Factors Influencing the Acceptance of Innovation Prototypes: Hotel Management and Booking Systems on Cloud Computing Technology: A Case Study of Hotels of All Sizes on Koh Larn, Chonburi Province

Abstract

This research aims to 1) study the levels of technology acceptance factors, including perceived usefulness, perceived ease of use, attitude towards use, behavioral intention to use, and the level of innovation acceptance of hotel management and booking systems on Cloud Computing technology, and 2) examine the impact of each technology acceptance factor on the acceptance of the prototype innovation of hotel management and booking systems on Cloud Computing technology. The case study involves hotels and accommodations of all sizes on Koh Larn, Chonburi province. The researcher employed quantitative research methods and developed a questionnaire as a measurement tool to collect data. The questionnaire utilized a 5-point rating scale. The validity and reliability of the questionnaire were verified before collecting data from the sample, which consisted of supervisory-level employees of accommodation businesses that are members of hotel or accommodation groups on Koh Larn, Chonburi province. The sample size calculated was 385 individuals. Data analysis was performed using statistical software, calculating means, and standard deviations, and conducting multiple linear regression analysis to determine the influence of independent variables on the dependent variable and to explore relationships and test research hypotheses.

The research findings revealed that: 1.) Most of the sample group were male, totaling 272 individuals, accounting for 70.65%. Individuals aged 20 years or younger were 189, making up 49.09%. Those with a bachelor's degree totaled 152, accounting for 39.48%. Individuals with 11 to 15 years of work experience were 142, making up 36.88%, and those with a monthly income between 9,001 to 15,000 baht accounted for 51.17%. 2.) The study of technology acceptance variables found that the perceived usefulness had an average score of 3.70, indicating a high level, the perceived ease of use had an average score of 3.60, indicating a high level, the attitude towards use had an average score of 3.51, indicating a high level, the behavioral intention to use had an average score of 3.40, indicating a moderate level, the acceptance of the innovation prototype for hotel management and booking on Cloud Computing had an average score of 3.50, indicating a high level. And 3) multiple linear regression analysis showed that the collected data met the initial assumptions for conducting the analysis. All independent variables included in the equation significantly influenced the dependent variable. Together, the independent variables could predict the dependent variable with an accuracy of 47.1%.