizing ports requires extensive training and upskilling of the existing workforce to handle new technology and procedures, resulting in long-term job possibilities and career advancement. Green jobs not only contribute to reaching environmental goals but also to improve the quality of life for individuals and their communities (Alamoush et al., 2020). Ultimately, decarbonizing ports is critical for meeting global climate targets and creating green jobs. The incorporation of modern green technology into port operations not only decreases environmental effect but also generates major job possibilities, therefore contributing to economic and environmental sustainability.

This study seeks to understand the economic and societal implications of port decarbonization, with a focus on green job creation. By examining economic benefits such as employment opportunities in renewable energy and environmental management, we investigate how decarbonization activities boost local economies and create long-term jobs. The societal advantages, such as improved public health, higher community involvement, and increased social welfare, highlight the overall benefits of switching to green technology. We provide valuable recommendations for policies to boost green job creation, as well as targeted investments and regulatory frameworks to help with the transition to a low-carbon economy. Finally, this study demonstrates that port decarbonization not only satisfies environmental goals, but also promotes economic growth and social well-being, presenting a strong argument for broader community support for green projects.

Ethiopia's apparel sector has seen a surge in export-led growth and ranks among countries like China and Bangladesh in industrial output and sourcing destinations. Industrial zones are being constructed to attract large-scale suppliers and buyers, accelerate export-oriented industrialisation, and foster linkages between domestic assemblers and foreign suppliers. The participation of domestic suppliers in the global supply chain system can ensure the sustainability of economic development and supply chain integration through key strategic partnership development. Regardless of industrial policy, government commitment, and remarkable economic growth, the country has achieved little economic, technological, and knowledge transformation due to the weak participation of domestic suppliers. This led us to question the reasons behind weak participation and challenges for domestic suppliers to enter and remain competitive in the global apparel supply chain (SC) networks. Moreover, the author is interested in understanding how international suppliers’ presence and linkages impact the performance and participation of apparel producers. Research on the context of developing nation suppliers' capability to penetrate the global SC challenges and business orientation towards creating a brand image is limited. This study investigates the reasons behind weak participation and challenges for domestic suppliers in global apparel SC networks to help the emerging economy design resilient policies. This study used random sampling techniques to investigate the participation of domestic suppliers in global SC networks. Dillman's (2000) research procedures were used to collect data from primary and secondary sources. The research is conceptualised using the absorptive capacity theory, as it fits the understanding of how weak domestic supplier participation inhibits supply chain integration and efficiency. The study was analysed using R software. Despite an integrated value chain approach and sustainable industrialization, no single operational domestic firm exists in the 26 industrial parks. The analysis showed that 77.78% of firms have domestic market motives. And 68% of them believe that their products are competitive in domestic markets in terms of price, supply, and quality. The analysis further revealed that 23% of domestic apparel and textile suppliers have market and profit orientations, while 8% are interested in forming branded firms. The weak participation of domestic suppliers in the standard industry parks was negatively correlated with the significance of participating in the global supply chain, r(27) = -0.526**, p<0.001. The significant participation of domestic suppliers in the global supply chain system significantly predicted the weak participation of domestic suppliers in the standard industry parks (b = -.618, t(25) = -3.091, p<.001). This work enhances SC integration and sustainability by providing insights for suppliers and academic concepts, highlighting the role of domestic suppliers in global supply chains, economic contribution, and competitiveness. Furthermore, this study shows the importance of domestic supplier participation in developing robustness against SC disruptions. Domestic suppliers are important sources of sustained economic development. Encouraging private investment is recommended for long-term prosperity. Policies should enhance productivity and competitiveness by linking foreign enterprises with domestic firms, promoting technological transfer, spillover effects, and managerial skill transfer, and requiring continuous monitoring and evaluation.

Purpose: Ports rely largely on trucks for hinterland transportation all over the world. With the increasing emphasis on sustainability as well as constant increase in the volume of containers transported across the globe, there is a growing focus on shift from road to rail transportation for connecting container terminals to the hinterlands. However, the existing situation at the ports is not accurately known. This study analyses the hinterland connectivity of container terminals by rail at the major seaports in the world.

Methodology: The analysis is done in two stages. In the first stage, the container terminals are classified into one of three categories based on their access to hinterland rail connectivity. This is done by examining the satellite views of the location of container terminals on OpenStreetMap, Google Maps and Baidu Maps. In stage two, several ports from Europe and USA are studied in further detail by analysing the data from the past years.

Findings: In Stage 1, 100 ports were identified and their container terminals were classified into the three categories. The study reveals that over half the total container terminals at the top 100 ports do not have access to rail. The geographical trends based on this classification is also presented. In Stage 2, the total volume throughput as well as the volumes handled by the different modes of transport are analysed for selected ports in Europe and USA. It is found that road transport still dominates the hinterland transport with only one exception. Furthermore, the destinations served by rail and their distances from the ports are studied to provide further insights into the hinterland rail connectivity of the container terminals. The minimum distance over which rail is used is much shorter than what has been previously suggested in literature.

Originality: The current situation of the container terminals worldwide with regards to their hinterland connectivity is missing from literature. This study serves as a database for various information related to the container terminals which can serve as a starting point for research with regards to terminal planning, sustainability, and hinterland transport. Additionally, a framework to quantitatively analyse the hinterland connectivity is also proposed.

Purpose: Combined transport integrates the advantages of sustainable transport modes, such as railroad or inland waterways, and flexible road transport. It aims at increasing the goods transport sustainability by covering the longest part of a transport path by train or waterway. Rail-road terminals are transshipment nodes of combined transport chains, where the Loading Units (LUs) are moved between trains and trucks. In the most cases, the LUs are also temporary stored in a storage area to decouple the fluctuations in the arrival of trains and trucks. Direct transshipments of LUs between rail and road avoid storage and improve the logistics performance of the terminals. In particular, they enable reducing storage handlings and costs as well as transshipment times of trains and trucks. In addition, they increase the maximum number of trains and trucks that can be processed per time unit (transshipment capacity).

However, the number of direct transshipments at combined transport terminals is currently very small. This is primarily due to the difficulty of synchronizing the arrival of trains and trucks. For estimating the effect of direct transshipments on the logistics objectives it is essential to assess the probability of such operations. This study therefore contributes to modeling the direct transshipments at rail-road combined transport terminals (1) by modeling the probability of such operations and (2) by modeling the effect of direct transshipments on the transshipment capacity of rail-mounted gantry cranes as main working systems of rail-road terminals.

Methodology: This study firstly analyses the requirements for direct transshipments, considering them for two main cases: train-to-truck transshipments and truck-to-train transshipments. Afterwards, it develops a quantitative model for determining the probability of direct transshipments for both cases. Further, it models the effect of direct transshipments on the transshipment capacity of the terminal. Models are evaluated using comprehensive simulation.

Findings: The models enable an analytical evaluation of the probability of direct transshipments and of their effect on the gantry crane transshipment capacity. The simulative evaluation confirms a high accuracy of the models. The probability of direct transshipments mainly depends on the synchronization of truck and train arrivals. In addition, the direct transshipments increase the transshipment capacity of a gantry crane.

Originality: There is a lack of research focusing on direct transshipments at combined transport terminals. Previously, simulation and mathematical optimization are used for their exploration. Taking into account the positive effect of these operations on the logistics objectives of the terminals, this study presents an approach for modeling the probability of direct transshipments and their effect on transshipment capacity of a gantry crane. It helps firstly to understand the cause-effect relations for their occurrence. Secondly, it supports derivation of suitable measures for increasing the number of direct transshipments and for improving logistics performance of rail-road combined transport terminals.

Due to the ever-increasing public demand for goods and services, a steady increase in global emissions can be observed, partly accounted for by the shipping industry. To reduce the ecological footprint of mentioned industry and thus increase its sustainability, this paper examines the extent to which the consumption of a ship can be reduced by path planning algorithms. The focus hereby is placed on the use case of maritime urban transportation and which adjustments to existing methods are necessary to be suited for this application. This means considering the specific requirements and restrictions that apply to the navigation of a ship in an urban environment. Therefore, an extensive study is being carried out to compare different algorithms regarding their suitability for said task. The factors that are already included in the methods and what would be needed to be added to the algorithm to complete this specific task are considered in this. Finally, an approach based on the A*-Algorithm is pursued in which the consumption along the route is to be reduced by taking environmental parameters into account. The resulting algorithms cost function can consider multiple criteria at the same time, therefore being able to solve multi objective optimization problems by applying the weighted product method and adhering to the pareto principle. To draw a comparison to the A*-Algorithm, the proposed method was applied to several use cases. Those were not only limited to urban surroundings, but also open waters. Furthermore, the effect of the environment in the form of the amount of obstacles along the route was investigated for the differing use cases. Thereby, the factors of consumption and runtime were regarded and evaluated for both methods. The use of the proposed algorithm to optimize the route planning of ships can ultimately lead to an increase in efficiency and a reduction in costs, thus increasing competitiveness and future viability.

In this paper we examine the performance of a quantum annealer on a single product Maritime Inventory Routing Problem (MIRP) with many-to-many route structure, hard inventory constraints, and end-of-horizon considerations. In today’s competitive market, mathematical optimization is becoming an increasingly popular tool to consider for planning a variety of logistics operations across the industry. MIRPs are a class of mathematical optimization problems with the aim to plan efficient sea trade. The task at hand is to optimize the distribution of a bulk product among supplying and demanding ports with limited inventories by a fleet of heterogeneous vessels. A literature review about problem and modelling variations as well as solution methods is provided.
Our considered MIRP variant is well-studied and stands out due to its generality, making it a good candidate to apply and conform to a variety of industry needs. However, one challenge of such models can come by the assumption of a finite planning horizon, penalizing any operations near its end. In order to mitigate such end-of-horizon effects and make the model more realistic, we propose a reward for non-empty vessel inventories at the end of the planning horizon.
With that we avoid the risk of inducing infeasilities, unlike previously applied methods in the MIRP literature.

