Jianhong Feng

Date of Award

Fall 2021

Document Type

Open Access Thesis


School of Hotel, Restaurant and Tourism Management

First Advisor

Ercan Sirakaya Turk


Hotels moved in the direction of intelligentization, network connection and sharing of travel modes in the 21st century. Automation, robotics, and artificial intelligence (AI) are expected to promote significant changes to hospitality and tourism sectors. Hotels that take advantage of these technological advances would benefit from this new business model as they can differentiate themselves from competitors who fail to adopt these new innovations. In the traditional hotel industry, guests are not served by automated technologies. Nowadays, non-human based business-models and service innovations have become the latest business strategy choice in the hospitality and tourism industry, especially during the current COVID-19 pandemic. Traditional hotels face complications such as long wait times, management inefficiency, and customer privacy. This thesis focuses on testing the efficacy of the modified Technology Acceptance Model (TAM) that is traditionally used to predict potential consumers’ acceptance and explores the reasons for acceptance of this novel and innovative service model. The basic tenets of the UTAUT posits that Perceived Usefulness (PU), Perceived Ease of Use (PE), Subjective Norm (SN), and Facilitating Conditions (FC) impact potential customers’ acceptance of the automated hotel. Data from a convenient sample of 256 customers were collected using Mturk, a crowdsourcing marketplace. The thesis further explores the effects of moderators like age, gender and culture.

The findings of this thesis reveal that PE, SN and SE have significant relationships with Attitude (A). Trust (T) and Attitude (A) have significant relationships with Behavioral Intention (BI). Moreover, there is no moderating effect of culture and age. Gender interferes with the relationship between A and BI.