Purpose This study aims to conduct a comprehensive scientometric review of social sustainability in supply chains, analyzing 970 articles published between 2002 and 2024 from Web of Science (WoS). The research addresses the critical gap in understanding social sustainability aspects compared to environmental dimensions in supply chain literature. Design/methodology/approach The study uses CiteSpace software to create structure-based visualizations and networks, analyzing prominent authors, documents, keywords, journals, countries and institutions in the field. The methodology involves systematic review and bibliometric analysis of the literature to identify key themes and patterns in social sustainability based supply chain research Findings The analysis reveals that research is predominantly concentrated in tier-1 and high-GDP nations. Key industries focusing on social sustainability include agriculture, food and beverage, transportation and logistics, manufacturing, fashion and retail sectors. These sectors primarily address issues such as labor regulations, fair wages and local community involvement and diversity. The study identifies major motor themes through co-citation and cluster analysis. Research limitations/implications The study is limited to articles indexed in WoS, potentially excluding relevant research from other databases. Future research directions should focus on advancing social supply chain management, integrating emerging technologies such as Blockchain, sensors and digital transformation, improving risk management, implementing fuzzy logic decision-making and enhancing transparency. Practical implications The findings provide organizations with insights into implementing social sustainability practices across supply chains. The study offers guidance for industry practitioners on addressing social challenges and integrating sustainable practices into their operations, particularly in areas of labor rights, community engagement and technological integration. Social implications The research highlights the importance of addressing social sustainability in global supply chains and its impact on local communities, labor conditions and societal well-being. It emphasizes the need for greater attention to social aspects of sustainability, particularly in developing nations and lower-tier supply chain partners. Originality/value To the best of the authorsâ knowledge, this study presents the first large-scale scientometric analysis of social sustainability in supply chains, offering a comprehensive overview of the fieldâs evolution from 2002 to 2024. It provides valuable insights for policymakers, firms, society and academia while establishing a roadmap for future research and practical implementation of social sustainability in supply chains.
Purpose As retail undergoes digital transformation, the integration of emerging technologies offers new opportunities for delivering services sustainably. This study aims to identify and map the key technological enablers shaping sustainability in retail services. Design/methodology/approach A structured literature review, informed by service-dominant logic and activity theory, was used to identify relevant technological enablers. The interpretive structural modeling technique was used to develop a hierarchical structure of these enablers. Subsequently, the Decision-Making Trial and Evaluation Laboratory method was applied to analyze the causal relationships and interdependencies among them. Findings High-driving enablers include Mobile Payment Systems, Big Data Analytics and Social Media Engagement Platforms. These cascade toward dependent technologies such as Blockchain and Automated Inventory Management. Real-Time Sustainability Dashboards, together with these drivers, exert strong interrelated influence. They create the conditions for effective deployment of downstream technologies and facilitate value co-creation across the retail service ecosystem. Research limitations/implications The study provides a strategic roadmap for retail managers to prioritize technological investments that deliver sustainable outcomes and enhance customer experiences. This approach supports the creation of a more responsible and future-ready retail service system. Originality/value This study presents a theory-informed framework to guide retail managers and service designers in integrating technology for sustainable outcomes. It bridges the sustainability-technology gap in retail service literature.
Web3 technologies, representing the next generation of a decentralised and user-centric Internet, offer innovative solutions to enhance adaptability, sustainability, and resilience in logistics systems aligned with the principles of Logistics 5.0. This study conducts a Systematic Literature Review (SLR) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, analysing peer-reviewed journal articles published between 2018 and 2024 and retrieved from Scopus, Web of Science Core Collection, IEEE Xplore, and ACM Digital Library. The review specifically focuses on trucking logistics, a sector characterised by high fossil-fuel dependency, operational fragmentation, and significant environmental impact. The findings reveal that Artificial Intelligence and Internet of Things technologies dominate current implementations, mainly supporting fleet management, route optimisation, accident prevention, and risk assessment. In contrast, blockchain applications remain limited, and metaverse-based solutions are largely exploratory and confined to training scenarios. Key research gaps include the scarcity of integrated Web3 solutions, the limited consideration of human-centric Logistics 5.0 dimensions, and the lack of large-scale empirical validation in real-world trucking operations. Based on the analysis, this paper proposes a conceptual framework that maps Web3 technologies to trucking logistics areas, investment priorities, and Logistics 5.0 objectives, offering actionable guidance for Logistics Service Providers transitioning from Logistics 4.0 to Logistics 5.0.
