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Go/No-Go Decision Model for Owners Using Exhaustive CHAID and QUEST Decision Tree Algorithms

Author

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  • Murat Gunduz

    (Department of Civil and Architectural Engineering, Qatar University, Doha P.O. Box 2713, Qatar)

  • Hamza M. A. Lutfi

    (College of Engineering, Qatar University, Doha P.O. Box 2713, Qatar)

Abstract

Go/no-go execution decisions are one of the most important strategic decisions for owners during the early stages of construction projects. Restructuring the process of decision-making during these early stages may have sustainable results in the long run. The purpose of this paper is to establish proper go/no-go decision-tree models for owners. The decision-tree models were developed using Exhaustive Chi-square Automatic Interaction Detector (Exhaustive CHAID) and Quick, Unbiased, Efficient Statistical Tree (QUEST) algorithms. Twenty-three go/no-go key factors were collected through an extensive literature review. These factors were divided into four main risk categories: organizational, project/technical, legal, and financial/economic. In a questionnaire distributed among the construction professionals, the go/no-go variables were asked to be ranked according to their perceived significance. Split-sample validation was applied for testing and measuring the accuracy of the Exhaustive CHAID and QUEST models. Moreover, Spearman’s rank correlation and analysis of variance (ANOVA) tests were employed to identify the statistical features of the 100 responses received. The result of this study benchmarks the current assessment models and develops a simple and user-friendly decision model for owners. The model is expected to evaluate anticipated risk factors in the project and reduce the level of uncertainty. The Exhaustive CHAID and QUEST models are validated by a case study. This paper contributes to the current body of knowledge by identifying the factors that have the biggest effect on an owner’s decision and introducing Exhaustive CHAID and QUEST decision-tree models for go/no-go decisions for the first time, to the best of the authors’ knowledge. From the “sustainability” viewpoint, this study is significant since the decisions of the owner, based on a rigorous model, will yield sustainable and efficient projects.

Suggested Citation

  • Murat Gunduz & Hamza M. A. Lutfi, 2021. "Go/No-Go Decision Model for Owners Using Exhaustive CHAID and QUEST Decision Tree Algorithms," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:815-:d:481109
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    References listed on IDEAS

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    3. Woosik Jang & Jung Ki Lee & Jaebum Lee & Seung Heon Han, 2015. "Naïve Bayesian Classifier for Selecting Good/Bad Projects during the Early Stage of International Construction Bidding Decisions," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, September.
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    1. Zhao Xu & Weijie Pan & Yukang Hou & Kailun He & Jian Lv, 2022. "A Decision Tree Model for Analysis and Judgment of Lower Limb Movement Comfort Level," IJERPH, MDPI, vol. 19(11), pages 1-21, May.

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