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Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.

This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.

This study aims to explore how to apply and integrate the performance management (PM) process in humanitarian supply chains (HSCs) among and between humanitarian organizations (HOs) and donors so as to improve cost-efficiency (CE) and lead-time effectiveness (LTE) in the stage of natural disaster preparedness.

This study adapts and operationalizes a framework for the PM process used in commercial supply chains to assess HSCs. A multiple-case study with two types of actors – six HOs and three donors—is used to describe the applications of the PM process and analyze the level of integration between the actors.

The activities in the PM process could sometimes be only vaguely described. Both actors emphasized improving CE, with less emphasis on LTE. Both actors have a low level of integration in each PM process activity, decreasing the CE and LTE. Therefore, guidelines for improving the level of PM process integration are provided.

To the best of the authors’ knowledge, this study is one of the first to combine literature on HSCs and PM process integration, thereby contributing to both literature fields. The concrete contribution of this study is a framework for PM process application and integration among and between HOs and donors.

The PM process framework can be used to assess PM process application, as well as current and increased level of integration, to improve CE and LTE. The current applications can also inspire other HOs and donors.

Previous studies indicate the lack of frameworks in the PM domain of HSCs, especially in the stage of natural disaster preparedness.

This article investigates the application of generative artificial intelligence (GenAI) in experiential learning for authentic assessment in higher education. Recognized for its human-like content generation, GenAI has garnered widespread interest, raising concerns regarding its reliability, ethical considerations and overall impact. The purpose of this study is to explore the transformative capabilities and limitations of GenAI for experiential learning.

The study uses “thing ethnography” and “incremental prompting” to delve into the perspectives of ChatGPT 3.5, a prominent GenAI model. Through semi-structured interviews, the research prompts ChatGPT 3.5 on critical aspects such as conceptual clarity, integration of GenAI in educational settings and practical applications within the context of authentic assessment. The design examines GenAI’s potential contributions to reflective thinking, hands-on learning and genuine assessments, emphasizing the importance of responsible use.

The findings underscore GenAI’s potential to enhance experiential learning in higher education. Specifically, the research highlights GenAI’s capacity to contribute to reflective thinking, hands-on learning experiences and the facilitation of genuine assessments. Notably, the study emphasizes the significance of responsible use in harnessing the capabilities of GenAI for educational purposes.

This research showcases the application of GenAI in operations management education, specifically within lean health care. The study offers insights into its capabilities by exploring the practical implications of GenAI in a specific educational domain through thing ethnography and incremental prompting. Additionally, the article proposes future research directions, contributing to the originality of the work and opening avenues for further exploration in the integration of GenAI in education.

Untimely delivery of goods and services, especially in a post-COVID landscape, is a critical harbinger of end-to-end fulfillment. Existing literature in supplier delivery modeling is focused on penalizing suppliers for late deliveries built into a contractual transaction, which eventually erodes trust. As such, a holistic modeling technique focused on long-term relationship building is missing. This study aims to design a supplier evaluation model that analytically equates supplier delivery performance to cost realization while replicating a core attribute of successful supply chains – alignment, leading to long-term supplier relationships.

The supplier evaluation model designed in this paper uses delivery deviation as a unit of measure as opposed to delivery duration to enhance consistency with enterprise resource planning protocols. A one-sided modified Taguchi-type quality loss function (QLF) models delivery lateness to construct a multinomial probability penalty cost function for untimely delivery. Prescriptive analytics using simulation and optimization of the proposed mathematical model supports buyer–supplier alignment.

The supplier evaluation model designed herein not only optimizes likelihood parameters for early and late deliveries for competing suppliers to enhance total landed cost comparisons for on-shore, near-shore and off-shore suppliers but also allows for the creation of an efficient frontier toward supply base optimization.

At a time of systemic disruptions such as the COVID pandemic, global supply chains are at risk of business continuity. Supplier evaluation models need to focus on long-term relationship modeling as opposed to short-term contractual penalty-based modeling to enhance business continuity. The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre.

The results from this analytical approach offer flexibility to a supply manager toward building redundancies in the supply chain using an efficient frontier within the supply landscape, which also helps to manage disruption and maintain end-to-end fulfillment.

The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. The authors offer a rational solution by creating an evaluation model that uses penalty cost modeling as an internal quality measure to rate suppliers and uses the outcome as a yardstick for negotiations instead of imposing penalties within contracts.

