PL EN


2018 | nr 1 | 105--115
Article title

Forecasting the number of passengers serviced at the maritime ports in Bulgaria

Authors
Content
Title variants
Languages of publication
EN
Abstracts
EN
The maritime transport in Bulgaria is controlled and coordinated by the Executive Agency "Maritime administration". This institutionis a legal entity on budget support to the Ministry of transport, information technology and communications, a second level user of budget credits, based in Sofia with regional offices in Bourgas, Varna, Lom and Rousse (where are the Bulgarian major ports). EAMA status is regulated by the Merchant Shipping Code – Art. 360, para. 1. The problem of forecasting in the new strategic documents is crucial to the formation of proper infrastructure policy which has to be innovative and for the future strategic development of the tourism in the country. This paper is aimed at presenting the lack of real forecasting in many of the strategic documents and projects adopted for the development of the maritime transport in Bulgaria (i.e. Directive2008/106/EC of European Parliament and Council on the minimum level of training of sea farers; Ordinance No. 9 of 2013 on the requirements for operational suitability of ports and specialised port facilities; Ordinance No. 10 of 2014 on the scope and content, preparation, approval and amendment of the general plans of the public transport ports). There are also many Mutual Agreements for Recognition of Seafarers" certificates. The paper provides a practical example for the use of the so called single or simple exponential smoothing without the presence of any seasonality and the lack of cyclicity on the number of passengersarrivals at the Bulgarian maritime ports.
Year
Volume
Pages
105--115
Physical description
Bibliogr. 31 poz.
Contributors
author
References
  • 1. Brown, R.G. (1959). Statistical Forecasting for Inventory Control. New York: McGraw-Hill.
  • 2. Brown, R.G. (1963). Smoothing, Forecasting, and Prediction of Discrete Time Series. Englewood Cliffs, NJ: Prentice-Hall.
  • 3. Brown, R.G., and Meyer, R.F. (1961). The Fundamental Theory of Exponential Smoothing. Operations Research, No. 9, p. 673-685.
  • 4. Chatfield, C., and Yar, M. (1988). Holt-Winters forecasting: Some practical issues. The Statistician, No. 37, p. 129-140.
  • 5. DeLurgio, S.A. (1998). Forecasting Principles and Applications. Pennsylvania State University: Irwin/McGraw-Hill, p. 21.
  • 6. Dimitrov, P. (2012). Long-run forecasting of ecotourism receipts for the needs of the bulgarian municipalities. Economics & Management Journal, Year VIII, Issue 1, p. 104-114.
  • 7. Dimitrov, P., Krasteva, R., and Kalaidzhieva, V. (2013). Association of the Bulgarian tourism industry with economic performance of some EU tourism emitting countries. In J. Santos, F. Serra, and P. Aguas (Eds.), Strategies in Tourism Organizations and Destinations (p. 177-188). Portugal: School of Management, Hospitality and Tourism of the University of the Algarve.
  • 8. Dimitrova, R., and Kyurova, V. (2013). Attitudes of local communities towards entrepreneurship in the sphere of alternative tourism. Paper presented at the 2nd International Conference, ICTIC 2013, 25-29 March 2013. Zilina, Slovak Republic.
  • 9. Dimitrova, R. (2013). Opportunities of marketing research for increasing competitiveness of the cultural tourism product. Paper presented at the INTERNATIONAL SCIENTIFIC CONFERENCE “CULTURAL CORRIDOR VIA DIAGONALS – CULTURAL TOURISM WITHOUT BOUNDARIES”, Sofia, Bulgari.
  • 10. Directorate General "Civil Aviation Administration" of the Ministry of Transport, Information Technology and Communications of the Republic of Bulgaria (2014). Statistics. Retrieved from http://www.caa.bg/page.php?category=27. Available online 29.05.2014.
  • 11. Filipova, M. (2010). Peculiarities of Project Planning in Tourism. Perspectives of Innovations Economics and Business /PIEB, International Cross – Industry Research Journal, Vol. 4(1), p. 57-59.
