Modeling the National Housing Programming Process to Improve Effectiveness and Reduce Costs
Keywords:
Program planning , national housing, BWM model, modelingAbstract
To achieve the goals of national housing initiatives, it is essential to utilize advanced planning models in conjunction with a comprehensive and integrated approach. Accordingly, the aim of this study is to model the national housing programming process in order to reduce costs and enhance effectiveness. This study is a developmental-applied research conducted using a qualitative method. Data collection tools included semi-structured interviews and a questionnaire. The statistical population consisted of 30 experts and managers in the fields of housing and urban planning, selected through purposive sampling. Interview data were analyzed using qualitative content analysis, which involved transcription of interviews, initial coding, clustering of similar codes, and extraction of key themes. In the final phase, seven proposed models were formulated and used to design a 22-item questionnaire based on the Likert scale. A second sample of 90 professors and relevant experts was selected using the snowball sampling method. Quantitative data were analyzed using the Best-Worst Method (BWM) weighting model. The results indicate that the criteria of demand forecasting, resource optimization, financial resource provision, and risk identification hold the highest importance across the various models. The scheduling and resource optimization model, with the lowest inconsistency and the highest optimal weight, provides the most accurate basis for decision-making. The needs analysis and demand forecasting model and the public-private partnership model also demonstrated high significance. In contrast, the budgeting and financial resources model showed the highest level of inconsistency, indicating a need for improvement in comparative assessments. The findings of this study suggest that national housing planning, using the proposed models—ranked by importance as follows: scheduling and resource optimization, public-private partnership model, new construction technology models, needs analysis and demand forecasting, quality management model, risk analysis model, and budgeting and financial resource provision model—is optimally achievable.
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Copyright (c) 2025 Sepehr Adibzadeh (Author); Bahman Adibzadeh; Ali Akbari (Author)
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