Status : Verified
| Personal Name | De La Vega, Sandi D. |
|---|---|
| Resource Title | A Store-based grocery assortment planning model incorporating variety and a substitution mechanism |
| Date Issued | 26 July 2019 |
| Abstract | Assortment Planning (AP) under Retail Category Management (RCM) practice continues to be a challenge to store-based grocery retailers due to the need to offer a large variety of product while maintaining profitability. By balancing the trade-off between product proliferation and store’s limited carrying capacity, a delisting strategy called internal SKU rationalization (ISR) is needed to remove unprofitable SKUs from the store’s assortment. By doing so, the store-based grocery retailers can gain short-term profitability because of the reduction in carrying cost reduction and the additional profit gained from transferable demand of delisted SKUs defined by an assortment-based substitution mechanism, where the remaining listed SKU can substitute a portion of the delisted SKU's demand in the assortment. Mathematically, this mechanism is defined using sales volume based on historical data. However, by focusing only on the sales volume and profit alone, the danger of delisting too much SKUs can lead to a significant reduction in store sales and retail patronage when the assortment has a wide variety of products and has low-frequently purchased subcategories. Therefore, there is a need to develop a Grocery RCM Assortment Planning model focusing on Internal SKU Rationalization (GRAP-ISR) that incorporates variety and an assortment-based substitution mechanism to delist unprofitable SKUs and maintain profitability. Using the Category Level Model Approach (CLMA), Gower Distance Measure, Subcategorization and Similarity Effects Concept, a Grocery RCM Assortment Planning Optimization Model (GRAPOM) is developed using monthly aggregated sales data and SKU attributes as input data for the GRAP-ISR framework developed in this study. The GRAPOM and Fadilog̃lu et al. [22] (FKP) model is implemented using a Python-based optimization package called PYOMO and open-source AMPL solver called CBC solver. In the absence of appropriate attribute-based metrics to evaluate the two AP |
| Degree Course | Master of Science in Industrial Engineering |
| Language | English |
| Keyword | Assortment Planning; Variety; Substitution Mechanism; Attributes; Gower Distance; Category Level Model Approach; Similarity Effects; PYOMO; CBC |
| Material Type | Thesis/Dissertation |
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Category : I - Has patentable or registrable invention of creation.
Access Permission : Limited Access