External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail
Social-economic variables influence transportation
demand largely. Analyses of discrete choice model consider
social-economic variables to study traveler-s mode choice and
demand. However, to calibrate the discrete choice model needs to have
plenty of questionnaire survey. Also, an aggregative model is
proposed. The historical data of passenger volumes for high speed rail
and domestic civil aviation are employed to calibrate and validate the
model. In this study, models with different social-economic variables,
which are oil price, GDP per capita, CPI and economic growth rate,
are compared. From the results, the model with the oil price is better
than models with the other social-economic variables.
[1] K. R. Buckeye, , "Ranking Alternatives Using Fuzzy Numbers, Fuzzy Set
and Systems," No. 15, 1992, pp. 21-31.
[2] A. Kanafan, and W. Youssef, "High-Speed Rail in California", University
of California Institute of Transportation Studies Review, Vol.no17,1994 ,
pp.2-8.
[3] J. J. Lin, C. M. Feng and L. C. Huang, "Forecasting the Taiwan High
Speed Rail System on Local Development," Transportation Planning
Journal (in Chinese version), Vol. 34, No. 3, 2005, pp. 391-412.
[4] Ministry of Transportation and Communications, A Report on the Survey
of High Speed Rail Travel Behavior, Taipei, Taiwan, 2007.
[5] L. W. Lan, "Impact of High Speed Railway on the Western Corridor of
Taiwan Area," Road News Quarterly, Vol. 30, No.1, 1991, pp. 15-22.
[6] C. T. Wang, and T. C. Liu, "The Aviation Market Characteristics of
Taiwan Area and Development Research," Transportation Planning
Journal (in Chinese version), Vol.28, No.3, 1999, pp. 451-484.
[7] T. C. Huang, "Website of Land/Air Transportation Transition Analysis in
Response to the Commencement of Revenue Operation of High Speed
Railway," Transportation Comments, Chinese Institute of Transportation,
2006.
[8] M. G. Karlafftis, and K. C. Sinha, "Modeling Approach Transit
Rolling-Stock Deterioration Prediction," Journal of Transportation
Engineering, Vol. 123, 1997, pp.223-228.
[9] C. L. Lu, "Study on Patronage Transfer Inclination Model of New Travel
Modes," Proceedings of the National Science Council (Part C:
Humanities and Social Sciences), Vol.8, No.2, 1997, pp. 242-259.
[10] L. H. Tuan, and Y. J. Wang, (1999). "Integrate the Travel Mode Selection
Models of Revealed Preference and Stated Preference Data,"
Transportation Planning Journal (in Chinese version), Vol.28, No.1,
1999, pp. 25-60.
[11] J. H. Wen, L. W. Lan and F. S. Hsu, "Research of Different Traffic
Information Resources with Impact on the Route Selection Behaviors of
Intercity Commuters," Proceedings of the 6th ROC Transportation
Network Seminar, 2001, pp. 1-9.
[12] Hung-Yen Chou, Chiang Fu (2007). A Study of Domestic Air Passenger-
Preference for High-Speed Rail Mode in Taiwan, The Journal of Global
Business Management, Vol.3, Num.2, pp.147-155.
[13] O. F.-Y. Shyr and M.-F. Hung, "Intermodal Competition with High Speed
Rail - A Game Theory Approach," Journal of Marine Science and
Technology, Vol. 18, No. 1, 2010, pp. 32-40.
[14] S.-C. Lo, "Dynamic Analyses for Passenger Volume of Domestic Airline
and High Speed Rail," Proceeding of World Academy of Science,
Engineering and Technology, Issue 61, 2012, pp.1279-1283.
[15] Website of Taiwan High Speed Rail, http://www.thsrc.com.tw/en/?lc=en,
2012
[16] A. J. Lotka, and A. James, Elements of Mathematical Biology, Dover,
publications New York, 1956.
[17] A. J. Lotka, Elements of Physical Biology, Williams and Wilkins,
Baltimore, 1925.