This chapter examines how blockchain can act as a trust and provenance layer within freight-oriented Intelligent Transport Systems (ITS). It outlines the core features of distributed ledgers and smart contracts, and shows how they enable secure data exchange, end-to-end traceability, automated payments, and verifiable digital identity for vehicles, containers, and shipments. The chapter maps integration with Internet of Things (IoT), big data analytics, and policy tools so that verified events from the field inform planning, operations, and compliance. Two case studies, involving TradeLens activity at Indian ports and a pharmaceutical cold chain pilot in Germany, illustrate gains in clearance times, auditability, and service reliability, alongside limits created by governance and interoperability. Adoption challenges are assessed across scale, regulation, and organizational readiness. Future pathways couple blockchain with artificial intelligence (AI), automated compliance, and decentralized freight marketplaces. Overall, the chapter positions blockchain as enabling infrastructure for transparent, resilient, and sustainable freight systems.
Asif Ahmad Bhat, Rizal Mohd Nor, Md Amiruzzaman, Md. Rajibul Islam · 5 authors
Blockchain, such as Bitcoin and Ethereum, has received significant attention and widespread usage in recent years. However, blockchain scalability has emerged as a challenging issue. This article explores the existing scalability options for blockchain, which can be categorized into two groups: first layer solutions and second layer solutions. First layer solutions involve network modifications like altering block size, while second layer solutions encompass techniques applied outside of the blockchain. Ethereum, the second largest blockchain, utilizes the Ethereum Virtual Machine (EVM) for executing smart contracts on the blockchain. Currently, there are several EVM-compatible blockchains with noticeable differences. In this study, we evaluated multiple platforms for conducting business processes in trade finance. We considered both Layer 1 and Layer 2 blockchain solutions and examined variations in cost and performance (speed). Based on the evidence gathered in this study, we provide recommendations for system designers to consider when selecting a blockchain platform.
Niels Agatz, Jan C. Fransoo, Elliot Rabinovich, Rui Sousa
Last mile operations (LMO), the processes involved in the critical last stage of delivering goods and services, have widespread relevance across major sectors of the economy, including retail, food services, healthcare, humanitarian services, energy distribution, telecommunications, public services, and others. These operations account for a significant portion of the costs, jobs, and economic output in these sectors. Global economic output involving last mile deliveries alone, for instance, is valued at $165 billion per year and is growing at about 10% per year (InsightAce Analytic 2024). Recent decades have witnessed an acceleration in the rate of evolution of LMO (Agatz et al. 2024; Boutilier and Chan 2022; Boyer and Hult 2005; Dreischerf and Buijs 2022; He and Goh 2022; Lyu and Teo 2022). Technology-driven innovations have catalyzed profound changes in the planning, design, and execution of LMO, with significant implications for the economics of these operations. Extending the last mile to the final user has increased convenience, accessibility, and reliability. Zipline, for example, has introduced drones to safely deliver lifesaving products in remote communities (Ackerman and Koziol 2019). An increasing number of pharmacies in Europe and Africa have been equipped with smart lockers to allow 24/7 access to critical medicines (Gobir et al. 2024). Some innovations leveraging platforms based on smartphone apps have given small corner stores in neighborhoods in cities across Latin America the means to sell and deliver daily groceries and other household staples to local residents (Escamilla et al. 2021). Other innovations, leveraging artificial intelligence, have found applications in vehicle routing tools and warehouse and fulfillment automation (such as Ocado's system (Mason 2019)), track-and-trace systems that provide real-time communications and visibility into delivery processes (such as Instacart and Uber Eats), anticipatory shipping algorithms to move inventories to specific areas ahead of realized demand (Chen and Graves 2021), and integration tools with third-party services (successfully deployed by ClickPost and ShipEngine). However, considerable challenges remain. For example, because of short time frames and high delivery volumes to many dispersed locations, LMO have little room for human error. Yet, since many firms tend to tap into low-skilled, temporary, or crowdsourced labor to provide these services, there is high variability in performance and worker availability. LMO are also expensive, due in part to rising labor costs, delivery failures, more demanding customers, and vehicle and parking restrictions. Although academic research in LMO has a long tradition in Operations Research (see e.g., Agatz et al. (2011), Otto et al. (2018), Boysen et al. (2019) and Reed et al. (2022)), LMO have barely been considered as an operations problem that requires process understanding and management within a sociotechnical system. The need for this is apparent, as increasing evidence points to managerial, economic, and sociotechnical challenges as major determinants of LMO success. Delivery workers have been noted to largely ignore the recommendations by routing algorithms in urban settings (Liu et al. (2023)); working conditions are an increasing societal and corporate concern; and customer experiences are less than satisfactory in many cases. Further, LMO are associated with negative externalities such as emissions, traffic congestion, and the abuse of public parking space. Operational costs are also very highâoften up to a point where LMO are loss-making, such as in grocery home delivery. And, while there have been extensive technological innovations, many seem to fail in scaling at large, which could potentially be due to a poor understanding of the LMO from a process perspective. We need new research to better understand these challenges, as well