The main aim of this work is to investigate the capabilities and limitations of Quantum annealing as a new solution method for MIRPs. Previously, this technology has only been considered on simpler problems like the capacitated vehicle routing problem. To this end, we generate a set of test instances, formalized as mixed-integer linear models, and benchmark them on both D-Wave’s quantum annealer and a laptop with CPLEX, while varying the computation time.
As one of the main takeaways, we find that on the linear test instances the annealer does not profit from longer computation times.

In this paper, we assess whether the impacts of the stricter 2015 Sulfur Oxides (SOx) regulation within the Sulphur Emission Control Area (SECA) influenced shipowners' strategies in SECA ports. This SOx level is currently the standard applied in all SECAs. This research is essential because there has been limited validation of assumptions in SECA literature. Indeed, SECAs are primarily assessed from the perspective of pollution reduction and benefits on human health (Zheng et al., 2019; Zhu et al., 2021; Wan et al., 2019; Zhang et al., 2020, 2022; Viana et al., 2015), but very few studies have evaluated the ex-post impacts of SECAs from the perspectives of shipowners or ports' outcomes (Fan et al., 2023; Chang et al., 2018).

The policy of interest was introduced in 2015 and applied to all SECA ports. We constructed our dataset from 2012 to 2019 and chose the Northern European ports for our analysis. Using a difference-in-differences model, our main contribution is to assess the impacts of SECAs on calling patterns at SECA ports, as well as on ship characteristics and the contract strategies employed by shipowners. In our identification strategy, we selected two groups of ports: the European Northern Sea ports, which were treated with the SECA policy in 2015, and the European Mediterranean Sea ports, which were the non-treated group. We trace the routings, vessel characteristics (capacity, age, compliance option) and contracts of vessels for all containerships calling at these 172 ports. Building this database provided us with more than 2 million lines of data.

The significant expected contribution is to answer and test the predominant body of SECA literature that focuses on optimizing shipowners' compliance strategies by providing ex-post results. We expect differentiated results depending on whether the route connects with another SECA or not, as well as potential differentiated effects depending on the size of the vessel and the compliance option chosen by the shipowners. Additionally, results may vary based on the specific companies involved and the contracts associated with the ship. These results will be valuable for addressing part of the academic literature and informing policymakers. Notably, substantial policy implications are expected in the phase of new ECAs being discussed for potential Atlantic and Korean SECAs. Additionally, there are more concrete proposals already on the Marine Environment Protection Committee agenda for the Norwegian and Canadian Arctic SECAs, and the introduction of the Mediterranean SECA is expected soon. This is particularly significant since the SOx level that will be applied is the same as the one reduced in the 2015 reform.

Events such as pandemics, natural disasters, and even terrorist attacks have increased the emphasis on mitigating disturbances and disruptions in supply chains, stimulating research on Supply Chain Resilience (SCR). However, the concept of resilience and how supply chains can become resilient remains unclear, making measuring resilience difficult. The literature presents multiple definitions of SCR, but in summary, SCR is described as the ability of a supply chain to anticipate, withstand, and recover from disruptions while maintaining operations and delivering products and services.

Concurrently, a new challenge has arisen with the emergence of digital technologies: a massive influx of unstructured data. Through advanced analytics techniques, Big Data Analytics (BDA) can analyze large and unstructured datasets to extract valuable insights and uncover hidden patterns, correlations, and trends that can guide decision-making, generate business value, and enhance supply chain operations. BDA enhances supply chains by increasing their visibility, analytical capabilities, flexibility, responsiveness, and reliability and improving their ability to adapt to external changes rapidly. By enabling supply chains to recover when disrupted, BDA increases its risk resilience capacity. These benefits highlight the importance of developing BDA capabilities and IT infrastructure to ensure better coordination. Although BDA has proven effective in helping supply chains resist disruptions and increase resilience, there remains a gap in understanding how SCR and BDA intersect and can be effectively leveraged together.

Through an initial literature review, research opportunities were identified. While studies have shown BDA's potential in improving SCR, the specific mechanisms and most effective BDA capabilities to do so remain poorly understood (Hasan, et al., 2024). Additionally, there is a limited exploration of the interaction between BDA capabilities and SCR, especially regarding the best configurations, challenges and barriers to BDA adoption and implementation in supply chains (Jiang, et al., 2023). Some authors point out the need to consider the various stages of supply chain resilience: readiness, responsiveness, and recovery (Zamani, et al., 2022).

The proposed research intends, through a systematic literature review, to identify the most effective BDA capabilities for improving SCR and explore how BDA can improve SCR's key dimensions. Therefore, the study aims to provide valuable insights for organizations seeking to build more resilient and adaptive supply chains. It also intends to lay the groundwork for further investigation into this critical area and to develop comprehensive strategies to enhance SCR through advanced data analytics.

References

Hasan, R. et al., 2024. Critical analysis of the impact of big data analytics on supply chain operations.. Production Planning & Control, 35(1), pp. 46-70.

Jiang, Y., Feng, T. & Huang, Y., 2023. Antecedent configurations toward supply chain resilience: The joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, Volume Volume 70.

Zamani, E. D., Smyth, C., Gupta, S. & Dennehy, D., 2022. Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review.. Annals of Operations Research, Volume Volume 327, p. 605–632.

This study highlights the financial, operational and strategic implications of circular economy (CE) strategies in the Tanzanian pharmaceutical industry. The continued generation of hazardous waste emphasises the urgent need for sustainable paradigms. While the circular economy is gaining momentum in developing countries, its customised application in the pharmaceutical sector is an area that has yet to be scientifically explored.

Using a survey-based approach, data from selected pharmacies in Tanzania was analysed to highlight the different dimensions of circular economy adoption and the associated impacts. The results show that practitioners recognise the fiscal benefits of cost savings and income diversification as well as barriers such as significant capital investment and the need to maintain quality.

From a strategic perspective, the adoption of CE goes beyond its environmental role; it represents an excellent opportunity to enhance a company's brand equity and gain a competitive advantage through resource optimisation and innovative paradigms. We advocate a paradigm shift towards a circular economy ethos that transcends archetypal industry boundaries and favours synergies within the supply chain. The implications of our findings lead to a compelling directive: adopting the principles of the circular economy requires a fundamental realignment of cognitive schema and operations. It becomes clear that fostering a collaborative ethos within the supply chain ecosystem, moving away from previous compartmentalisation in favour of holistic, ecosystemic integration, is a sine qua non. This also underlines the need for a "circular mindset" that embraces the ethos of resource optimisation, waste minimisation and value maximisation. By improving resource accessibility, reducing environmental impact and expanding commercial opportunities, the circular economy is crystallising as a strategic imperative for business resilience and competitiveness.

Therefore, the creation of platforms for collaboration and the dissemination of information between actors to promote synergies and operational efficiency within the supply chain is essential. At the same time, investments must be made in infrastructure that is suitable for the circular economy. Infrastructural foundations such as logistics hubs and knowledge dissemination centres must be created to support the circular economy. Fostering innovations in product design, packaging, and transportation to augment resource efficiency and environmental sustainability is vital. Finally, the existing legal framework must be improved in order to incentivise the introduction of the circular economy and promote compliance with sustainability principles.

Purpose

Digital Twin (DT) concepts are widely discussed in the context of the Industry 4.0 paradigm, and recognized as a key opportunity to enhance the competitiveness of manufacturing enterprises. Yet, the concept of the Logistics Digital Twin (LDT) has received comparatively scarce attention. LDT applications offer improved visualization and comprehension of logistics operations, enabling advanced analysis, simulation, and optimization. Despite various scientific studies, there is still no unified understanding regarding the definition and practical implementation of DT concepts in the logistics sector. This paper addresses the use of DT applications in logistics operations, presenting a relevant use case, its intended purpose, and the current state of technological readiness. The authors explore common definitions, characteristics, and functionalities of DT applications, highlighting recent developments and their implications. Additionally, based on the research findings, the authors identify current research gaps, and present potential directions for future research in the field of logistics operations. The purpose of this paper is to explore mechanisms of supply chain inclusion in Base of the Pyramid (BOP) settings. It distinguishes micro-, small- and medium-sized enterprises (MSME)-led local supply chains on the one hand and multinational enterprises (MNEs)-led global supply chains on the other hand. This paper aims to answer the following research question: Which mechanisms of supply chain inclusion are employed empirically by MSMEs and how can these mechanisms influence social impact creation in MNE-led global supply chains?

Design/methodology/approach

A large-scale empirical study of MSMEs operating in BOP markets is performed and a cluster analysis conducted to systematically categorize supply chain inclusion. The cluster analysis and current literature yield theory-based implications for MNE-led global supply chains.

Findings

The cluster analysis reveals three meaningful clusters of supply chain inclusion in BOP markets and highlights two main aspects. They include direct vs indirect mechanisms of inclusion and diversity in supplier relationships with local organizations aimed at either “sourcing” local capabilities needed for inclusion or “outsourcing” the inclusion. Based on these aspects, two scenarios are proposed and evaluated for local-global supply chain symbiosis.

