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Journals / Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi / 2026 / Cilt: 15

Conjoint analysis with hierarchical Bayesian approach: An application example for a bike sharing program

Hiyerarşik Bayes yaklaşımıyla bileşik analiz: Bisiklet paylaşım programı için bir uygulama örneği

Yusuf Kağan Demir(NİĞDE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, İNŞAAT MÜHENDİSLİĞİ BÖLÜMÜ, İNŞAAT MÜHENDİSLİĞİ PR.)0000-0003-3139-9854
Hatice Göçmen Demir(NİĞDE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, İNŞAAT MÜHENDİSLİĞİ BÖLÜMÜ, İNŞAAT MÜHENDİSLİĞİ PR.)0000-0002-7827-2132
Pages
1–10
Publication Date
2026-01-15
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study aims to clearly summarize the implementation and analytical steps of the proposed approach.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study examines the individual-level application of conjoint analysis—an increasingly common method in marketing research—using a Hierarchical Bayes (HB) approach.
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Key Findings & Data:The study summarizes the theoretical foundations of HB modeling and demonstrates, step by step, how the method can be implemented in the open-source R environment using the ChoiceModelR package, illustrated through a bike-sharing program case study.
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Conclusion & Impact:This study aims to clearly summarize the implementation and analytical steps of the proposed approach.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Bileşik analiz · Hiyerarşik Bayes · Bisiklet paylaşım sistemi

Abstract

This study examines the individual-level application of conjoint analysis—an increasingly common method in marketing research—using a Hierarchical Bayes (HB) approach. The HB framework models respondents’ utility coefficients jointly with the population-level distribution, enabling the representation of heterogeneity in individual preferences and providing stable estimates even with small sample sizes. The study summarizes the theoretical foundations of HB modeling and demonstrates, step by step, how the method can be implemented in the open-source R environment using the ChoiceModelR package, illustrated through a bike-sharing program case study. Using a synthetically generated dataset, the performance of the Hierarchical Bayes Multinomial Logit (HB-MNL) model is validated. The model accurately recovers the “true” parameters used in data generation, thereby demonstrating the robustness of the HB approach. The resulting individual-level coefficients enable market share simulations under alternative pricing and service scenarios, highlighting HB as a powerful tool for supporting demand estimation and design decisions in urban transportation projects. This study aims to clearly summarize the implementation and analytical steps of the proposed approach.

Özet

Bu çalışmada, pazarlama araştırmalarında yaygınlaşan bir yöntem olan bileşik (conjoint) analiz anketinin Hiyerarşik Bayes (HB) yaklaşımı ile bireysel düzeyde uygulanması incelenmektedir. HB yaklaşımı, katılımcı fayda katsayılarını popülasyon dağılımıyla birlikte ele alarak bireysel tercihlerdeki heterojenliğin modellenmesine olanak tanır ve küçük örneklem büyüklükleri için kararlı tahminler sağlar. Çalışma, HB modellemesinin teorik yapısını özetlemekte ve bu yöntemin bir bisiklet paylaşım programı örneği üzerinden açık kaynaklı R ortamında (ChoiceModelR paketi ile) adım adım nasıl uygulanacağını göstermektedir. Sentetik veri seti kullanılarak HB-Çok Terimli Logit (HB-MNL) modelinin performansı doğrulanmıştır. Model, veri üretiminde kullanılan "gerçek" katsayıları yüksek doğrulukla tahmin ederek, HB yaklaşımının gücünü kanıtlamıştır. Elde edilen birey düzeyindeki katsayılar, farklı fiyatlandırma ve hizmet senaryoları için pazar payı simülasyonlarını mümkün kılması sayesinde HB'nin, kentsel ulaşım projelerinde talep ve tasarım kararlarını desteklemek için güçlü bir araç olduğu ortaya konmuştur. Bu çalışma, yöntemin uygulama ve analiz adımlarını anlaşılır biçimde özetlemeyi amaçlamaktadır.

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Cite This Article

Demir, Y. K., Demir, H. G. (2026). Conjoint analysis with hierarchical Bayesian approach: An application example for a bike sharing program. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, Cilt: 15, 1–10. https://doi.org/10.28948/ngumuh.1838077

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