as to propose new operational practices and business models based on the application of recent innovations. Such research requires a broadening of the phenomenological and theoretical scope of LMO research beyond traditional work in Operations Research. Theories on innovation applied to Operations Management can offer a valuable foundation to study research questions surrounding the scalability of technologies to support new business models in the last mile (Arthur 1994). Similarly, theoretical models examining technology, productivity, and employment can provide a foundation to understand how innovations can change the nature of work in last-mile settings (Autor et al. 2003; Autor 2015). Additional opportunities also exist to use transaction and information cost theories to understand how technological innovations may change organizational boundaries and the nature of organizations in the last mile (Afuah 2003). This confluence of innovations in the field, the multidimensional phenomena that determine performance, and the perspectives from theories from the operations management field provide an opportunity to shape a research program in LMO that will benefit from the Operations Management academic community. This was one of the main goals of our call for papers for the special issue on âInnovations, Technologies, and the Economics of Last-Mile Operations.â Another objective of this special issue was to formalize a research agenda and offer future directions for research to advance our understanding of LMO. To that end, in Section 2, we delve deeper into these operations, their functionalities, distinctive features, and challenges in the context of Operations Management. Then, in Section 3, we expand on research opportunities to tackle the most pressing challenges in LMO and identify knowledge gaps in Operations Management to be addressed in this endeavor. We close in Section 4 with conclusions, recommendations, and potential initiatives to build on the momentum created so far and further advance LMO as a knowledge area within Operations Management. In doing so, we introduce the several papers in the special issue as exemplars of research that can be done in the LMO domain. LMO are made of processes triggered by an agent (e.g., consumer, user, patient, worker, organization) that enable the provision of a service to this agent at the agent's selected location and time (or time period). LMO involve interactions with the agentâwho participates in the process and co-creates valueâand, by definition, comprise different service processes (Sampson and Froehle 2006). These processes are triggered by an agent's request for service and include the preparation and movement of goods and/or tangible resources (people, equipment) required for providing the service to the agent's selected location at the agent's selected time. A key trait of LMO is the fact that agents select the location and time of the provision of the service and that the provision of the service requires at least in part co-location with the agent. We submit that LMO can be classified into two main categories that differ significantly in the nature and extent of the associated customer co-creation activities (Sampson and Froehle 2006): goods-focused and agent-focused. Goods-focused LMO entails the provision of agent access to goods at a selected location and time, involving the preparation and movement of goods (e.g., groceries, meals) and resources (e.g., delivery vans, delivery people) to that location. A typical example would be e-commerce deliveries to consumer homes. Agent inputs are limited, primarily including information about the required goods (product selection and quantities) and delivery (time and location), as well as engaging in minor interactions with the provider during goods reception. The core value added is the movement of the goods to the agent's selected location and time. Goods-focused LMO correspond to âdelivery servicesâ and have received most research attention. Agent-focused LMO entail the provision of more general services to an agent at a selected location and time, involving the preparation and movement of service provision resources (e.g., people, equipment, inventory) to that location. A typical example would be performing repairs of equipment owned by the agent at its selected location, involving the movement of technicians, tools, and inventory (spare parts) to the agent's location. Another example would be an emergency ambulance service, which involves the movement of equipment (vehicle, medical instruments), medical staff, and inventory (medical supplies) to the agent's location. Agent inputs are substantial, including information about the required service, service delivery time and location, and agent's resources, as well as engaging in relevant service co-creation activities at the agent's location. The core value added is the transformation of the agent's inputs (e.g., agent-owned equipment, the agent self). Typically, the level of customization and agent co-creation increases from goods-focused to service-focused LMOs, while the transaction volumes decrease. LMO processes are characterized by a set of distinctive features that raise unique challenges for the management of operations. Based on our conceptualization of LMO and extant literature, we summarize LMO's distinctive features and associated challenges in Table 1. The remainder of the editorial will discuss LMO against this framework and address in more detail several of the distinctive features and challenges. The distinctiveness of LMO processes, their pervasiveness and widespread economic relevance, and the managerial challenges that remain unaddressed jointly motivate the development of a specific research program for LMO within the field of Operations Management. Need to cover very diverse geographical areas, with specific challenges: Reliance on a large number of independent resources (including subcontractors, crowdsourced labor, inventory, contracted or rented equipment, third-party platforms) has the following implications: The features and challenges presented in Section 2 provide a framework for the development of new LMO research that can broaden the scope of LMO subject knowledge, as well as strengthen the theoretical