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  • Ai-assisted recruitment in hospitality: drivers of candidate satisfaction and perceptions of recruiter credibility
    Publication . Elmashhara, Maher Georges; Tiago, Maria Teresa Borges; Silva, Susana C.
    Purpose – Artificial Intelligence (AI)-assisted recruitment is evolving in the hospitality industry. However, a critical gap persists in understanding what recruiters expect from AI tools and how these tools can be designed to meet those expectations. To address this gap, this study adopts a dual-perspective approach, examining the drivers and outcomes of AI-assisted recruitment logistics from the viewpoints of recruiters and recruits. Design/methodology/approach – We employed a mixed-method approach across two studies. Study 1 consisted of 12 interviews with hospitality managers to explore their desired outcomes of using AI tools in the recruitment process. Study 2 involved the development of a chatbot-based scheduling system, followed by a survey with 256 participants to examine what drives desirable AI-assisted recruitment outcomes from the candidates' perspective. Findings – Study 1 reveals that beyond operational efficiency, recruiters use AI tools to enhance candidate satisfaction with the recruitment experience and to improve recruiter trustworthiness and attractiveness. Study 2 demonstrates that the key drivers of these outcomes are perceived usefulness, trust, and enjoyment. Practical Implications – AI tools that assist the recruitment process should be designed to enhance candidate satisfaction and positively influence perceptions of recruiter credibility. To achieve this, their design should prioritize perceived usefulness, address privacy and security concerns, and offer an enjoyable user experience. Originality/Value – This study investigates real user interactions with a functioning scheduling chatbot, offering a more authentic and valid assessment. Moreover, it extends the application of AI tools in hospitality beyond customer service, shedding light on their role in recruitment logistics.
    2026-01-18Artigo de investigação Acesso aberto Ver mais