Although e-wallet adoption has grown in recent years, there are some countries like Peru with low penetration rates. Contrary to prior studies that focused on customers' adoption of e-wallets, this study focuses on merchants' adoption to fully understand the use of these services. Additionally, considering that e-wallets are two-sided markets with the co-existence of two distinct economic agents (customer and merchants) interacting through these platforms, this study is the first to assess the dynamics of inter-side benefits from the merchants' perspective. Finally, interoperability was also included to determine its role in countries where the interaction between different e-wallets is limited.

Based on two-sided markets and social cognitive theory, a model was proposed including merchants' perceived benefits associated with the use of e-wallets, for them and for their customers (inter-side). Additionally, technical issues such as interoperability were measured. Data were collected from nanostore owners in Lima in 2022. A structural equation modeling technique was used to determine the impact of both types of benefits and technical features on merchants' adoption of e-wallets. Finally, a polynomial regression with response surface methodology was used to assess the interaction of the benefits for both sides of the platform from the merchants' perspective.

The two-sided-market features of e-wallets were validated. From merchants' view, the use of these platforms is the result of balancing the benefits for them and for their customers, and the interaction between these two types of benefits varies according to the socio-economic level in which the nanostore operates. Additionally, interoperability was found to be important for merchants, so future policies should commit to achieve an ecosystem that facilitates the interoperability not only among e-wallets but also between e-wallets and third-party services. Finally, since service availability is also important for merchants, e-wallet providers should invest in improving their infrastructure's scalability.

Prior studies have mainly focused on the customer side of e-wallets, with little research about the adoption of digital payment methods by the merchant side. In addition, no study has focused on the effect of one of the sides of the platform on the other side (inter-side benefits) when adopting these services. Finally, the effect of interoperability across platforms has not been addressed in detail yet. This study aims to fill these gaps by proposing a framework to understand the adoption of these services by merchants in terms of inter-side benefits and technical issues.

This study aims to present a conceptual framework aimed at promoting educational innovation in supply chain management and logistics (SCM&L). The framework can help to design active learning experiences regarding student learning outcomes that tackle current challenges in the discipline. Emphasizing the significance of linking students’ learning to real-world scenarios, the framework enables reflective learning through hands-on engagement in a constructive alignment, overcoming existing pedagogical limitations in the field.

This study presents a qualitative research methodology that relies on the case study method. Three instances are presented to illustrate educational efforts of active learning in countries of Latin America, Bolivia, Mexico and Peru, linking real-world relevant situations to disciplinary teaching and learning.

The innovative learning experiences introduced in this study transform real-world SCM&L operations into distinctive educational opportunities. These experiences facilitate learning not only within traditional classrooms but also in urban areas of the Latin American region, enabling students to interact with educational partners in authentic settings to achieve their intended learning outcomes. These experiences are characterized by their focus on establishing meaningful connections between learning and local communities, businesses or specific contexts.

The study recognizes various limitations of conceptual, methodological, execution-related and research process aspects. First, not all academics in the SCM&L discipline may universally acknowledge the importance of educational innovation and active learning experiences because of limited pedagogical awareness. Moreover, execution-related limitations arise from the demanding nature of incorporating active pedagogical approaches into courses, as they can be resource-intensive and time-consuming. Regarding research process limitations, the case study limits generalizability and broader inferences because of its particular views and locations, which require further investigation with other instances across other disciplines and geographical regions for validation.

The practical implementation of this framework within the MIT SCALE network for Latin America and the Caribbean (LAC) demonstrates its potential in meeting diverse academic and institutional expectations and providing educational benefits to students.

The study makes a valuable contribution to prioritizing and coordinating pedagogical research by investigating the success of learning outcomes achieved through active and experiential implementations in various contexts. It provides inspiring examples of innovative learning experiences that can drive new developments not only within the LAC region but also in other areas, prompting a shift away from traditional educational approaches.

This research presents a conceptual framework, which is developed from the insights obtained in the three learning experiences to guide future efforts in SCM&L education. The findings demonstrate how to structure active learning experiences based on authentic assessment and illustrate the potential for increased cooperation among institutions in Latin America. It also promotes the recognition of novel SCM&L active learning experiences and highlights some of the benefits of this approach.

This research examines what motivates professional truck drivers to engage in eco-driving by linking their self-reports with objective driving scores.

Theory of Planned Behavior (TPB) is illustrated in an embedded, single-case study of a Finnish carrier with 17 of its truck drivers. Data are obtained through in-depth interviews with drivers, their fuel-efficiency scores generated by fleet telematics and a focus group session with the management.

