Determination of Effective Travel Variables on Air Transport Demand with Using Structural Equation

Document Type : Research Paper

Authors

1 MSc. Grad., Department of Civil Engineering, Yazd University, Yazd, Iran

2 Associate Professor, Department of Civil Engineering, Yazd University, Yazd, Iran

3 Associate Professor, College of Engineering, Yazd University, Yazd, Iran

Abstract

Air transport system has always been involved in all aspects of life because of its high potential in transporting passengers and goods. In this research we surveys the effects of travel variables on demand of domestic air transport, and for gathering required information from passengers, a questionnaire was designed including 20 effective parameters on air transport demand with questions These parameters were investigated based on their importance using “Factor Analysis” and finally proved that the factors “price paid by passengers”, ”services offered by air transport system” and “time” has had the greatest impact on air transport demand with more than 20 % influence. “Structural Equation Modeling” has been used for checking the “Factor Analysis” results. The results of the model proved the correctness of factor analysis. Furthermore, the result of factor analysis has showed that the most important parameter has been “low cost travel” with the factor load of 0.9-1 in all case studies. Results show that both groups with factor load of more than 0.5 in the obtained factors have identified the factor “services” as the important and effective factor with the influence value of more than 20%.

Keywords


-Anand, S. (2014) "Application of factor analysis to k-means clustering algorithm on transportation data", International Journal of Computer Applications, No. 95, pp. 40-46.
-Barnhart, C. and Fearing, D. (2012) "Demand and capacity management in air transportation", The Association of European Operational Research Societies  No. 1, pp.135-155.
-Bass, P., Donoso, P. and Munizaga, M. (2011) "A model to assess public transport demand stability", Transportation Research Part A 1; No.45, pp.755-764. 
-Bieger, T., Wittmer, A. and Laesser, C. (2006) "What is driving the continued growth in demand for air travel, Customer value of air transport?", Journal of Air Transport Management No.13, pp. 31-36.
-Beria, P.  and Laurino, A. (2016) " Determinants of daily fluctuations in air passenger volumes. The effect of events and holidays on Milan Malpensa airport " Journal of Air Transport Management No. 53,pp. 73-84.
-Goedeking, P. (2010) "Assessing and comparing the strengths and weaknesses of aviation networks", Transportation Research Part A No.10, pp.119-125.
-Israel, G. (2013) “Determining Sample Size 1.”,  University of Florida ,  p.1-5.
-Janic, M. (2015)"Reprint of ‘‘Modeling the resilience, friability and costs of an air transport network affected by a large-scale disruptive event’’. Transportation Research Part A, Vol.71, pp.77-92.
-Kopsch, F. (2011) "A demand model for domestic air travel in Sweden" Journal of Air Transport Management, No.20, pp.46-48.
-Lieshout, R, Malighetti P, Redondi R, Burghouwt G. (2015)"The competitive landscape of air transport in Europe" Journal of Transport Geography; Vol.50, pp.68-82.
-Liu, D. (2015)"Measuring aeronautical service efficiency and commercial service efficiency of East Asia airport companies: An application of Network Data Envelopment Analysis" Journal of Air Transport Management; No.52, pp.11-22.
-Lupo, T. (2015) “Fuzzy ServPerf model combined with ELECTRE III to comparatively evaluate service quality of international airports in Sicily”, Journal of Air Transport Management Vol. 30, pp.1-11.
-Rolim, P., Bettini, H. and Oliveira, A. (2016)" Estimating the impact of airport privatization on airline demand: A regression-based event study", Journal of Air Transport Management No. 54, pp.31-41.
-Saffarzadeh, M. and  NaserAlavi, S. S. (2009) "Airline schedule planning using heuristic search method", Journal of  Transportation Engineering  , Volume 6 , Number 2 (19); Pp.175 -184.
-Scarpel, R. (2014) "A demand trend change early warning forecast model for the city of São Paulo multi-airport system”, Transportation Research Part A, No.65, pp.23-32.
-Scotti, D. and Dresner, M. (2015) "The impact of baggage fees on passenger demand on US air routes", Transport Policy, Vol. 43, pp.4-10.
-Sherry, L. (2014) "A method for quantifying travel productivity for corporate travel managers", Journal of Air Transport Management, No.42: pp.118-124.
-Xiao, Y, Fu, X. and Zhang, A. (2013) "Demand uncertainty and airport capacity choice", Transportation Research Part B Vol. 57, pp.91-104.
-Yang, H. and Fu, X. (2015)"A comparison of price-cap and light-handed airport regulation with demand uncertainty", Transportation Research Part B, Vol.73, pp.122-132.