Research limitations/implications

This study aims to contribute to the existing literature with a more fine-grained understanding of the inclusion of BOP actors in local supply chains and by proposing alternative trajectories for global supply chain inclusion. This local-global distinction is a new addition to the logistics and supply chain strategy management discourse.

Practical implications

The findings outline several important decisions that logistics managers need to make to include BOP actors in supply chain activities. This enhances strategic capabilities of logistics service providers within supply chain settings across all industries.

Originality/value

This paper contributes a novel, combined perspective of local supply chains (MSMEs) and global supply chains (MNEs) towards the issue of strategic base of the pyramid management in logistics.

Although seen as a central enabler of the Circular Economy (CE), inter-organizational information sharing to facilitate repair, reuse and recycling remains insufficient (Jäger-Roschko and Petersen 2022; Plociennik et al. 2022). Driven by regulations of the European Union, digital product passports mirror a suitable opportunity to store, update and retrieve needed information digitally (Psarommatis and May 2024; Preut et al. 2021). As a product-specific dataset, they encompass information such as contained materials, usage data or repair manuals. This study explores the crucial role of information sharing in the context of the CE, shedding light on the digital product passport. We aim to illustrate what needs to be done to improve information sharing in this domain and how it can be enhanced by digital product passports.

A grounded theory approach was applied to gain comprehensive insights into what information is needed, whether companies are willing to share data, and how digital product passports might assist here. In this context, semi-structured interviews with key stakeholders of the CE from different sectors were conducted, including manufacturers, repairers, and recycling companies.

Our analysis reveals various needs for CE-relevant information due to challenges to extend product life. Fortunately, e.g., customer demands and regulatory requirements have made many companies that could potentially provide required information recognize the importance and urgency of sharing CE-relevant information. However, the study also demonstrates the uneven willingness to share information and put intentions into practice because of missing clarity about the detail level of information to be shared and accompanying concerns regarding data security and loss of competitive advantages. Also, efficient information exchange is often hindered by companies´ low level of digitization.

The interview results highlight that digital product passports have great potential to ease information sharing in the CE and that collaboration and exchanging information among stakeholders create leverage. Being vital to jointly generate value and overcome reluctance, a collaborative mindset and incentives to share information in the CE have to be established. Moreover – using the full potential of digital product passports – an environment that fosters a balance between transparency and data protection must be built to effectively deal with the mentioned challenges.

This research is of utmost relevance for policymakers and stakeholders involved in the CE and adds to the current academic discourse by addressing challenges related to the adoption of digital product passports. It encourages information sharing in the CE and contributes to a better understanding of the vital role digital product passports play in this relation. Moreover, it underlines the need for strategies that ensure transparency while maintaining data security, enhance information sharing willingness and collaboration, and support the adoption of digital product passports. In giving guidance on what information to share and how, this research derives recommendations for information sharing in the CE and contributes to its accelerated transition.

Introduction

The benefits of RoRo shipping in terms of quicker turnaround times compared to container transport are apparent, primarily attributed to higher departure frequencies and reduced dwell times in terminals (Woxenius and Bergqvist 2011). Addressing bottlenecks is crucial for achieving these efficiencies. Despite limited coverage in the literature, simulation studies of RoRo terminal operations are lacking (Abourraja et al. 2023). However, the disclosure of the modelling of terminal processes as a basis for simulation studies has so far only been carried out to a very limited extent. This study aims to comprehensively delineate current terminal processes in the Baltic Sea region, facilitating simulation studies and digital integration initiatives (Santos and Santos 2024).

Methodology

The research framework of Design Science Research (DSR) (Peffers et al. 2008) guided this study. A literature review was conducted to identify prevalent approaches to modeling operational processes within RoRo terminals and ports. Additionally, interviews were conducted with various stakeholders in the RoRo sector to understand current terminal processes. Twenty-three interviews were conducted initially, involving players in the sector. BPMN was employed for modeling, followed by validation of BPMN models in five feedback sessions involving sector participants.

Findings:

The findings reveal a macro-level model illustrating the interconnections among distinct functional areas within RoRo terminals, categorized by accompanied and unaccompanied transport in import and export contexts. This model forms the foundation for four additional models delineating import and export processes, further subdivided based on accompanied and unaccompanied transport. It offers insights into the operational engagements of individual stakeholders and their mutual interactions.

Discussion:

The delineation of individual process steps across all terminal stakeholders can serve as a foundation for operational simulation studies and facilitate the integration of digital methodologies to enhance terminal performance. Previously, there was no comparable, nuanced process delineation within the RoRo/RoPax sector. A deductive approach was employed to outline an archetypical terminal operation process, adaptable to specific terminals, thus providing a framework for simulation studies and digital solution integration. Additionally, depicting these processes fosters comprehension of the diverse stakeholders in the RoRo sector.

Conclusion

The study investigates current operational protocols at RoRo terminals in the Baltic Sea region, laying the groundwork for conducting simulation studies and integrating digital methodologies to improve operational efficiency. The results produce a detailed macro-level model illustrating interdependencies among functional domains, allowing for customization to meet individual terminal needs. This model can be utilized in future research to identify key performance indicators (KPIs) and subsequently integrated into simulation models. Additionally, it can be expanded to encompass aspects of passenger transport that have not yet been examined..

Research at the nexus of manufacturing operations and sustainability is becoming increasingly popular because of growing concerns about climate change, ground and water pollution, local and regional impacts on air quality, and the effects of increased industrial activity on community health and safety (Drake & Spinler, 2013; Corbett & Kleindorfer, 2001). Empirical academic research on sustainable operations management (SOM) was collected and analyzed in this article. Using a systematic review of the literature, the study investigated 102 articles and books on SOM that were published between 1994 and 2023. Elkington (1994) and Gupta and Sharma (1996) are two significant articles from the mid-1990s that the study included. SOM received more attention as a result of these important contributions to the integration of sustainability aspects in OM. (1) The definitions of SOM, (2) the practices of SOM, and (3) the empirical results of SOM practices on sustainable performance were the primary concerns that have guided the analysis of this study. The 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) approach was used for reports. To locate research that is eligible, four methods were used. First, to ensure that a wide range of scientific output is covered, the study initially performed an electronic search in two databases, Scopus and SCimago. Second, In order to determine how sustainability is integrated into operations, the study examined SOM journal articles that were published in five of the leading journals for operations management, including the International Journal of Operations and Production Management (five articles) and the Journal of Cleaner Production (nine articles). Third, to locate pertinent material, the study searched Google books and related web databases. Finally, the study looked through internet databases to find relevant conference proceedings. The features of the eligible studies found and the analysis to the above research objectives have been then presented systematically. The systematic literature review revealed that several researchers have empirically examined the relationship between some aspects of SOM practices and one or more of the dimensions of manufacturing firms' sustainable performance; however, no clear findings have been obtained thus far. Considering this discovery, the study suggested that future research bridges this knowledge gap by conducting a comprehensive analysis of the connection between SOM practices and sustainable performance. Moreover, two significant findings from the systematic literature review have been emphasized. On the one hand, manufacturing companies should take part in triple bottom line (economic, environmental, and social) issues to attain sustainability in their operations. SOM, on the other hand, broadens the firm's scope. It includes not just implementing internal SOM practices (such as sustainable product design and manufacturing processes) that improve the firm's sustainability performance but also extending sustainable practices to the supply chain that supports the firm's performance in sustainability. Besides, the study offered a widely comprehensive definition of SOM. Additionally, analysis and conclusions about how SOM practices explain business success were made from the systematic literature review. This report also identified methodological and theoretical limitations and provides several recommendations for further research.

Disasters pose a significant challenge for last-mile operations, straining emergency logistics systems' ability to provide timely aid and support. Therefore, ensuring the rapid and cost-effective distribution of goods to people in need is one of the most critical tasks of humanitarian logistics.

In this context, we formulate a Fleet Size and Mix Vehicle Routing Problem for Disaster Management (FSMVRP-DM) that extends the known FSMVRP with a fleet composition decision and adapts it to the specifics of disaster relief logistics. The model aims to optimize routing and fleet decisions to minimize the sum of operating costs and population deprivation costs. Moreover, we introduce a prioritization approach to monitor deprivation time during transport resource scarcity.

In non-disruptive times, drones are restricted by “no-fly-zones” – for example, environmental protection areas. However, this restriction might be temporary repealed by authorities during disaster relief. The additional possibilities may increase efficiency significantly, though this requires communication and coordination through public-private collaboration. Our model considers this to prevent extended supply gaps at specific demand points and minimize suffering costs.

A case study is conducted in the German state of Baden-Württemberg to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. The findings highlight the advantages of integrating diverse and innovative fleet types, such as drones, and prioritizing the supply of multiple demand points when resources are scarce.

Consequently, optimizing fleet size and composition can result in substantial cost reductions and efficient resource allocation. Overall, our research offers decision support for authorities by enhancing information transparency, facilitating resource management, strengthening the effectiveness of disaster response capabilities, and providing resilient and adaptive strategies for last-mile distribution efforts. Certain factors should be addressed in future works, such as time windows, additional network constraints, and heuristic algorithms. Nevertheless, our study derives valuables insights that will contribute to improving last-mile logistics in the future.

