Algorithmic Pricing in the digital age

Algorithmic pricing is an emerging business practice that uses computational algorithms to determine the prices of products and services based on a number of dynamic factors. This phenomenon has generated growing interest in various sectors, ranging from e-commerce to transport supply management and beyond. However, as it spreads, relevant ethical issues emerge that require careful consideration and effective solutions. This thesis aims to examine the ethical aspects related to algorithmic pricing, exploring its impact on competition, price transparency, social fairness and the consumer. To do this, different types of pricing algorithms will be analyzed, including those based on machine learning algorithms, dynamic pricing strategies, and revenue optimization algorithms; in addition, the sectors where they are most applied will be analyzed, after introducing a historical excursus and the fundamental concepts. The effect of algorithmic pricing on competition will be investigated, considering how the ability of algorithms to adapt quickly to market conditions can foster anti-competitive practices such as price discrimination. Next, we will examine the issue of price transparency and how the opacity of algorithms can make it difficult for consumers to understand the pricing process and assess whether they are receiving fair treatment. To address these ethical issues, various potential solutions, both existing and future, will be examined. These could include introducing stricter government regulations on the use of pricing algorithms, promoting transparency and corporate accountability, adopting ethical-based pricing algorithms, and promoting digital literacy among consumers to enable them to better understand how pricing algorithms work and their implications.