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<p>In this study, the problem of selecting a suitable parking area faced by İzmir Demokrasi University employees was analysed using the analytic hierarchy process (AHP), a multi-criteria decision-making method. Four potential parking areas around the university’s main building were evaluated based on six criteria: (1) traffic safety, (2) parking area capacity, (3) distance to the university’s main building, (4) topographical condition, (5) environmental factors, and (6) ease of access. Face-to-face surveys were conducted with 50 academic and administrative staff members, and the data collected were analysed systematically using the AHP methodology. The criterion weights were hence determined to be: traffic safety (0.3712), distance to the university’s main building (0.2450), ease of access (0.1783), parking area capacity (0.1279), environmental factors (0.0467), and topographical conditions (0.0309). The measure clearly identified one parking area as most suitable of the four, with scores of 48% (for the most suitable), 25%, 18%, and 9%. All consistency ratios (CR) obtained during the analysis were below the 0.1 threshold, indicating statistically consistent judgements. These findings offer practical insights for urban planners and university administrators and contribute to the development of data-driven, user-centred decision support systems.</p>

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A Decision Support Model Based on the Analytic Hierarchy Process (AHP) for Parking Area Selection: A Sample for İzmir Demokrasi University, Türkiye

  • 期刊论文

  • 发表日期：

    2025年9月19日

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  • Ziya Cakici,
  • Ezgi Kilic,
  • Mehmet Ali Ilhan

摘要

In this study, the problem of selecting a suitable parking area faced by İzmir Demokrasi University employees was analysed using the analytic hierarchy process (AHP), a multi-criteria decision-making method. Four potential parking areas around the university’s main building were evaluated based on six criteria: (1) traffic safety, (2) parking area capacity, (3) distance to the university’s main building, (4) topographical condition, (5) environmental factors, and (6) ease of access. Face-to-face surveys were conducted with 50 academic and administrative staff members, and the data collected were analysed systematically using the AHP methodology. The criterion weights were hence determined to be: traffic safety (0.3712), distance to the university’s main building (0.2450), ease of access (0.1783), parking area capacity (0.1279), environmental factors (0.0467), and topographical conditions (0.0309). The measure clearly identified one parking area as most suitable of the four, with scores of 48% (for the most suitable), 25%, 18%, and 9%. All consistency ratios (CR) obtained during the analysis were below the 0.1 threshold, indicating statistically consistent judgements. These findings offer practical insights for urban planners and university administrators and contribute to the development of data-driven, user-centred decision support systems.