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This chapter presents the main findings of the EU-funded SATORI project on ethics assessment of research and innovation (R&I) in its first 18 months. It offers summarised descriptions of the ways in which ethics assessment and guidance of R&I are currently practiced in different scientific fields, in different countries in Europe, the United States and China, and in different types of organisations.

The main findings include the following. Although the most extensive institutions, policies and activities exist in the medical and life sciences, there is evidence of a growing institutionalisation of ethics assessment in non-medical fields. Increasing coordination and cooperation between ethics assessors can be observed at the EU and global levels. Each of 15 types of organisations that were studied performs an important role in ethics assessment, which may not always be well established and sometimes poses significant challenges. Although significant differences exist among the countries that were studied in terms of the degree to which ethics assessment of R&I is institutionalised, all seem to be expanding their ethics assessment and guidance infrastructures.

The findings are an important means by which partners in the SATORI project will take their next steps: the identification of best practices, the development of proposals for harmonisation and shared standards, and, to the extent possible, the proposal of common principles, protocols, procedures and methodologies for the ethical assessment of research and innovation in the European Union and beyond.

Business and operational excellence models are frequently employed by organisations as self-assessment tools for ensuring continued performance improvement. This paper presents an integrated methodology for excellence self-assessment that is applicable at organisational and functional levels.

The self-assessment methodology was sequentially developed, based on a theoretical and practical perspective, and a case study was presented.

This study develops: (1) a framework of excellence enablers and results criteria for each of the organisational, functional (core and supportive processes) and operational levels; (2) a framework of the characteristics of maturity levels of excellence according to enablers, results, organisational context, in addition to other assessment components; (3) a framework of the assessment and improvement steps for achieving excellence.

Although several proposed methodologies are available for the self-assessment of business and operational excellence, these only partially focus on various organisational aspects (such as the organisational and functional level, and organisational context) and are primarily used as business excellence models by non-large organisations. This study aims to fill the research gap in this regard.

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.