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Markdown optimization in apparel retail sector

Authors: Yıldız, Sevde Ceren;

Markdown optimization in apparel retail sector

Abstract

Over last decades, rapidly growing textile and apparel industry has become an important sector. The branding and ever-changing fashion sense have been a trigger for a major competition environment. Nowadays, increasing competition has accompanied by rapidly changing demand. This changing demand leads to imbalances between aggregate demand and inventory when combined with long lead times. In a sector where lead time is longer than the season, such as fashion sector, the elapsed time between demand and lead time makes dynamic prices important. Dynamic pricing is to change the sales price of the product over time, taking into account the remaining inventory and taking into account the up-to-date customer demand. In this way, the inventory level of the products during the season can be controlled through demand and the cost of stock keeping and transportation can be reduced. In this study, an empirical model is developed by using the empirical sales data which consisting of different product groups over multiple selling seasons. As distinct from the literature, weighted least square estimation is used as a regression method in order to generate empirical demand model. Developed empirical model is used in markdown optimization as dynamic demand for revenue maximization. The mathematical model determines the optimal discount level for each product and also, determines when markdown prices should be applied while maximizing company revenue and considering inventory goals. As a result, it is observed that when the markdowns were applied to the products, the sales increases and the inventory level of each product is used up until the end of the season.

Hızla gelişsen tekstil ve hazır giyim sektörü en önemli perakendecilik sektörlerindenbiridir. Markalaşma ve sürekli değişen moda anlayışı büyük bir rekabet ortamınıntetikleyicisi olmuştur. Günümüzde bu sektörde giderek artan rekabet koşulları,hızla değişen talepleri de beraberinde getirmiştir. Talepteki bu değişiklik yüksektedarik süreleriyle birleştiği zaman toplam talep ile envanter arasında dengesizlikleresebep olmaktadır. Moda sektörü gibi tedarik süresinin sezona göre dahauzun olduğu sektörlerde talep ile tedarik süresi arasında geçen süre dinamik fiyatlandırmayı önemli hale getirmiştir. Dinamik fiyatlandırma, tüketicinin istekve ihtiyaçlarını göz önünde bulundurup satıcının karını gözeterek, ürünün satış fiyatının zamana bağlı olarak değiştirilmesidir. Bu sayede, sezon içinde ürünlerinstok seviyesi talep vasıtasıyla kontrol edilerek stok tutma ve taşıma maliyetleriazaltılabilir.Talep tahmini yapmak için işbirliği yapılan şirketten gelen farklı ürün gruplarınaait alınan verileri kullanarak ampirik bir model geliştirilmiştir. Literatürden farklıolarak, ampirik model ağırlıklı en küçük kareler yöntemi kullanılarak oluşturulmuştur.Geliştirilen ampirik model indirim optimizasyon modelinde gelir maksimizasyonuamacıyla dinamik bir talep olarak kullanılmıştır. Matematiksel model, envanterhedeflerini göz önünde bulundurarak, şirketin gelirini maksimize edecekşekilde her bir ürün için en uygun indirim seviyesini ve zamanını belirlemektedir.Sonuç olarak, ürünlere indirim uygulandığında, satışlarının arttığı ve envanterseviyelerinin sezon sonuna kadar tükendiği görülmüştür.

83

Country
Turkey
Related Organizations
Keywords

Dynamic pricing, Fashion -- Forecasting., Markdown optimization, Pricing -- Mathematical models., Endüstri ve Endüstri Mühendisliği, İndirim optimizasyonu, Markdowns., Textile Industry., Talep tahmini, Industrial and Industrial Engineering, Dinamik fiyatlandırma, Retail trade -- Textile Industry., Regression analysis., Demand forecasting, HF5428 .Y5 2018, Fashion merchandising -- Economic forecasting.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Green