Purpose Estimation of the rental price of a residential property is important to real estate investors, financial institutions, buyers and the government. These estimates provide information for assessing the economic viability and the tax accruable, respectively. The purpose of this study is to develop a neural network model for estimating the rental prices of residential properties in Cape Town, South Africa. Design/methodology/approach Data were collected on 14 property attributes and the rental prices were collected from relevant sources. The neural network algorithm was used for model estimation and validation. The data relating to 286 residential properties were collected in 2018. Findings The results show that the predictive accuracy of the developed neural network model is 78.95 per cent. Based on the sensitivity analysis of the model, it was revealed that balcony and floor area have the most significant impact on the rental price of residential properties. However, parking type and swimming pool had the least impact on rental price. Also, the availability of garden and proximity of police station had a low impact on rental price when compared to balcony. Practical implications In the light of these results, the developed neural network model could be used to estimate rental price for taxation. Also, the significant variables identified need to be included in the designs of new residential homes and this would ensure optimal returns to the investors. Originality/value A number of studies have shown that crime influences the value of residential properties. However, to the best of the authors’ knowledge, there is limited research investigating this relationship within the South African context.
The property market plays a vital role in the economy through the provision of constructed space for productive activities and employment opportunities. Evidence gleaned from the literature suggests that the level of security within an area affects property prices. In the current study, the distance between a property and the police station was used as a proxy variable for measuring the perceived level of security. The data on rental prices of residential properties and its attributes were retrieved from a reliable property source (www.property24.com). A Neural network model was used for evaluating the impact of the presence of a police station on rental prices of residential properties within Cape Town, South Africa. Experimental results showed that the developed model is 77.27% accurate when used to predict the rental prices of residential properties. Floor area, number of bathroom, number of bedroom and proximity of a police station have the most significant impact on the rental price of residential properties. Greater efforts are needed to provide insights into the effect of sustainability on rental prices of residential properties. This information would serve a justification for embedding sustainability into residential construction projects.
The rationale behind any construction project varies; it might be to achieve value, time, quality, cost or just satisfaction for the client. Irrespective of any or all of these reasons, the team members involved in conception, inception, construction and delivery of a project are aware that a good teamwork is of essence. This is in the context of growing needs of client and the ever-growing improvement in methods of project delivery as influenced by technology. This article looks into the team type in the Nigerian construction industry from the angle of a virtual team (VT) using the mixed-method research design. VT is simply a type of team wherein the members operate from different geographical regions and function majorly with the aid of information and communications technology media. Data for the study were collected from relevant literature, interviews were conducted with 20 selected professionals in the construction industry and, thereafter, a questionnaire was drafted from the results of the interviews and administered to selected relevant professionals. The study revealed that communication among team members, flexibility of operation and decision making are usually the most influencing strengths of the VT, while some of its weaknesses are a need for special training, conflict among team members and client’s acceptance of team type. Reduction in time-to-market, collaboration ability of team members and delivery time of project were seen as opportunities, while recognized threats were members’ performance level and complexity of technical application. The study concludes that the success of the VT depends highly on exploiting the opportunities opened to it.
A vital building block for construction project globally is construction materials which are huge, costly and are often delivered in great quantities to the construction sites. One of the key roles in the successful completion and delivery of a project is effective construction materials management. However, it has been established that material wastage is a prevalent problem in developing countries which can be tackled with modern technologies for effective material management. It is based on this assertion that this paper focuses on the challenges to use of modern technologies for effective material management in the South African construction industry. The study adopted a quantitative approach where questionnaires were administered to professionals in the South African construction industry. Descriptive statistics tools were used to analyse the gathered data. Findings showed that the common challenges to using of modern technologies for effective material management in the construction in South African are; Scale of construction projects, Cultural barriers, environment challenges, financial challenges, and Behaviours of people in key positions. The way forward are; change in business approaches and procedure, and implementation of skill set is necessary
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