How can a chatbot influence the customer experience of your tourism business?

With the constantly ongoing advancements of Industry 4.0, several interconnected developments can be seen affecting both the digital and operational environments of tourism businesses. These so-called Tourism 4.0 innovations refer to Industry 4.0 innovations (Big Data, Internet of Things, Blockchain, Artificial Intelligence etc.) that have been specifically refined to suit the needs of the tourism industry, ultimately bringing additional value to customers¹. To scratch the surface of this multidimensional phenomenon, this blog post will focus on technology-mediated communication tools, specifically chatbots, and their influences on customer experience.

Yet, we must notice the other side of the equation. In addition to addressing the influences of chatbots on customer experience, the issue will also be appraised from the perspective of Customer Experience Management (CEM). But first, as stated by Opute, Irene and Iwu², it is vital to define the concept of “customer experience” before addressing topics related to the leveraging of digital technologies. Thus, in order to fully comprehend the complexity of the topic, we first need to create a framework of understanding.

Understanding the fundamentals of customer experience

Customer experience is a common topic of interest in both general business research and tourism-specific research. Due to differences in industry-specific characteristics, it is vital to understand the difference between online customer experience and (overall) customer experience.

In their conceptual model of online customer experience, Rose, Clark, Samouel and Hair³ identify various antecedent variables affecting the Cognitive Experiential State (CES), as well as the Affective Experiential State (AES) of customers. While antecedents affecting CES are closely related to the concept of flow (e.g., interactive speed, online presence, challenge, and skill), antecedents influencing AES are often associated with individual perceptions of website functionality, aesthetics and assumed benefits. The above-noted Experiential States lead to the preferable outcomes of an online customer experience: (1) customer satisfaction; (2) trust; and (3) repurchase intentions.

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Stankov’s and Gretzel’s¹ conceptualization addresses similar concepts in a different context. Their conceptualization showcases the role of Tourism 4.0 technologies in creating tourist experiences. Similarly, concepts related to the state of flow (i.e., object-oriented factors) are seen to have an effect on the user experience. Conversely, their Human-Centered Design (HCD) approach gives great emphasis to additional variables, specifically subject-oriented factors (e.g., previous experiences, behavioural patterns, and contextual differences). Ultimately, the aforementioned factors result in a subjective user experience. However, this is just a part of the full story. The main idea of the conceptualization is to illustrate the user experience as a mediator, supporting the formation of the overall tourist experience. In other words, a user experience is a tool creating either goal-surpassing or goal-limiting effects, which have an essential impact on the overall experience.

Hwang’s and Seo’s⁴ findings also emphasize the role of technology-mediated experiences as middlemen between the customer and the overall customer experience. Their conceptualization reviews the topic from a CEM perspective, thus giving greater emphasis to the characteristics and consequences of the overall customer experience. According to this broader description, the overall customer experience is shaped according to a set of internal factors (e.g., customer demographics) and external factors (e.g., online environment, technology, and service attributes). As a result, the overall customer experience revolves around aspects of co-creation, authenticity, transcendence, and transformation. What is the final outcome of the overall customer experience? Mentioned outcomes include emotional and behavioural outcomes, changes in brand perception, as well as other subjective outcomes.

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Chatbots: What, How, Why & Why not?

What are chatbots?

Essentially, chatbots are auto-generated software having some sort of ability to interact with its user. This interaction can take place in the forms of audio or text⁵. These natural language-based dialogues between chatbots and users⁶ take place on multiple platforms, including company websites and mobile applications⁷, to name a few.

How do chatbots work?

Chatbots require certain prerequisites to function. At this point it is vital to understand the differences between the two most common chatbots of today – rule-based chatbots and AI-chatbots. Rule-based chatbots operate on a basis of set rules. These chatbots can only function within the framework of these set rules, which limits their functionality⁸.What happens when a rule-based chatbot is not able to process your request? Melian-Gonzalez, Gutierrez-Tano and Bulchand-Gidumal⁷ highlight the complementary relationship required between chatbots and humans. Consequently, when a chatbot is not able to process a piece of information, the request is transferred to a human (i.e., a customer service representative of a company). Another limiting factor is the inability to learn from previous interactions; rule-based chatbots cannot storage processed information into a knowledge base or a data storage⁸.