foundations supporting LMO research. This framework also serves as a reference for new research to inform about new technologies and business models in LMO and their implementation and execution. The remainder of this section expands on these research directions. Research on LMO has concentrated on goods-focused LMO, in particular the delivery of goods from a transportation hub or inventory location to an end consumer. As discussed in Section 2, we propose a conceptualization of LMO to include LMO, which also LMO with a of and the of agent a diverse set of such as and of goods and services, also organizational in with we to expand research to a set of LMO. more be given to LMO. services are in this to to and such as vehicle and services at Another area in point is the of can request of products local In this a of goods-focused and of products need to be to and more research is involving LMO. An area of application is LMO supporting services by as part of the growing of (or et al. 2021). For example, of tools need to support equipment across dispersed customers, with of and for and activities at Similarly, of equipment in the provide such tools with their at their given the of LMO on public and the research LMO increasing the of settings beyond For example, in there are many LMO innovations by changes in the and (e.g., Lyu and Teo 2022). In the on and human corporate et al. are to major on LMO (e.g., the of such as and for with and for the economics of the negative externalities of In in the and are the of specific LMO to agents and Although these LMO settings are features, and there is the opportunity to further and increasing its provide opportunities to on how innovations from one could be to In our understanding of LMO can benefit from the knowledge from goods-focused LMO. given the of LMO in the research could benefit from a that beyond may considered in their can be by examining the within the For example, while the of consumer points in may deliveries and the of the LMO service may by the as by to their This of the transportation can to less routing and potentially This requires a of the LMO system. in a context and challenges associated with LMO call for more research to the in Operations Research different in this space. research is to the of LMO, with a to a on the and of these operations. The we provide in this as well as the papers in this special many opportunities for research in LMO. for instance, the by et al. and et al. how an can key in LMO to beyond Research on LMO has been from an Operations Research with a on we a and theoretical framework the scope of LMO. a understanding of LMO would benefit from the distinctive of LMO and associated challenges in an the nature of the challenges, such diverse theoretical In this we areas for future development in LMO. The understanding of the LMO challenges associated with the need to agent demand and high variability would benefit from of knowledge from service operations (Sampson and Froehle 2006). LMO service processes, have received from this perspective. are of the service, introduce operational provide opportunities to the service, and significantly operational service need to agents et al. and and service 2006). of relevant agent in include of deliveries at lockers in e-commerce of products information by the service or with the of the service of relevant service operations include service and (e.g., and the integration of of service delivery (e.g., et al. in this special to in service as a of variability with inventory, and et al. and the use of management to agents to that and operations (Agatz and et al. For instance, grocery use in their home delivery services to more delivery time (Agatz et al. 2021). The of LMO challenges associated with processes would from a of operations and 2021), operations et al. and operations et al. 2022). This of knowledge can a deeper understanding of the significant that LMO process (e.g., crowdsourced labor, agents the management and performance of LMO processes (e.g., et al. 2024). In the there is a for increasing automation and and which to the need to further how and by and agents LMO on LMO processes by public call for of urban and urban et al. in the and execution of LMO. For example, LMO in areas can provide can also be to neighborhoods in of of and and The study of the economics and operational associated with a of and of activities that are with that are from on business models (e.g., platforms and models et al. as well as integration (e.g., and and (e.g., et al. We offer a final for development in LMO, to the of of LMO deployed in across different sectors and These involve a large number of that need to be LMO the of and and and would be a for the of knowledge (e.g., which of LMO are to which The costs of the with the in and technology, have to a very development of new tools to the These new tools to the challenges due to the high cost of labor and the labor of many of the LMO The most have been in as delivery or These to at cost because labor in the delivery The may in be with traditional such as an vehicle from a delivery As with of the LMO extensive research has been on the of its operations in many research has been from a service process such as the with the agent the service, or operations on the and the of the vehicle with the public that for delivery has been for a very long time, and applications can be scaling and of of these technologies to be We understanding of such scaling or which conditions scaling would be A set of technologies to the with the for the use of smart a service process this is as changes the operational and is by the of the agent. has been to this in close with an implementation at a large and Teo 2022). In are with the of as agents in the service in of lockers and high costs per is a need for future research that consumer within the management of operations. The extensive of and of across the last mile has for extensive use of This for extensive of delivery delivery and et al. and to future and agents on to et al. 2022). to many other of in the may ignore the information or system and the service business models have in that have LMO across different These include in the delivery of products and services to The benefit of these models is that transaction costs