Employee’s perceived impact with Facial Recognition (FR) technologies usage in Vietnam hotels – An experimental approach using self-developed FR software prototype.

Facial Recognition (FR) technology is an emerging technology with many great potentials for different applications and industries. While it has been widely used in retailing, computing, security control, criminal justice, etc., studies regarding its benefits resulting from adoption in hotel operation from managers’ perspectives are still limited. The development and adoption of FR technologies varied considerably from one country to another. Except for China and Australia where facial recognition technology has been widely adopted in the last couple of years due various government’s needs and requirements (Lyu et al., 2023), the rest of the world is still quite behind in the use of this new technology from fear of technological uncertainties and/or privacy law infringements. As a matter of fact, starting from 2019, the state of California in the U.S. banned the use of FR technology by all its law enforcement agencies (Greene, 2019). Hence it is expected the benefits FR technologies could bring to the actual operation are likely to be different between difference countries with different cultural background. More importantly, as most hotel managers may have limited usage experiences and understanding of FR technologies applied at work, prior studies in capturing their perceptions on FR technologies are likely to be inconsistent and unreliable.

Facial recognition technology has been recently adopted in a number of hotels in Vietnam, following the global trend in the hospitality industry worldwide. The main objective of this research is to examine the perceived benefits from hotel managers that FR technology can bring to their hotel business after they have all tried the experimental prototype FR software used in their respective hotel operations in Vietnam. Prior studies have identified a number of expected benefits with FR technology usage in the hotel industry and they can be grouped under four major dimensions namely ‘Variety of Hotel Offerings and Services”, “Quality of Hotel Services”, “Process Efficiency in Hotel Operations and Training” and “Process Diffusion of New and Current Hotel Services” (Au and Le, 2023; Gupta et al., 2023; Morosan & Gunden Sorathia (2023).

In the design of the survey questionnaire for this study, the sample subjects primarily are hoteliers from four departments of (1) front-office, (2) concierge, (3) house-keeping and (4) security in the hotel. The reason behind the selection of these four departments has to do with the fact that most current applications of FR technology in the hotel industry are for identity authentication, troublemaker identification, and crowd or traffic flow control. The measurement items of Facial Recognition (FR) Technology Usage are adapted from the study of Lee et al. (2019) on service design and innovation performance perceptions. 7 items are measured on a 5-point Likert scale with anchors ranging from 1 (for “Strongly Disagree”) to 5 (for “Strongly Agree”). The Resulted Benefits from the Facial Recognition (FR) Technology Usage in the hotel industry are derived from a previous study of Au & Le (2023) and other studies of Morosan & Gunden Sorathia (2023). A total of 17 items were grouped into four dimensions and the hypothesized relationship (H1-H4) in Diagram 1 below.

An important component in the quantitative investigation of this study is the experimental trials of hoteliers with the facial recognition (FR) software prototype for hotel operations to help determine the significant Resulted Benefits from FR technology adoption afterwards. The FR software prototype was built by the author and a development team from the Center of Software Engineering (CSE) of Duy Tan University. Specifically, this software prototype can accommodate for various experiments and experimental trials of FR technology in different hotel work functions by setting up different functionalities for various hotel-service scenarios. A total of 542 valid survey questionnaire were collected from 32 four and five-star hotels and resorts in Danang City of Vietnam.

For the test of measurement items and structural model in this study, the two-step procedure proposed by Anderson & Gerbing (1988) was adopted. First, Confirmatory Factor Analysis (CFA) would be used to evaluate the construct validity, and then the research hypotheses would be tested. The Composite Reliability of all research variables are 0.8 or above, with Squared Multiple Correlation values greater than the threshold of 0.5, indicating strong level of internal consistency. The Average Variance Extracted of all variables were greater than 0.5, indicating the convergent validity of the items.


