## 3 Framework and Methodology  
The existing literature shows that numerous models were developed to measure performance by using critical success factors, performance measures, and indicators. However, they mostly address metric requirements for the manufacturing industries rather than construction. Studies conducted in the construction industry have placed more emphasis on the measurement of project performance rather than company performance [11]. The methodology, shown in Figure 1, is summarized stepwise as follows:  
* A literature review was conducted to identify the factors that impact the performance of the construction organizations. Factors shortlisted from the literature review were analyzed for their impact on the performance of the construction organization. These factors were also referred to as Critical Success Factors (CSFs).
* Based on the literature review conducted, factors that have an impact on organizational performance were shortlisted. The proposed performance assessment model included both qualitative and quantitative factors. The model was developed in order to determine the overall performance in terms of the category of rank. Due to the nature of the research question, the researcher adopted a mixed-method qualitative and quantitative approach.
* A questionnaire was designed to evaluate the impact and implementation of the shortlisted non-financial CSFs in their respective organizations. The questionnaire also asked about the participant's total number of experiences, the designation held in the current organization, and the name of the organization. The questionnaire was distributed to professionals across the construction industry via in-person interaction, emails, and an online Qualtrics survey.
* Simultaneously, a database for quantitative factors was compiled for all organizations, whose employees participated in the survey. From this data, factors representing financial trend analysis and market diversification of organization were calculated.
* Analytic Hierarchical Process (AHP) was used to shortlist 18 qualitative factors. The impact rating of the 18 factors was derived from participants as an expert opinion. The results of this process was validated from the Best Subset Regression function. The subset with the highest Rsq and adjusted Rsq was used for modeling purposes.
* A performance assessment model for the construction organization was developed using a Hierarchical Fuzzy Expert System. As the number of factors was extensive and their values were on different scales, it was recommended to use the Hierarchical Fuzzy Expert System (HFES).
* The first layer of HFES was developed by building two sub-models of the fuzzy expert system for non-financial (qualitative) factors and financial (quantitative) factors. The input variables were the respective sub-factors, and the output was the impact value of the combined effect of sub-factors.
* The output from the first layer was used as input for the second layer of the fuzzy expert system. The input variables were assigned fuzzy membership, and fuzzy relations were established. The defuzzification gave the category of the rank of the organization.  
* The model was tested and mathematically validated by Average Validity Percentage (AVP) and Average Invalidity Percentage (AIP) in order to determine the accuracy in assessing the performance of the construction organization [41].