and and service offer access to products and services, and such that a per or could high operational the economic of these models in on transaction costs and involved in consumer demand for in inventories and for services in the of by service more in the of these is the of and on different of these platforms and have examining in platforms (e.g., et al. and In very have these on We are of research by et al. This research on local grocery delivery platforms to that consumer demand increases with the number of in these and This has implications for operations in these platforms since that these can in and inventory management and Additional research is to LMO platforms in other settings to identify This would involve in these platforms are in the number of and these are is that and there is an economic to many may the from these As a will be subject to negative externalities the number of may be subject to negative externalities on the because increases in the number of can increasing costs in consumer demand at these economic models have primarily the of LMO implications would need to include operational such as and For instance, for delivery with very short delivery there be very opportunity for to very high costs of operations for these to to the preparation of be in the the of a at a for or the preparation of a in a these operations have been largely from the last-mile delivery delivery these operations to with and into the LMO. For instance, an understanding from an operations would better understand the economics and of grocery which has and very in the and which to be in and In this special the work by et al. the in the of LMO in delivery. Other models have based on the use of to These include and access to fulfillment for an Although evidence that significantly their this may value with this may on added operational as change their to from their These may costs and other to the from for these will be to the economic value of models in to other To our knowledge, the has to address these In other costs are different service work to support the LMO. For instance, has the where independent as points and delivery with the This with in (Escamilla et al. 2021). In delivery has also such a for a long time et al. In this special the work by et al. how of can be by a operations with a delivery also how is has that this requires and execution across many independent for which this service is a is a need for research to understand the operations of this business from such as and process questions for other business models where delivery is crowdsourced in part or in An to LMO models involves systems by and to the drones and have an extensive in Africa delivering medical emergency in areas with poor have operations in with an on in technologies delivery for food delivery on and part deliveries on research questions to scaling and where these extensive development in specific with an to to in public space. extensive research has been on for delivery LMO research questions to the the customer interactions and in the service and the business development performance offer extensive opportunities for and Further, a better understanding of the conditions which this business can be is an research that is largely in a better understanding of a LMO. is extensive in the LMO on routing with little to routing execution. a have the of in execution and their on future demand for services and products et al. et al. Similarly, have the of such as parking on the execution of LMO et al. 2022; et al. 2024). A of opportunities to expand on this For example, research could information routing and could also consumer (e.g., to and service to the delivery in a of to resources and service also exist to the use of artificial to points of routing for and demand for more The also largely in the information in LMO, in the in the delivery of goods to the two with the of applications based on geographical information systems and geographical systems most of these have been to in apps by workers to their delivery As with most other processes, is subject to in inputs to These can be to a from a location service in the an of a of delivery an of these and their in These significantly last-mile delivery operations this we are of research to the and relevance of this has been primarily as a technological there is a of understanding from a process and perspective. can be from how research on inventory in has extensive research in Operations Management et al. is in the LMO context is how delivery agents have been to information that is very to from LMO execution in to have been subject to extensive of to has been in the of and in other sectors. In the of work to management has received extensive providing a very different on and operations and We there is a need and opportunity for and work on this for LMO. its growing and in many and across business LMO has received little in the operations management In research on LMO has been in the operations research We that LMO is a service that in close with the agent the As work on LMO can build and on the extensive on service operations. The of LMO is a of the in which has been by the of new technologies and the associated development of new business models the two many have been on many of the new have been less about the and and of their LMO. As the for better understanding and of the LMO more the challenges and the work on LMO extensive and research that our understanding and new LMO technologies and business models on a with many of theoretical understanding better operations that can deliver the service at a cost and the negative work can in the of the many technologies that The papers in this special issue selected from a of and provide and perspectives on LMO. to the Operations Management on LMO across the retail, and food service The by and to to Last-Mile on In this to and inventories across fulfillment to last-mile delivery by in consumer based on a with a service provider a of fulfillment the involved in these and the need for to across these In their Last-Mile Delivery and address the LMO economics and operational and the of on independent resources from third-party study the integration of a major grocery delivery with a third-party last-mile delivery that the integration for