Conversely, AI-chatbots have the ability to utilize complex datasets and even predict customer behaviour (to a certain extent). These highly intellectual chatbots have a Natural Language Processing (NLP) layer, or they utilize an Artificial Intelligence Markup Language (AIML) to obtain and process customers’ textual and/or oral requests. Moreover, AI-chatbots are often associated with the concept of Machine Learning (ML). ML functions enable AI-chatbots to not only process customers’ requests, but also to make assumptions about customer behaviour and deliver suggestions accordingly⁹.

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Why do customers choose or choose not to interact with chatbots?

In Pillai’s and Sivathan’s¹⁰ study, a total of 1480 Indian customers as well as 36 senior managers were surveyed to identify different antecedents of chatbot adoption. Their findings indicate that the main antecedents of chatbot adoption include perceived ease of use, perceived trust, perceived intelligence, and the human-like characteristics of the chatbot (anthropomorphism).

Conversely, a more recent study identifies several negative antecedents affecting the adoption intention (AIN) of chatbots. In the above-mentioned study, undergraduate students from two Spanish Universities were surveyed, obtaining a total of 476 valid responses. The findings imply that individual habits, such as previous use of chatbots, inconveniences in communication (i.e., having to adopt own language in order for the chatbot to understand), as well as having a negative general attitude towards Self-Service Technologies (SSTs) have a negative effect on adoption intention⁷.

Chatbots & customer experience: providing value or increasing frustration?

Chatbots contribute to the customer experience in various ways. A recent Malaysian case study, conducted in co-operation with Air Asia Berhad, analyses the influences of chatbots on customer experience. The study presents a variety of positive outcomes. Firstly, the ease of use is highlighted; utilizing a chatbot requires little or no technical competence. Secondly, the constructed AIRA chatbot is able to operate 24/7, providing immediate responses to customers’ queries. This notion was greatly emphasized, since prior to the case study, the service quality of the company was on an insufficient level¹¹.

The findings of Suanpang’s and Jamjuntr’s¹² case study add to the above-mentioned notions. During their study, an AI chatbot was constructed for tourists visiting the Active Beach Zone in Thailand. Their findings indicate the following: (1) chatbot usage minimized the cognitive overload of customers; and (2) chatbot usage contributed to overall customer satisfaction. A mention-worthy element adding to the overall customer satisfaction was the chatbots ability to provide personalized information and customized content.

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Boiano’s, Borda’s, Gaia’s, Rossi’s and Cuomo’s¹³ case study addresses the opportunities presented by chatbots in the context of museums and heritage organisations. The results of their pilot project in Milan imply that chatbot usage increased the immersion of museum tours, encouraging younger customer segments to pay more attention to historic environments and objects.

Conversely, a vital element of experiences, co-creation, divides opinions among scholars. While Bowen and Morosan¹⁴ state that chatbots among other technical developments add to the co-creation of remarkable visitor experiences by efficiently utilizing customer data, other scholars recognize the disruptive elements of the same phenomenon. According to a statement, autonomous devices are seen to “dehumanize co-created experiences” because of their power of overtaking the responsibilities of human beings¹⁵.

Be ahead of the game: identifying future opportunities and threats of chatbots in tourism

By now you should understand the following topics:

      1. The fundamentals of customer experience
      2. The adoption, use, and functionality of chatbots
      3. How do chatbots influence the customer experience?

Adding to the understanding of these topics, a conceptual framework has been constructed.

Source: Author
What about the future of chatbots? What kind of opportunities and threats do you need to acknowledge as a manager?

One of the biggest mistakes you can make as a manager is to focus only on the more direct outcomes of chatbot usage. Chatbots can certainly minimize labour costs, create additional value for customers, as well as give you a competitive edge over your competitors. However, there are additional (indirect) focus points that you should consider.

Firstly, we must acknowledge that advancements in technology increase customer expectations. Consequently, you must consider how your chatbot can be developed to suit the changing needs of customers. Could you utilize Deep Learning practices or additional Application Programming Interfaces to train your chatbot? Do these training practices fit your budget?