Globalization, growing population and urbanization, and changing buyer behavior due to pandemics such as COVID-19 increased e-commerce practice adoption throughout the globe. Following an improved access to digital ordering and settling payments for online transactions, ensuring faster, cheaper, sustainable and inclusive last mile delivery is becoming critical. Studies show last mile delivery logistics is considered as very ineffective, expensive (acounting for 13 to 75% of the full supply chain cost), and polluting (resulting in environmental and social externalities such as air and noise pollution, accidents and road congestion, parking problems, causing the emergence of health problems) globally. Research in this area is fragmented with disparate conclusions. Ethiopia is the second populus nation in Africa with huge potential for last mile delivery business. Addis Ababa (new flower in local language) is the Capital of Ethiopia with a projected residents of 5,704,000 in 2024 of which roughly 40% is below 25 years of age. The government of Ethiopia has been currently working towards the realization of Digital Ethiopia by 2025 initiative for ensuring prosperity and creation of job for the youth. In Addis Ababa, city logistics infrastructure is limited or unparraleled with rate of population growth and urbanization. Congestion is becoming more prevalent in the city. People are getting busy as cost of living is increasing hence looking for easy, reliable and efficient last mile delivery services. Some of the routes in the city are not allowed for motor cycles operated by last mile delivery service providers. Business are not concentrated. Most of the vehicles used at the moment are fuel based.There is a tendency from the government towards enforcing the use of electric vehicles aspiring to make the city sustaianble as its name. Eventhough, more than 20 last mile delivery providers have emerged in the city, the status of urban last mile delivery is uncharted from the pecular context of Addis Ababa City. Considering last mile delivery logistics as a multidisciplinary issue, this study aims to explore sustainability of urban last mile delivery logistics. The study will conduct urban last mile delivery logistics stakeholder and process mapping in order to identify weakest link with regard to sustainability, efficiency and inclusivity. Sociogram will be used as a tool to explore level of influence, direction of influence, and strength of relationship among the stakeholders. The study will also utilize the decision making trial and evaluation laboratory (DEMATEL) technique to identify and categorize urban last mile delivery logistics sustainability factors into cause and effect groups. The study will identify urban last mile delivery logistics characteristics of top priority from a developing economy perspective. The findings of this study will guide city logistics leaders and government officials where to focus for improving sustainability while addressing real-time needs of citizens in the urban area.

Logistics operations embedded in global supply chains generate a significant amount of greenhouse gas emissions which, until recently, have only been viewed from a more holistic perspective. Scope 3 emissions include indirect emissions that occur in the upstream and downstream activities of an organisation e.g., from transportation providers, suppliers, retailers, employees, and customers. Scope 3 emissions make up a majority of the carbon footprint of most organizations, but studies show that they are hard to measure and manage in the context of companies due to several reasons (Kojo, 2023), e.g., data availability and quality. Also, the reporting and verification of Scope 3 emissions are not consistent and transparent. Therefore, we need new solutions that can make it easier to collect, combine and share emissions data in the logistics service chain.

End-to-end visibility in the logistics chain goes beyond a focal company’s boundary and extends to freight ecosystem partners, such as customers, suppliers, freight forwarders, and logistics service providers. This requires a means to organise the collaboration. The concepts of digital platforms and digital ecosystems have emerged within this context bringing different ecosystem stakeholders together, allowing them to communicate, share data and interact and, therefore, also simplify the complexities of day-to-day transactions among cargo stakeholders (Wang & Sarkis, 2021).

Our study provides insights on how a digital logistics marketplace including emissions data is developed in a project consortium consisting of four development cases connected by the marketplace. The cases focus on different logistics service operations (truck, train, port). The three-year development process is still ongoing, and at this point we can report the observations and findings from the first year.

This research follows a qualitative approach to examine the development of a digital marketplace for emissions-aware logistics services in the context of the EU co-funded project ADMIRAL. Currently we have an initial concept of an emission-aware logistics marketplace as well as the first experiences of defining such a platform. However, several issues are challenging the development of such a marketplace – such as data sharing, governance model and overcoming the chicken and egg problem. The marketplace aims to facilitate interaction between the sellers (producers) and the buyers (users). The sellers operating on the platform offer their logistics services according to rules set by the platform operator. The emission-aware buyers acquire these services via the platform. The marketplace is not only a transaction platform, but it also provides capability for application developers and integrators to build and integrate applications on top of the marketplace utilising the developer portal. The marketplace operator facilitates the operation and enables value creation between the different parties of the platform. Furthermore, the operator determines and controls who can access the platform and under what conditions (e.g., curation). Thus, the marketplace has many challenges to tackle, and it remains to be seen how we will succeed in our journey towards a multimodal marketplace platform for Scope 3 emission-aware logistics.

The global logistics industry faces the urgent challenge of reducing its CO2 emissions. With increasing pressure from governments, consumers, and investors to adopt more sustainable practices, proactive measures to decarbonize are essential. Transport and logistics account for approximately 14% of global CO2 emissions, highlighting the urgency to make significant progress in this sector. This presentation at the Hamburg International Conference of Logistics outlines a comprehensive roadmap to reduce Scope-3 emissions in the transport sector. Scope-3 emissions encompass all indirect emissions in a company’s value chain and are particularly difficult to manage. Reducing these emissions is crucial for achieving global climate goals and ensuring the long-term competitiveness of the logistics industry. Companies must follow several steps to successfully decarbonize:

• Transparency: Calculate the CO2 footprint using primary data or emission factors
• Hot Spot Identification: Identify “CO2 hotspots” to prioritize decarbonization activities
• Define Decarbonization Roadmap: Identify decarbonization levers, create a timeline, and assign responsibilities
• Track Measures: Develop data dashboards to visualize the current status and progress of decarbonization efforts

A specific project example illustrates the practical applications and successes of this strategy. A leading logistics provider based in Hamburg identified its most emission-intensive routes and conducted a detailed analysis of the main sources of emissions. Innovation workshops with suppliers led to sustainable transport solutions such as alternative fuels and more efficient transport methods. A global network of sustainability champions coordinated the implementation of these solutions across different regions.

Supported by a “Green Solution Map,” which provided a clear overview of available green offerings, and a tracking tool to monitor progress, the project achieved a significant reduction in Scope-3 emissions and set new benchmarks for sustainable practices in the logistics industry.

Decarbonizing the logistics industry offers the opportunity to innovate in sustainability and lead the way. With a strategic roadmap, targeted interventions, promotion of innovation, and global collaboration, significant emission reductions can be achieved. This presentation aims to inspire logistics professionals and equip them with the knowledge and tools to drive decarbonization efforts within their organizations, contributing to a more sustainable future.

In response to the escalating challenges of last-mile delivery (LMD) due to various factors such as urbanization and the rise of e-commerce, this study explores the innovative integration of autonomous delivery robots within a Van-and-Robot (VnR) system, exemplified by the BeIntelli project.

In recent years, the integration of fully or semi-autonomous vehicles has attracted considerable attention. Technological innovations are propelling the logistics industry toward the adoption of autonomous delivery robots for LMD. This approach aims to enhance operational efficiency through optimized routing and extended operational hours, reduce costs primarily by lowering labor expenses, and promote sustainability through the use of electric vehicles. However, the integration of autonomous delivery robots into urban logistics faces multiple challenges, including limitations in their range or capacity. The conceptual framework that combines vans with robots offers a promising solution to extend the operational capabilities of robots and utilize vans as mobile depots, directly addressing the challenges of LMD. Despite the growing interest from both industry and academia there is currently a noticeable gap in the conceptualization and practical implementation of this concept, even though the necessary technologies are increasingly accessible. This study aims to broaden its research focus to include the technical design and development of such a VnR system, specifically within the context of the BeIntelli research project.

Employing a qualitative morphological analysis, including a morphological box and cross-consistency matrix, the research delineates feasible VnR configurations. This methodology, enriched by patent review, identifies essential categories and variants for the VnR system. For this concept, the integration into the logistics process takes precedence over specific technical construction details. Collaboration with experts, including developers of the delivery robot, the autonomous driving stack for the transporter, and integrators of the vehicle's material flow system, is crucial in constructing the cross-consistency matrix to determine viable combinations. A specific, project-constrained variant is developed and executed as a proof-of-concept within the BeIntelli project, showcasing the practical application of the theoretical framework.

The study aims to contribute to urban logistics innovation, emphasizing the importance of structured analytical methodologies and collaborative development for the advancement of autonomous delivery solutions. The implementation of constructive projects could be enhanced by a conceptual framework, facilitating detailed and practical investigations into the challenges described. Additionally, the utility is derived from the definition and identification of subcomponents and process steps within the concept, enhancing understanding of its constituents and, consequently, informing the design of the concept. Through the BeIntelli project, this research not only presents a viable implementation of the VnR system but also sets a precedent for future exploration in enhancing urban delivery systems.

There is plenty of research on the vehicle routing problem (VRP) and its application in last mile logistics. For home deliveries with an in-person handover offering time windows (TW) increases customer satisfaction and first attempt delivery rate. In general, it can be stated that the smaller the time windows the higher the successful first attempt delivery rate. To improve the predicted delivery time and keep the time windows offered traffic and congestions risks can be integrated in the VRP. In the logistics context most analyses focus on the B2C and B2B market with small package deliveries. At the customer location a fixed or stochastically chosen stop time is used.

In the field of service management the technician routing and scheduling problem (TRSP) considers varying services times at the destination. Also here, time windows have to be considered.

As the e-commerce market is expanding in terms of product portfolio heavier and bulky items like furniture and household appliances are added to the online stores. At the same time the vendors add services like final assembly or installation at the customers site to increase customer satisfaction. Due to the size and weight of the items to be delivered and the additional services offered the stop (and service) time at the customer site is longer and therefore relevant for an adapted VRP-TW.