the delivery and the has implications for understanding the economics of these LMO The by and and for an Delivery on the delivery and to delivery performance and customer The and based on a study with a last-mile delivery to identify these and to delivery time, delivery and customer future the by and and Delivery An of on to how real-time demand and delivery reliability. The study from in with a last-mile delivery to an real-time demand and delivery and a and delivery reliability. these papers the of our framework presented in Table we a on features 2, and address the economic and operational challenges of dispersed customer demand with service delivery. these to advance our understanding of economic and operational in LMO, opportunities remain for the other LMO and in the public research on LMO would benefit from a including human as a service delivery worker, as a and as a use of the public space. In doing so, LMO research has the potential to expand the field far beyond the extensive work that has been done in transportation and operations on and to different theoretical perspectives within the field, as well as relevant with as diverse as customer labor business information and urban We are to the of Operations and for their We would also to the and for their to the special
Infrastructure maintenance is inherently complex, especially for widely dispersed transport systems like roads and railroads. Maintaining this infrastructure involves multiple partners working together to ensure safe, efficient upkeep that meets technical and safety standards, with timely materials and budget adherence. Traditionally, these requirements are managed on paper, with each contract step checked manually. Smart contracts, based on blockchain distributed ledger technology, offer a new approach. Distributed ledgers facilitate secure, transparent transactions, enabling decentralized agreements where contract terms automatically execute when conditions are met. Beyond financial transactions, blockchains can track complex agreements, recording each stage of contract fulfillment between multiple parties. A smart contract is a set of coded rules stored on the blockchain that automatically executes each term upon meeting specified conditions. In infrastructure maintenance, this enables end-to-end automation-from contractor assignment to maintenance completion. Using an immutable, decentralized record, contract terms and statuses are transparent to all parties, enhancing trust and efficiency. Creating smart contracts for infrastructure requires a comprehensive understanding of procedural workflows to foresee all requirements and liabilities. This workflow includes continuous infrastructure monitoring through a dynamic, data-driven maintenance model that triggers necessary actions. Modern process mining can develop a resilient Maintenance Process Model, helping Operations Management to define contract terms, including asset allocation, logistics, materials, and skill requirements. Automation and reliable data quality across the procedural chain are essential, supported by IoT sensors, big data analytics, predictive maintenance, intelligent logistics, and asset management.
The construction industry is known for its intricate and fragmented nature, often plagued by inefficient processes and data management challenges. Distributed Ledger Technology (DLT) presents a promising solution, potentially revolutionizing data sharing, transparency, and security. However, the successful adoption of DLT necessitates a comprehensive understanding of its implications, effective organizational changes, and strategic implementation strategies. This study examines the critical factors in adopting DLT into construction processes and workflows. A mixed-methods approach was employed, combining quantitative surveys and qualitative interviews with key stakeholders in the Nigerian construction industry. The findings emphasize the importance of educating staff about DLTâs benefits, strategic planning aligned with business goals, collaboration with DLT experts, universities, and industry partners, careful planning and robust security measures, and organizational changes such as dedicated DLT teams and engaging suppliers. Recommendations include prioritizing continuous improvement, investing in training programs, and exploring integration with emerging technologies. The study provides empirical insights into DLT adoption challenges and strategies, synthesizing these findings with existing literature, and offers a roadmap for construction firms, policymakers, and researchers seeking to leverage DLT for enhanced efficiency and innovation in the construction industry.
The integration of Artificial Intelligence (AI) and Big Data Analytics (BDA) into Supply Chain Management (SCM) has transformed the industry by enhancing efficiency, accuracy, and responsiveness. This review paper provides a comprehensive analysis of current AI applications in SCM, focusing on demand forecasting, inventory management, logistics, and transportation. Various AI techniques, including time-series forecasting, clustering, neural networks, SARIMA, and LSTM models, are discussed in detail. The impact of cutting-edge technologies on supply chain traceability and efficiency, such as blockchain and the Internet of Things (IoT), is also examined in this article. Despite the significant advancements, challenges such as gaps in closed-loop supply chains, terminology inconsistencies, and the need for better technical-managerial alignment persist. This review recognizes future research directions to address and solve these challenges and highlights the potential for AI to drive further innovations in SCM. Through case studies and bibliometric analyses, this paper underscores the significance of a comprehensive strategy for supply chain redesign, integrating physical, facilities, and information management to enhance sustainability and market responsiveness. Keywordsâ Supply chain management , Artificial Intelligence (AI), Big Data Analytics (BDA), Demand forecasting, Inventory management, Logistics optimization, Blockchain , Internet of Things (IoT), Smart Transportation, Tactical planning, Strategic planning, Advanced available-to-promise (AATP), Sustainability in supply chain.