Secondly, let us review the situation from an experience design perspective. As said, technology is just a mediator for the overall experience; the overall experience includes holistic and human-centred elements¹⁶. Still, as technology develops, Bowen and Morosan¹⁴ question whether it is the technology that primarily drives value creation. In other words, this would require rethinking the whole experience, since technology can provide more value to the client in the form of a better product, a lower price, or both.

Thirdly, we must address the threats of chatbot usage. The more apparent negative outcomes of chatbot usage include frustration and skepticism towards technology. Could this be affected by determining whether it is mandatory or voluntary for customers to use your chatbot? Furthermore, there is a future threat to consider. Researchers have questioned whether the trend of replacing the human labour force with chatbots will have negative influences on how customers perceive chatbots. This negative perception ultimately affects adoption intentions⁷.

Acknowledgements

This blog post was written as a part of the Information and Communication Technology in Tourism Business course at the International Master’s Degree Programme in Tourism Marketing and Management (University of Eastern Finland Business School). Read more about the programme at https://www.uef.fi/tmm

References:

¹Stankov, U., & Gretzel, U. 2020. Tourism 4.0 technologies and tourist experiences: a human-centered design perspective. Information Technology & Tourism, 22(3), 477-488.

²Opute, A. P., Irene, B. O., & Iwu, C. G. 2020. Tourism service and digital technologies: A value creation perspective. African Journal of Hospitality, Tourism and Leisure, 9(2), 1-18.

³Rose, S., Clark, M., Samouel, P., & Hair, N. 2012. Online customer experience in e-retailing: an empirical model of antecedents and outcomes. Journal of retailing, 88(2), 308-322.

⁴Hwang, J., & Seo, S. 2016. A critical review of research on customer experience management: Theoretical, methodological and cultural perspectives. International Journal of Contemporary Hospitality Management.

⁵Kumar, V. M., Keerthana, A., Madhumitha, M., Valliammai, S., & Vinithasri, V. 2016. Sanative chatbot for health seekers. International Journal Of Engineering And Computer Science, 5(03), 16022-16025.

⁶Dale, R. 2016. The return of the chatbots. Natural Language Engineering, 22(5), 811-817.

⁷Melián-González, S., Gutiérrez-Taño, D., & Bulchand-Gidumal, J. 2021. Predicting the intentions to use chatbots for travel and tourism. Current Issues in Tourism, 24(2), 192-210.

⁸Alotaibi, R., Ali, A., Alharthi, H., & Almehamdi, R. 2020. AI Chatbot for Tourist Recommendations: A Case Study in the City of Jeddah, Saudi Arabia. International Journal of Interactive Mobile Technologies, 14(19), 18-30.

⁹Calvaresi, D., Ibrahim, A., Calbimonte, J. P., Schegg, R., Fragniere, E., & Schumacher, M. 2021. The Evolution of Chatbots in Tourism: A Systematic Literature Review. Information and Communication Technologies in Tourism 2021, 3-16.

¹⁰Pillai, R., & Sivathanu, B. 2020. Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management.

¹¹Kasinathan, V., Abd Wahab, M. H., Idrus, S. Z. S., Mustapha, A., & Yuen, K. Z. 2020. Aira chatbot for travel: case study of AirAsia. In Journal of Physics: Conference Series, 1529(2), 022101. IOP Publishing

¹²Suanpang, P., & Jamjuntr, P. 2021. A Chatbot Prototype by Deep Learning Supporting Tourism. Psychology and Education Journal, 58(4), 1902-1911.

¹³Boiano, S., Borda, A., Gaia, G., Rossi, S., & Cuomo, P. 2018. Chatbots and new audience opportunities for museums and heritage organisations. Electronic visualisation and the arts, 164-171.

¹⁴Bowen, J., & Morosan, C. 2018. Beware hospitality industry: the robots are coming. Worldwide Hospitality and Tourism Themes.

¹⁵Buhalis, D., Harwood, T., Bogicevic, V., Viglia, G., Beldona, S., & Hofacker, C. 2019. Technological disruptions in services: lessons from tourism and hospitality. Journal of Service Management.

¹⁶Tussyadiah, I. P. 2014. Toward a theoretical foundation for experience design in tourism. Journal of travel research, 53(5), 543-564.

Facial recognition systems – the key to a more seamless future of tourism services?

