Purpose The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya. Design/methodology/approach The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs. Findings The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable. Practical implications A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent. Originality/value While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXCR) and private capital inflows have a significant effect on the changes in HPs. Nonetheless, the study adds two little-known indicators in the projection of HPs, which are the EXCR and HHI.

The organizational performance of local contractors in Kenya remain poor. Little or no research has been done to improve this. The purpose of this research was to establish the bivariate relationships among the dimensions and determinants of organizational performance of local contractors in Kenya. A quantitative research strategy and a survey research design were adopted. The unit of observation comprised of contractors and consultants while the unit of analysis was the contractor. The sampling frame consisted of all NCA1 contractors, NCA2 contractors, NCA3 contractors, and consultants who had professionally interacted with these contractors in recent projects. A sample size of 604 was adopted. Simple random sampling was used to select the contractors. Questionnaires were administered both physically and online. Study variables have been measured perceptually. A response rate of 63% was achieved. All the 45 relationships among the dimensions of organizational performance were positive and significant at 0.01. All the 45 relationships among the determinants of organizational performance were positive and significant at 0.01. All the 100 relationships between the ten dimensions and ten determinants of organizational performance were positive and significant at 0.01 level. The three most dominant determinants of organizational performance were quality of service, organizational structure of the firm and suppliers effectiveness. Improved organizational performance of local contractors can be achieved by enhancing their internal and external environment.

Purpose This paper studies the dynamic effects of selected macroeconomic factors on the performance of the housing market in Kenya using Autoregressive Distributed Lag (ARDL) Models. This study aims to explain the dynamic effects of the macroeconomic factors on the three indicators of the housing market performance: housing prices growth, sales index and rent index. Design/methodology/approach This study used ARDL Models on time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Findings The results indicate that household income, gross domestic product (GDP), inflation rates and exchange rates have both short-run and long-run effects on housing prices while interest rates, diaspora remittance, construction output and urban population have no significant effects on housing prices both in the short and long run. However, only household income, interest rates, private capital inflows and exchange rates have a significant effect on housing sales both in the short and long run. Furthermore, household income, GDP, interest rates and exchange rates significantly affect housing rental growth in the short and long run. The findings are key for policymaking, especially at the appraisal stages of real estate investments by the developers. Practical implications The authors recommend the use of both the traditional hedonic models in conjunction with the dynamic models during real estate project appraisals as this would ensure that developers only invest in the right projects in the right economic situations. Originality/value The imbalance between housing demand and supply has prompted an investigation into the role of macroeconomic variables on the housing market in Kenya. Although the effects of the variables have been documented, there is a need to document the short-run and long-term effects of the factors to precisely understand the behavior of the housing market as a way of shielding developers from economic losses.

Organizational performance is the ultimate measure of the success of any local contractor. It involves the analysis of a firm’s performance measured against its goals and objectives. Whilst it is generally agreed that the organizational performance of local contractors is insufficient, such a notion is arbitrary and most of the time based on anecdotal evidence. The purpose of this research was therefore to establish the level of organizational performance of local contractors here in Kenya. A survey research design was adopted. A questionnaire with the evaluation criteria of organizational performance was used to collect data. The sampling frame included all NCA1, NCA2 and NCA3 contractors. In order to avoid bias in the evaluation process, consultants were included in the survey to obtain an external perspective. The level of organizational performance in local contractors was established at three levels. First, 50 measurable indicators were used. The highest performing indicator was found to be the durability of projects executed by local contractors (mean=7.52). The lowest indicator was established to be the net profit margin of contractors (mean=5.34). The second level involved establishing the level of organizational performance based on the 10 dimensions identified from the literature review. This was achieved by calculating the means of the respective indicators. The best performing dimensions of organizational performance were found to be quality of products (mean=7.308) and client satisfaction (mean=6.923). The least performing dimensions were found to be profitability (mean=5.406) and employee satisfaction (mean=5.683). The final level involved establishing the overall organizational performance of local contractors. This was achieved by calculating the mean of the ten dimensions. The organizational performance of local contractors was established to have a percentage score of 63.74%. This was found to be moderately high meaning there was still plenty of room for improvement.

This research found that the Rwanda construction Industry is faced with critical risk management practices on construction projects. This evaluation has identified the high likelihood of construction failures that fall under logistics, physical, construction, subcontractors, and design related factors. Risks wither remedial or by mitigation associated with the criteria of risk factors are frequently averaged, and certainly used to identify some risk factors it does not identify all of the problems that can result in failure. Similarly, the findings indicate that the most common used analysis techniques were expert systems which include software package, decision support system and computer-based analyses techniques, direct judgement using experience and personal skills, transfer or sharing risk to/with other parts and comparing analysis which means comparing similar projects with similar conditions