1. This article presents a Bayesian functional approach to modeling and forecasting the product life cycle curve with product attributes and promotion.
2. It compares this approach to common parametric curve models, and provides an empirical case study with JD.com data.
3. The article also includes an additional experiment on Intel’s data, as well as concluding remarks and acknowledgments.
The article is generally reliable and trustworthy, providing a comprehensive overview of the proposed Bayesian functional approach for modeling and forecasting the product life cycle curve with product attributes and promotion. The authors provide detailed descriptions of their methodologies, including FDA for PLC curves, promotion modeling, Bayesian functional regression, estimation and prediction, clustering and classification. They also compare their approach to common parametric curve models in an empirical comparison section, as well as providing a real-world case study with JD.com data to demonstrate its effectiveness in practice. Furthermore, they include an additional experiment on Intel’s data to further validate their results.
The only potential bias that could be identified is that the authors do not present any counterarguments or alternative approaches to their proposed methodologies; however, this does not detract from the overall trustworthiness of the article since it is focused on presenting their own research rather than comparing different approaches or debating which one is better suited for certain tasks.