Discrepancies between drivers’ intentions and eco-driving behaviors are illustrated in a two-by-two matrix that classifies drivers into four categories: ideal eco-drivers, wildcards, wannabes and non-eco-drivers. Attitudes, subjective norms and perceived behavioral control are examined for drivers within each category, revealing that drivers’ perceptions did not always align with the reality of their driving.

This study strengthens the utility of TPB through data triangulation while also revealing the theory’s inherent limitations in elucidating the underlying causes of its three antecedents and their impact on the variance in driving behaviors.

Managerial insights are offered to fleet managers and eco-driving solution providers to stipulate the right conditions for drivers to enhance fuel-efficiency outcomes of transport fleets.

This is one of the first studies to give a voice to professional truck drivers about their daily eco-driving practice.

Food supply chain resilience is a critical aspect in ensuring the continuous and reliable flow of food, particularly in the face of disruptions. This study aims to address specific gaps in the existing literature by conducting a bibliometric analysis. The primary objective is to identify key areas of concern and lacunae related to disruptions and resilience within the food supply chain. The study also strives to contribute to the field by developing a comprehensive framework that evaluates the factors influencing resilience. Furthermore, the research intends to propose effective strategies for mitigating and recovering from disruptions, emphasizing the urgency of these measures in light of identified gaps in the current body of literature.

To achieve these objectives, the authors extracted the most relevant papers from Scopus and Web of Science (WoS) databases. The analysis parameters included a comprehensive review of current food supply chain practices and an exploration of trending research topics, such as sustainability, adaptability, circular economy and agility. Notably, the study recognized the pervasive impact of COVID-19 on food supply chain disruptions, with a high occurrence in the literature. Using advanced analytics tools like VOSviewer and Biblioshiny, the research delved into the role of modern technologies, including Industry 4.0, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML) and blockchain in addressing disruptions and enhancing resilience.

The research reveals a significant impact of the COVID-19 pandemic on food supply chain disruptions, underscoring the critical need for strategies to bolster resilience. Notably, the study identifies the pivotal role of modern technologies (Industry 4.0, IoT, AI, ML and blockchain) in mitigating disruptions and enhancing resilience in the food supply chain. The bibliometric analysis conducted through VOSviewer and Biblioshiny provides valuable insights into research trends and focal areas within the literature.

The observed importance of Industry 4.0, IoT, AI, ML and blockchain implies a practical need for integrating these technologies into food supply chain operations. Moreover, the paper discusses strategies for reducing the impact caused by disruptions, providing practical guidance for resilience planning in food supply chains. Researchers can leverage the findings to direct future efforts toward areas with identified gaps and opportunities, fostering advancements in the field and offering practical insights for real-world applications.

By amalgamating insights from bibliometric analysis and the developed framework, this study contributes to a holistic understanding of the challenges and opportunities in fortifying the resilience of the food supply chain. The identified factors and strategies offer valuable insights for researchers and practitioners seeking to address disruptions in food supply chains. The study’s unique contribution lies in bridging theoretical perspectives with practical applications, enhancing the relevance of business-to-business/industrial supply chain theories.

The field of supply chain management (SCM) needs to attract and retain workers to solve the current talent shortage. The purpose of this research is to identify and evaluate factors that influence career advancement in SCM and compare male and female supply chain experts' perceptions of the importance of those factors.

First, 32 factors perceived as affecting career advancement in SCM were identified by conducting a literature review and consulting 36 experts. Those factors were grouped into four categories: “environmental and structural”, “human capital”, “individual” and “interpersonal”. Those factors were validated via the Delphi method, and ten factors were retained for further study. Second, the voting analytical hierarchy process was used to determine the priority weights experts assigned to these factors. The weights assigned by male and female experts were compared to determine if there were differences between the women's and men's perceptions of the factors' importance.

The findings reveal that the category of human capital factors is the most important, followed by individual factors and the least important is interpersonal factors. The experts consulted for this research emphasized “skills”, “a good fit between an individual and an organization” and “self-confidence” as important factors for career advancement. There were two unexpected results. First, the experts rejected all the environmental and structural factors. Second, no significant difference was found between the male and female groups' evaluations.

Prior to this study, no integrated approach to identify and evaluate the factors perceived which affect career advancement in SCM had been developed. This research is a single empirical and integrative study in France that provides valuable insights for academics and practitioners.