Factors affecting commercial housing prices in Vietnam

Purpose - The study aims to identify the affecting factors and their impact rates on the commercial housing prices. The study also aims to suggest implications related to commercial housing prices to develop the commercial housing market. Design/methodology/approach - The study investigates housing investors, real estate agents and buyers to identify factors that might affect commercial housing prices. The proposed research model has 7 latent factors and is tested by Cronbach' alpha and exploratory factor analysis by SPSS20.0 software. Findings - There are 7 groups with 24 factors affecting commercial housing prices. The neighboring factor group has the greatest impact rate (18.54%); the housing service group has the lowest impact rate (11.48%). Research limitations/implications - The study has only determined the affecting factors and their impact rates on commercial housing prices in Bac Ninh city. Therefore, it is necessary to conduct research on factors affecting commercial housing prices in other provinces and cities of Vietnam in the coming time. In addition, the proposed research method can also be consulted when it is necessary to determine the factors affecting commercial housing prices in other countries around the world. Practical implications - The study proposes some implications related to commercial housing prices such as commercial housing valuation; housing selection with suitable prices for people intending to buy houses; state support policies for commercial housing investors to develop commercial housing with reasonable prices. Social implications - The implementing the implications proposed in the study will facilitate people's easier access to commercial housing; real estate investors do business more efficiently. Originality/value - To the best of the authors’ knowledge, this paper presents for the first time a method to determine the affecting factors and their impact rates on commercial housing prices in Vietnam. The paper also points out a number of specific factors affecting commercial housing prices that are different from those shown in previous studies.