Facial recognition check-in services at hotels

Xu, Feng; Zhang, Yun; Zhang, Tingting; Wang, Jing

doi:10.1080/19368623.2020.1813670

Cited by 29 publications

(25 citation statements)

References 58 publications

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“…For instance, travel agents, online travel agencies, tour operators, and regional tourism organizations help the industry indirectly in ways that facilitate tourists in choosing different combinations such as combination of air travel, accommodation, hotel transfer, and sightseeing (Gaur et al, 2021 ). Doing so presents an opportunity for each party to adopt breakthrough technologies (Xu et al, 2021 ). In addition, the industry addresses numerous other issues such as infrastructure, transparency, security, and safety.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In India, the Aadhar Project has rolled out facial authentication, which would be phased in from 2020 onward (Mir et al, 2020 ). Through AI-based facial recognition, guests will be able to check in quickly and effortlessly in hotels and airports without waiting for a staff member to help them do so (González-Rodríguez et al, 2020 ; Jun & Vogt, 2013 ; Xu et al, 2021 ). In airports, AI-driven facial recognition can contribute to the environment by avoiding the use of paper-based boarding passes (Bromberg et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry

et al. 2022

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This study aims to investigate the role of artificial intelligence (AI) driven facial recognition to enhance a value proposition by influencing different areas of services in the travel and tourism industry. We adopted semi-structured interviews to derive insights from 26 respondents. Thematic analysis reveals the development of four main themes (personalization, data-driven service offering, security and safety, and seamless payments). Further, we mapped the impact of AI- driven facial recognition to enhance value and experience for corporate guests. Findings indicate that AI-based facial recognition can facilitate the travel and tourism industry in understanding travelers’ needs, optimization of service offers, and value-based services, whereas data-driven services can be realized in the form of customized trip planning, email, and calendar integration, and quick bill summarization. This contributes to strengthening the tourism literature through the lens of organizational information processing theory.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry

et al. 2022

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“…Identity verification systems, such as passwords or magnetic cards, are used to determine whether a person has access to a location, and it also allows for video recording (Abdelmoaty & Soliman, 2020). This system is distinguished by its ability to retrieve specific moments and search for videos based on date and time (Lunkes et al, 2019;Xu et al, 2021). Huang et al (2021) added that thermal imaging cameras, which detect and measure temperature differences, allow monitoring of what can be seen to ensure safety.…”

Section: Access Control and Control Systemsmentioning

confidence: 99%

The Impact of Smart Services on the Efficiency and Effectiveness of Employees Performance in Hotels

Hassan

Mahmoud

Hussien³

2022

Minia Journal of Tourism and Hospitality Research MJTHR

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“…As facial recognition technology in Singapore’s hotel industry is relatively new (Rajagopal, 2019), an integrative understanding of the factors explaining consumer intention to adopt the technology is pivotal to the success of the government initiatives. Furthermore, while the need to explore consumer behavior in respect of biometric technologies has been accentuated in the literature (Ioannou et al , 2020), research on customer attitudes and adoption behaviors toward facial recognition technology in a hotel setting is relatively scant (Morosan, 2019; Xu et al , 2021). According to Murphy and Rottet (2009), there are different stances (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…The technology can digitally identify guests and retrieve their information, allowing hotel employees to deliver a customized and efficient customer service experience (Hertzfeld, 2018). Despite the positive outlook on facial recognition technology, customer acceptance level of the technology in hospitality settings is fairly modest (Xu et al , 2021). The slow acceptance of facial recognition technology in the hotel industry is partly attributed to the technology’s performance reliability, which can potentially result in a false rejection or false acceptance (Delac and Grgic, 2004).…”

Section: Introductionmentioning

confidence: 99%

An integrative model of facial recognition check-in technology adoption intention: the perspective of hotel guests in Singapore

Boo

Chua

2022

IJCHM

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Purpose This study aims to explain how hotel guests form attitudes toward facial recognition technology in Singapore by integrating technology acceptance model (TAM), privacy calculus theory and personal innovativeness. Design/methodology/approach A self-administered online questionnaire was developed with measurements adopted from past research. Guests who stayed in four- or five-star hotels in Singapore were recruited via systematic random sampling. Structural equation modeling was conducted to examine the proposed integrated models. Findings Results showed that hotel guests performed calculative cognitive processes, weighing the benefits and risks of using facial recognition check-in system. Contradictory to the past research which suggested that trust activates both perceived risk and benefits, this study demonstrated that trust independently directed consumer attention on the benefits gained while risk perception was triggered by privacy concern. Furthermore, the current study revealed that the ease of use of facial recognition check-in system could possibly backfire. Practical implications The research indicates that the effort to adopt new technology in the hotel industry is promising in view of the growing millennials and Generation Z population who are digital natives. Furthermore, the current study highlights ways to elevate institutional trust and divert consumers’ attention from risk perception to enhance their positive attitude and behavior toward accepting facial recognition check-in system. Originality/value This study integrated TAM with privacy calculus theory and personal innovativeness in examining the acceptance of facial recognition check-in system in the hotel industry in Singapore. This study is also the first, to the best of the authors’ knowledge, to investigate the relationships among privacy concern, perceived risk, institutional trust and perceived benefits, as well as their effects on consumers’ attitudes and behavior toward the biometric system.

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Facial recognition check-in services at hotels

Cited by 29 publications

References 58 publications

The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry

The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry

The Impact of Smart Services on the Efficiency and Effectiveness of Employees Performance in Hotels

An integrative model of facial recognition check-in technology adoption intention: the perspective of hotel guests in Singapore

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