BỘ GIÁO DỤC VÀ ĐÀO TẠO TRUÔNG ĐẠI HỌC KINH TÉ TP. HỔ CHÍ MINH BÁO CÁO TỐNG KẾT ĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024 FACTORS IMPACTING INTENTION TO USE AI CHATBOT IN TOURISM: A CASE STUDY IN VIETNAM Thuộc nhỏm chuyên ngành: Kinh tê TP. Hồ Chí Minh, tháng 2/2024 TOPIC SUMMARY This study looks into the various elements that influence people's intentions to utilize AI chatbots in the tourist industry, with a focus on the Vietnamese market. The report uses a case study technique to find unique insights on the adoption process of AI chatbots in the tourism industry.
The investigation includes cultural, contextual, and user experience dimensions, offering a thorough knowledge of the primary factors and difficulties driving tourists' intentions to use AI chatbots in Vietnam. TABLE OF CONTENTS CHAPTER 1: RESEARCH OVERVIEW. Research overall objectives. Research questions and objectives.
Structure of the study. 14 CHAPTER 2: LITERATURE REVIEW. Overview of AI Chatbot. Technology adoption model (TAM).
Synthesis of studies related to factors impacting the intention to use AI Chatbot in tourism. Hypotheses and research model. Ease of use and AI Chatbot usage intention. Anthropomorphism and AI Chatbot usage intention.
Usefulness and AI Chatbot usage intention. Social influence and AI Chatbot usage intention. Trust and AI Chatbot usage intention. Interactivity and AI Chatbot usage intention.
Information quality and AI Chatbot usage intention.39 CHAPTER 3: RESEARCH METHODOLOGY. Scale of constructs. Ease of Use scale. Social Influence scale.
Information Quality scale. AI Chatbot usage intention scale. Sample descriptive analysis. Descriptive statistics results.
Assessment of measurement model. Indicator outer loadings. Assessment of structural model. Coefficient of determination and adjusted R2.
Analysis of Effect size f2. Path coefficients and hypotheses testing.59 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS. Limitations and directions for further research. Directions for Further Research.
Quantitative research questionnaire. Questionnaire English version. Questionnaire Vietnamese version 86 LIST OF FIGURES Figure 1: Technology adoption model (TAM). 19 Figure 2: Proposed research model.39 Figure 3: Research process.
43 LIST OF TABLES Table 1: Summary of related studies. 20 Table 2: Analysis of factors affecting the intention to use AI Chatbot in tourism. 29 Table 3: Research sample descriptive analysis. 49 Table 4: Descriptive statistics results.51 Table 5: Construct Outer Loadings.52 Table 6: Construct reliability and validity.
53 Table 7: Heterotrait-Monotrait (HTMT) ratio. 55 Table 8: Inner VIF values.56 Table 9: Coefficient of determination values. 56 Table 10: Effect size f2 results. 57 Table 11: Hypothesis testing results.58 LIST OF ABBREVIATIONS AVE: Average Variance Extracted AP: Anthrophonism EU: Ease of use IQ: Information quality IT: Interactivity PLS - SEM: Partial Least Squares - Structural Equation Modeling HTMT: Heterotrait - Monotrait SI: Social influence TR: Trust TRA: Theory of Reasoned action TPB: Theory of Planned behavior TAM: Technology adoption model UN: Usefulness UI: AI Chatbot usage intention CHAPTER 1: RESEARCH OVERVIEW 1.
Background In recent years, the surge in interest surrounding text and text-to-speech artificial intelligence (AI) agents has reshaped customer service and revolutionized modern business strategies. Integrated into digital marketing approaches, these agents have emerged as indispensable communication channels (Kumar el al., 2019), operating 24/7 to respond to customer queries and requests, thereby saving both human resources and costs (Chung et al. Despite concerns about privacy and security in disclosing personal data to various mobile apps (Martinez-Roman et al., 2020), virtual assistants prove invaluable, capable of replacing entire support teams at a fraction of the cost. The COVlD-19-induced closure of premises and the challenges associated with maintaining physical infrastructure further underscore the role of AI in providing efficient and cost-effective solutions for businesses, with McKinsey reporting potential service cost savings of up to 40% through technology-driven customer experience enhancements.
Beyond these efficiencies, the adoption of virtual assistant technology has permeated diverse industries, ranging from tourism (Melian-Gonzalez et al., 2021) to education, banking (Fryer et al., 2019; Quah & Chua, 2019), healthcare (Nadarzynski et al., 2019; Lee & Malcein, 2020; Paul et al., 2021), social media (Zarouali et al., 2018), customer service (Luo et al., 2019; Chung et al., 2020), and mobile shopping (Van Eeuwen, 2017). The benefits extend from addressing customer requests and queries (Daugherty et al., 2019; Gkinko & Elbanna, 2022) to ensuring consistent, agile, and user-friendly service delivery (Luo et al. The ability of chatbots to manage a vast number of queries simultaneously has heightened service efficiency and quality (Cheng et al. Notably, the increased adoption of smartphones has further accentuated the imperative to investigate factors influencing AI adoption, as businesses strive to engage consumers anytime, anywhere (Wang et al.
Despite the widespread adoption, empirical evidence on the impact of AI on customer trust in the service industry remains scarce. This study endeavors to fill this gap by developing an integrated framework to scrutinize relationships in the burgeoning economy of Vietnam. With Vietnam rapidly embracing digital transformation, this study aims to explore the impact of AI applications on communication quality with customers and their trust. Moreover, the study delves into the influence of the COVID-19 pandemic on these dynamics.