Biometric systems are becoming a more mundane part of our everyday lives. We use for example our fingerprints and facial recognition systems to unlock our devices, to make mobile payments and to pass the border control routines at airports. These technologies are developing all the time, making them more accurate and simpler to use, pervading to a growing extent of the services and systems we use. One of the fields that could benefit from the opportunities that biometric systems create, is the tourism industry and its different sub-fields. In tourism, technologies like this are already widely in use in some areas, and during recent years, partly because of the pandemic situation that forced the companies in this field to develop themselves further, the adoption of contactless services has been increasing rapidly (Ivasciuc, 2020).

Although biometric technology has a huge potential to make businesses better and create more satisfying service experiences for the customers, there are still some concerns and suspicion amongst the customers towards these solutions. (Pai et al. 2018) These doubts can prevent the greater scale implementation of these technologies, regardless of the convenience and possibilities they create. Biometric systems can refer to a variety of technologies that examine human characteristics to verify the user. (Jain et al. 2011). This blog post focuses mainly on the usage of facial recognition technology (FRS) in the tourism industry.

Utilizing facial recognition technologies can create several advantages for tourism businesses, as well as for businesses in general. Adopting FRS based solutions is particularly useful in the tourism field, because of the specific features that the industry has. For example, in hospitality, the businesses must simultaneously take care of two major areas, security and customer satisfaction. Morosan (2019) suggests that FRS represents an ideal solution for hotels that are constantly balancing between these two quality challenges. (Morosan, 2019)

According to Mills et al. (2010), biometric technology creates advantages for the tourism and hospitality field in the areas of safety, customer convenience and operational efficiency. An increased level of convenience can lead to greater customer satisfaction when customers do not have to carry their key cards or loyalty cards and wait in massive lines of people. Biometric solutions, or in this case, facial recognition systems, could also lead to an increase in sales and revenue when payments are being made easier for the client. And even though FRS creates advantages in customer satisfaction and safety, perhaps the most critical benefits are related to operational efficiency, since tourism businesses and services usually must handle large volumes of people for example at airports. (Mills et al., 2010)

Facial recognition systems are already widely in use in the aviation industry, where passengers usually must undergo a repeated set of identification processes and check-ins at airports. Travel documents are usually presented to a variety of authorities such as the immigration department or customs, and of course to the airlines themselves. Since this process is very time-consuming and frustrating for the passengers, automation via FRS is an efficient tool to make air travelling more comfortable. At airports, FRS solutions are already a popular solution for example in border-control formalities. (Samala et al. 2020)

To make the airport experience even more convenient, some airports started to offer a fully automated airport experience. For example, at the beginning of 2021, Delta airlines launched the first domestic digital identity test in the U.S which makes the contactless airport experience possible. Customers can now use facial recognition as an identification verification in every service touchpoint with their mobile application. Traditional ID verification is not needed at any point of the travel. (Delta-news hub, 2021; Parker, 2021) The growing numbers of tourists are forcing the aviation industry to increase its performance with more efficient contactless solutions, and of course, the development has also been pushed by the Covid-19 pandemic. (Ivasciuc, 2020).

Facial recognition in the hospitality industry

One other field within tourism that would gain benefits from the FRS is the hospitality industry. As Pai et al. (2018) demonstrate with their findings, as users start to trust biometrical systems such as FRS, they will eventually become more satisfied with hotels using this technology. FRS is still at an early adoption stage in the hospitality industry, which means that the early adopting companies could gain a competitive advantage. (Pai et al. 2018)

Even though there are some existing examples of hotels implementing FRS in their services, especially in the Asian countries, automated hotel services that utilize FRS are not widespread regardless of the possibilities that they create. Automated FRS services have been launched for example in China, in two of the Marriott-chain hotels. At these facilities, it is possible for the client to execute the whole check-in process simply with an ID and facial data. (Marriott international, 2018). A more recent example comes from Vietnam, where a pioneering Vinpearl-resort chain launched the use of FRS in its hotel facilities in Nha Trang (Vinpearl, 2021).

What are the advantages of FRS for hotels?

