Valuation inaccuracy has been attributed amongst others to behavioural issues such as the usage of Anchoring and Adjustment Heuristics. There is however a dearth in the research of the other principal heuristics namely availability, representative and positivity. This research is hereby aimed at discovering the effects of these heuristics on the accuracy of property valuation. To accomplish this, the study undertook a cross-sectional questionnaire survey of 159 of the 270 Head Offices of Estate Surveying and Valuation firms in Lagos Metropolis, while 29 and 30 questionnaires were distributed to the Head Offices of the entire Estate Surveying and Valuation Firms in Abuja and Port Harcourt respectively. For ease of coverage, Lagos Metropolis was stratified into six zones; thereafter respondents were selected randomly. The respondents were required to carry out simulated valuations using each of the four types of heuristics and also with supplied current market data. The T-test at the 95 per cent confidence interval was employed to test for inaccuracy in heuristically determined values relative to the sale values (values of the ‘control’ properties). The result reveals that heuristic-determined values, particularly that of representative, are not as accurate as those derived from supplied current market data. The authors recommended more focus on research of representative heuristics while consistent usage of heuristics should be dissuaded, to prevent loss of clients’ confidence in valuation reports.

In this article, two sets of questionnaires were administered to professionals and clients (commercial banks) on their willingness to negotiate the professional fees charged by the Estate Valuers assuming that the mortgage in valuation was financed by bank loan. A range of fees options were provided. Other factors such as the business environment and mortgage valuation can influence the negotiated fees when the data obtained from the survey data is analyzed.

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The quality of facilities in educational institutions has been on the increase globally and is receiving much attention in educational research. This is necessitated by the fact that higher educational institutions worldwide are facing commercial competition imposed by economic forces resulting from the development of global education markets. In view of this, this study assessed students' perception of the quality of academic facilities in private universities in Ogun State, Nigeria. This is with a view to improving the quality of university facilities in order to provide a conducive learning environment for students which will aid in good academic performance. 954 questionnaires were randomly administered to students in five private universities in the study area and a response rate of 71% was achieved. Using descriptive statistics, the results revealed that their needs were fairly met with the majority of the facilities sampled in the library, ICT laboratory and classrooms. The study recommended that facility providers should take note of the facilities whose quality students perceive as not meeting their needs, so as to be able to respond appropriately. This will entail ensuring that provision is made for such facilities in terms of budgeting for upgrading or replacement.

Genetic algorithm (GA) is an example of evolutionary algorithms that are bio-inspired computational methods. GA has been applied to numerous fields. It has been applied in different aspects of construction and building but that is scarcely any review that documents it. The paper reviewed the application of GA in construction and building. It was revealed that energy management is the major area of application which are further subdivided into load scheduling, prediction, and optimization. Other nonenergy applications are pricing, environment, and construction design or real estate. The review presents research information to researchers. The information can assist in the optimization of construction processes which can reduce the construction time and costs, ensure optimal allocation and use of energy, prediction of energy demands and supply in houses and incorporation of sustainability in construction and management of real estate.