Multiple regression modelling: contemporary spatial planning and economic modelling of tourism industry (case study of Shaki district)

  • Nofal Artunov Institute of Geography of Azerbaijan, 115 H. Javid Avenue, Baku AZ 1143, Azerbaijan

Abstract

The study conducted a thorough analysis of the territorial planning of the tourism industry and a multiple regression analysis of tourism revenues in the Shaki district from 2010 to 2021. The main objective of the research was to identify the factors influencing the formation of income in the tourism industry in the context of regionalisation and the current direction of tourism development. Studying the negative and positive aspects of the tourism industry and the planning sequence, as well as the existing theoretical approaches to tourism planning, was necessary to achieve this goal. Comparative analysis, regression analysis, and correlation analysis methods were used to analyse the factors affecting tourism, and the final version of the mathematical statistical model was obtained based on successive models by establishing hypotheses. The study found that the number of hotel rooms and foreign tourists is the main influential factor in the formation of income. The proposed model had following parameters: p < 0.005 and R2 = 0.4886, making it the final option. The research highlights the importance of deep learning about current and future situations of any research destination and tourism planning issues, such as the effective use of resources and the prediction of incomes. It demonstrates that the reduction in tourism income is primarily due to the decrease in foreign tourists’ interest caused by rising hotel and food costs. The research also reveals that the focus has shifted to other neighbouring districts, such as Gabala and Gakh, with tourist flows directed away from the Shaki district. Overall, this study provides valuable insights into the factors affecting tourism revenue in the Shaki district, which can inform future policy and decision-making in the tourism industry. As a result of these findings, stakeholders will be able to identify the key drivers of tourism growth and take the necessary measures to attract more tourists and increase revenue from tourism.

Author Biography

Nofal Artunov, Institute of Geography of Azerbaijan, 115 H. Javid Avenue, Baku AZ 1143, Azerbaijan

PhD (geography); recearcher at the department of economical and political geography

 