As Wang (2018) presents, at Marriott hotels, an intelligent check-in system reduces the check-in time from three minutes to one minute which is a remarkable advantage compared to more traditional hotel services (Wang, 2018). According to Morosan (2020) FRS is a promising technology for the hospitality industry since it makes it possible for hotels to optimize consumer tasks such as authentication and payments and increase security in the facility. FRS brings major possibilities to enhance both security and service quality. (Morosan, 2020) Intelligent property management systems could use integrated FRS to identify familiar guests already when they are approaching the service desk to offer a more personalized experience (Hertzfeld, 2018).

Utilizing FRS would be a major step for businesses operating in the hospitality field toward a more seamless and satisfying customer experience. According to Morosan (2020), it is the legacy process of guest authentication that creates the most critical service bottlenecks in the hospitality industry. These bottlenecks are very frustrating for both the guests and the workers, especially during peak hours.  Even though solutions such as self-check-in kiosks or mobile check-in systems have already been deployed by some hotels to answer this problem, service bottlenecks seem to still be an inevitable part of hotel services. Self-check-in solutions create a possibility of security risks, which may be one of the reasons why many hotels prefer to operate on traditional patterns. (Morosan, 2020) However, FRS differs from other self-check-in solutions with its ability to create automated services accurately and also safely (NEC Corporation, 2018).

In the hotel service ecosystem, guests are identified in many service touchpoints, such as in the check-in situation, payments and when accessing different facilities such as the guest’s room, gym or spa area. As Morosan (2020) describes “a repeated need for guest authentication is one of the idiosyncrasies of the hospitality industry”. Typically, guests use keys or key cards to access different areas of the facility, but often these keys end up being lost or damaged, which creates frustrating, unnecessary situations for the guests during their stay. With FRS, it would be possible to create a key that is rather hard to lose, the customers own face.

FRS brings possibilities to create more personalized service encounters and ultimately, it could even be used as a tool to understand the guests’ feelings more deeply as AI is increasingly becoming better at recognizing human emotions. The so-called emotion recognition technology (ERT) aims to detect emotions from facial expressions and is a growing multi-billion industry.  (Hagerty & Albert, 2021). This could also be used as a tool in the hospitality industry, where the staff’s ability to recognize customers’ feelings play a critical role. As Koc & Boz (2019) argue, as the emotion/facial recognition abilities of the staff improve, it is likely that also the interactions between the customers and the employees improve too. According to them, improving staff’s ability to recognize customer feelings drives the development in service encounters. (Koc & Boz, 2019).

For example, far-fetched and simplified, if the check-out kiosk that is utilizing ERT technology recognizes that a significant number of guests leave the facility showing more stress signals than when arriving, it might be an indicator that there is something terribly wrong with the service provided. This kind of data is something that the service employees could never be able to collect and examine during their hurries. Of course, applying these kinds of solutions collides with privacy issues very quickly and sounds more like a dystopian future in some people’s ears than service development.

What does research tell about customer attitudes towards FRS?

Applying facial recognition technology raises concerns in people’s minds, which may be one of the factors putting breaks into this development in the tourism industry. (Morosan, 2019) For example, in Russia, privacy issues were quickly brought up when Moscow launched its new FRS based payment option in the city’s metro system. (The Guardian magazine, 15.10.2021).

Privacy issues have also been brought up by Xu et al.  (2020). They argue in their study on FRS usage in hotel check-in services, that perceived privacy has an even bigger impact on customers’ trust than security. Their research demonstrates that perceived privacy, security and trust in the system significantly affect the acceptance of FRS in hotel services amongst the guests (Xu et al., 2020).

Pai et al. (2018) studied the Chinese tourist’s perceived trust and intentions to use biometric technology in Macau. Their study also revealed that privacy and security concerns were the main sources creating distrust of biometric use in hospitality. (Pai et al. 2018). There are also concerns regarding the accuracy of these systems and their equality. For example, research done by Buolamwini & Gebru (2018) demonstrates this by pointing out algorithmic fairness, as FRS technology examined in their research was more capable of recognizing white males than females with a darker tone of skin. (Buolamwini & Gebru, 2018)

