There are different sustainability indicators that may affect the construction projects which are necessary to be identified in order to improve the construction industry. This paper proposes a qualitative assessment framework that can assist construction project teams with a useful tool to identify and prioritize sustainability indicators impacting their projects. First, a literature review is conducted to identify the sustainability indicators that need to be considered in achieving a more sustainable construction project in Egypt. The factors are then ranked through a survey questionnaire and experts' judgment using a 7-point Likert scale to identify the most significant factors. The AHP is used in this paper to determine experts' importance weights. A case study of an infrastructure project in Egypt is conducted to identify, and prioritize different sustainability indicators affecting the construction of infrastructure projects in Egypt. The consent of framework development can be generalized and applied to other countries by changing related sustainability indicators and expert opinions. The framework solves a major problem that faces infrastructure construction project teams who want to Prioritize and assess quantitatively sustainability indicators existed in their projects prior to the start of construction phase.
This paper presents a Fuzzy Consensus Qualitative Risk Analysis framework to identify and prioritize risks encountered in real estate projects, which is applied to developing countries. The framework incorporates the consensus and quality of experts in the process of evaluating risk events and is composed of (1) a Fuzzy Expert System (FES)to determine qualification of experts;(2) Fuzzy Similarity Aggregation Algorithms to aggregate experts' opinions; and (3) a threedimensional prioritization approach to rank the risks, qualitatively. Risks are identified through a literature review and interviews with experts who rank the risks in terms of their probability of occurrence, impact and level of detection; each is described using five linguistic terms that are defined by membership functions (MFs) on a 5-point rating scale. The FES determines an importance weight factor for each expert, based on a set of predetermined qualification attributes. Experts' opinions are aggregated in a linguistic framework, based on the proximity of their opinions on the scale to ensure that their aggregated decision is a result of common agreement. The importance weight factor is combined with the consensus weight factor of each expert in the aggregation process using a scalar modifier and the Euclidean Distance Measure Function is used to determine the linguistic criticality of every risk event. A threedimensional prioritization approach applies a set of ranking rules to every risk that enables experts to rank and visualize the priority of the risks in a three-dimensional space. The framework contributes to the Real estate industry by solving a major problem for project teams in developing countries to qualitatively evaluate risks in a fully supported linguistic framework, using fuzzy logic, which addresses the vagueness and imprecision that exist in the decision-making process.
This paper presents a Qualitative Risk Analysis Framework to identify and prioritize environmental risks encountered in infrastructure projects, which is applied to developing countries. The framework incorporates consensus and quality of experts in the process of evaluating environmental risk events and is composed of (1) Fuzzy Expert System (FES) to determine attributes of experts; (2) Fuzzy Similarity Aggregation Algorithms to aggregate experts' opinions; and (3) three-dimensional prioritization approach to rank the risks, qualitatively. The FES determines an importance weight factor for each expert, based on a set of predetermined qualification attributes. Experts' opinions are aggregated in a linguistic framework, based on the proximity of their opinions on the scale to ensure that their aggregated decision is a result of common agreement. The importance weight factor is combined with the consensus weight factor of each expert in the aggregation process using a scalar modifier and the Euclidean Distance Measure Function is used to determine the linguistic criticality of every environmental risk event. A three-dimensional prioritization approach applies a set of ranking rules to every risk that enables experts to rank and visualize the priority of the risks in a three-dimensional space. The framework contributes to the Construction industry by solving a major problem for project teams in developing countries to qualitatively evaluate environmental risks in a fully supported linguistic framework, using fuzzy logic, which addresses the vagueness and imprecision that exist in the decision-making process. It provides an improvement over other fuzzy qualitative-based models, using FES, instead of relying on an arbitrary assessment of experts' qualifications in aggregating their opinions.
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