Understanding Consumer Behavior with the Use of the Technology Acceptance Model in Online Booking
DOI:
https://doi.org/10.18502/kss.v9i10.15716Abstract
This study aimed to examine consumer buying intention using the Technology Acceptance Model (TAM). This study seeked to determine the direct effect of perceived usefulness, perceived ease of use, and perceived trust on buying intention through online booking applications. This type of research was explanatory, which explained the causal relationship between the variables and used a quantitative approach. The population used in this study was all people who had installed online booking applications. The sampling method of 450 respondents in this study was nonprobability sampling with a purposive sampling technique, whereby the questionnaire was distributed in the form of a survey through social media. Hypothesis testing was carried out using the t-test. Data analysis used multiple linear regression analysis, which was processed with SPSS software. From the results of testing the three hypotheses that had been carried out, it was concluded that the variables of perceived usefulness, perceived ease of use, and perceived trust had a significant and positive effect on the variable of buying intention through online booking applications.
Keywords: consumer behavior, Technology Acceptance Model, online booking
References
Taherdoost H. A review of technology acceptance and adoption models and theories. Procedia Manuf. 2018;22:960–7. DOI: https://doi.org/10.1016/j.promfg.2018.03.137
Turban E, Outland J, King D, Lee JK, Liang T-P, Turban DC, et al. Electronic commerce payment systems. Electron Commer 2018 A Manag Soc Networks Perspect. 2018;457–99. DOI: https://doi.org/10.1007/978-3-319-58715-8_12
Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Manage Inf Syst Q. 1989;13(3):319–40. DOI: https://doi.org/10.2307/249008
Ajzen I. Understanding attitudes and predictiing social behavior. Englewood cliffs; 1980.
Fatmawati E. Technology Acceptance model (TAM) untuk menganalisis penerimaan terhadap sistem informasi di perpustakaanM INFORMASI PERPUSTAKAAN. Iqra J Perpust dan Inf. 2015;9(1):196942.
Jogiyanto H. Behavioral Information Systems. Yogyakarta Andi Offset, Co Ltd.; 2007.
Ramayah T, Ignatius J. Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. ICFAI J Syst Manag. 2005;3(3):36– 51.
Wallace LG, Sheetz SD. The adoption of software measures: A technology acceptance model (TAM) perspective. Inf Manage. 2014;51(2):249–59. DOI: https://doi.org/10.1016/j.im.2013.12.003
Yilmazlar M, Takunyaci M, Çorapçigil A. Analyzing the psychological symptoms of students in undergraduate program in elementary science teaching. IIB Int Ref Acad Soc Sci J. 2014;5(15):46–59.
Mandilas A, Karasavvoglou A, Nikolaidis M, Tsourgiannis L. Predicting consumer’s perceptions in on-line shopping. Procedia Technol. 2013;8:435–44. DOI: https://doi.org/10.1016/j.protcy.2013.11.056
Zahra FA. Pengaruh Perceived Usefulness, Perceived Ease of Use dan Perceived Risk Terhadap Intention to Shop Online (Studi pada Potensial Pasar Airbnb di Pulau Jawa). J Ilm Mhs. 2018 Feb;7(1).
Juniwati J. Influence of perceived usefulness, ease of use, risk on attitude and intention to shop online. Eur J Bus Manag. 2014;6(27):218–29.
Kucukusta D, Law R, Besbes A, Legohérel P. Re-examining perceived usefulness and ease of use in online booking: the case of Hong Kong online users. Int J Contemp Hosp Manag. 2015;27(2):185–98. DOI: https://doi.org/10.1108/IJCHM-09-2013-0413
Kotler P, Keller KL. Marketing Management. 15th ed. New York: Pearson Education Inc.; 2016.
Mayer RC, Davis JH, Schoorman FD. An integrative model of organizational trust. Acad Manage Rev. 1995;20(3):709–34. DOI: https://doi.org/10.5465/amr.1995.9508080335
Shim S, Eastlick MA, Lotz SL, Warrington P. An online prepurchase intentions model: the role of intention to search: best overall paper award—The Sixth Triennial AMS/ACRA Retailing Conference, 2000?. J Retailing. 2001;77(3):397–416. DOI: https://doi.org/10.1016/S0022-4359(01)00051-3
Thamizhvanan A, Xavier MJ. Determinants of customers’ online purchase intention: an empirical study in India. J Indian Bus Res. 2013;5(1):17–32. DOI: https://doi.org/10.1108/17554191311303367
Hassanein K, Head M. The impact of infusing social presence in the web interface: an investigation across product types. Int J Electron Commerce. 2005;10(2):31–55. DOI: https://doi.org/10.2753/JEC1086-4415100202
Haekal A, Widjajanta B. Pengaruh kepercayaan dan persepsi risiko terhadap minat membeli secara online pada pengunjung website classifieds di inonesia. J Bus Manag Educ. 2016;1(1):183–95. DOI: https://doi.org/10.17509/jbme.v1i1.2287
Phonthanukitithaworn C, Sellitto C, Fong MW. User intentions to adopt mobile payment services: A study of early adopters in Thailand. J Internet Bank Commerce. 2015;20(1).
Howes-Tonks R. The definition of online booking tool [in under 100 words] - Click Travel [Internet]. 2019. Available from: https://www.clicktravel.com/blog/thedefinition- of-online-booking-tool-in-under-100-words/
Pavlou PA. Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int J Electron Commerce. 2003;7(3):101–34. DOI: https://doi.org/10.1080/10864415.2003.11044275
Mowen JC, Minor MS. Consumer Behavior: A Framework. Upper Saddle River (NJ): Prentice Hall; 2001.
Sekaran U, Bougie R. Research methods for business: A skill building approach. John Wiley & Sons; 2016.
