Ming‐Zhao Tang, Tian‐Hui You, Bing‐Bing Cao

Advance selling strategy and pricing decisions with online reviews

  • Management of Technology and Innovation
  • Management Science and Operations Research
  • Strategy and Management
  • Computer Science Applications
  • Business and International Management
Save to CiteDrive Show PDF

AbstractMotivated by marketing practices in advance selling, this paper studies the optimal pricing decisions and advance selling strategy with online reviews. The firm may charge a full or partial price in advance selling and then determine whether to continue selling products in the spot market. We characterize the equilibrium pricing decisions, selling scheme, and advance selling strategy in the monopoly market. We find that no matter what kind of advance selling strategy is implemented, the firm should choose the two‐period selling scheme instead of the one‐period one to market the product. Notably, when the two‐period selling scheme is chosen, either the skimming pricing or the penetration pricing may be optimal for the firm. Specifically, when the review valence is significantly lower, the skimming pricing is always favored by the firm; otherwise, the penetration pricing is more profitable. Moreover, the disclosure quality and review valence jointly affect the choice of firm's optimal advance selling strategy. In detail, advance selling with a full‐price strategy is always dominant if the disclosure quality is high; otherwise, the firm's optimal advance selling strategy is determined by the review valence. Meanwhile, we also analyze several extensions to explore meaningful insights and provide decision‐making support for the firm facing a complex marketing environment.

Need a simple solution for managing your BibTeX entries? Explore CiteDrive!

  • Web-based, modern reference management
  • Collaborate and share with fellow researchers
  • Integration with Overleaf
  • Comprehensive BibTeX/BibLaTeX support
  • Save articles and websites directly from your browser
  • Search for new articles from a database of tens of millions of references
Try out CiteDrive

More from our Archive