The scope of this research is to analyze the processes at the customer location in more detail with a special focus on the process steps beginning with the search for a parking spot to unloading and the delivery of multiple items into the customers apartment or house. The objective is to identify patterns and indicators that allow for a more accurate prediction of the total stop time. One of the hypotheses is that deliveries in the city center take longer due to limited parking spaces which result in longer walking distances combined with multi-story buildings with narrow staircases compared to deliveries in suburban areas where the delivery van can park in the driveway.

To identify these patterns and indicators delivery service teams of a logistics service provider have been equipped with motion tracking devices. Based on the Motion Mining technology by MotionMiners which have been successfully applied in the context of manual warehouse picking process analysis the motions are classified into basic activities (e.g. walking, carrying, unloading, documentation) from which the duration of the individual process steps can be derived. Linking the empirical data with the logistics aspects of the delivery task (e.g. number of pieces, volume, weight, address, ZIP code) allows for a stop time prediction of similar delivery tasks in the future.

Overall, the results enable a more precise transport planning which could on the one hand optimize the utilization and workload of the delivery crews and on the other hand increase customer satisfaction as more accurate delivery time windows can be offered.

Increasing CO₂ reduction and reporting obligations as well as rising customer demands for sustainability-related data increase the need for accurate calculation and reporting of transport-related CO₂ emissions. Currently, the widespread use of standard emission factors is leading to a lack of accuracy, preventing effective management of CO₂ emissions and the visibility of CO₂ reduction measures taken. To increase the accuracy of determining transport-related CO₂ emissions, the importance of primary data is growing which in turn requires the exchange of sustainability- and transport-related data. In general, small and medium-sized companies (SMEs) are at a disadvantage in adopting green practices due to their limited resources. Nevertheless, there is a lack of research focusing on transport SMEs, which often act as subcontractors for larger logistics service providers, although they are responsible for carrying out most of the environmentally damaging activities. Therefore, this study investigates the role of transport SMEs regarding carbon disclosure and the influence of proactive environmental behavior on emission data sharing and competitiveness. The purpose of this study is to explore the effects that a company`s environmental strategy and its shipper-carrier relationship can have on the sharing of CO₂ emission data.

A qualitative study based on semi-structured interviews (n = 30) with different stakeholders from the logistics industry is conducted. The interview sample focuses on SMEs carrying out transport to investigate their behavior. The interview data is analyzed by using qualitative content analysis following Mayring (2015). Afterwards, we conduct a quantitative study in form of a survey to confirm and validate results, as well as testing a series of hypotheses derived from literature and results of the interviews. The data were collected through a web-based survey sent to shippers, LSPs, and carriers. Studying a sample of 107 responses, the conceptual model is tested using the partial least squares structural equation modeling (PLS-SEM) method.

This paper shows that companies with a proactive environmental strategy tend to have a closer relationship with their business partners. Furthermore, a better shipper-carrier relationship increases the level of emission information sharing between these companies. Furthermore, transport SMEs perceive the exchange of emission data as a competitive advantage.

This study provides important insights into the role of sharing emission data focussing on the perspective of transport SMEs. The study demonstrates that collaboration and a long-term relationship between shippers and carriers can be an essential pillar and enabler to remain competitive and pursue a successful sustainability strategy. Therefore, companies should be encouraged to close cooperation between clients and customers increasing the mutual exchange of information.

This paper contributes a new perspective on the role of sharing emission data through the lens of an SME and its behavior in preparing for future sustainability reporting obligations.

The transition to renewable energy and alternative fuels is already a key strategy to achieve the agreed-upon climate target of limiting global temperature rise to 2 degrees Celsius. However, sectors such as cement production, which are difficult to decarbonize, require additional solutions like Carbon Capture and Storage (CCS) to reduce CO₂ emissions further. CCS involves capturing CO2 directly at the emission source and then permanently storing the greenhouse gas in underground geological formations. Often, the locations of CO2 sources are not close to storage sites, necessitating the development of a new supply chain that can connect these points through various transportation modes and capacities. While pipelines and maritime transport are extensively studied for their capacity to move large volumes of CO₂, vehicle transport, like trucks or trains, presents a viable alternative for the initial phase of CCS deployment or for smaller-scale emissions. This research focuses on the characteristics of emission sources, transportation modes, and the transshipment between them as well as permanent storage sites within the CCS supply chain. To achieve a viable and cost-effective supply chain that can scale with increasing sizes, we formulate the problem as a mixed-integer linear program aimed at minimizing the net present value over a specified planning horizon. The model accounts for both investment and operational costs of various components of the supply chain, including intermediate storage facilities for switching between pipeline and vehicle transportation modes, as well as facilities for altering the conditions of CO₂. The size of the supply chain is constrained by an annual emission capture target, in alignment with CO₂ reduction goals. For a case study, the model is solved using the IBM Solver CPLEX, and preliminary findings are presented. The results are analyzed in terms of cost per ton of captured CO₂ and the selection of transportation modes over different periods within the planning horizon.

On a global scale, organizations are not just passively observing but actively developing responses to address the multifaceted challenges of climate change. Decarbonization strategies and net zero commitments are not just emerging but becoming crucial steps for climate change mitigation and adaptation. This underscores the urgent need for sustainable development, balancing economic growth with environmental preservation and social well-being. The urgency of this issue cannot be overstated, and organizations must act swiftly and decisively to decarbonize their supply chains. Despite these efforts, significant gaps remain in developing and adopting supply chain decarbonization strategies.

Through a literature review, this study aims to identify research opportunities to understand how organizations implement decarbonization strategies by focusing on the practices that precede their implementation, and the factors influencing the adoption of supply chain decarbonization strategies. However, studies on net zero in operations management are still short, with many opportunities for further research. This research focuses on the research gaps around supply chain decarbonization to assist in the transition toward neutrality.

Research must explore which practices are antecedents of decarbonization strategies and what decisions are made regarding supply chain decarbonization strategies. The literature recognizes the need to identify critical determinants in a net zero supply chain context to achieve a competitive advantage (Balci and Ali, 2024). Decarbonization responses rarely consider multiple initiatives in integrated actions. Identifying the ‘best’ strategy is challenging once it varies over time, carbon intensity, and firm-level characteristics (Berger-Schmitz et al., 2023). Thus, it is necessary to examine under what conditions commitments are being translated into emissions reductions and how organizations are developing their supply chain decarbonization strategies to achieve competitive advantages. Operations management scholars need to contribute to understanding how achieving neutrality might affect interactions among all three dimensions of environmental, social, and economic performance (Zhang et al., 2024).

This review supports researchers and practitioners in deepening their knowledge of supply chain decarbonization and its role in achieving broader environmental and organizational sustainability goals. Developing a portfolio of decarbonization measures, understanding the business benefits of net zero strategies, and identifying key factors influencing the adoption of supply chain decarbonization strategies are critical steps for organizations to address climate change. The study provides a foundation for future research that can drive meaningful progress toward a sustainable future.

References

Balci, G., and Ali, S. I. (2024), "The relationship between information processing capabilities, Net-Zero capability and supply chain performance", Supply Chain Management, 29(2), 351-370, https://doi.org/10.1108/SCM-06-2023-0320

Berger-Schmitz, Z., George, D., Hindal, C., Perkins, R., & Travaille, M. (2023), “What explains firms' net zero adoption, strategy and response?”, Business Strategy and the Environment, 32(8), 5583–5601, https://doi.org/10.1002/bse.3437

Zhang, Q., Wong, C. W. Y., & Klassen, R. (2024), “Carbon neutrality: Operations management research opportunities”, Journal of Operations Management, 70(3), 344–354, https://doi.org/10.1002/joom.1303

3D Printing (3DP) has been regarded as a disruptive technology with myriads of benefits, this includes decentralized manufacturing, rapid prototyping, reorchestration and domestication of supply chains, lowering logistics costs, as well as sustainable and circular implications. However, limited focus has been given to integrating 3DP technologies with traditional manufacturing, particularly in the context of demand and production disruptions.

This study investigates the impact of utilizing a single 3DP as a production tool to mitigate disruptions, through considering production of 5 auto parts (side mirror cover, sun visor clip, door lock knob, rear view mirror cover, and a door handle), with a predefined set of demand and production size, the study assumes production, shortage and holding costs as percentages for traditional manufacturing, while calculating the actual production costs for 3DP, including two different infill rates.

On the other hand, to evaluate the effect of disruptions, a Monte Carlo simulation is employed to simulate different probabilities affecting the demand and supply quantities across a large set of instances. This allows to observe the effect of using a 3DP on different part sizes and through different scenarios of demand and production instances. The study uses MS Excel to perform various calculations.

Moreover, we assess the effect through considering several Key Performance Indicators (KPIs): demand fulfillment rate, holding cost, shortage cost, total production costs and unit production costs. Notably, the model shows that holding cost increased when combining with 3DP, as holding cost is a percentage of produced parts, suggesting that other manufacturing strategies as Make to Order, Engineer to Order and Just in Time are better fit for 3DP, thus decreasing holding costs and increasing demand fulfillment rates.

Additionally, part weight plays a major role as a variable, smaller parts mean more parts to be produced, increasing production and holding costs as well as demand fulfillment rate, while decreasing shortages. This is observed for instance for the sun visor clip, door lock knob, and door handle as demand fulfillment rates increase by 28%, 19%, and 15% respectively at a 20% infill rate. Conversely, as part weight increases, the benefits of 3DP regarding demand fulfillment rates diminish. Hence, reducing part weight through utilizing better 3DP designs approaches as Design for Additive Manufacturing (DfAM) practices would yield the positive benefits of higher fulfilment rate while minimizing production and holding costs.