Krzysztof Gogol, Johnnatan Messias, Maria InĂȘs Silva, Benjamin Livshits
Late 2023 witnessed significant user activity on EVM chains, resulting in a surge in transaction activity and putting many rollups into the first live test. While some rollups performed well, some others experienced downtime during this period, affecting transaction finality time and gas fees. To address the lack of empirical research on rollups, we perform the first study during a heightened activity during the late 2023 transaction boom, as attributed to inscriptions - a novel technique that enables NFT and ERC-20 token creation on Bitcoin and other blockchains. We observe that minting inscription-based meme tokens on zkSync Era allows for trading at a fraction of the costs, compared to the Bitcoin or Ethereum networks. We also found that the increased transaction activity, over 99% attributed to the minting of new inscription tokens, positively affected other users of zkSync Era, resulting in lowered gas fees. Unlike L1 blockchains, ZK rollups may experience lower gas fees with increased transaction volume. Lastly, the introduction of blobs - a form of temporary data storage - decreased the gas costs of Ethereum rollups, but also raised a number of questions about the security of inscription-based tokens.
Last mile delivery as a challenging area of supply chain is facing growing challenges for e-commerce firms. One of the most important aspects of these challenges is related to the sustainability of last mile delivery. This study has targeted customers' awareness and eagerness to play an effective role for sustainable last mile delivery. The paper has also focused on the capabilities of blockchain technology for enabling the tracking and tracing of the contributions of the customers through NFT (non-fungible tokens) tokens. The paper has designed surveys to examine the awareness and tendency of customers for sustainable last mile delivery. It has been found that there is a significant gap when it comes to completely understanding the blockchain and its potential benefits in terms of reducing CO2 emissions concludes. The results show that a high proportion of respondents who indicated a willingness to delay and consolidate deliveries if offered an NFT token incentive. Finally, it has been concluded that there is high potential for blockchain technology to promote sustainability in the last mile delivery industry.
Innovations can help ports become smarter and more effective and differentiate themselves from competitors. This study aims to explore the current state of innovations and smart technologies at Brazilian ports. The study sampled sixteen ports, representing 70% of port movements in Brazilian public ports in 2021. This is an exploratory and descriptive field study involving qualitative analysis. The results show that the surveyed ports are seeking strategies to innovate. Only one of the surveyed ports had a registered patent. Half of all ports had agreements with educational/research institutions, companies, or other ports for developing innovations. By contrast, no port engaged in technology transfer contracts with educational/research institutions, companies, or other ports. Few surveyed ports collaborated with HUBs, laboratories, or innovation centres. The three most widely used smart technologies at the surveyed ports were cloud computing, automated systems, and drone technologies. This study shows that Brazilian ports are undergoing a transformation process, but they find themselves in different stages of maturity regarding the appropriation and development of new technologies. New technologies are still incipient for some ports, while others have yet to adopt them. For example, only a few surveyed ports used smart technologies such as the Internet of Things, blockchain technology, or automated systems. Innovations and the inclusion of new technologies can generate benefits, but they require time and financial resources.
The rapidly growing e-commerce sector has created new opportunities and challenges to the logistics industry. Nonetheless, the majority of Hong Kong logistics industry, especially small-and-medium (SMEs) firms, lack operational decision support to adequately handle the seasonal, fragmented, and fluctuating e-commerce orders. To grasp the opportunities of the e-commerce logistics business, logistics service providers (LSPs) should enhance their capability in information exchange and operational planning. With these improvements, the logistics industry would be better able to sustain and expand their e-commerce logistics business. In this paper, a Blockchain-based E-Commerce Analytics Model is developed to enhance digital supply chain integration. Firstly, timely operational decision support would be achieved as blockchain technology, after that, the ML algorithm would enable the logistics industry to manage data efficiently and to forecast dynamic e-commerce order demand. Subsequently, the proposed model allows LSPs to flexibly re-allocate the right number of resources in real time to deal with the hour-to-hour fluctuating arrival of orders in distribution centers. Additionally, the proposed model enables logistics practitioners to predict the sales performance related to e-commerce.
S. Thangamayan, Kalyani Pradhan, Ganesh Babu Loganathan, S. Sitender · 6 authors
The typical food traceability systemâs data layer is made up of relational databases managed by core businesses, which cannot ensure data security. It is inefficient and requires a lot of upkeep. The food supply chain has numerous actors, making it difficult for consumers to safeguard their rights when purchasing food with quality issues. Due to the numerous organizations involved in the food supply chain, food safety monitoring and traceability have become challenging. The supply chainâs major organizations have control and administrative authority over the data under the current food traceability system, which is overly centralized for traceability information. The safety and dependability of food may be ensured by using the food traceability system to track food information. We can witness a series of detailed insights into food from the manufacturing source to the consumption terminal. A blockchain-based food tracking system is created as a solution to these issues. On the Ethereum platform, the system was created. It was also employed in the blockchain system, in addition to its features of decentralization, tamper-proof, and traceability. To implement the data update service and the food recall function, introduce the Food and Drug Administration node. Consumers have the option to not only enquire about food traceability throughout the manufacturing process but also to file complaints regarding the traceability systemâs rights protection.
