Classification and Analysis of Decision Support Systems for the Construction Industry

Abstract

The implementation of a Decision Support System (DSS) in the construction industry involves many variables. The nature of the problem to be solved is the key factor, but the methodological approach to the problem, the DSS technique and the nature of the data available must also be considered. This paper presents a classification and analysis of DSS for the construction industry to help decision-makers choose the appropriate systems in the field of construction engineering and management. A rigorous content analysis was conducted on over one-hundred journal articles spanning over thirty years from the Journal of Construction Engineering and Management published by the American Society of Civil Engineering (ASCE). Five different taxonomies were applied to analysis the nature of the problem, decision, complexity, data-system and tool-technique. The findings show that DSS are mostly static, unstructured, and model-centric, and that simulation and suggestion techniques are the most used for the industry. In general, there are many ways of solving DSS problems in the construction industry, but the decision maker must strive to find the best solution for each specific problem. This study is intended to assist in the proper selection of DSS for a variety of construction engineering and management problems.