Abstract :

A taxi service provided by the I Gusti Ngurah Rai International Airport plays an important role in meeting the transportation needs of travelers, as it provides a convenient and effective means for people to go from the airport to their destination. However, in today’s competitive industry, airport taxi service may find it difficult to attract and retain a growing number of passengers. This research aims to identify strategies that can be used by airport taxi service, where this research will focus on identifying significant attributes that influence passengers’ decisions to use airport taxi services and determine the most effective strategies in an effort to increase the number of passengers. The research analysis was conducted using a discrete choice model approach to determine individual behavior. Multinomial logistic regression (MNL) model was used for the three alternative mode choices observed between Taxi, Minivan, and Grab. The model uses influential attributes such as waiting time, travel time, price, safety, convenience, capacity, and promotion. The research data was obtained quantitatively with data collection techniques using questionnaires with respondents spread across major cities in Indonesia.  Based on the results of the analysis, it shows that the most significant attributes affecting taxi selection are safety, price, convenience, travel time, and capacity.

 

---

Keywords :

Airport Taxi, Consumer Choice Decision, Discrete Choice Model, Significant Attribute

---

References :

1. Kemenhub, “Pemerintah Terus Berupaya Pulihkan Sektor Transportasi di Masa Pandemi,” 22 July 2020. [Online]. Available: https://dephub.go.id/post/read/pemerintah-terus-berupaya-pulihkan-sektor-transportasi-di-masa-pandemi.
2. Kahfi, “Mandiri Institute Sebut Belanja di Destinasi Wisata Meningkat,” 18 July 2022. [Online]. Available: https://www.validnews.id/ekonomi/mandiri-institute-sebut-belanja-di-destinasi-wisata-meningkat.
3. J. Pot and S. Koster, “Small airports: Runways to regional economic growth?,” Journal of Transport Geography, 2022.
4. Jia, Y. Caoa, Y. Dua and H. M. Zhang, “Comparative Analyses of Taxi Operations at the Airport,” in Transportation Research Procedia, 2017.
5. Wang, B. Ma and R. Bai, “How Does Green Product Knowledge Effectively Promote Green Purchase Intention?,” Sustainability, 11(4), p. 1193, 2019.
6. P. Peter and J. C. Olson, Consumer Behavior & Marketing Strategy, McGraw-Hill, 2010.
7. Kotler and G. Armstrong, Principles of Marketing, Pearson, 2010.
8. Chen and S. Li, “Mode Choice Model for Public Transport with Categorized Latent Variables,” Mathematical Problem in Engineering, 2017.
9. Kotler, Marketing Management, Prentice Hall, 2003.
10. G. Schiffman and L. L. Kanuk, Consumer Behavior, Prentice Hall, 2000.
11. Stobierski, “Willingness to Pay: What it is & how to calculate?,” October 2020. [Online]. Available: https://online.hbs.edu/blog/post/willingness-to-pay.
12. Forbes-Brown, “An Assessment of Consumers’ Willingness to Pay for Attributes of Milk and Dairy Products with the 100% Canadian Milk Symbo,” University of Saskatchewan Library, 2013.
13. N. Wulansari and M. D. Astari, “Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia),” in MATEC Web of Conferences, 2018.
14. Albalate and G. Bel, “What shapes local public transportation in Europe? Economics, mobility, institutions, and geography,” Transportation Research Part E: Logistics and Transportation Review, vol. 46, no. 5, pp. 775-790, 2010.
15. Souche, “Measuring the structural determinants of urban travel demand,” Transport Policy, vol. 17, no. 3, pp. 127-134, May 2010.
16. E. T. Horn, “Procedures for planning multi-leg journeys with fixed-route and demand-responsive passenger transport services,” Transportation Research Part C Emerging Technologies, vol. 12, no. 1, pp. 33-55, 2004.
17. F. Yeganeh, N. Khademi, H. Farahani and M. A. Besharat, “A qualitative exploration of factors influencing women’s intention to use shared taxis: A study on the characteristics of urban commuting behavior in Iran,” Transport Policy, pp. 90104, 2022.
18. Gardner, J. Cui and E. Coiacetto, “Harassment on public transport and its impacts on women’s travel behaviour,” Australian Planner, pp. 8-15, 2017.
19. Alonso, R. Barreda, L. dell’Olio and A. Ibeas, “Modelling user perception of taxi service quality,” Transport Policy, pp. 157-164, 2018.
20. Disney, “Competing through quality in transport services,” Managing Service Quality, vol. 8, no. 2, pp. 112-118, 1998.
21. Riskarini and Y. Ardianto, “Service Quality, Price and Product Promotion Towards Customer Trust, Impact on Customer Loyalty Grab Bike Depok Region,” Journal of Business, Management, and Accounting, pp. 280-287, 2021.
22. S. Koppelman and C. Bhat, “A Self Instrcuting Course in Mode Choice Modeling: Multinomial and Nested Logit Models,” U.S. Department of Transportation, Federal Transit Administration, 2006.
23. d. D. Ortúzar and L. G. Willumsen, Modelling Transport, Fourth Edition, John Wiley & Sons, Ltd, 2011, pp. 43-44.
24. Bierlaire, “Calculating indicators with PandasBiogeme,” 2018.
25. E. Train, Discrete Choice Methods with Simulation, Cambridge University Press, 2009.