[18] V. Volterra, "Variazioni e Fluttuazioni del Numero D-individui in Specie
Animali Conviventi," Mem. R. Acadd. Lincei Series IV, Vol. 2, 1926,
pp.31-113.
[19] F. M. Bass, , "A New Product Growth for model consumer durables,"
Manag. Sci., Vol.15, 1969, pp.215-227.
[20] F. M. Bass, Comments on "A New Product Growth for Model Consumer
Durables´╝é Manag. Sci., Vol. 50, 2004, pp.1833-1840.
[21] C. Fisher and R. H. Pry, "A Simple Substitution Model of Technological
Change," Technological Forecasting and Social Changes, Vol.3, 1971,
pp.75-88.
[22] A. Norton and F. M. Bass, "A Diffusion Theory Model of Adoption and
Substitution for Successive Generations of High-Technology Products,"
Manage. Sci., Vol. 33, 1987, pp.1069-1086.
[23] V. Mahajan, E. Muller and F. M. Bass, "New-product diffusion models in
marketing : a review and directions for research," J. Marketing, Vol. 54,
1990, pp.1-26.
[24] N. Meade and T. Islam, "Modelling and forecasting the diffusion of
innovation - A 25-year review," Int. J. Forecasting, Vol. 22, 2006,
pp.519-545.
[25] P. Parker, and H. Gatignon, "Specifying Competitive Effects in Diffusion
Models - An Empirical Analysis,"Int. J. Res. Marketing, Vol. 11, 1994,
pp.17-39.
[26] C. W. I. Piotorius and J. M. Utterback, "Multi-mode interaction among
technologies," Res. Policy, Vol. 26, 1997, pp.67-84.
[27] J. R. Williams, "Technological evolution and competitive response,"
Strategic Manage. J., Vol.4, 1983, pp.55-65.
[1] K. R. Buckeye, , "Ranking Alternatives Using Fuzzy Numbers, Fuzzy Set
and Systems," No. 15, 1992, pp. 21-31.
[2] A. Kanafan, and W. Youssef, "High-Speed Rail in California", University
of California Institute of Transportation Studies Review, Vol.no17,1994 ,
pp.2-8.
[3] J. J. Lin, C. M. Feng and L. C. Huang, "Forecasting the Taiwan High
Speed Rail System on Local Development," Transportation Planning
Journal (in Chinese version), Vol. 34, No. 3, 2005, pp. 391-412.
[4] Ministry of Transportation and Communications, A Report on the Survey
of High Speed Rail Travel Behavior, Taipei, Taiwan, 2007.
[5] L. W. Lan, "Impact of High Speed Railway on the Western Corridor of
Taiwan Area," Road News Quarterly, Vol. 30, No.1, 1991, pp. 15-22.
[6] C. T. Wang, and T. C. Liu, "The Aviation Market Characteristics of
Taiwan Area and Development Research," Transportation Planning
Journal (in Chinese version), Vol.28, No.3, 1999, pp. 451-484.
[7] T. C. Huang, "Website of Land/Air Transportation Transition Analysis in
Response to the Commencement of Revenue Operation of High Speed
Railway," Transportation Comments, Chinese Institute of Transportation,
2006.
[8] M. G. Karlafftis, and K. C. Sinha, "Modeling Approach Transit
Rolling-Stock Deterioration Prediction," Journal of Transportation
Engineering, Vol. 123, 1997, pp.223-228.
[9] C. L. Lu, "Study on Patronage Transfer Inclination Model of New Travel
Modes," Proceedings of the National Science Council (Part C:
Humanities and Social Sciences), Vol.8, No.2, 1997, pp. 242-259.
[10] L. H. Tuan, and Y. J. Wang, (1999). "Integrate the Travel Mode Selection
Models of Revealed Preference and Stated Preference Data,"
Transportation Planning Journal (in Chinese version), Vol.28, No.1,
1999, pp. 25-60.
