Integrated decision support system for the selection and implementation of delay analysis in construction projects

The goal of this study is to establish an objective, user-friendly, and reliable decision support system, called delay analysis selection and implementation system (DASIS), which allows delay analysts and practitioners in the construction industry to select a type of delay analysis that is most appropriate for given conditions and to perform the selected type of delay analysis. DASIS integrates a delay analysis selection system (DASS) module and an implementation module (DAIS) that performs the type of delay analysis selected by DASS in construction projects. The model that operates the DASS module consists of (1) four different delay analysis approaches currently available to practitioners; (2) a set of 26 attributes that affect the selection of a type of delay analysis; (3) a case-base involving 3,776 cases described by these 26 attributes and their corresponding output values (i.e. , the most appropriate delay analysis approach); (4) a set of 7 categories consisting of subsets of attributes; (5) the weights of the attributes and the categories; and (6) a spreadsheet designed in Microsoft Excel that performs the calculations involved in case-based similarity assessment. The implementation module is a computerized analytics and automation platform that performs the type of delay analysis selected by DASS. In developing the DASS module, 26 attributes that influence the selection of the most appropriate type of delay analysis were identified based on a thorough literature review and were organized in seven categories. These attributes were used to evaluate the four types of delay analysis (i.e. , static, dynamic, additive, and subtractive analyses). Based on the results of this evaluation, a case-base of 3,776 cases was generated while considering the constraints of each category. The weights of the attributes and categories were determined by using several methods. To determine the best-fit between a target case (defined by its 26 attributes) and the 3,776 cases stored in the case-base were used to perform a case-based similarity assessment to calculate weighted case similarity scores, and to find the best-informed solution to the delay analysis type selection problem. In developing the DAIS module, the four types of delay analysis were coded in Microsoft Excel using macros programmed in Visual Basic for Applications (VBA). This automated tool performs the selected delay analysis by DASS. The fully integrated DASIS model finds the best-fit match between a target case and cases stored in the case-base by means of similarity assessment methods by using weighted case similarity scores, hence identifying the most appropriate type of delay analysis for use in the target case, performs the selected type of delay analysis and generates a report about the results of the delay analysis to the analyst instantaneously, allowing the contractual parties to settle the issues quickly. This study is the first attempt to establish an objective decision support system (DASS) to assist delay analysts by automating the selection of a type of delay analysis using combinations of well recognized and reliable attributes and similarity assessment techniques. In addition, DASS is immediately followed by DAIS in an integrated system (DASIS) that does not only do the selection of the most appropriate type of delay analysis, but that also implements the selected delay analysis, hence providing ease of use and high speed. A case study based on fictitious scenarios is presented to demonstrate and validate the research approach. The use of the entropy weight method to calculate the weights of the attributes can be considered a minor limitation of the study. Finally, DASIS can be reformulated as a web-based application that allows analysts to work online using ordinary browsers anywhere and anytime.