Kadim Lahcen Nadime, Jamal Benhra, Rajaa Benabbou, Salma Mouatassim
The rapid growth of e-commerce has placed considerable strain on traditional logistics systems, prompting a need for innovative solutions to optimize delivery processes and enhance customer satisfaction. This research paper presents a decentralized crowdsourced delivery application that leverages blockchain technology and smart contracts to address the challenges faced by centralized logistics models. The proposed system allows e-commerce companies to outsource product deliveries to carriers from a diverse pool, offering greater flexibility and cost-effectiveness while also enhancing transparency and trust among all parties involved. Built on the Ethereum blockchain, the application manages both the delivery and return processes, generating verifiable proofs of delivery (PoD) and proofs of return (PoR) for each transaction. The paper provides a comprehensive analysis of the system architecture and the implementation of the application using smart contracts. Furthermore, it explores the potential impact of the proposed system on e-commerce companies, carriers, and customers, and identifies challenges and future directions for research and development in this field. The findings of this study contribute to the ongoing discourse on the transformative potential of blockchain technology and crowdsourcing in the e-commerce logistics industry, offering valuable insights into the design and real-world application of a decentralized delivery system.
Jun Chen, Shiyan Xu, Kaikai Liu, Shuqi Yao · 6 authors
In order to cut down on costs to the greatest possible extent, enterprises hope to distribute goods to different customers at the lowest costs possible. Based on this, this paper proposes an optimal location method for an intelligent transportation logistics warehouse. This scheme combines a variety of complex mechanisms to allow IoT devices to provide input. The scheme makes full use of the irreducibility of a blockchain system to promote the development and design of blockchain logistics applications. This method is aimed at tracking the progress of transportation of products in the whole supply chain. Experimental results show that, compared with traditional methods, the optimal positioning method has the advantages of fewer calculations, a high positioning accuracy, and a low overall cost, and it obtains the best warehouse positioning results. Based on the Internet of Things and blockchain technology, the application of intelligent logistics systems enables enterprises to intuitively understand their current inventory and the transportation status of goods, thus better controlling changes in enterprise resources.
Ella Tallyn, Joe Revans, Evan Morgan, Keith Fisken · 5 authors
Smart contract systems could change the nature of last-mile delivery for the better through enhanced precision, coordination and accountability. However, technological complexity poses a challenge for end-users participating in the design process, making it hard to explore their experiences and incorporate their perspectives. We describe a case study where technological prototypes create smart contract experiences for professional couriers and receptionists, allowing them to speculate about emerging possibilities, whilst remaining grounded in their current practices. Participants enacted a series of deliveries, choreographed by smart contracts, and their responses were explored in post-experience, one-to-one interviews. Working with professionals to explore the potential impact of smart contract technologies, revealed the systemic webs of value underlying their existing work practices. This has implications for design of such technologies, in which increased automation, efficiency and accountability must be delicately balanced with the benefits of sustaining personal values, relationships and agency.
Blockchain technology is provoking significant transformations in the logistics industry, creating a complex environment that challenges business change. This study endeavors to advance the research regarding blockchain-based logistics management by identifying tensions and paradoxes accompanying blockchain adoption for handling digital freight information. Addressing the gap of scarce empirical research on adopting this technology, we conducted 12 expert interviews in the German logistics industry. While confirming and advancing previous research, we found several incompatibilities between the technology and its application, as practitioners tend to adopt blockchain features selectively instead of full acceptance of the respective privacy model. Our analysis reveals that the automation of several functionalities on a platform is among the features of blockchains with the greatest potential to create change in handling digital freight information when related governance mechanisms are in place. Building on these findings, the study proposes main strategies to manage the observed tensions, particularly separation, differentiation, and integration strategies. Thereby, our research contributes to the understanding of digital transformations based on immutability and disintermediation when logistics service providers are engaged in blockchain projects.
The problem of minimizing the number of intermediaries in the supply chain is long overdue in the logistics industry. How to carry out logistics operations without the participation of a large number of intermediaries, whose main task is to guarantee the transaction and document flow? Is this possible with Blockchain technology? While this technology is still evolving, there are still many challenges that remain to be addressed. One of the main challenges in implementing this technology in logistics is to reach agreement on its use among all stakeholders. When interaction between different stakeholders in the supply chain with different interests is achieved, then the full potential of this technology to improve the efficiency of logistics processes will be revealed. This will facilitate the emergence of new business models and processes in global trade logistics and increase transparency in the supply chain. Smart contracts with embedded business rules promise not only to reduce transaction costs but to create more agile value chains that enable closer cooperation.