This analysis also shows that 3DP can be beneficial under conditions of low production and high demand instances, with high shortage costs and low holding cost percentages. The practical implications of this study include providing stakeholders with a tool to assess the deployment of 3DP and study its effect on covering disruptions. While future development of the study and the tool can include change in 3DP costs, specifically labor costs, the consideration of other parts, different sets of demand and production quantities, and different production and inventory models. Moreover, validation based on practical case studies should be considered for more robust insights for stakeholders.

Introduction

Offshore wind energy is a pillar in the decarbonization strategy of the German government as there is enough space and steady winds in the North and Baltic Seas to make this a viable and important energy source. The logistics however pose a great challenge especially during the Operation & Maintenance (O&M) phase due to the great distances, harsh winds, and weather conditions at sea. AIS (Automated Identification System) data transmits every vessel’s position, speed, and course-over-ground, at certain intervals based on said speed, which can allow the routes of O&M vessels to be traced. The research was done within the LogReview project funded by the German Federal Ministry for Economic Affairs and Climate Action.

Methodology

To trace the routes of O&M vessels, a large AIS-dataset provided by the Danish Maritime Authority was used. This dataset consisted of 3.5 Terabytes of public available data, in addition to data collected in the LogReview project from three receivers based in the North Sea at the FINO 1, and FINO 3 research platforms, as well at the island of Heligoland. To extract meaningful data from this data set, the following steps had to be done: Data Pre-processing, Data Cleaning, Data Slicing and Data Analysis through means of the Panda library of Python. After these steps, the data was filtered for crew transfer vessels (CTV) and stored in a SQL Lite database. The coordinates in latitude and longtitude of offshore wind turbines, from the research platforms mentioned above, were stored in a library created for this project. The meaningful data was filtered into days and months with both statistical graphs and plotted tracks created using the Python library Folium. With the completion of these steps, it was possible to derive the exact tracks of the Offshore Wind O&M Vessels within the wind farms including the duration of their visit to a particular wind turbine. This further allowing the deduction of the time of O&M procedures.

Findings

The tracks of the Offshore O&M vessels based on AIS-data shows the O&M processes over a longer time period and can help to improve these processes. Better processes will lead to shorter distances travelled and thus lower costs which is one key part to make offshore wind more cost effective.

Discussion

By using AIS data, wind farm operators can use a new tool to make data driven decisions for their CTVs doing O&M. During the first few years of its lifespan, the original equipment manufacturer is responsible for O&M. But after the initial contract is settled, the responsibility shifts to the wind farm owner. Manufacturers typically are unwilling to share their O&M strategies, citing business secret protection. The analysis of AIS patterns will allow for identification of the optimal O&M schedule used by the manufacturer, to decrease costs for the wind farm owner when O&M ownership changes hands.

Conclusion

In conclusion this approach shows that AIS-data can be used to get a better insights into offshore wind O&M processes and provide an opportunity to improve these.

Additive manufacturing (AM) is rapidly advancing from prototyping to industrial serial production but faces persistent quality issues. Most current research occurs in lab settings, focusing on successful print quality and neglecting real-life data and errors that interrupt or spoil print jobs.

To address these shortcomings, we conduct a case study and conduct 13 interviews with AM service providers, AM manufacturers, and AM operators. We target companies in the transportation industry that have substantial experience with AM. This industry is particularly well-suited for AM adoption due to the long operational lifespan of vehicles and the relatively low installed base. With this study, we contribute to a better understanding of main AM printing challenges by asking (i) which factors lead to build failures? and (ii) how can firms develop learning curves to reduce build failures? We focus on the print job itself and excludes the preceding (e.g., part design, data preparation, or material supply) and subsequent (e.g., post-processing, quality assurance) processes. We use an exploratory research design building on qualitative interview data from various AM experts.

We find that build failures occur mainly due to three reasons. First, build failures often occur during the initial setup phase, typically within the first one to three print jobs, due to machine settings, part design, or material characteristics. While these failures are common in the ramp-up phase and must be planned for, they become rare in the serial production phase once print job repeatability is established, although software tools cannot eliminate them. Second, build failures often occur during the first few layers of a print job due to adhesion issues on the build plate, temperature or humidity issues with the material, or calibration of the extruder nozzle and its movement. Operators can mitigate these failures by closely observing the initial phase of the print job, thoroughly preparing and calibrating the printer, build plate, and nozzle, and storing materials in cabinets with controlled temperature and humidity as per ISO/ASTM DIS 52920 standards. Third, build failures can occur due to unforeseen external influences like power blackouts or physical movement of the printer, causing issues such as vibrations, clogged extruders, uneven layers, and extrusion stops. Although difficult and costly to mitigate completely, firms can plan for these events by installing backup energy supplies and positioning printers in locations with minimal physical impacts, though eliminating all possible external influences remains challenging.

We find that learning curves play a major role in mitigating build failures. If firms collect data about print jobs and build failures over time, they become capable of understanding the weaknesses of the print job and mitigating build failures. Learning curves can be developed over time, production volume, and knowledge of operators. Firms can achieve learning curves by focusing on single AM technologies and following quality standards (e.g. ISO/ASTM DIS 52920). Our findings contradict the image of using AM as “plug and play” and support the perspective that companies with little experience should consider using third party AM service providers.

Dairy services are considered as sources of income, employment, nutrition and health for the smallholder rural and urban farmers. The main objective of this study is to assess the inter linkage of dairy farm and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed through calculating the mean values and percentages. Findings show that dairy business in the study area is characterized by shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination to the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at milk production stage is characterized by low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers, producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yoghurt and table butter. Most small-scale milk processors are engaged in traditional production system. Additionally, milk consumption and marketing part of the chain are dominated by the informal market (channel) where market problem, lack of skill and technology, shortage of loan and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

The investigation is to examine intra-organizational supply chain relationships of firms which will help to look and give an emphasis for internal processes and operations strength and achievements to make an influence even for external relationship management and outstanding performances of organizations. The purpose of the study is to scrutinize the internal supply chain relationships with in manufacturing companies located in Tigray. The qualitative and quantitative data analysis methods were employed during the study by applying the primary data sources (questionnaires & interviews) and secondary data sources (organizational reports and documents) with the purposive sampling method. Thus, a descriptive research design was also applied in the research project in line with the cross-sectional research design which portrays simply the magnitude of the issues and problems by collecting the required and necessary data once from the sample respondents. This is because, the study variables don’t have any cause and effect relationship in the research project that requires other type of research design than a descriptive research design, it already needs to be assessed and analyzed with the detail description of the results after quantifying the outcomes and degree of the issues and problems based on the data gathered from respondents. The collected data was also analyzed by using the statistical package for social sciences (SPSS Version 20). The intra-organizational relationships of the companies are moderately accomplished which requires an improvement for enhancing the performances of each units or departments within the firms so as to upgrade and ensuring progress of the companies’ effectiveness and efficiency. Moreover, the manufacturing companies have low industrial discipline and working culture, weak supervision of man power, delayed delivery in the process with in the companies, unsatisfactory quality of products, underutilization of capacity, low productivity and profitability which in turn results to minimize the performance of intra-organizational supply chain relationships and to reduce the companies’ organizational efficiency, effectiveness and sustainability. Hence, the companies should have to give an emphasis to build and manage effectively the intraorganizational supply chain relationships because nothing can be done without creating a successful and progressive relationships with an internal units or functional areas and individuals for the production and provision of the required and qualified products which permits to meet the intended customers’ desires. The study contributes to improve the practical applications and to give an emphasis on the policy measurements and implications of the manufacturing companies with regard to intra-organizational supply chain relationships.

Manufacturing industries have a great role in the development of the world’s economies. However, the relationship with their suppliers and customer are faced with myriad of challenges which, along with the increased competition on the global market and extended supply chains, impact their overall performance. This study was conducted to scrutinize and analyze the challenges of manufacturing firms’ relationship with suppliers and customers in Tigray region of Ethiopia. Data was collected from primary and secondary data sources through questionnaires, interviews, and organizational survey and review of reports. Both qualitative and quantitative approaches were employed to analyze, make discussion, and interpret the data. The results show that low accomplishments have been reported by the manufacturing firms in managing their relationship with suppliers and customers such as low commitment, building unreliable suppliers, low feedback and low quality of information sharing, and adoption of unautomated information and communication technology. Furthermore, the companies didn’t give much attention and have feeble execution in following up customer requests and interests in time, providing consistent services, looking into the future and long-term business opportunity, responsiveness and cooperation which in turn lead to reduced satisfaction of customers, lower demand of the products and decreasing the sales volume, falling profitability and productivity of the companies. Hence, it is recommended that the companies make an improvement and progresses on the accomplishment and adoption of good practices of supplier and customer relationship, which may help them become more effective and efficient. Making frequent communication, maintaining high degrees of trust and commitment, dependency and cooperation, and developing supplier base by providing training may help the companies have better, successful and longer relationships.

