Forecasting Model of Residential Rental Rates for Dormitories or Apartments in the Area Surrounding the Educational Institute: A Case Study of Thammasat University, Rangsit Campus
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Abstract
Migration to work or study in Pathum Thani province increases the demand for temporary accommodation. Tenants' decision to rent a room depends on various factors. This research aimed 1) to study physical factors affecting residential rental rates in the areas surrounding Thammasat University, Rangsit Campus, and 2) to construct a linear model for forecasting rental rates. The research model is a quantitative research using the theory of multiple regression analysis as a research conceptual framework. A studied area is a dormitory or apartment within a radius of 5 kilometers surrounding Thammasat University, Rangsit Campus. The samples in this research were the 400 entrepreneurs of a dormitory or apartment within a radius of 5 kilometers surrounding Thammasat University, Rangsit Campus, selected by convenient sampling. The research tool is a checklist. Data were analyzed by using multiple regression analysis by selecting variables with the stepwise method. The research results showed that 1) physical factors affecting residential rental rates in the areas surrounding Thammasat University, Rangsit Campus consist of 10 factors: fitness, room interior, security guard, usable area, free internet or wifi, convenience store, restaurant, beauty salon, elevator, and laundry and 2) The best rental rate forecasting model is Linear – Linear model which has a high percentage accuracy equal to 77.10% or only accounted for the error equal to 22.90%. It is the only form of forecasting equation that has a Durbin-Watson value which is between the Durbin-Watson value obtained by opening the table, indicating that the tolerances are independent of each other with the mean of residual value equal to 0.000 and the sum of square residual equal to 84.940. The equation for forecasting rental rate was LogY of the standard value of monthly rental rate equal 0.338 (standard value of fitness) + 0.274 (standard value of room interior) + 0.034 (standard value of security guard) + 0.214 (standard value of usable area) + 0.082 (standard value of free internet or wifi) - 0.205 (standard value of convenience store) + 0.160 (standard value of restaurant) - 0.111 (standard value of beauty salon) + 0.113 (standard value of elevator) + 0.078 (standard value laundry).
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References
Amthong, N. (2016). A study of reasons of continuing to stay at the dorm moo 7, Don Huaror District, Muang, Chonburi [Master’s Thesis, Burapha University].
Benoit, K. (2011). Linear regression models with logarithmic transformations. London: Methodology Institute, London School of Economics.
Miles, J., & Shevlin, M. (2001). Applying regression and correlation: A guide for students and researchers. London: SAGE Publications.
Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed). San Diego, California: Harcourt Brace College.
Prakobmoon, L. (2013). Factors influencing student decision making to choose student accommodation in Pathumthani province [Master’s Thesis, Rajamangala University of Technology Thanyaburi].
Prasithrathsint, S. (2013). The use of statistics in research is accurate and meets international standards (6th ed). Bangkok: Samlada.
Thaneeyapanich, N. (2556). NP Apartment business plan [Master’s Thesis, Bangkok University, Business Administration].
Theetanapat, S., & Pasunon, P. (2015). The factors affecting the decision to rent private dormitory of Silpakorn University Sanamchandra Palace campus’s students [Master’s Thesis, Silpakorn University].
Thinakanan, S. (2008). Creating an instrument to measure variables in social science research approach to action. Bangkok: Chulalongkorn University Printing House.
Thirasirimeteekul, N., & Jarutat, T. (2021). Living conditions of Chulalongkorn University students residing at dormitories around Chulalongkorn University. Sarasatr Journal, 1, 27-38.
Vanichbuncha, K. (2010). Advanced statistical analysis with SPSS for Windows. Bangkok: Department of Statistics, Faculty of Commerce and Accountancy, Chulalongkorn University.
Wongrattana, C.(2001).Techniques for using statistics for research. Bangkok: Srinakharinwirot University.
Wongsuphachartkun, F. (2015). Factor effecting decision on room rental in Bangkok metropolitan region. [Master’s Thesis, Thammasat University].
Yamane, T. (1973). Statistic: An introductory analysis (3rd ed). New York: Harper and Row Publications.
