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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.

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 chapter explores how customer's attributes, shopping behavior, and preferences affect the retail choice in fiercely competitive retail environments of megacities from developing countries. We study how small, family-owned retailers (i.e., nanostores) compete against organized chains from the modern channel (i.e., convenience stores and supermarkets) at different socioeconomic levels in 9 out of 16 boroughs from Mexico City. Primary data were collected using a combination of instruments (i.e., observation, interviews, and surveys) that were applied to relevant stakeholders of the retail footprint where nanostores develop their operations. We analyze the data via statistical tools such as descriptive statistics and independent nonparametric tests to understand the significant factors of the competitive landscape in which nanostores are immersed. We supplement our research methodology by using causal loop diagrams to identify opportunities in the way suppliers, shopkeepers, competitors, and customers interact with each other and new business models for the nanostore supply chains. By breaking down our result analysis into low-, middle-, and high-income areas, we provide insightful recommendations to increase nanostores' survival, improve their operations, and grow them in Mexico City by addressing issues from the supply, store management, and customer service.

The field of Supply Chain Management (SCM) has mainly focused on applications for large firms, where significant amount of theory has been developed in the last decades. Little attention has been received by micro and small enterprises (MSEs) that in Latin America represent approximately 99% of all businesses and are the key for the development of the economy, employment, and growth of the region. Due to MSEs' lack of productivity, only a fraction of them survive and thus contribute to Latin America's economic growth. In this chapter, we discuss the connection between MSEs' productivity growth and SCM. We present key takeaways from the literature and summarized different research approaches used to study this emerging field, specifically related to the impact of the size of the company, the use of surveys to gather data, and the importance of field interventions. We also present a large-scale project (i.e., MIT GeneSys) that focuses on improving survival of MSEs in developing countries and discuss some preliminary learnings gained via conducting shadowing/immersion of ∼250 MSEs from Mexico, Colombia, Chile, Ecuador, Peru, and Bolivia. We conclude the chapter by presenting some recommendations for the future research agenda for the emerging field of SCM for MSEs in Latin America.

Food manufacturing companies which are essential for national economies, need to attach importance to the adoption of both the lean manufacturing (LM) operational excellence methodology and the Industry I4.0 (I4.0) technologies that empower LM to achieve operational improvement. This study aims to focus on the Greek food manufacturing companies and determine the degree of implementation of LM practices and I4.0 technologies and the impact of I4.0 on LM.

A survey was conducted based on a structured questionnaire which included items reflecting LM practices and I4.0 technologies. A sample of Greek food manufacturing companies were approached and 102 of them fully completed the questionnaire. Descriptive statistics were applied to determine the degree of implementation of LM practices and I4.0 technologies, while the impact of I4.0 on LM was determined through the linear regression analysis.

The degree of implementation of LM practices in the responding food manufacturing companies is high, while the degree of implementation of I4.0 technologies is low to medium. The findings also support a significant and positive impact of I4.0 on LM.

The small size of the sample of the responding Greek food manufacturing companies, the subjective character of the data collected and the cross-sectional nature of the study, constitute the main limitations of the study. Based on these limitations, further studies can be designed.

The present study findings can guide the managers of the food manufacturing companies to further increase the degree of implementation of LM practices through adopting I4.0 technologies. Therefore, they can improve quality, eliminate waste, survive and be more competitive in the current difficult business environment. Academics can also benefit from the present study, given that it provides the LM practices and I4.0 technologies that can be further tested and validated in the food sector.

To the best of the authors’ knowledge, this is the first study that focuses on LM and I4.0 in the Greek food manufacturing companies operating in a business environment where the crises of finance, energy and the Covid-19 pandemic dominate.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

The purpose of this paper is to present a systematic approach to conduct a diagnosis of the current status of a company’s quality management systems (QMS) and business processes.

The approach proposed is based upon the assessment of the maturity level of a company’s QMS, for which a “maturity diagnostic instrument” is also proposed, a self-assessment exercise using a business excellence model and a first-party quality audit.

The integration of a QMS’ maturity assessment, a self-assessment exercise and a quality audit may provide a more thorough evaluation of various company’s systems and operations. This paper provides organisations, and their managers, with a systematic approach to help them understand better the current performance of their QMSs and business processes.

This paper’s main contribution consists in the proposal of a novel approach for organisation to measure and understand the status of their QMS and business processes. Subsequently, better management decisions to improve a company’s operations can be taken.