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This study aims to explore how the attitudes, motivations and practices of informal entrepreneurs, who choose service exclusion, prevent them from recognizing and taking advantage of transformative opportunities and embracing change.

The authors conducted a two-year study to explore five types of informal entrepreneurs (musicians, street vendors, artists, owners of informal smoke shops and street food vendors). The authors used semi-structured interviews and applied thematic analysis (ATA) of popular music and narratives to shed light on their attitudes, motivations and practices.

The study shows how potential service participants freely exclude themselves from services and transformative service initiatives, preventing them from realizing opportunities and embracing change that can improve their well-being. The study also demonstrates that to serve human needs fairly, service designers need to recognize that some actors require more attention and resources than others to achieve their potential.

The study challenges the notion that any population experiencing vulnerability wants help and chooses to participate in transformative service initiatives. Service participants can, in fact, exclude themselves from services and transformative service initiatives by free will, demonstrating that service exclusion is a multidirectional phenomenon, not unidirectional. Additionally, the paper analyzes narratives gathered from aesthetic expressions, using principles of ATA, introducing music thematic analysis as a research approach.

This article introduces the Responsible AI for Service Excellence (RAISE) framework. RAISE is a strategic framework for responsibly integrating AI into service industries. It emphasizes collaborative AI design and deployment that aligns with the evolving global standards and societal well-being while promoting business success and sustainable development.

This multidisciplinary conceptual article draws upon the United Nations' Sustainable Development Goals (SDGs) and AI ethics guidelines to lay out three principles for practicing RAISE: (1) Embrace AI to serve the greater good, (2) Design and deploy responsible AI and (3) Practice transformative collaboration with different service organizations to implement responsible AI.

By acknowledging the potential risks and challenges associated with AI usage, this article provides practical recommendations for service entities (i.e. service organizations, policymakers, AI developers, customers and researchers) to strengthen their commitment to responsible and sustainable service practices.

This is the first service research article to discuss and provide specific practices for leveraging responsible AI for service excellence.