Abstract

PurposeThe purpose of this paper is twofold: first, to suggest a modified sales comparison model that is scalable and adaptable to value under conditions of certainty and uncertainty. The model can potentially be applied to residential property, non-residential property and large item plant and machinery in determining the value, rental or capitalisation rate. The second purpose is to address practitioner and end user bias, which if unaddressed can lead to potentially inconsistent valuation results.Design/methodology/approachLiterature was reviewed on decision theory, specifically cognitive limitations, heuristics and biases. A qualitative approach is followed in the paper although the output of the proposed model itself is quantitative.FindingsThe paper argues that practitioners and end users alike tend to avoid advanced statistical techniques when valuing under conditions of certainty, while advanced statistical techniques would not be possible under conditions of uncertainty. In addition, practitioners can, due to the representative heuristic, be over-confident in their ability, skill or knowledge when performing valuations under conditions of certainty. When valuing under conditions of uncertainty, practitioners tend to avoid simple rule models as they consider the process too unique to be standardised. The combined effect is inconsistent valuation results unless it can potentially be addressed through an integrated and modified sales comparison model that takes into account varying degrees of certainty and uncertainty.Practical implicationsThe proposed modified sales comparison model is an integrated model that can be adopted by practitioners in valuing residential, non-residential and large plant and machinery. It can potentially be used to value under conditions of certainty and uncertainty and improve valuation consistency. End users such as mortgage lenders and investors can benefit from the adoption of this model.Originality/valueThe aim of this paper is to propose an integrated and modified sales comparison model for valuing under conditions of certainty, normal uncertainty and abnormal uncertainty. The integrated model can value based on direct comparison under conditions of certainty and uncertainty while addressing the in practice avoidance of advanced statistical techniques and the implications of the representative heuristic and halo effect as cognitive biases on valuation consistency.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call