Cluster Analysis of Airline Passengers Based on the Impact of Perceived Risks Towards Online Airline Tickets Purchasing

  • Maytinee Vongtharawat Faculty of Liberal Arts and Science, Kasetsart University, Nakon Patom
  • Prasobchai Pasunon Faculty of Management Science, Silpakorn University, Petchaburi
Keywords: Perceived Risks, Online Airline Tickets Purchasing, Cluster Analysis, Airline Passengers


The objective of this research is to cluster the group of airline passengers based on the impact of perceived risks towards online airline tickets purchasing. This quantitative research employed a purposive sampling method by collecting data from 390 Thai airline passengers who had experience of online airline tickets purchasing. The perceived risks questionnaire was the research tool for gathering and collecting data from target sample. The statistical tools for data analysis were percentage (%), mean (gif.latex?\bar{X}), standard deviation (S.D.) and K-Means clustering analysis. The empirical results obtained that most of Thai passengers have risk perception of online airline tickets purchasing at the moderate level: security risk (gif.latex?\bar{X}= 3.16), performance risk (gif.latex?\bar{X}= 3.10), financial risk (gif.latex?\bar{X}= 3.04), time risk (gif.latex?\bar{X}= 2.55), and psychological risk (gif.latex?\bar{X}= 2.51). Specially, Thai airline passengers are divided into 2 groups by K-Means clustering analysis: (1) “Risk Lover” (57.44%) and (2) Risk Aversion (42.56%). The finding contribute to value information for full service and low cost airlines and concerned organization to determine risk reduction strategy of online flight booking service.


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กัลยา วานิชย์บัญชา. (2550). สถิติสำหรับการวิจัย. กรุงเทพฯ: จุฬาลงกรณ์มหาวิทยาลัย

กัลยา วานิชย์บัญชา. (2556). การวิเคราะห์สถิติ: สถิติสำหรับการบริหารและวิจัย. กรุงเทพฯ: จุฬาลงกรณ์มหาวิทยาลัย

เจนวิทย์ นวลแสง. (2561). จริยธรรมการวิจัยในมนุษย์กับการวิจัยทางสังคมศาสตร์. วารสารการเมือง การบริหารและกฎหมาย. ปีที่ 10, ฉบับที่ 2, หน้า 131-155

ประสบชัย พสุนนท์. (2553). เอกสารคำสอนวิจัยการตลาด 1. นครปฐม: เพชรเกษมพริ้นติ้ง

ละเอียด ศิลาน้อย. (2560). การใช้สูตรทางสถิติ (ที่ถูกต้อง) ในการกำหนดขนาดของกลุ่มตัวอย่างเพื่อการวิจัยเชิงปริมาณในทางมนุษยศาสตร์และสังคมศาสตร์. วารสารวิจัยและพัฒนา มหาวิทยาลัยราชภัฏบุรีรัมย์. ปีที่ 12, ฉบับที่ 2, หน้า 50-61

Agag, G. and El-Masry, A. A. (2016). Understanding Consumer Intention to Participate in Online Travel Community and Effects on Consumer Intention to Purchase Travel Online and WOM: an Integration of Innovation Diffusion Theory and TAM with Trust. Computers in Human Behavior. Vol. 60, pp. 97-111. DOI: 10.1016/j.chb.2016.02.038

Airline Reporting Corporation (ARC). (2019). Sales and Documents Statistics. Access (29 December 2019). Available (

Amaro, S. and Duarte, P. (2015). An Integrative Model of Consumers’ Intentions to Purchase Travel Online. Journal of Tourism Management. Vol. 46, pp. 64-79. DOI: 10.1016/j.tourman.2014.06.006

Bauer, R. A. (1960). Consumer Behavior as Risk Taking. In Proceeding of the 43rd Conference of the American Marketing Association. In Hancock, R. S., Ed., Dynamic Marketing for a Changing World, pp. 389-398

Best, J. W. (1981). Research in Education (4th ed.). New Jersey: Prentice Hall

Boksberger, P. E., Bieger, T., and Laesser, C. (2007). Multidimensional Analysis of Perceived Risk in Commercial Air Travel. Journal of Air Transport Management. Vol. 13, No. 2, pp. 90-96. DOI: 10.1016/j.jairtraman.2006.10.003

Buhalis, D. and Law, R. (2008). Progress in Information Technology and Tourism Management: 20 Years on and 10 Years After the Internet - The State of eTourism Research. Tourism Management. Vol. 29, pp. 609-623. DOI: 10.1016/j.tourman.2008.01.005

Cochran, W. G. (1953). Sampling Techniques. New York: John Wiley & Sons

Considine, E. and Cormican, K. (2016). Self-Service Technology Adoption: An Analysis of Customer to Technology Interactions. Procedia Computer Science. Vol. 100, pp. 10-109. DOI: 10.1016/j.procs.2016.09.129

Cunningham, L. F., Gerlach, J. H., Harper, M. D., and Young, C.E. (2005). Perceived Risk and the Consumer Buying Process: Internet Airline Reservations. International Journal of Service Industry Management. Vol. 16, No. 4, pp. 357-372. DOI:10.1108/09564230510614004

