An Optimization Model for Product Placement on Product Listing Pages

Abstract

The design of product listing pages is a key component of Website design because it has significant influence on the sales volume on a Website. This study focuses on product placement in designing product listing pages. Product placement concerns how venders of online stores place their products over the product listing pages for maximization of profit. This problem is very similar to the offline shelf management problem. Since product information sources on a Web page are typically communicated through the text and image, visual stimuli such as color, shape, size, and spatial arrangement often have an effect on the visual attention of online shoppers and, in turn, influence their eventual purchase decisions. In view of the above, this study synthesizes the visual attention literature and theory of shelf-space allocation to develop a mathematical programming model with genetic algorithms for finding optimal solutions to the focused issue. The validity of the model is illustrated with example problems.

Implementing Green Supply Chain Management for Online Pharmacies through a VADD Inventory Model

“…Additionally, customers tend to focus on the left or top of the page [22] and often move along the zigzag path from the upper left to the lower right [23,24]. Chen et al [25] synthesized the characteristics of visual attention in the literature to develop an economic model that optimizes the product image placement. Nevertheless, they did not discuss decisions related to the supply system and inventory.…”

“…Hariga et al [28] considered the effect of shelf space and display area location decisions on demand. For online retailing, the color, shape, size, and spatial arrangement of different product images are believed to influence the customer’s attention, which, in turn, affects their purchasing decisions [25]. According to this, Chen et al [29] considered the product stored in its own warehouse and proposed a visual-attention-dependent demand (VADD) inventory model, where the demand rate is a function of the display area and size assigned to the product image.…”

Listing2Speak: A Data-Driven Analytical System to Evaluate the E-Commerce Product Listing using Artificial Intelligence and Big Data Analysis

“…Yan-Kwang C. et al synthesized the visual attention literature and shelf space allocation theory to build a mathematical planning model with genetic algorithms to find the optimal solution to the focal problem by investigating the effects of display mode (image text vs. plain text) and display format (list vs. array) on users' online shopping performance and attitudes [1]. Their method combined the results of experiments and surveys to provide data support and eventually constructed a mathematical model using functional equations and genetic algorithms.…”

Swipe, Scroll, Add-To-Cart: a case study of e-commerce gallery designs for small screen devices

“…Other studies that focused on this page looked at the effect of the order of products listed (Cai & Xu, 2008;Y. Xu, Cai, & Kim, 2013;Yan-Kwang, Chiu, & Yang, 2014).…”