Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/23849
Title: Identifying Factors Associated with Price Categories of Motorcycles in Sri Lanka using Discriminant Analysis
Authors: Chanika, P.A.L.
Attanayake, A.M.C.H.
Gunaratne, M.D.N.
Keywords: Canonical Discriminant Analysis, Associated Factors, Pricing of Motorcycles
Issue Date: 2021
Publisher: Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka
Citation: Chanika, P.A.L., Attanayake, A.M.C.H.& Gunaratne, M.D.N. (2021) Identifying Factors Associated with Price Categories of Motorcycles in Sri Lanka using Discriminant Analysis, Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka.Trade & Productivity Commission Secretariat, Ministry of Industrial Export and Investment Promotion, Sri Lanka.
Abstract: The motorcycle is one of the most popular modes of transportation in Asia because it is a fast, economic and convenient mode of transportation. According to the motor vehicle registration statistics of the department of motor traffic, motorcycle is the best-selling vehicle in Sri Lanka. Pricing of the motorcycles is one of the major concerns for motorcycle byers and importers. The purposes of this study are to identify the factors which are associated with the prices of motorcycles and to construct a model to determine the price of a motorcycle based on significant factors. Specifications and features of selected motorcycles were collected from secondary data sources. ‘Motorcycle Category’, ‘Fuel Efficiency’, ‘Engine Power’, ‘Brake System’, ‘Torque’, ‘Length’ were the significant factors which had an association between the price categories of motorcycles among 15 properties of motorcycles considered under study. The canonical discriminant analysis was used to develop the model and to predict the price categories of motorcycles. The significant categorical variables were used as the dummy variables. Torque was omitted from the model because of the presence of multicollinearity. The two significant discriminant functions were classified the data into four categories of price. The 75% responds were correctly classified into four price categories. Motorcycle category, Fuel Efficiency, Engine Power, Brake System and Length were found as significantly associated factors to the prices of motorcycles. Decision makers in the field can make good use of those factors in developing their pricing strategies in the motorcycle industry
URI: http://repository.kln.ac.lk/handle/123456789/23849
ISSN: 2719-2415
Appears in Collections:Statistics & Computer Science

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