Companies are increasingly caught between regulatory pressure, the expectations of their stakeholders and media attention when it comes to sustainability related issues. Supply chains specifically have become a focus of attention due to frequent violations of environmental and labour standards. When analysing sustainability in the context of supply chains, so-called ESG (Environment, Social, Governance) ratings from credit rating agencies are often used. However, these can be opaque, obscure underlying problems and vary from agency to agency. Conducting surveys and interviews in cooperation with companies offers deeper insights into a company’s actions, but is time and resource intensive when aiming to cover the full supply chain. Using available information from the company’s sustainability reports can provide a more in-depth picture while simultaneously allowing for large-scale analysis. To this end, Natural Language Processing (NLP) offers a wide range of tools to use on such text-based sources. This study aims to provide a methodological approach to assess the information present in sustainability reports with a variety of NLP-methods and apply them in the context of supply chain networks. To demonstrate the procedure, a set of reports from two related industries, namely logistic service providers and the aviation industry, was collected. First, it is analysed whether or not the contents of the reports correlate with the ESG performance of a company. Instead of relying on the aforementioned ratings for this purpose, a set of proxies related to ESG issues is used. It is argued that a positive correlation resembles honest efforts, while a negative correlation could hint at efforts to subvert from bad performance or controversies, so-called “greenwashing”. To investigate this correlation, a topic model is employed to cluster the sentences within the reports. Subsequently, a classification algorithm is assigning these topics to their respective ESG dimension. Sentence similarity is then used for the alignment of topics across firm-year observations. The correlation is tested through an econometric model to verify whether the topics discussed in the underlying reports influence the individual sustainability dimensions’ performance of a company.

Urban delivery optimization often involves using Euclidean distances to test routing models and provide practical recommendations. However, the different nature of delivery environments and means of transportation can result in discrepancies between Euclidean distances and actual distances, which then presents a challenge to the effective application of routing models in real-world scenarios. Spatial metrics may offer a way to bridge this gap by helping us understand the structure of networks, as they analyze the connections between locations, provide information about road layouts, and identify bottlenecks and barriers. This presentation will explore the relationship between selected spatial metrics and network efficiency in routing problems, focusing on the difference between pedestrian, bicycle, and road networks in different urban areas. Initial findings suggest that the accuracy of Euclidean distances varies depending on the type of network and the size of the area considered. For localized trips, bicycle and pedestrian routes are generally more efficient than routes for motorized traffic. However, there are some cases where this may not hold true, depending on the overall structure of the transportation network. Therefore, it may be helpful to consider the specific urban structure before applying general findings to real-life scenarios.

Currently, supply chains are characterized by an increasing number of actors, and collaborative solutions have been adopted to enhance value within these supply chains. At the same time, companies are increasingly adopting logistics outsourcing to establish relationships with logistics service providers (LSPs). According to the literature, LSPs are crucial in conducting supply networks and are pivotal in promoting collaboration (Prataviera et al., 2023). However, there remains a gap in understanding their role in fostering collaboration, primarily because most studies adopt a dyadic supplier-customer approach, overlooking the role of LSPs (Luo et al., 2023). Therefore, this study aims to analyze the role of LSPs in promoting collaboration among companies in the two-wheel sector in Portugal. To this end, a questionnaire focused on company interactions, logistics outsourcing, and the quality of relationships was distributed to 92 companies, achieving a response rate of 45.65%.

Three main conclusions emerged from the analysis of the data collected. Firstly, based on Social Network Analysis (SNA), which facilitates the representation of companies and calculation of metrics at both node and network levels, an LSP emerges as one of the key players. LSP provides services to other companies that manufacture parts, components, and bicycle assembly. Secondly, there is a notable adoption of logistics outsourcing, reflecting a trend where companies outsource non-core activities to concentrate on core functions. Notably, transport and customs services are the most frequently outsourced activities, with companies citing flexibility, cost reduction, and improved delivery times as the primary benefits, underscoring the fundamental role of LSP in supply chains. On the other hand, significant barriers associated with logistics outsourcing include commitment and governance mechanisms. Thirdly, regarding relationship quality, significant differences in perception were observed within the LSP-customer dyad across six dimensions studied: trust, commitment, satisfaction, collaboration, communication, and relationship-specific assets. Customers perceive a higher level of trust compared to the LSP. Conversely, LSP rates its customers higher in the remaining dimensions, especially in relationship-specific assets.

This empirical study captures the characteristics of the two-wheel sector in Portugal, focusing on its structure and prominent players. Unlike prior studies that overlooked the role of LSPs, this study explores their role as pivotal network actors, identifying companies' outsourced logistics activities and the benefits and barriers associated with this practice. Moreover, there is also a focus on evaluating the quality of the relationship with the LSP, which makes it possible to capture possible differences in perception in dyadic relationships.

Introduction

The globalization of the international economic system and the progress made in the field of information and communication technologies have led to the development of very extensive trade networks. The accompanying unbundling of production systems, driven by low transport costs, has accelerated the diversification towards global supply and value chains. This well-intentioned idea to promote global economic development led to a relocation of production facilities towards economically favorable regions, in particular emerging and developing countries with mostly low social and environmental standards. As a result of that, the United Nations (UN, 2011) and, subsequently, the OECD (2016, ongoing) adopted guidelines on respecting responsibilities in the global supply chains.

However, international regulations are needed ensuring compliance with due diligence obligations along global supply chains. Various European countries (e.g., Germany) have already adopted regulations, which is why companies in Austria, for example, are already indirectly obliged with corporate due diligence obligations. The EU adopted its Corporate Sustainability Due Diligence Directive (CSDDD) in 2024 which will act as a harmonized legal framework. Its most important goals include, among others, the reduction of human rights related and environmental risks along supply chains and ensuring compliance with the 1.5°C climate target.

This paper deals with the potential effects of regulations which focus on due diligence obligations along the supply and value chains of companies. Based on a survey supplemented by structured in-depth interviews with companies and interviewees in Austria, a critical assessment of existing and upcoming legislation is presented.

Methodological approach

Based on a literature review, a mixed approach consisting of an online survey and supplementary in-depth interviews was chosen as the underlying research method. A compact, yet broadly based questionaire was developed for the online-survey, which comprises a total of 24 questions consisting of single choice, multiple choice and open text questions divided into seven sections. In addidtion to two general chapters on company key figures, comments and contact data, five content-based sections have been considered: introduction to legal aspects, human right related risks, environmental risks, risk management and challenges/risks and chances/opportunities associated with the due diligence acts. A guideline has also been developed for the structured in-depth interviews in order to obtain specific additional information regarding the survey from the interviewees.

Preliminary results

This survey with various partners among companies in Austria will run until the end of June 2024, which is why only a few preliminary results can be analyzed at present. Among the companies survey it turned out, that only a few companies were aware of existing regulations. Some of the supply chain laws surveyed are at least partially known, e.g., the Corporate Sustainability Due Diligence Directive (CSDDD), Conflict minerals regulation (CMR) from EU and USA, Supply Chain Acts from Germany and Switzerland. Others regulations from Norway, the Netherlands, Australia, France and Great Britain are, however, rather unknown. Further results will follow.

Purpose

Truck drivers are a central occupational group within transportation, including about 4.5 million persons within the EU. A major focus in transportation research is safety (Barnett, 2020; Schindler & Bianchi Piccinini, 2021). Existing approaches examined for example sleep patterns (Cai et al., 2021; Onninen et al., 2021) or physical stress (Sekkay et al., 2020) in relation to road accidents. However, mental stress of drivers is increasing due to external time pressure or increased technological complexity (Kamzanova et al., 2014), as is the lack of drivers caused by this and bad working conditions. For this reason, research with a human-centered approach is duely needed. This paper analyzes human factor issues influencing safety in order to contribute to improved conceptual frameworks for road transportation safety.

Approach

Since road traffic is a cybernetic model consisting of subsystems, a mixed-methods approach is used. Human behaviour plays a central role in the occurrence of accidents (Lajunen et al., 2004). Therefore, we use a mixed-method design including interviews to identify both objective and subjective factors which indicate human driver stress. To this end, we combine various vital parameter quantitative data with qualitative interviews. Heart rate variability as a neurocardiac function reflects the heart-brain interaction (Perrone et al., 2021) and can therefore be used as an indicator of mental stress (Taelman et al., 2011). For this reason, a mobile ECG was applied. In addition, the brain exhibits a course of alpha spindles, which reflect the neurological function of alertness (Schmidt et al., 2009). Therefore, a mobile cEEGrid is used as examination method (Bleichner & Emkes, 2020). During stress, cortisol is released (Aguilar Cordero et al., 2014). It is one of the best-known hormones for stress assessment (Antoun et al., 2017) and is analyzed by taking saliva samples. Truck drivers are particularly exposed to external stress factors (Shattell et al., 2010). These include, for example, the driving itself, the behavior of other drivers, visibility, and weather conditions, also collected in the course of this study (Hill & Boyle, 2007). All data is time-stamped to enable synchronization and qualitative interviews were conducted with drivers. These are analyzed in a rule-guided and systematic way (Mayring, 2000). We then use supervised learning methods of AI to identify stressful situations.

Findings

The survey data is diverse, with enclosed Figure 1 showing a small extract. At the top left is an excerpt from the ECG of a driver journey. The top right shows the number of alpha spindles recorded by different drivers over the course of the ride. The changes in a driver’s pulse rate and HRV in different traffic situations are shown at the bottom. The other data was also processed individually and analyzed by machine learning applications. The investigation has brought several new insights. This innovative approach shows that by collecting human-centered data in combination with the use of artificial intelligence, stressful factors can be identified. This approach can contribute to healthier work for truck drivers and an increase in road safety.