References

  1. Eminov ZN. Kurort-turizm təsərrüfatı, Azərbaycan respublikasının coğrafiyası. In: Mammadov RM, editor. İqtisadi, sosial və siyasi coğrafiya. Bakı: Avropa Nəşriyyatı; 2015. s. 271–277. Azerbaijani.
  2. Holloway J. The business of tourism. Harlow: Longman; 1998. 350 p.
  3. Mill R, Morrison A. The tourism system: an introductory text. Dubuque: Kendell Hunt Publishing Co.; 1998. 387 p.
  4. Pender L, Sharpley R, editors. The management of tourism. Thousand Oaks: SAGE Publications; 2005. 384 p.
  5. Lang R. Planning for integrated development. In: Dykeman FW, editor. Papers of the conference on integrated development beyond the city; 1985 June 14–16; Sackville, Canada. Sackville: Mount Allison University; 1985. p. 81–104.
  6. Mason P. Tourism: environment and development perspectives. Godalming: World Wide Fund for Nature; 1995. 104 p.
  7. Roday S, Biwal A, Joshi V. Tourism operations and management. Oxford: Oxford University Press; 2010. 502 p.
  8. Ezani J. Strategies for development: the role of planning in tourism [Internet; cited 2015 Arpil 2]. Available from: http://www.enugustatetourismboard.com/p.php.
  9. Gee C, Sola EF. International tourism: a global perspective. Madrid: World Tourism Organisation; 1997. 406 p.
  10. Risteskia M, Kocevskia J, Arnaudov K. Spatial planning and sustainable tourism as basis for developing competitive tourist destinations. Procedia – Social and Behavioural Sciences. 2012;44:375–386.
  11. Vasilevska L, Vasić M. Strategic planning as a regional development policy mechanism: European context. Spatium. 2009;21:19–26.
  12. Chettiparamb A, Thomas H. Tourism and spatial planning. Journal of Policy Research in Tourism, Leisure and Events. 2012;4(3):215–220. DOI: 10.1080/19407963.2012.726157.
  13. Dede OM, Ayten AM. The role of spatial planning for sustainable tourism development: a theoretical model for Turkey. Tourism: an International Interdisciplinary Journal. 2012;60(4):431–445.
  14. Şahinler S. The basic principles of fitting linear regression model by least squares method. Journal of Agricultural Faculty of the Mustafa Kemal University. 2000;5(1–2):57–73. Turkish.
  15. Wu DC, Li G, Song H. Econometric modelling and forecasting of tourism demand, methods and applications. London: Routledge; 2023. 327 p. DOI: 10.4324/9781003269366.
  16. McGehee NG, Andereck KL. Factors predicting rural residents’ support of tourism. Journal of Travel Research. 2004;43(2):131–140. DOI: 10.1177/0047287504268234.
  17. Sheldon PJ, Var T. Tourism forecasting: the state-of-the-art. Discussion Paper Series. 1985;4(2):183–195. DOI: 10.1002/for.3980040207.
  18. Getz D. Models in tourism planning. Tourism Management. 1986;7(1):21–32.
  19. Weston R, Gore PA Jr. A brief guide to structural equation modeling. The Counselling Psychologist. 2006;34(5):719–751. DOI: 10.1177/0011000006286345.
  20. Anderson JC, Gerbing DW. Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin. 1988;103(3):411–423. DOI: 10.1037/0033-2909.103.3.411.
  21. Tasci AD. Assessment of factors influencing destination image using a multiple regression model. Tourism Review. 2007;62(2):23–30. DOI: 10.1108/16605370780000311.
  22. Lee JW, Manorungrueangrat P. Regression analysis with dummy variables: innovation and firm performance in the tourism industry. In: Rezaei S, editor. Quantitative Tourism Research in Asia. Singapore: Springer; 2019. p. 113–130. DOI: 10.1007/978-981-13-2463-5_6.
  23. Hara T. Quantitative tourism industry analysis. Oxford: Butterworth – Heinemann; 2008. 282 p.
  24. Costa J, Ferrone L. Sociocultural perspectives on tourism planning and development. International Journal of Contemporary Hospitality Management. 1995;7(7):4–9. DOI: 10.1108/09596119510101877.
  25. Ahn B, Lee B, Shafer CS. Operationalising sustainability in regional tourism planning: an application of the limits of acceptable change framework. Tourism Management. 2002;23(1):1–15.
  26. Bowerman BL, O’Connell RT, Murphree ES, Orris JB. İşletme İstatistiğinin Temelleri. Ankara: Nobel Akademik Yayıncılık; 2013.736 p. Turkish.
  27. Erilli NA, Alakuş K. Parameter estimation in Theil-Sen regression analysis with Jackknife method. Eurasian Econometrics, Statistics & Emprical Economics Journal. 2016;5:28–41.
  28. Nunkoo R, Ramkissoon H. Structural equation modelling and regression analysis in tourism research. Current Issues in Tourism. 2012;15(8):777–802. DOI: 10.1080/13683500.2011.641947.
  29. Zaman T, Alakus K. Comparison of resampling methods in multiple linear regression. Journal of Science and Arts. 2019;19(1):91–104.
  30. Magnello ME. Karl Pearson and the establishment of mathematical statistics. International Statistical Review. 2009;77(1):3–29. DOI: 10.1111/j1751-5823.2009.00073.x.
  31. Deng L, Pei J, Ma J, Lee DL. A rank sum test method for informative gene discovery. In: Won K, Kohavi R, editors. Proceedings of the tenth ACM SIGKDD International conference on knowledge discovery and data mining; 2004 August 22–25; Seattle, USA. New York: Association for Computing Machinery; 2004. p. 410–419. DOI: 10.1145/1014052.1014099.
  32. Cui W, Sun Z, Ma H, Wu S. The correlation analysis of atmospheric model accuracy based on the Pearson correlation criterion. IOP Conference. Series: Materials Science and Engineering. 2020;780(3):32–45. DOI: 10.1088/1757-899X/780/3/032045.
  33. Weston J, Elisseeff A, Schölkopf B, Tipping M. Use of the zero norm with linear models and kernel methods. The Journal of Machine Learning Research. 2003;3:1439−1461.
  34. Zaid MA. Correlation and regression analysis. Ankara: Statistical Economic and Research and Training Centre for Islamic Countries; 2015. 33 p.
  35. Gupta SC, Kapoor VK. Fundamentals of mathematical statistics. Mumbai: Sultan Chand and Sons; 2014. 1303 p.
  36. Gunn CA. Tourism planning. New York: Taylor and Francis; 1988. 464 p.
Published
2023-12-28
Keywords: spatial planning, tourism industry, regression model, Shaki district, prediction, tourism planning
Supporting Agencies The author of the article would like to thank the anonymous referees of journal for all their valuable comments and suggestions, which helped in improving of the theoretical part of the article.
How to Cite
Artunov, N. (2023). Multiple regression modelling: contemporary spatial planning and economic modelling of tourism industry (case study of Shaki district). Journal of the Belarusian State University. Geography and Geology, 2, 80-89. Retrieved from https://journals.bsu.by/index.php/geography/article/view/6071