Post-pandemic, Vietnam has witnessed remarkable growth in tourism, positioned among the world’s fastest-growing destinations, with the Vietnam National Administration of Tourism reporting growth rates ranging from 50% to 75%. However, challenges persist, necessitating efforts to enhance tourism products, the tourism environment, and service quality. In response, the government is actively developing a master plan to apply information technology in the tourism sector, aligning with the global trend towards smart tourism. Online booking, facilitated by simplicity, availability, personalized recommendations, and travel packages, has gained significant traction, with 30-40% of hotel guests booking rooms online, a trend expected to surge in the coming years (VECOM).
In the realm of chatbots, their ubiquity is underscored by platforms such as Amazon, Google, IBM, Apple, Messnow, and Hekate, among others, offering free creation tools. Chatbots are increasingly becoming indispensable for businesses, particularly in the tourism sector. Pioneering initiatives, such as the "Chatbot Danang Fanstaticity" integrated into Facebook, have showcased the technology's accessibility. Moreover, Vinpearl in Vietnam has embraced AI with its AI Butler, a virtual assistant leveraging AI, big data analysis, and natural language processing to enhance the visitor experience.
As Da Nang emerges as a Southeast Asian leader in deploying chatbot technology, businesses are recognizing the transformative potential of virtual assistants in elevating customer engagement and satisfaction. The global chatbot market’s anticipated growth from 190.8 million USD in 2016 to 1.25 billion in 2025 underscores the increasing acceptance, with customer service and relationship management standing out as primary sectors (Thormundsson, 2023). As smartphones become an integral part of daily life, particularly for the younger demographic, understanding AI adoption factors becomes paramount for businesses aiming to captivate consumers in a digitally connected world (Sarwar & Soomro, 2013). The study in Vietnam serves as a crucial exploration of Al’s impact, offering insights into the evolving dynamics of customer trust, technology adoption, and the broader implications for businesses navigating the post-pandemic era.
Research overall objectives We determine the factors impacting the intention to use AI Chatbot in tourism of Vietnamese people from 18 to 45 years old. From that result proposing ideas to improve the quality of AI Chatbot. Detail objectives The specific objectives set out in the study are as follows, based on the general objective: The first goal is to identify the factors influencing youth AI Chatbot in tourism usage intentions in Vietnam. The second goal is to analyze, evaluate, and test the factors influencing youth AI Chatbot usage intention in tourism in Vietnam.
The final goal is to draw conclusions about the key factors influencing AI Chatbot usage intention in tourism and then propose managerial implications for businesses that have been trading in using AI Chatbot while traveling to help them break into the market. Research questions and objectives 1. Research questions How does the ease of use affect the intention to to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How does the anthropomorphism affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How do the usefulness affect the intention to to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How does the trust affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How does social influence affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How docs embarrassment about purchase affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How does interactivity affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? How does the information quality affect the intention to use AI Chatbot in tourism for all Vietnamese people from 18 to 45 years old? What suggestions are made to improve and promote AI Chatbot usage intentions in tourism in the current period? 1. Research subjects The research subjects of this study are the factors affecting the intention to use AI Chatbot in tourism for Vietnamese people from 18 to 45 years old.
Research scope Time: The investigation, survey, and data collection will be carried out from January to February 2024. Subjects of the survey: For the convenience of the research subjects, which are the factors affecting the intention to use AI Chatbot in tourism, our research team has selected the target respondents who are all citizens of Vietnam from 18 to 45 years old. These subjects are not bound to be people who have never used, used, or have a need to use AI Chatbot. Research methods The study employed quantitative analysis of survey data gathered through questionnaires.
Various techniques were employed to validate the scales, encompassing outer loading analysis, evaluation of internal consistency metrics through Cronbach's Alpha, composite reliability analysis, assessment of average variance extracted (AVE), and scrutiny of the ratio of distinguishing characteristics - unique features. HTMT, denoting Heterotrait - Monotrail, was utilized in the examination. For hypothesis testing, the study employed the Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis technique. The model's fit was assessed through the coefficient R2.
The process involved encoding raw survey data from the questionnaire into Excel 2019, utilizing SPSS 20 for descriptive statistical analysis, and employing SmartPLS 4 for conducting the remaining tests. Structure of the study The study comprises five chapters, organized as follows: Chapter 1: Research Overview. Within this chapter, the research team expounds on the rationale behind selecting the topic, elucidates research objectives, poses research questions, defines research subjects, outlines the research scope, and details the methods employed in conducting the research. Chapter 2: Literature Review.
This chapter furnishes a comprehensive understanding of AI Chatbot and the theories underpinning the research. It lays the groundwork for proposing a research model and formulating hypotheses. Chapter 3: Research Methodology. The authors delve into the design of the study, elaborate on the scales utilized by the research team, and elucidate the procedures for survey sample acquisition in this chapter.
This section critically assesses the analysis results and scrutinizes the effectiveness of the scale. It also gauges whether the initially proposed hypotheses find support in the data. Chapter 5: Conclusion and Recommendations. The final chapter explores potential implications derived from the research findings.
It puts forth practical recommendations for businesses engaged in traveling trade. Additionally, this chapter outlines the limitations of the current study, aiming to address these shortcomings for future research endeavors. CHAPTER 2: LITERATURE REVIEW 2. Introduction Chapter 2 serves the purpose of establishing the theoretical underpinnings of the research paper.
It involves the construction of a research model, accompanied by hypotheses delineating the relationships among the model's concepts. The chapter is structured into four sections: (1) an overview of AI Chatbot, (2) foundational theories, (3) a comprehensive literature review, and (4) the formulation of research hypotheses and the presentation of the proposed research model.