The rapid global development in Science and Technology has fuelled economic globalization. This tendency has put pressure on available resources flowing through global supply chains. Supply chains are not only considered as carriers of resources from upstream through to downstream the firm but also strategic assets for competition. To sustain their competitiveness, firms are forced to embrace environmental and social concerns in addition to mainstream economic motives. Research has indicated that firms from both developed and developing countries adopt sustainability practices from varied perspectives (Saeed & Kersten, 2019). There is scanty literature on sustainability in developing countries due to infancy of the sustainability agenda as opposed to the developed world. While Northern researchers focus on matters such as carbon gases emissions and carbon footprint measures and private certifications as remedial actions for reducing impacts of both industrial and human-made greenhouse gases (GHGs) and similar climate change agents (Wakamatsu and Maruyama, 2024; Tsutsumi, Furukawa and Kitamura, 2024; Blanco, 2021; Boukherroub et al., 2017; Jairo et al., 2015), their counterparts in the South are still uncertain and lagging behind except for Brazil, China and India (Saeed and Kersten, 2019:9).

We argue that knowledge about China, Brazil and India does not warrant generalizability for all developing countries. Hence we pose the following research question: which factors determine sustainability adoption by manufacturing firms operating in Tanzania? Responding to this question will contribute to an invaluable understanding of the dynamics involved between developing and developed countries not only because of eminent differences in market conditions but also obvious departures in the rules and standards exercised by the ‘two worlds’.

Theoretically, the study treats sustainability adoption as an innovation and therefore deploys the diffusion of innovation (DOI) theory. Through DOI it is assumed that manufacturing firms initiate sustainable practices and export (diffuse) them to trading partners along the chain. Chain members will adopt them because the prevailing conditions both internally and externally.

Our sample comprised a total of 106 firms which were drawn among first tier supplier and customer firms with manufacturing firms providing recommendations. We collected the data through a questionnaire. We also supplemented our data by conducting interviews with selected company executives and browsing on company web pages. A regression analysis through a probit model was used to analyze the quantitative data while qualitative information was analyzed thematically.

Findings indicate that most firms have adopted sustainable practices along their supply chains. They attributed their adoption to compatibility, external pressure and relative advantage as key factors. The same are significantly and positively related to adoption of sustainable supply chains in the model. However, supply chain complexity is not a significant determinant for adoption. These findings point to policy in two ways. First, policies made to guide the industrialization process should require businesses to internalize sustainability practices right from their inception rather than later. Second, even though the results could be generalized across industries, it is recommended that regulatory enforcement should focus on industry-specific characteristics as sustainability uptake differs across the studied industries.

A systematic review guided by standards of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement was employed whereby different databases including Emerald, Nature and Science Direct were consulted. PRISMA was used to uncover knowledge about CE business models practiced by industries for sustainable logistic operations, the degree of ReSOLVE model implementation in SSA and alignment of Environmental Management Act, 2004, National Environmental Management Policy (NEMP 1997), Five-Year Development Plan (FYDP 2021/22 - 2025/2026) and the Sustainable Industries Development Policy (SIDP 1996-2020) in Tanzania with the United Nations General Assembly, 2015. Five (5) mostly practiced CE business models for sustainable logistic operations were established namely big data driven supply chain management, sustainable production and consumption, crowd sourced logistics, industrial ecology and ReSOLVE framework. These business models have enabled a strategic shift towards circular approaches. Presently, Uber and Bolt operations in Tanzania was highlighted as the best example of urban transport transformation. Also, the ReSOLVE model was found to motivate adoption of renewable energy technologies, resource sharing, and virtualization of processes, although its widespread adoption in SSA is still emerging. Implementation of CE is intrinsically linked to sustainable logistic operations that showed improvements in materials distribution and enhancing reverse logistics such that it is difficult to differentiate the CE practices and sustainable logistic operations.

In addition, this study indicated varying degrees of ReSOLVE model implementation in product design, production planning and sustainable logistic operations in SSA especially Tanzania, Ghana, Uganda, Togo, Kenya and South Africa. Despite the limited adoption CE business models, industrial application of the six ReSOLVE components have been realized. For example, industrial symbiosis is exemplified by a Tanzanian sugar factory whereby wastes from one unit serves as input for another that enhanced resource efficiency and industrial sustainability. Finally, alignment of the Environmental Management Act, National Environmental Management Policy, Five-Year Development Plan (FYDP 2021/22 - 2025/2026) and the Sustainable Industries Development Policy (SIDP 1996-2020) policy instruments in Tanzania with the United Nations sustainability goals is evident. Such that all policies collectively promote polluter pays principle, CE practices, sustainable consumption and shift to renewable energy which are all aligned with the United Nations General Assembly 2015 goals mainly Goal 12.2, 12.5 and Goal 7. However, the FYDP does not explicitly mention the polluter pays principle with the assumption that the EMA and its regulations will be enforced accordingly. Hence, this study provides vital contribution to government policy making institutions in SSA about appropriate CE practices for sustainable logistic operations.

Tanzania's economy heavily relies on agriculture, with 80% of the population employed in this sector, contributing 30% to the GDP. The primary crops for rural households are maize, rice, wheat, cassava, and bananas. Sustainable supply chain management is crucial for the long-term sustainability of the agricultural industry. Recent studies have shown that implementing sustainable practices in the farming transport sector can significantly reduce environmental impact and operational expenses. For example, firms embracing sustainable supply chain management have reduced fuel consumption by 15% and decreased their carbon footprint by 20% over five years.

The study employed three theories – resource Dependency Theory, Stakeholder Theory, and Institutional Theory – to underpin sustainable supply chain management practices in the transportation sector. These theories promoted environmental conservation, efficiency, and social responsibility within the supply chain.

The research methodology involved in-depth interviews and focus group discussions with transporters in Tanzania's Kilimanjaro and Arusha regions. Qualitative data analysis was conducted using NVIVO, which allowed for the organization, coding, and exploration of audio recordings, transcripts, and other relevant documents from the interviews and discussions.

The study found that sustainability awareness in supply chain management is increasing, but transporters still need to improve their sustainable practices. Transporters utilizing renewable energies are few. Those adopting sustainable practices gain a competitive advantage because they offer lower costs. By implementing sustainable practices, transporters can reduce operating costs, offer lower prices, and gain a competitive edge. However, limited resources and cultural barriers hinder the widespread adoption of sustainable practices. Collaboration with stakeholders and government support are necessary to overcome these challenges. This collaborative approach can address these challenges and promote economic development and environmental sustainability in the agricultural supply chain. By emphasizing the role of each stakeholder in this cooperative effort, the study aims to empower and motivate the audience to take action.

The study's findings have direct and practical implications for owners/managers and policymakers. It is recommended that owners/managers embrace the use of renewable energies and SSCM initiatives as a source of competitive advantage. On the other hand, policymakers are urged to develop policies to guide transporters using cleaner energies by making them cheaper and easily accessible. These recommendations are not only feasible but also necessary for the sustainable development of the agricultural supply chain in Tanzania.

In conclusion, the study reiterates its key findings, emphasizing the crucial role of transporters in the agricultural sector in the SSCM framework. It underscores their direct impact on environmental protection, social responsibility, and the overall viability of businesses in Tanzania's agricultural supply chain. The study also underscores the importance of a collaborative approach involving businesses, government, and civil society to address the challenges of implementing sustainable practices within the supply chain. By highlighting the audience's role in this collaborative effort, the study aims to make them feel valued and integral to the process. These findings are significant and provide a clear road map for the future of sustainable supply chain management in Tanzania's agricultural sector.

Global warming and greenhouse gas (GHG) emissions have reached unsustainable levels leading to drastic changes that need to be implemented to reduce and reverse the current GHG outputs. Notably, the automotive industry is seeing a paradigm shift in transitioning from the traditional internal combustion engines (ICE) towards electric powered vehicles (EV). This can be seen in Europe, where there has been a remarkable demand increase of EVs in line with governmental policies on reducing the sales of ICEs. Consequently, automotive original equipment manufacturers (OEMs) are actively pursuing updating their capabilities to accommodate this new manufacturing shift. One of the challenges arising with this shift is how to manage end-of-life battery recycling of EVs.

This study investigates, how OEMs, can gain a competitive advantage within the automotive industry by managing the end-of-life of batteries. Hence, this study develops a critical review of relevant literature, integrating the current state of manufacturing shift from ICE vehicles, EV battery technologies and battery recycling methods. The paper introduces a conceptual framework consolidating the different business functions required to develop a core competence in EV battery recycling. The study then presents an empirical case on one of the leading automotive OEMs in Europe, in which semi-structured interviews were conducted with senior experts responsible for the identified business functions.

The research highlights three main crucial aspects to be considered by OEMs. Namely, understanding the complexity and interdependences of the major factors within the industry, such as regulatory, technological, and financial factors. Secondly, ensuring that the external variables are considered, such as competition rivalry, supplier power and how the company’s internal capabilities can shape these dynamics. Finally, to create a lasting competitive advantage, it is crucial to develop a strategic fit between the business strategy, level of technological and infrastructure maturity within the industry’s evolving market dynamic.

The study concludes that for OEMs to create a competitive advantage via battery recycling, they will need to assess their internal competencies as well the external environment to create a strategy enabling them to become market leaders. Hence, the recommendation for the case in focus is to first capitalise on their current internal strength points as their manufacturing know-how, skilled workers, and their dealer’s network. Second, to create a hub-spoke network to facilitate the efficient and effective management, collection, and relevant processing of the end-of-life batteries within Europe. Finally, developing close collaborations with different stakeholders in the battery recycling industry, to achieve cost advantages through a closed loop supply chain.