The Measurement Model of Tourism Destination Images Using Fuzzy Inference System

  • I Nyoman Sutapa Petra Christian University
  • Magdalena Wullur Faculty of Economics and Business, Sam Ratulangi University, Kampus Unsrat, Bahu, Manado 95115, INDONESIA
Keywords: Tourism services quality; Mamdani’s fuzzy inference system; travellers perception.

Abstract

The article discusses the measurement model of tourism destination images perceived by travellers based on five dimensions of the service quality, i.e. tangibles, reliability, responsiveness, empathy, and assurance. Measurement problems occur when a traveller assesses the quality of a tourism destination service subjectively with vague boundaries and perceives the image of a tourism destination to vary. To address these issues, we designed an inference model using Mamdani's fuzzy inference system. The results of this study are quantitative assessments of the image of tourism destinations by various travellers based on qualitative perceptions of the quality of service experienced by the traveller.

 

 

References

Survey Team of Potency and Competitiveness of North Sulawesi Tourism Industry in Facing MEA (in Bahasa Indonesia edition). (2016). Tourism Industry Report, North Sulawesi Province. PSE-KP, Gadjah Mada University.
Bhat, M. A. (2012). Tourism Service Quality: A Dimension-specific Assessment of SERVQUAL. Global Business Review, 13 (2), 327–337.
Akroush, M. N., Jraisat, L. E., Kurdieh, D. J., Al-Faouri, R. N. & Qatu, L. T. (2016). Tourism service quality and destination loyalty –the mediating role of destination image from international tourists’ perspectives. Tourism Review, 71 (1), 18-44.
De Ona, J., de Ona, R., Eboli, L., & Mazzulla, G. (2016). Index numbers for monitoring transit service quality. Transportation Research Part A: Policy and Practice, 84, 18-30.
Farias, S., Aguiar, F., Kovacs, M., & Sales, F. (2013). Destination image on the web: evaluation of Pernambuco's official tourism destination websites. Business Management Dynamics, 2 (10), 35-48.
Said, A., Shuib, A., Ayob, N., & Yaakub, F. (2013). An evaluation of service quality from visitors’ perspectives: the case of Niah National Park in Sarawak. International Journal of Business and Society, 14 (1), 61-78.
Sreekumar, Mahapatra, S., & Mahapatra, S. S. (2015). Service Quality of Indian Banks: A Fuzzy Inference System Approach, Asian Academy of Management Journal, 20 (2), 59–80.
Zadeh, L. (1996). Fuzzy logic computing with words. IEEE Transactions on Fuzzy Systems, 4, 103–111.
Sabri, N., Aljunid, S. A., Salim, M. S., Badlishah, R. B., Kamaruddin, R., & Malek, M. F. A. (2013). Fuzzy Inference System: Short Review and Design. International Review of Automatic Control, 6 (4), 441-449.
Mamdani E. H. & Assilian, S. (1975). An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller. International Journal of Man-Machine Studies, 7, 1-13.
Hankinson, G. (2005). Destination brand images: a business tourism perspective. Journal of Services Marketing, 19 (1), 24-32.
Kim, S., Holland, S., & Han, H. (2013). A structural model for examining how destination image, perceived value, and service quality affect destination loyalty: a case study of Orlando. International Journal of Tourism Research, 15 (1), 313-328.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64 (1), 12-40.
Published
2018-12-01
Section
Articles