Publicação
From Tech to Tables: RAISA’s impact on employees and restaurant efficiency
| Resumo: | This study explores the perceptions, attitudes, and experiences of restaurant professionals toward the adoption of robotics, artificial intelligence (AI), and service automation (RAISA) technologies within the hospitality sector. Grounded in an integrated theoretical framework that combines the Technology Acceptance Model (TAM) and the Information Systems (IS) Success Model, the research aims to evaluate fourteen propositions (P1–P14) concerning the relationships between constructs such as Perceived Usefulness, Fear of AI, System Quality, Behavioral Intention, and Net Benefits. A qualitative methodology was adopted to gain indepth insights into the lived experiences of industry practitioners, with data collected through ten semi-structured interviews with both founders and employees from restaurants and hospitality businesses based in Lisbon, Portugal. The transcripts were analyzed using MAXQDA 24 software, combining manual and automatic coding techniques to identify patterns and thematic relationships. The results were visualized through multiple analytical tools, including code matrixes, co-occurrence models, and case comparisons. Findings indicate strong support for many of the theoretical relationships, particularly those linking Perceived Ease of Use and Perceived Usefulness with Attitude Toward Use and Behavioral Intention. However, other propositions, such as those involving Information Quality and System Quality, were only partially supported or not supported, indicating areas where further development of AI tools may be needed. The study contributes to the growing literature on AI adoption in hospitality by offering empirical evidence from a specific geographic and professional context, while also highlighting the complex interplay of trust, usability, and job-related concerns in shaping employee engagement with RAISA technologies. Finally, the research underscores the need for targeted training, organizational support, and human-centered AI strategies to foster effective and sustainable adoption in the restaurant sector. |
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| Autores principais: | Kalinina, Zoia |
| Assunto: | Artificial Intelligence Service Automation Restaurant Industry TAM IS Success Model Qualitative Research SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This study explores the perceptions, attitudes, and experiences of restaurant professionals toward the adoption of robotics, artificial intelligence (AI), and service automation (RAISA) technologies within the hospitality sector. Grounded in an integrated theoretical framework that combines the Technology Acceptance Model (TAM) and the Information Systems (IS) Success Model, the research aims to evaluate fourteen propositions (P1–P14) concerning the relationships between constructs such as Perceived Usefulness, Fear of AI, System Quality, Behavioral Intention, and Net Benefits. A qualitative methodology was adopted to gain indepth insights into the lived experiences of industry practitioners, with data collected through ten semi-structured interviews with both founders and employees from restaurants and hospitality businesses based in Lisbon, Portugal. The transcripts were analyzed using MAXQDA 24 software, combining manual and automatic coding techniques to identify patterns and thematic relationships. The results were visualized through multiple analytical tools, including code matrixes, co-occurrence models, and case comparisons. Findings indicate strong support for many of the theoretical relationships, particularly those linking Perceived Ease of Use and Perceived Usefulness with Attitude Toward Use and Behavioral Intention. However, other propositions, such as those involving Information Quality and System Quality, were only partially supported or not supported, indicating areas where further development of AI tools may be needed. The study contributes to the growing literature on AI adoption in hospitality by offering empirical evidence from a specific geographic and professional context, while also highlighting the complex interplay of trust, usability, and job-related concerns in shaping employee engagement with RAISA technologies. Finally, the research underscores the need for targeted training, organizational support, and human-centered AI strategies to foster effective and sustainable adoption in the restaurant sector. |
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