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The purpose of this paper is to analyze the commercial property development risk factors from the entrepreneur’s point of view against social, economic, environmental, technological and political risk assessment criteria. After that, this study aims to assess the risk factors based on the analytical network process (ANP) model and to prioritize the key risk factors to identify which risk factor is highly affected to the commercial development process.

The data were collected through face-to-face interviews using a structured questionnaire. The analysis of the risk factors involved the ANP model using super decision software.

The results revealed that there are five major risk factors such as environmental, social, economic, technological and political risk, and 32 sub-risk factors. According to the super matrix calculation, the synthesized values for three projects were 0.0704, 0.0532 and 0.0431, respectively. It was identified that Ward City was 0.0704, indicating that it is comparatively less risky and, hence, can be categorized as the best development and considering the sub-risk factors; the results show that the highly affected risk factors for the development are: the council approval process, climate changes and natural disaster, and the least affected risk factors are confidence to the market, lifecycle value, investment return and currency conversion factor.

The paper includes implications for the development of commercial properties, risk and risk assessment criteria to make risk management strategies and policy implementation.

The research findings are helpful in improving risk management strategies in the country, and policy formulation should focus on the above identified three risk factors in order to mitigate the risk in every stage and to achieve sustainable project development while increasing the satisfaction of long-term investment goals.

Developing residential units is crucial in the socio-economic development of a country. The investor faces not only uncertain transaction price (price risk), but also uncertainties about the marketing period risk. Predicting when the incurred money is being realized is difficult because of the imperfect nature of the real estate market. Thus, the purpose of this study is to analyze the variables that explain the time on the market (TOM) of housing units, identifying the relationships in-between and the effects on TOM of residential properties.

Following a multi-stage sampling process, a random sample of 120 housing units was selected. Data were collected using a self-administered questionnaire. The questionnaire contained 57 variables that can affect TOM. Semi-structured interviews were conducted to confirm some of the data and information on residential units from the developers. Direct observations were conducted to verify certain physical attributes and, finally, they were comprehensively analyzed using quantitative analysis techniques in SPSS 16.0 Statistical package.

Results confirmed that lesser advertising prices, attractive environment, proximity to the city center and proper shape of lands reduce the TOM. Similarly, higher prices, longer distance to the city center and irregular shape of land increase the TOM. The results strengthen the necessity of a comfortable environment appropriate to live, probably with greenery or water bodies, which is a key influential factor that reduces the TOM in Sri Lanka.

wIn the Sri Lankan context, there are few contributions to the real estate literature in this regard. Many scholars have concentrated on physical and economic characteristics, whereas this research adds the environmental factors. Therefore, this research makes a significant contribution to the body of knowledge in this area, as it puts more attention on including several variables, as well as newly introduced variables as determinants. Consumers can apply the research findings to assess the relative importance of housing attributes and services which they perceive most valuable, and then to make their purchase decisions. The findings also contribute to the investigations of the behavior of housing attributes and enable knowing as to what factors are to be promoted and what to be omitted to gain a shorter TOM.