However, some studies indicate that privacy seems not to be that big of a deal in preventing the adoption of FRS, especially among young people. Norfolk & O’regan (2020) studied biometric technologies in the music festival context using an extended technology acceptance model. They found that as opposed to security and convenience, privacy, accuracy, and reliability did not have a significant impact on the acceptance of biometrics in a music festival setting. Their findings argue against the very common view that privacy, accuracy, and reliability are the most critical factors impacting the usage of biometrics. For young festival-goers, it seemed to be more about the actual usefulness of the technology than fears of lost privacy and security. (Norfolk & O’regan, 2020)

Cifti et al. (2021) studied the customer acceptancy of FRS in fast-food restaurants, which is another industry heavily pushing automated encounters to provide quicker service. Their findings support the notion that the impact of perceived privacy on the willingness to adapt FRS is not that significant. As Cifti et al. conclude, the differences regarding the issue of privacy might vary depending on the nationality of the user, culture type or hospitality service level. (Cifti et al. 2021)

Examining the existing research and cases of the adaption of FRS in the tourism industry, it seems an opportunity for many businesses in this field. FRS solutions have already spread into a variety of service encounters, that must handle large volumes of people and verify their personal details. FRS makes these encounters more fluent for the traveller as well as creates efficiency for the service provider.

As research points out, adopting FRS raises concerns amongst some people. Is my data safe and how is it used? That’s a question many people are asking when given an opportunity to use biometrical identification for the first time in a business setting. This is what companies adopting FRS should put emphasis on to create pleasant encounters between the customers and the technology. Overall, adopting FRS would develop tourist business’s security, efficiency and convenience, but only if the critical points that are preventing the usefulness and the trustworthiness of the system in the customers’ eyes are addressed and dealt with properly.

References:

Buolamwini, J. &amp; Gebru, T.. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. <i>Proceedings of the 1st Conference on Fairness, Accountability and Transparency</i>, in <i>Proceedings of Machine Learning Research</i> 81:77-91 Available from: https://proceedings.mlr.press/v81/buolamwini18a.html.

Cifti, O. Choi, E & Berezina, K. 2021. Lets face it: are customers ready for facial recognition technology at quick-service restaurants? International journal of hospitality management Vol. 95, 102941

Delta-airlines news hub. 2021. Retrieved 14.10.2021 from: https://news.delta.com/delta-launches-first-domestic-digital-identity-test-us-providing-touchless-curb-gate-experience

Hertzfeld, E. 2018. Agilysys adds facial recognition to its PMS, hotel management, available at: https://www.hotelmanagement.net/tech/agilysys-adds-facial-recognition-to-its-pms

Ivasciuc, I. 2020. “Augmented reality and facial recognition technologies. Building bridges between the hospitality industry and tourists during pandemic”. Available at: https://www.proquest.com/docview/2491984008?OpenUrlRefId=info:xri/sid:primo&accountid=11739

Jain, A.K., Ross, A.A. and Nandakumar, K. (2011), Introduction to Biometrics, Springer, New York, NY.

Koc, E. & Boz, H. Development of hospitality and tourism employees emotional intelligence through developing their emotion recognition abilities. Available at: https://www.tandfonline.com/doi/full/10.1080/19368623.2019.1608885

Norfolk, L. & O’regan, M. 2020. Biometric technologies at music festivals: An extended technology acceptance model. Available at: https://doi.org/10.1080/15470148.2020.1811184

Mills, J. Meyers, M & Byun, S. 2010. “Embracing broadscale applications of biometric technologies in hospitality and tourism: Is the business ready?” Available at: https://www-emerald-com.ezproxy.uef.fi:2443/insight/content/doi/10.1108/17579881011078377/full/html#b21

Marriott International, Alibaba Group trials facial recognition check-in. (2018). SMB World Asia (Online), http://ezproxy.uef.fi:2048/login?url=https://www.proquest.com/trade-journals/marriott-international-alibaba-group-trials/docview/2069110987/se-2?accountid=11739

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Parker, J. 2021. First look:delta, tsa launch facial recognition at atlanta airport. Retrieved 12.10.2021 from: https://www.forbes.com/sites/jenniferleighparker/2021/10/27/first-look-delta-tsa-launch-facial-recognition-at-atlanta-airport/?sh=19ee4e454dc2

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Xu, F. Zhang, Y. Zhang, T. & Wang, J. 2020. Facial recognition check in services at hotels. Journal of hospitality marketing & management, Volume 30, 2021, 3