Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications The paper includes implications for the development of commercial properties, risk and risk assessment criteria to make risk management strategies and policy implementation. Originality/value 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.

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Housing is the most representative land use in any urban area. At present renting of houses instead of buying is a significant phenomenon in the housing market. The ultimate goal of owning a rental property is to make profits with little additional effort. With the absence of a guideline, land owners arbitrary evaluate the property and charges unaffordable values. Since there is no alternative, depending on the need, tenant has to accept it. On the other hand, as each piece of property is unique, it is difficult to fix a rent. This becomes worse in boarding homes. With this background the focus of this paper is on developing an index as a guideline to determine the rental value in housing market. The case study specifies the renting based on higher education institute. Hence three types of renting units such as bed, room and annex selected. The data collection was completed through a structured questionnaire. The significant of each variable is evaluated through a multiple regression model. The findings categorized into levels on the basis of the coefficient values. The results indicate that distance to main junction is the most significant variable in the three types of properties.

Airbnb is most famous as a part of the growing "sharing", "peer-to-peer", or "digital" economy where the platform transformed the traditional tourist accommodation services through its novel business model. In order to comprehend the influence of Airbnb on the tourism and hospitality landscape, it is critical first to understand the market and how Airbnb operates. Therefore, in this study, we explore the operation of Airbnb in Sri Lanka using descriptive statistics and maps by analysing the scrapped data of the Airbnb website. The study results show that Airbnb has been well established on Sri Lankan soil as an alternative accommodation service provider, and the listings have been scattered across the country. However, most listings tend to concentrate in the city centres of famous touristic districts and tourist resort regions in Sri Lanka. These findings will provide a valuable avenue for further investigation of the operation of Airbnb in Sri Lanka.

Irrigation settlements in Sri Lanka were characterized by equal sized allotments among settlers at the time of their establishment. Over time, informal land markets were created and land fragmentation and consolidation occurred simultaneously. This resulted in cultivation of a number of small plots by an individual farmer as well as that of large extents by one or more farmers. This paper assesses the effects of such sub-divisions and consolidations on paddy land productivity in irrigation settlements in Sri Lanka. Specific objectives were to examine the effects of land size on land productivity, labor productivity and use of machinery in paddy farming. Primary data gathered from 1,230 lowland plots covering 935 paddy farms from three irrigated settlements in Anuradhapura district were used for the analysis. Land and labour productivities of plots and farms were regressed against land size and other plot-specific and farm-specific characteristics respectively to test the nature of relationships between productivity and land size. Bivariate probit models were estimated to determine the effects on land size on the likelihood of machinery use in paddy farming. The results of the econometric estimation of the above models provided mixed results with respect to the inverse relationship between land size and productivity found in many developing countries. Though the relationship between plot size and land productivity was clearly positive, an inverse relationship between farm size and land productivity was noted as land size increased beyond a certain limit. The relationship between labor productivity and land size was also similar: labor productivity first increased with land size and then decreased. This observation was equally valid for both plots and farms. The results further indicated that mechanized farms were more productive and that the likelihood of mechanization increases with farm size. Measures to consolidate small land plots until they reach their maximum potential are recommended in order to enhance agricultural productivity in irrigated settlements in Sri Lanka.