  • 12. Gardner, E.S. Jr., and McKenzie, E. (1985). Forecasting trends in time series. Management Science, Vol. 31, p. 1237-1246.
  • 13. Gardner, E.S. Jr., and McKenzie, E. (1988). Model identification in exponential smoothing. Journal of the Operational Research Society, Vol. 39, p. 863-867.
  • 14. Gardner, E.S. Jr. (1985). Exponential Smoothing: the state of the art. Journal of Forecasting, Vol. 4, p. 1-28.
  • 15. Gardner, E.S. Jr. (1987). Chapter 11: Smoothing methods for short-term planning and control. The Handbook of forecasting – A Manager’s Guide. In S. Makridakis, and S.C. Wheelright (Eds.) (p. 174-175). New York: John Wiley & Sons.
  • 16. Hamilton, J.D. (1994). Time Series Analysis. Princeton, New Jersey: Princeton University Press.
  • 17. Holt, C.C. (1957). Forecasting trends and seasonals by exponentially weighted averages. O.N.R. Memorandum 52/1957, Carnegie Institute of Technology.
  • 18. Hyndman, R.J., Koehler, A.B., Snyder, R.D., and Grose, S. (2002). A state space framework for automatic forecasting using exponential smoothing methods. International Journal of Forecasting, Vol. 18, p. 439-454.
  • 19. Hyndman, R.J. et al. (2008). Forecasting with Exponential Smoothing – The State Space Approach. Berlin: Springer.
  • 20. Hyndman, R.J. (2014). Initializing the Holt-Winters method. In Hyndsight – A blog by R.J. Hyndeman. Retrieved from http://robjhyndman.com/hyndsight/hw-initialization/.
  • 21. Ivanov, M. (2007). A try and conclusions from the forecasting of the business processes with the help of time series (a MS PowerPoint presentation in Bulgarian language). Retrieved from http://www.nbu.bg/PUBLIC/IMAGES/File/departments/informatics/ Izsledvania/Martin_Ivanov_prolet_2007.pdf. Available online 29.05.2014.
  • 22. Ledolter, J., and Abraham, B. (1984). Some comments on the initialization of exponential smoothing. Journal of Forecasting, Vol. 3, p. 79-84.
  • 23. Mishev, G., and Goev, V. (2012). Statistical Analysis of Time Series. Sofia, Bulgaria: Avangard-Prima Publishing House.
  • 24. Pegles, C.C. (1969). Exponential forecasting: some new variations. Management Science, Vol. 15(5), p. 311-315.
  • 25. Sikrakov, S. (1996). Conjuncture and Forecasting of International Markets. Sofia, Bulgaria: Stoilov Publishing House.
  • 26. Sofia Airport. (2014). Sofia Airport Traffic Trends 2008-2013 and Forecast 2014-2015. In Appendix 2: Announcement on the opening of consultations on the airport charges at Sofia Airport, published on 28.02.2014. Retrieved from http://www.sofia-airport.bg/UserFiles/ Appendix%202_Traffic%20Forecast.pdf. Available online 30.05.2014.
  • 27. Stankova, M., and Vassenska, Iv. (2013). Projections of culture and local diversity upon tourism destination attractiveness. In J. Santos, F. Serra, and P. Aguas (Eds.), Strategies in Tourism Organizations and Destinations (p. 221-233). Portugal: School of Management, Hospitality and Tourism of the University of the Algarve.
  • 28. Taylor, J.W. (2003). Exponential Smoothing with a damped multiplicative trend. International Journal of Forecasting, Vol. 19, p. 715-725.
  • 29. Tashman, L.J., and Kruk, J.M. (1996). The use of protocols to select exponential smoothing procedures: a reconsideration of forecasting competitions. International Journal of Forecasting, Vol. 12, p. 235-253.
  • 30. Tsay, R.S. (2005). Analysis of Financial Time Series. New York: John Wiley & Sons.
  • 31. Williams, D.W., and Miller, D. (1999). Level-adjusted exponential smoothing for modeling planned discontinuities. International Journal of Forecasting, Vol. 15, p. 273-289.
Notes
Rekord pochodzi z bazy danych BazTech.
Document Type
Publication order reference
YADDA identifier
bwmeta1.element.baztech-d1b85977-60f9-4212-9be2-32a0330c8520
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.