gummfd

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

1300-1884 1304-4915

Gazi Üniversitesi

10.17341/gazimmfd.1745517

Information Extraction and Fusion Data Engineering and Data Science Industrial Engineering

Bilgi Çıkarma ve Füzyon Veri Mühendisliği ve Veri Bilimi Endüstri Mühendisliği

Perakendecilikte ikame ürün seçimi için Gower benzerliği tabanlı bir yaklaşım

Gower similarity-based approach for substitution product selection in retailing

https://orcid.org/0000-0003-2781-658X

Sağır

Müjgan

ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ

https://orcid.org/0000-0002-4429-5125

Sökel

Abdüssamet

ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ

03 31 2026

41 1 693 702 07 18 2025 02 01 2026

1986

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

Bu çalışma, perakende sektöründe müşteri memnuniyetini artırma ve satış performansını optimize etmede ürün ikamesinin önemli rolünü ele almaktadır. İkame, istenen bir ürünün mevcut olmaması durumunda gerçekleşir ve tüketicilerin benzer ihtiyaçları karşılayan alternatif ürünleri seçmesine yol açar. Bu süreç, özellikle geniş ürün çeşitliliğine ve yüksek müşteri beklentilerine sahip sektörlerde kritik öneme sahiptir. Çalışma, geçmiş satış verileri olmasa bile, yalnızca ürün özelliklerine dayanarak ikame ürünleri belirlemek için etkili bir yöntem olarak Gower benzerlik katsayısını tanıtmaktadır. Gower benzerlik metriğinden yararlanan yaklaşım, ürün benzerliklerini hesaplamak için kategorik, ikili ve sürekli değişkenler gibi karma veri türlerini entegre eder. Sonuçlar, önerilen yöntemin satış davranışında yüksek tutarlılığa sahip ikameleri belirlediğini ve böylece bu veri odaklı çerçevenin güvenilirliğini doğruladığını göstermektedir. Bulgular, talep tahmini ve ürün çeşitliliği planlamasına değerli içgörüler sunarak, dinamik perakende pazarlarında ürün bulunmamasıyla ilgili riskleri azaltmak ve envanter kararlarını optimize etmek için etkili bir çözüm sunmaktadır.

This study addresses the significant role of product substitution in retail for enhancing customer satisfaction and optimizing sales performance. Substitution occurs when a desired product is unavailable, leading consumers to select alternative products that fulfill similar needs. This process is particularly crucial in industries with extensive product variety and high customer expectations. The study introduces Gower's Similarity Score as an effective method for identifying substitute products based solely on product attributes, even in the absence of historical sales data. By leveraging Gower's similarity metric, the approach integrates mixed data types—categorical, binary, and continuous variables—to calculate product similarities. The results demonstrate that the proposed method identifies substitutes with high consistency in sales behavior, thereby validating the reliability of this data-driven framework. The findings contribute valuable insights into demand forecasting and assortment planning, offering a robust solution for mitigating risks related to product unavailability and optimizing inventory decisions in dynamic retail markets.

ürün ikamesi veri odaklı perakende optimizasyonu gower benzerliği talep tahmini envanter yönetimi

product substitution data-driven retail optimization gower similarity demand forecasting inventory management

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