Stackelberg model based game theory approach for assortment and selling price planning for small scale online retailers

Publication Type:
Journal Article
Citation:
Future Generation Computer Systems, 2019, 100 pp. 1088 - 1102
Issue Date:
2019-11-01
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© 2019 Assortment Planning (AP) is one of the most significant and challenging decision for online retailers (e-tailers) to make. This decision becomes even more complex when a supplier is considered as a distinctive participant in decision making model. In the bricks and mortar mode of retailing, retailers are more powerful than suppliers in getting the required goods in the required quantity. However, this is not the case for small scale e-tailers. Such e-tailers are faced with situations where large-scale retailers indirectly force the suppliers to refuse supplying to them. In such cases, effective AP decision making approaches are needed for small scale e-tailers to get the required goods to satisfy the customers’ demand. While current advancement in smart cities provide a powerful platform and support for successful operations of online retailing, this needs to be supported by appropriated modeling approaches that assist the e-tailer in getting their required product assortment. In this paper, a game-theoretic model is developed to support the small scale e-tailer in AP decision making. Such that it has two strategies to decide from. The first strategy is that it can offer the product with supreme quality by procuring it from the main powerful supplier and the second strategy is to offer the product from a less popular brand. The first strategy is modeled as a non-cooperative Stackelberg supply chain in which the supplier plays a leader and the e-tailer is a follower and the second strategy is modeled as an assortment planning problem while considering utility degradation of providing alternative brand to the customers. Various analyses are done to find the best strategy in different scenarios before recommending the best strategy to be followed by the e-tailer in given situations.
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