Deng, R. and Ritchie, B. W. (2018). International University Students’ Travel Risk Perceptions: An Exploratory Study. Current Issue in Tourism. Vol. 21, No. 4, pp. 455-476. DOI: 10.1080/13683500.2016.1142939

Dowling, G. R. and Staelin, R. (1994). A Model of Perceived Risk and Intended Risk-Handling Activity. Journal of Consumer Research. Vol. 21, No. 1, pp. 119-134. DOI: 10.1086/209386

Featherman, M. S. and Pavlou, P. A. (2003). Predicting E-Services Adoption. A Perceived Risk Facets Perspective. International Journal of Human Computer Studies. Vol. 59, No. 4, pp. 451-474. DOI: 10.1016/S1071-5819(03)00111-3

Gretzel, U. and Fesenmaier, D. R. (2009). Information Technology: Shaping the Past, Present and Future of Tourism in The SAGE Handbook of Tourism Studies. London: Sage

Hanafizadeh, P. and Khedmatgozar, H. R. (2012). The Mediating Role of the Dimension of the Perceived Risk in the Effect of Customers’ Awareness on the Adoption of Internet Banking in Iran. Electronic Commerce Research. Vol. 12, No. 2, pp. 151-175. DOI: 10.1007/s10660-012-9090-z

IATA. (2020). Safely Restarting Aviation ACI and IATA Joint Approach. Access (12 May 2020). Available (

IATA. (2019a). Annual Review 2019. Access (29 December 2019). Available (

IATA. (2019b). Program: E-Ticketing. Access (29 December 2019). Available (

ICAO. (2019a). Annual Report 2018. Access (29 December 2019). Available (

ICAO. (2019b). Aviation Benefi ts Report 2019. Access (29 December 2019). Available (

Koo, T. T., Caponecchia, C., and Williamson, A. (2015). Measuring the Effect of Aviation Safety Risk Reduction on Flight Choice in Young Travellers. Safety Science. Vol. 73, pp. 1-7. DOI: 10.1016/j.ssci.2014.10.008

Ku, E. S. and Chen, C. D. (2013). Fitting Facilities to Self-Service Technology Usage: Evidence from Kiosks in Taiwan Airport. Journal of Air Transportation Management. Vol. 32, Issue C, pp. 87-94. DOI: 10.1016/j.jairtraman.2013.07.001

Krbová, P. K. (2016). Generation Y Attitudes Towards Shopping: A Comparison of the Czech RePublic and Slovakia. Journal of Competitiveness. Vol. 8, Issue 1, pp. 38-54. DOI: 10.7441/joc.2016.01.03

Lee, J. and Morrison, A. M. (2010). A Comparative Study of Website Performance. Journal of Hospitality and Tourism Technology. Vol. 1, pp. 50-67. DOI: 10.1108/17579881011023016

López-Bonilla, J. M. and López-Bonilla, L. M. (2013). Self-Service Technology Versus Traditional Service: Examining Cognitive Factors in the Purchase of the Airline Ticket. Journal of Travel and Tourism Marketing. Vol. 30, Issue 5, pp. 497-508. DOI: 10.1080/10548408.2013.803396

McKinsey & Company. (2018). True Gen: Generation Z and Its Implications for Companies. Access (6 May 2020). Available (

Muda, M., Mohd, R., and Hassan, S. (2016). Online Purchase Behavior of Generation Y in Malaysia. Procedia Economics and Finance. Vol. 37, pp. 292-298. DOI: 10.1016/S2212-5671(16)30127-7

Nunkoo, R. and Ramkissoon, H. (2013). Traveler’s E-Purchase Intent of Tourism Products and Services. Journal of Hospitality Marketing and Management. Vol. 22, Issue 5, pp. 505-529. DOI: 10.1080/19368623.2012.680240

Priporas, C. V., Stylos, N., and Fotiadis, A. K. (2017). Generation Z Consumers’ Expectations of Interactions in Smart Retailing: A Future Agenda. Computers in Human Behavior. Vol. 77, pp. 374-381

Rezaei, S., Shahijan, M. K., Valaei, N., Rahimi, R., and Ismail, W. K. (2016). Experienced International Business Traveller’s Behavior in Iran: A Partial Least Squares Path Modelling Analysis. Tourism and Hospitality Research. Vol. 18, Issue 2, pp. 163-190. DOI: 10.1177/1467358416636930

Wiertz, C. and Ruyter, K. D. (2007). Beyond the Call of Duty: Why Customers Contribute to Firm-hosted Commercial Online Communities. Organization Studies. Vol. 28, pp. 347-376. DOI: 10.1177/0170840607076003

Yang, Y., Liu, Y., Li, H., and Yu, B. (2015). Understanding Perceived Risks in Mobile Payment Acceptance. Industrial Management and Data Systems. Vol. 115, No. 2, pp. 253-269. DOI: 10.1108/IMDS-08-2014-0243

Zhou, Z. (2004). E-Commerce and Information Technology in Hospitality and Tourism. Canada: Delmar Learning

How to Cite
Vongtharawat, M., & Pasunon, P. (2020). Cluster Analysis of Airline Passengers Based on the Impact of Perceived Risks Towards Online Airline Tickets Purchasing. RMUTI JOURNAL Humanities and Social Sciences, 8(1), 68-81. Retrieved from
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