AI-assisted recruitment in hospitality: drivers of candidate satisfaction and perceptions of recruiter credibility

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 to design them to meet those expectations. To address this gap, this study aims to adopt a dual-perspective approach, examining the drivers and outcomes of AI-assisted recruitment logistics from the viewpoints of recruiters and recruits. Design/methodology/approach The authors used 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 the desired 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.

Authors

Institutions

Publication Details

Journal
International Journal of Contemporary Hospitality Management
Published
2026-02-12
DOI
https://doi.org/10.1108/ijchm-05-2025-0709
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-assisted recruitment in hospitality: drivers of candidate satisfaction and perceptions of recruiter credibility

Maher Georges Elmashhara, Susana C. Silva, Maria Teresa Borges Tiago
International Journal of Contemporary Hospitality Management
AI in Service Interactions
article

AI-assisted recruitment in hospitality: drivers of candidate satisfaction and perceptions of recruiter credibility

Maher Georges Elmashhara, Susana C. Silva, Maria Teresa Borges Tiago
article en

Abstract

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 to design them to meet those expectations. To address this gap, this study aims to adopt a dual-perspective approach, examining the drivers and outcomes of AI-assisted recruitment logistics from the viewpoints of recruiters and recruits. Design/methodology/approach The authors used 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 the desired 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.

International Journal of Contemporary Hospitality ManagementVol. 38(3)
Universidade dos Açores (PT), Manchester Metropolitan University (GB), Universidade Católica Portuguesa (PT)
Industry, innovation and infrastructure
Openalex Percentile: Top 59%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.