[11] J. H. Wen, L. W. Lan and F. S. Hsu, "Research of Different Traffic
Information Resources with Impact on the Route Selection Behaviors of
Intercity Commuters," Proceedings of the 6th ROC Transportation
Network Seminar, 2001, pp. 1-9.
[12] Hung-Yen Chou, Chiang Fu (2007). A Study of Domestic Air Passenger-
Preference for High-Speed Rail Mode in Taiwan, The Journal of Global
Business Management, Vol.3, Num.2, pp.147-155.
[13] O. F.-Y. Shyr and M.-F. Hung, "Intermodal Competition with High Speed
Rail - A Game Theory Approach," Journal of Marine Science and
Technology, Vol. 18, No. 1, 2010, pp. 32-40.
[14] S.-C. Lo, "Dynamic Analyses for Passenger Volume of Domestic Airline
and High Speed Rail," Proceeding of World Academy of Science,
Engineering and Technology, Issue 61, 2012, pp.1279-1283.
[15] Website of Taiwan High Speed Rail, http://www.thsrc.com.tw/en/?lc=en,
2012
[16] A. J. Lotka, and A. James, Elements of Mathematical Biology, Dover,
publications New York, 1956.
[17] A. J. Lotka, Elements of Physical Biology, Williams and Wilkins,
Baltimore, 1925.
[18] V. Volterra, "Variazioni e Fluttuazioni del Numero D-individui in Specie
Animali Conviventi," Mem. R. Acadd. Lincei Series IV, Vol. 2, 1926,
pp.31-113.
[19] F. M. Bass, , "A New Product Growth for model consumer durables,"
Manag. Sci., Vol.15, 1969, pp.215-227.
[20] F. M. Bass, Comments on "A New Product Growth for Model Consumer
Durables´╝é Manag. Sci., Vol. 50, 2004, pp.1833-1840.
[21] C. Fisher and R. H. Pry, "A Simple Substitution Model of Technological
Change," Technological Forecasting and Social Changes, Vol.3, 1971,
pp.75-88.
[22] A. Norton and F. M. Bass, "A Diffusion Theory Model of Adoption and
Substitution for Successive Generations of High-Technology Products,"
Manage. Sci., Vol. 33, 1987, pp.1069-1086.
[23] V. Mahajan, E. Muller and F. M. Bass, "New-product diffusion models in
marketing : a review and directions for research," J. Marketing, Vol. 54,
1990, pp.1-26.
[24] N. Meade and T. Islam, "Modelling and forecasting the diffusion of
innovation - A 25-year review," Int. J. Forecasting, Vol. 22, 2006,
pp.519-545.
[25] P. Parker, and H. Gatignon, "Specifying Competitive Effects in Diffusion
Models - An Empirical Analysis,"Int. J. Res. Marketing, Vol. 11, 1994,
pp.17-39.
[26] C. W. I. Piotorius and J. M. Utterback, "Multi-mode interaction among
technologies," Res. Policy, Vol. 26, 1997, pp.67-84.
[27] J. R. Williams, "Technological evolution and competitive response,"
Strategic Manage. J., Vol.4, 1983, pp.55-65.
@article{"International Journal of Business, Human and Social Sciences:63549", author = "Shih-Ching Lo and Yu-Ping Liao", title = "External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail", abstract = "Social-economic variables influence transportation
demand largely. Analyses of discrete choice model consider
social-economic variables to study traveler-s mode choice and
demand. However, to calibrate the discrete choice model needs to have
plenty of questionnaire survey. Also, an aggregative model is
proposed. The historical data of passenger volumes for high speed rail
and domestic civil aviation are employed to calibrate and validate the
model. In this study, models with different social-economic variables,
which are oil price, GDP per capita, CPI and economic growth rate,
are compared. From the results, the model with the oil price is better
than models with the other social-economic variables.", keywords = "forecasting, passenger volume, dynamic competitive
model, social-economic variables, oil price.", volume = "6", number = "7", pages = "1919-5", }
