Advance Selling and Advertising: A Newsvendor Framework

Abstract

Many firms offer consumers the opportunity to place advance orders at a discount when introducing a new product to the market. Doing so has two main advantages. First, it can increase total expected sales by exploiting valuation uncertainty of the consumers at the advance ordering stage. Second, total sales can be estimated more accurately based on the observed advance orders, reducing the need for safety stock and thereby obsolescence cost. In this research, we derive new insights into trading off these benefits against the loss in revenue from selling at a discount at the advance stage. In particular, we are the first to explore whether firms should advertise the advance ordering opportunity. We obtain several structural insights into the optimal policy, which we show is driven by two dimensions: the fraction of consumers who potentially buy in advance (i.e., strategic consumers) and the size of the discount needed to make them buy in advance. If the discount is below some threshold, then firms should sell in advance and they should advertise that option if the fraction of strategic consumers is sufficiently large. If the discount is above the threshold, then firms should not advertise and only sell in advance if the fraction of strategic consumers is sufficiently small. Graphical displays based on the two dimensions provide further insights.

Advertising Popularity Feature Collaborative Recommendation Algorithm Based on Attention-LSTM Model

“…e temporal information in the process of popularity change is difficult to capture, while the content features of ads largely determine the popularity of ads, which are an essential condition for the popularity prediction task [31]. In this paper, DAFCT first adopts RNN to mine the temporal information to capture the popularity trend of advertisements and introduces the attention mechanism to eliminate the interference of external factors; then adopts deep neural network to process the content features, and adopts embedding technique to reduce the computational complexity of the model for sparse and high-dimensional features; finally, the concatenate method is used to combine the temporal information and content features.…”

The role of voucher sale in advance for a capital-constrained supply chain

“…Noparumpa et al [31] investigate a form of flexibility with advance selling of wine to mitigate wine quality rating risk. Wu et al [39] analyze effect of placing advance orders at a discount and taking a new product to market as research object. They focus on how advance selling increase total expected sales by exploiting customers' valuation and estimate total sales to reduce cost of safety stock.…”

Online advance selling or not: Pricing strategy of new product entry in a supply chain

“…Li, Shan, and Li (2016) proposed a decision‐making model of consumers' overconfidence in valuation based on the consumers' loss aversion behaviors under the retailer's AS strategy in two periods. Wu, Zhu, and Teunter (2020) explored whether firms should advertise the advance ordering opportunity when consumers are loss averse. They found that, when the discount in AS was sufficiently low, and the scale of informed consumers was sufficiently large, the firm should sell in advance and advertise the AS activities.…”