An Optimal Model at the Interface of Operations with Social Media Marketing

Abstract

Social media sales and the logistics of products is being shuttled into a new technological paradigm. The purpose of this paper is to review the role of social media sales force and its effects on lot size process and the pricing under an infinite-time horizon assumption. We begin with reviewing the role and importance of social media in business; with a focus on the mathematic deterministic model for decision making that offer ways in which social media influences each step. Scenarios are specifically considered. In the first scenario, price is determined by the market. What size to hold inventoried products and what to budget for promotions on a social media platform are the important variables in market determined pricing. In the second scenario, price is examined by the decision maker based on maximizing the profit margin. In this first case scenario, advertising and product prices are jointly considered to maximize the profit margin. In this second case scenario, lot sizing is considered to minimize costs of holding inventories and placing orders. In both scenarios, the profit function outcome is concave. Therefore, the model optimizes solutions for pricing, lot-sizing for social media advertising policies.

Channel competition in omni‐channel supply chain considering social media advertising

“…Followed the research of Teyarachaku (2018), the market demand function of the product is developed as in the social media channel considering the impact effect of the exponential propagation of social media advertising, where the non‐negative constant is the function parameter and is the marketing advertising investment coefficient. Add the influence of advertising effect to the demand D considering the offline channel retailer R for advertising, , where is the initial demand, is the advertising investment of retailer R, is the advertising effect factor, and the larger is the greater the effect of retailer R's advertising investment on the demand for the good.…”

“…Huang et al (2013) conducted a comprehensive statistics and investigation by incorporating the decision variables of price, rebate, delivery time, space, quality and advertising into the demand function, and discussed advantages and disadvantages of the advertising demand function. Teyarachaku (2018) incorporated the influence of social media advertising into the demand function, and studied the role of social media sales and its influence on the batch process and pricing. Khorshidvand et al (2021) constructed a multi-level and multi-channel supply chain decision model considering channel price, green product policy, and advertising level and applied three different methods for analyzing the situation of online and traditional channels.…”