An exact pricing algorithm for revenue maximization under the logit demand function

Author First name, Last name, Institution

• Moddassir Khan Nayeem, The University of Texas at San Antonio
• Omar Abbaas, The University of Texas at San Antonio
• Suzan Alaswad, Zayed UniversityFollow
• Sinan Salman, Zayed UniversityFollow

Document Type

Article

Source of Publication

Expert Systems with Applications

Publication Date

7-15-2026

Abstract

Determining the optimal selling price is a challenge in revenue management, especially in markets characterized by nonlinear and price-sensitive demand. While traditional models, such as linear, power, and exponential demand functions, offer analytical convenience, they often fail to capture realistic purchase dynamics, leading to suboptimal pricing. The logit demand function addresses these limitations through its bounded, S-shaped curve, offering a more realistic representation of consumer behavior. Despite its advantages, most existing literature relies on heuristic approaches, such as pricing at the inflection point, which prioritizes maximum price-demand sensitivity but does not guarantee maximum revenue. This study proposes a novel, exact pricing algorithm (EPA) that analytically derives the revenue-maximizing price under the logit demand function using the Lambert W function. By providing a closed-form solution, the approach eliminates reliance on heuristic methods and corrects the common practice of considering the inflection point price as market price. In fact, we demonstrate that the optimal price is consistently lower than the inflection-point price under reasonable assumptions, leading to lower prices for consumers and higher revenue for sellers. Numerical experiments validated against a real-world e-commerce dataset demonstrate that the EPA-optimal price is consistently lower than the inflection-point price, resulting in an average 20% price reduction accompanied by a 15% increase in revenue. Furthermore, comparative analysis reveals that the EPA significantly outperforms some benchmarks, bypassing the 33% actual revenue gap observed in machine learning models and the 34% gap found in dynamic pricing policy.

DOI Link

10.1016/j.eswa.2026.132223

ISSN

0957-4174

Publisher

Elsevier BV

Volume

320

Disciplines

Business

Keywords

Lambert function, Logit demand function, Pricing strategy, Revenue maximization

Scopus ID

105034727282

Recommended Citation

Nayeem, Moddassir Khan; Abbaas, Omar; Alaswad, Suzan; and Salman, Sinan, "An exact pricing algorithm for revenue maximization under the logit demand function" (2026). All Works. 7960.
https://zuscholars.zu.ac.ae/works/7960

Indexed in Scopus

yes

Open Access

no