Exploring Time-Series Forecasting Models for Dynamic Pricing in Digital Signage Advertising

Audience attention is vital in Digital Signage Advertising (DSA), as it has a significant impact on the pricing decision to advertise those media. Various environmental factors affect audience level toward advertising signage. Fixed-price strategies, which have been applied DSA for decisions, are generally inefficient at maximizing potential profit of service provider, that could changing fast and not considered current solutions timely manner. Therefore, time-series forecasting method suitable solution DSA, improves by modeling changes signage optimal pricing. However, difficult determine an price model with increasing number available models recent years. Based 84 research articles reviewed, data characteristics analysis terms linearity, stationarity, volatility, dataset size helpful determining forecasting. This paper reviewed widely used identified related each model. A framework proposed demonstrate selection process dynamic based its analysis, paving way future DSA.