Purpose -Artificial intelligence (AI) adoption is critical in the age of digital technology. This review article aims to evaluate the literature on AI in the hospitality industry.Method -A narrative synthesis was used in this review article. Moreover, the literature was reviewed systematically to explore AI in the hospitality industry. The literature and information were obtained from various books and research articles on EBSCO, Google Scholar, Scopus, Web of Science, and ScienceDirect. The inclusion criteria were studies that clearly defined AI in all aspects of the hospitality industry, were published and written in English and were peer-reviewed. Content analysis was employed.Results -The use of AI is a strategic and critical factor in economic development. Furthermore, AI technologies are increasingly being used as digital assistants. They help businesses in the hospitality industry in a variety of ways, including improving customer service, expanding operational capability, and lowering costs. However, there are some risks associated with AI advancements, such as job loss in low-tech sectors, loss of control due to robot autonomy, and safety, security, and privacy concerns. 1307Conclusion -AI technologies have both positive and negative effects on the workforce and job employment in the hospitality industry.Recommendations -The recommendation is to consider a quantitative study regarding AI adoption in the hospitality industry or other sectors. Also, a qualitative approach could give a clear view of insight results for further study.Research Implications -This review article contributed to the existing literature on AI adoption in the hospitality industry. Hence, it could be used to guide future research on AI adoption in the hospitality industry. It may also aid academics in broadening their research by incorporating more potential elements.Practical Implications -This review article could lead to a better understanding of AI adoption in the hospitality industry. Moreover, it may assist business owners, managers, and marketers in the hospitality industry or any sector to achieve and enhance high business performance by implementing appropriate strategies to meet the needs and expectations of both customers and employees through the use of AI.
This study aims to predict the intention to use smart education technology during the COVID-19 pandemic among higher education students in Thailand. The determinants of intention to use smart education technology adopt the technology acceptance model (TAM) through the mediating effect of student satisfaction. The online convenience sampling collected data from 238 higher education students in Thailand to confirm the theoretical framework. The data were analysed using SPSS Version 27 and the partial least square structural equation model (PLS-SEM). The findings support that the TAM model comprises perceived ease of use and perceived usefulness. Student satisfaction is a significant mediator between the TAM model and the intention to use smart education technology. However, the TAM model has no significant direct effect on the intention to use smart education technology. This study may benefit educators and instructors in improving the intention to use smart education technology by adopting the TAM model and student satisfaction. Moreover, the results could apply in any sector to improve the intention to use smart technology through predictors of the TAM model and mediating role of users’ satisfaction.
Purpose -The digital economy is becoming more popular these days. Thus, this article aims to review the growing trend in the digital economy systematically.Method -A narrative synthesis was employed. Moreover, the literature was reviewed systematically to describe the digital economy. The literature and information were obtained from various books and research articles on EBSCO, Google Scholar, Scopus, Web of Science, and ScienceDirect. The inclusion criteria were studies that clearly defined digital economy, were published and written in English, and were peer-reviewed. 1352Results -There is a growing trend in the digital economy. Moreover, the opportunities and digital economy challenges are important to many countries' economic systems.Conclusion -It is critical to carefully pay attention to the digital economy to enhance and grow the economic systems.Recommendations -The recommendation is to consider empirical research. A qualitative approach, such as interviews, could also give insight results and a clear view. Moreover, it is recommended to consider a quantitative study, such as online surveys.Research Implications -This review article contributed to the existing literature on the digital economy. Hence, it could be used to guide future research on the digital economy.Practical Implications -This review article could lead to a better understanding of the digital economy. Therefore, the implications could be applied to any sector in better understanding and implementing appropriate strategies, regarding the digital economy.
Purpose -Mobile banking is becoming increasingly popular in Thailand. This study investigates the relationship between cyber security knowledge, awareness, and behavioural choice protection among mobile banking users in Thailand.Method -A quantitative approach was employed. The questionnaire was developed based on reliable and valid sources. The online questionnaire was adopted to collect the data through convenience sampling of 414 mobile banking users in Thailand. The data were analysed using SPSS Version 27 and ADANCO 2.3 for hypothesis testing.Results -The results reveal that cyber security knowledge significantly impacts cyber security awareness and behavioural choice protection. Cybersecurity awareness significantly impacts behavioural choice protection. Cyber security awareness significantly mediators between cyber security knowledge and behavioural choice protection.Conclusion -Cyber security knowledge and awareness are critical for influencing behavioural choice protection among Thai mobile banking users. As a result, banks must develop an effective cybersecurity strategy to meet the needs and expectations of mobile banking users. As a result, there may be an increase in mobile banking users, and high business performance may incur.Recommendations -This study employed sampling to explain only mobile banking from customers' perceptions. It may not cover other sectors. Hence, there should be increased sampling in a variety of industries. Furthermore, this study consists of a self-administered questionnaire for quantitative analysis. Thus, more insightful analysis through qualitative research could also explain the association between cyber security awareness, cyber security knowledge, and behavioural choice protection among mobile banking application customers or other sectors in Thailand.Research Implications -This study contributed to the existing literature on cyber security awareness, cyber security knowledge, and behavioural choice protection. Therefore, the findings of this study may help academics expand their research by incorporating additional potential factors. These metrics could guide future cybersecurity research and its outcomes in the digital era.Practical Implications -The implications could be applied to any sector in explaining the association between cybersecurity awareness, knowledge and behavioural choice protection among mobile banking application customers or other sectors in Thailand.
The widespread adoption of digital technologies in various economic activities paves the way for the establishment of a unified digital space. ChatGPT, an artificial intelligence language model, can generate increasingly realistic text, with no information on the accuracy and integrity of using these models in scientific writing. This study aims to investigate factors influencing public perceptions toward the acceptance of ChatGPT as the Robo-Assistant, using a mixed method. The quantitative approach in this study employed convenience sampling to collect data through closed-ended questionnaires from a sample size of 1,880 respondents. Statistical analysis software was used for data analysis. The researchers used binary regression to examine the relationship between various independent variables (such as score, gender, education, social media usage) and the acceptance of ChatGPT, as dependent variable. As part of the qualitative approach, in-depth interviews were conducted with a purposive sample of six participants. The qualitative data was analyzed using the content analysis method and the NVivo software program. Findings show that ChatGPT awareness and usage are influenced by variables like score, gender, education, and social media usage. Occupation and monthly income were not significant factors. The model with all independent variables was able to predict the use of ChatGPT as the Robo-Assistant in Thailand with an accuracy rate of 96.3%. The study also confirms acceptance of ChatGPT among Thai people and emphasizes the importance of developing sociable robots that consider human interaction factors. This study significantly enhances our comprehension of public perceptions, acceptance, and the prospective ramifications associated with the adoption of ChatGPT as the Robo-Assistant. The acquired findings offer indispensable guidance for the effective utilization of AI models and the advancement of sociable robots within the domain of human-robot interaction.
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