Algorithmic Pricing and Price Controls: Ways Ahead

Journal of Revenue and Pricing Management, 2020

To date, pricing and revenue management literature has mostly concerned itself with how firms can maximize revenue growth and minimize opportunity cost. Rarely has the ethical and legal nature of the field been subjected to substantial comment and discussion. This viewpoint article draws attention to some inherent ethical concerns and legal challenges that may come with future developments in pricing, in particular online personalized pricing, thereby seeking to initiate a broader discussion about issues such as dishonesty, unfairness, injustice, and misconduct in pricing and revenue management practices. Reflecting on how legislators and regulators in Europe seek to limit recent developments in personalized pricing, we argue that not much is to be expected from the legal system, at least not in the short run, with regard to guiding the pricing and revenue field in setting and implementing minimum standards of behavior. Scholarly attention should however not only be directed to the legal challenges of new forms of direct price discrimination, such as algorithmic personalized dynamic pricing, but also to the ethical and legal implications of more granular forms of indirect price discrimination, through which consumers will be allowed to 'freely' sort themselves into different microsegments, especially when the 'self-selection' is enticed by deceptive personalized applications of psychological pricing and neuromarketing.

Sustainability

Algorithmic pricing may lead to more efficient and contestable markets, but high-impact, low-probability events such as terror attacks or heavy storms may lead to price gouging, which may trigger injunctions or get sellers banned from platforms such as Amazon or eBay. This work addresses how such events may impact prices when set by an algorithm and how different markets may be affected. We analyze how to mitigate these high-impact events by paying attention to external (market conditions) and internal (algorithm design) features surrounding the algorithms. We find that both forces may help in partially mitigating price gouging, but it remains unknown which forces or features may lead to complete mitigation.

Computer Networks, 2000

We envision a future in which the global economy and the Internet will merge and evolve together into an information economy bustling with billions of economically motivated software agents that exchange information goods and services with humans and other agents. Economic software agents will di er in important ways from their human counterparts, and these di erences may have signi cant bene cial or harmful e ects upon the global economy. It is therefore important to consider the economic incentives and behaviors of economic software agents, and to use every available means to anticipate their collective interactions. We survey research conducted by the Information Economies group at IBM Research aimed at understanding collective interactions among agents that dynamically price information goods or services. In particular, we study the potential impact of widespread shopbot usage on prices, the price dynamics that may ensue from various mixtures of automated pricing agents (or \pricebots"), the potential use of machine learning algorithms to improve pro ts, and more generally the interplay among learning, optimization, and dynamics in agent-based information economies. These studies illustrate both bene cial and harmful collective behaviors that can arise in such systems, suggest possible cures for some of the undesired phenomena, and raise fundamental theoretical issues, particularly in the realms of multi-agent learning and dynamic optimization.

Economic Affairs, 2005

BRICS Law Journal

The authors examine certain legal problems of antitrust regulation in the digital economy facing the international community, including BRICS member countries. This article focuses on the problems associated with the use of price algorithms by enterprises as a threat factor to competition. The concept of “price algorithm” and the goals of its use by enterprises are analyzed; it is concluded that the use of price algorithms is just one of the tools for conducting economic activity. At the same time, enterprises can pose a threat to competition by using price algorithms as an element of concluding anti-competitive agreements (concerted actions) between enterprises and illegal coordination of their activities. Restriction of competition through the use of price algorithms can harm consumers of goods, works, and services and should be controlled by antitrust authorities. Based on the analysis of the antitrust laws of the BRICS member countries, it is concluded that currently the concept...

THEMIS Revista de Derecho

Over the past couple of years, many competition and antitrust scholars have feared the dawn of ‘algorithmic collusion’. Some have thus suggested expanding the notions of ‘collusion’ and ‘agreement’ in order to capture such coordination. Rather than using an expansive reading of ‘collusion’, the author of this article suggests an approach that works with the core and original intent of Article 101(1) TFEU: the fostering of independent conduct and prevention of market coordination. It finds this to be doctrinally undisputed and also consistent with long-standing competition policy debates, as well as an egalitarian notion of price that lays the foundation of the free market economy. On this basis, and considering given uncertainties, an operational notion of ‘collusive risk’ is put forward.

Journal of Business Ethics

Price discrimination is widely considered unethical/unfair by consumers, as has been borne out by decades of psychological research and mainstream press reporting. However, little academic work has been done to investigate the ethics of price discrimination. The work that has been done to date concludes that while price discrimination is not unethical, despite widespread lay perceptions, it is at best morally neutral. We argue price discrimination is more ethical than unitary pricing, when done ‘progressively,’ meaning firms charge customers as a function of their willingness-to-pay. We introduce this specific kind of price discrimination as ‘Progressive Pricing’ and demonstrate it ethically outperforms a ‘Unitary Pricing’ scheme (where everyone pays the same price, regardless of their willingness-to-pay), at least within a broadly consequentialist framework. We do this by comparing a Unitary Pricing scheme to a Progressive one, analyzing them through the lenses of four different co...

Philosophy of Management

Pricing policies and fair-trade practices are critical for sustaining commercial relationships between firms and customers. Nevertheless, in current business practices, fairness has been mistakenly reduced to a minimalistic ethic wherein justice only demands legal and explicit norms to which commercial parties voluntarily agree. Aimed at giving a different explanation of commercial agreements, this paper will introduce a Virtue Ethics (VE) explanation of the relationship between pricing and the common good by taking up classical concepts related to justice in commerce. In particular, we will explore three principles associated with the notion of fairness in commerce as defined in Neo-Aristotelian ethics towards a relationship between a common good and justice in pricing, i.e., proportionality, benevolence and well-being. To exemplify how these criteria of justice apply to decision-making in commercial practices, we will discuss several cases of fair and unfair commercial relationships.

Communications of the ACM

Examining the potential legal consequences of uses of pricing algorithms.

2019