Effective supply chain management is a critical capability to fulfill consumer demand. Since the ultimate goal of a performing supply network is to deliver products/services to the end customers, customer response to stock-out (a post-disruption event) should be an important variable. Incorporating the purchasing behavior into the supply network analysis to "bridge" customer responses to stock-out (a marketing phenomenon) and bullwhip effect (a supply chain phenomenon) requires more quantitative modeling, which is currently absent. Indeed, most supply chain modeling takes the end customer as a passive recipient of products/services provided by upstream elements and treats any unfilled orders as backlog. However, with more competitive worldwide sourcing, consumers increasingly shop at alternative outlets to find the items they need, which has significant impact on the supply chain dynamics of stock-out brand and competing brand, and even the overall supply network. In this paper, responses from different customers experiencing stock-out is modelled to effectively identify supply chain mitigation strategies.
In this research, a high-level Petri-net is developed to model a supply network with two brands of product and two stores, and five types of customer stock-out responses from marketing literature are identified. In the first experiment, the responses are incorporated in the model to quantitatively assess the correlation between customer response and bullwhip effect of both the stock-out brand and the competing brand. In the second experiment, the data from a marketing research of P&G Company is applied to analysis the impact of stock-out intensity on bullwhip effect of 5 specific product categories, which presented 5 different customer response compositions.
Based on the ANOVA analysis of the experiment results, some managerial relevance statements are provided for both the stock-out brand and competing brand. (1) For the stock-out brand, it's suggested that managers should a) focus on customers who prefer to switch store or delay purchase; and b) work together with their retailers to develop customers' store loyalty and encourage customers to substitute within the same brand in a different size. (2) For the competing brand, the manufacturer and its retailers should make great effort to distinguish the demand switched from the stock-out brand from the real demand and grab the opportunity to develop more loyalty customers. (3) Implication to managers for both the stock-out brand and the competing brand is that the incentive to customer behavior should vary with market share and stock-out duration in order to mitigate the bullwhip effect.
Through linking supply chain dynamics to customer purchase behaviors based on simulation technology, the impact of stock-out disruption is quantified from the viewpoint of customer behavior for improving supply chain efficiency. We expect that this paper can provide the foundation for a future stream of research for studying the complex topic of disruption stock-out risk in a supply chain by taking into consideration of customer behaviors from marketing perspective.
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