Diagram 1 – Hypothesized Relationships












Using a series of regression analysis, Table 1 shows the significance test results of Facial Recognition (FR) Technology Adoption on its four possible Resulted Benefits in the hotel industry: Facial Recognition (FR) Technology Adoption has a positive and significant effect on Variety of Hotel Offerings and Services (β＝0.585, p< 0.001). Facial Recognition (FR) Technology Adoption has a positive and significant effect on Qualities of Hotel Services (β＝0.509, p< 0.001); Facial Recognition (FR) Technology Adoption has a positive and significant effect on Process Efficiency in Hotel Operations and Training (β＝0.523, p< 0.001) and finally Facial Recognition (FR) Technology Adoption has a positive and significant effect on Process Diffusion of New and Current Hotel Services (β＝0.559, p< 0.001). Thus, all 4 hypothesis are supported.

Table 1 – Regression Results
Independent variable DEPENDENT VARIABLE
β
Variety of Hotel Offerings and Services Qualities of Hotel Services Process Efficiency in Hotel Operations and Training Process Diffusion of New and Current Hotel Services
Facial
Recognition (FR) Technology
Usage 0.585*** 0.509*** 0.523*** 0.559***
R2 0.342 0.259 0.273 0.312
F 281.120 188.472 202.826 245.423


It is evident that the adoption has had a significantly positive impact on various aspects of current hotel products and services. Of the four significant Resulted Benefits from Facial Recognition (FR) Technology in the hotel industry, the Variety of Hotel Offerings and Services appears to receive the strongest effect from the adoption (R2 = 0.342, β = 0.585, p< 0.001), meaning that hoteliers (after the experimental trials) mostly think of FR technology as helping increase the product and service variety of their hotels. This is to be followed by Process Diffusion of new and current Hotel Services (R2 = 0.312), in which hoteliers find it not too much of a hassle to adopt and customize the new technology as well as modified services at different work functions and across different platforms or devices. Process Efficiency in Hotel Operations and Training and Qualities of Hotel Services are the two resulted benefits that can be least explained by the adoption of FR technology (H9: R2 = 0.273, H8: R2 = 0.259). This implies that hoteliers still do not see the efficiency enhancement and quality improvement as the biggest benefits from the adoption of FR technology for their hotel operations and services. As surprisingly as it turned out, improvements in Qualities of Hotel Services were not perceived as the biggest benefit of FR technology adoption in the hotel industry as expected. It appeared that hoteliers mostly saw FR technology as helping their current operations and services become faster and more efficient, but not as delivering some major quality improvements that can be recognized and appreciated by hotel guests. Indeed, while FR technology may help change or create many new hotel operations and services, most of them are in the back-office, not visible and well-recognized to the hotel guests. This is not because of the innovativeness of the technology itself, but more because of how it is being currently used in the hotel industry. Additional time thus may be needed before the technology becomes more mature for all of its potential and applications to be realized in this industry. Hotels and resorts that effectively embrace and implement FR technology may gain a competitive advantage in the industry. They can differentiate themselves by offering advanced security measures, personalized services, and efficient operations through the use of FR systems, which can attract and retain guests and customers in an increasingly competitive industry.


References
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Au, N., & Le, B. (2023). Potential of Facial Recognition Technology Adoption in the Hotel Industry - The Perspectives of Managers. International Joint Conference on Hospitality and Tourism 2023, Bangkok, Thailand.
Greene, T. (2019). California bans law enforcement from using facial recognition software for the next 3 years. The Next Web, 10 October. Available at: https://thenextweb.com/artificial-intelligence/2019/10/10/california-bans-law-enforcement-from-using-facial-recognition-software-for-the-next-3-years/
Gupta, S., Modgil, S., Lee, C. K., & Sivarajah, U. (2023). The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry. Information Systems Frontiers, 25(3), 1179-1195.
Lyu, T., Guo, Y., & Chen, H. (2023). Understanding people’s intention to use facial recognition services: the roles of network externality and privacy cynicism. Information Technology & People.
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