Maximizing Profit via Assortment and Shelf‐Space Optimization for Two‐Dimensional Shelves

Personality quiz is a powerful tool that enables costumer segmentation by actively asking them questions, and marketers are using it as an effective method of generating leads and increasing e‐commerce sales. We study the problem of how to select and sequence a group of quiz questions so as to optimize the quality of customer segmentation. We assume that the customer will sequentially scan the list of questions. After reading a question, the customer makes two, possibly correlated, random decisions: (i) she first decides whether to answer this question or not, and then (ii) decides whether to continue reading the next question or not. We further assume that the utility of questions that have been answered can be captured by a monotone and submodular function. In general, our problem falls into the category of non‐adaptive active learning‐based customer profiling. Note that under our model, the probability of a question being answered depends on the location of that question, as well as the set of other questions placed ahead of that question, this makes our problem fundamentally different from existing studies on submodular optimization. We develop a series of question selection and sequencing strategies with provable performance bound. Although we focus on the application of quiz design in this study, our results apply to a broad range of applications, including assortment optimization with position bias effect.

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“…2013, Feldman and Topaloglu 2015, Hbner et al. 2020, Li 2007, Rusmevichientong et al. 2014, Strauss and Talluri 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Cascade Submodular Maximization: Question Selection and Sequencing in Online Personality Quiz

Tang

Yuan

2021

Production and Operations Management

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“…The model is solved through a decomposition approach. Hübner et al (2020) extend the model with a definition of assortment and item arrangement. Akkaş (2019) quantifies the level of shelf space that should be assigned to perishable products considering the fact that the assigned shelf space impacts product expiration.…”

Section: Shelf Space Planning Modelsmentioning

confidence: 99%

Decision support for managing assortments, shelf space, and replenishment in retail

Hübner

Kühn

2023

Flex Serv Manuf J

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Efficiently managing retail space is critical as the increase in product variety is in conflict with limited shelf space and instore replenishment constraints. This paper develops a general framework for retail space management and presents a decision support model with the related problems within the framework of optimizing assortment, shelf space assignment and replenishment. An integrative approach to these planning problems becomes particularly relevant for fast-moving consumer goods and groceries, where stores are regularly replenished from distribution centers. The planning problem at hand is a multi-product shelf space allocation problem where demand is a composite function of the shelf space allocated and assortment-related demand substitution, and actual replenishment practices from retail are incorporated. The model developed extends existing models of shelf space management by jointly considering space-elastic demand and assortment-based substitution and integrating restocking constraints. For the latter, we consider real-world replenishment processes of retailers that distinguish between period-based and ad-hoc replenishment from the backroom. We develop three solution approaches that are based on efficient pre-processing and a nonlinear binary integer programming formulation of the problem. The computation tests based on retail data show the efficiency of the solution approaches in terms of computation time and solution quality. We reveal the improvement in profit levels that can be achieved from integrating assortments, shelf space planning and replenishment where challenges arise in obtaining feasible solutions with limited shelf space and replenishment constraints. We also use sensitivity analyses to demonstrate the high impact of replenishment constraints on profits and solution structures.

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“…By pre‐sorting incoming shipments of newly arrived merchandise, often stacked in roll cages, according to the specific store's layout, sales personnel can avoid zigzagging through the store and instead follow a clear route from shelf to shelf. Due to the high cost and scarcity of shop floor space in urban areas (Hübner et al, 2020), brick‐and‐mortar stores are typically densely packed with shelves. Consequently, navigating roll cages through the narrow aisles is time‐consuming and physically demanding.…”

Section: Introductionmentioning

confidence: 99%

Put it in the bag: Order fulfillment with a pocket sorter system

Boysen

Briskorn

Füßler

et al. 2023

Naval Research Logistics

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Due to high real estate costs in urban areas, shop floor space is scarce in most brick‐and‐mortar stores. Maneuvering newly arrived merchandise through narrow aisles during shelf replenishment is time‐consuming for the sales staff and impedes customers. Therefore, many retail chains nowadays aim for store‐friendly shipments (SFS). By mirroring the layout of a store in the buildup of its dedicated shipments, the need for a zigzag movement through the store when replenishing shelves can be avoided. On the negative side, however, additional effort arises in the distribution centers. A suitable warehousing system to assemble SFS without excessive effort is a pocket (or pouch or bag) sorter, where each item is put into its separate bag. These bags, filled with items, are automatically transported while hanging from an overhead conveyor and can be sorted into any sequence before being delivered to the workstations that build SFS. This article investigates the assembly of SFS with a pocket sorter and presents scheduling procedures to enhance the efficiency of this process for a given set of store orders. We demonstrate that, despite its notorious complexity, the problem can be solved by simple decision rules with good performance. In a case study, we show that this approach can dramatically reduce the completion times of store orders, resulting in savings of more than 60% of the total working hours compared to a simple real‐world policy. Another 30% of reduction can be obtained by standardized store layouts.

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Maximizing Profit via Assortment and Shelf‐Space Optimization for Two‐Dimensional Shelves

Cited by 21 publications

References 70 publications

Cascade Submodular Maximization: Question Selection and Sequencing in Online Personality Quiz

Cascade Submodular Maximization: Question Selection and Sequencing in Online Personality Quiz

Decision support for managing assortments, shelf space, and replenishment in retail

Put it in the bag: Order fulfillment with a pocket sorter system

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