When should a company introduce a new ethical norm? This article uses the value-belief-norm theory to argue that the more an ethical issue threatens a company's ethical value and the more the company has an ethical responsibility to protect such value against such threat, then the more desirable it is for a company to establish ethical norms to protect said value. Distinguishing seven characteristics of an ethical issue and four conditions for a company's ethical responsibility helps identify the situations in (...) which a company should introduce a new ethical norm. The resulting framework, with corresponding guidelines, specifies two accelerators and one inhibitor that influence the desirable speed for introducing new norms. (shrink)

Online retailers are using advances in data collection and computing technologies to “personalize” prices, i.e., offer goods for sale to shoppers at their reservation prices, or the highest price they are willing to pay. In this paper, I offer a criticism of this practice. I begin by putting online personalized pricing in context. It is not something entirely new, but rather a kind of price discrimination, a familiar pricing practice. I then offer a fairness-based argument against it. When an online (...) retailer personalizes prices, it competes unfairly for the social surplus created by a transaction. I defend this argument against objections, and offer a simple remedy: online retailers should either disclose that they are personalizing prices, or stop doing so. (shrink)

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 ismoreethical 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 consequentialist ‘Social Welfare Functions’ (Utilitarian, Egalitarian, Prioritarian, and Leximin), which are used by welfare economists and philosophers to rank the distributions of different social outcomes, concluding that Progressive Pricing is preferred regardless of which Social Welfare Function(s) one finds most plausible. (shrink)

This article provides an overview of the field of business ethics.

More and more, we face AI-based products and services. Using these services often requires our explicit consent, e.g., by agreeing to the services’ Terms and Conditions clause. Current advances introduce the ability of AI to evolve and change its own modus operandi over time in such a way that we cannot know, at the moment of consent, what it is in the future to which we are now agreeing. Therefore, informed consent is impossible regarding certain kinds of AI. Call this (...) the problem of radical ignorance. Interestingly, radical ignorance exists in consent contexts other than AI, where it seems that individuals can provide informed consent. The article argues that radical ignorance can undermine informed consent in some contexts but not others because, under certain institutional, autonomy-protecting conditions, consent can be valid without being (perfectly) informed. By understanding these institutional conditions, we can formulate practical solutions to foster valid, albeit imperfectly informed consent across various decision contexts and within different institutions. (shrink)

Firms use algorithms to make important business decisions. To date, the algorithmic accountability literature has elided a fundamentally empirical question important to business ethics and management: Under what circumstances, if any, are algorithmic decision-making systems considered legitimate? The present study begins to answer this question. Using factorial vignette survey methodology, we explore the impact of decision importance, governance, outcomes, and data inputs on perceptions of the legitimacy of algorithmic decisions made by firms. We find that many of the procedural governance (...) mechanisms in practice today, such as notices and impact statements, do not lead to algorithmic decisions being perceived as more legitimate in general, and, consistent with legitimacy theory, that algorithmic decisions with good outcomes are perceived as more legitimate than bad outcomes. Yet, robust governance, such as offering an appeal process, can create a legitimacy dividend for decisions with bad outcomes. However, when arbitrary or morally dubious factors are used to make decisions, most legitimacy dividends are erased. In other words, companies cannot overcome the legitimacy penalty of using arbitrary or morally dubious factors, such as race or the day of the week, with a good outcome or an appeal process for individuals. These findings add new perspectives to both the literature on legitimacy and policy discussions on algorithmic decision-making in firms. (shrink)

Understanding the moral right and wrong in the context of business practice has long captivated the attention of researchers and business leaders (Brenkert, 2019). Fueled by ethical failures recoun...

In recent years, insurance companies have begun tracking their customers’ behaviors and price premiums accordingly. Based on the Market-Failures Approach as well as the Justice-Failures Approach, I provide an ethical analysis of the use of tracking technologies in the insurance industry. I focus on the use of telematics in car insurance and on the use of fitness tracking in life insurance. The use of tracking has some important benefits to policyholders and insurers alike: it reduces moral hazard and fraud, increases (...) actuarial fairness, and incentivizes safe behavior. These benefits, however, are outweighed by significant moral objections. First, the use of tracking technologies significantly undermines the fairness of the interaction between insurance companies and policyholders. Specifically, the use of tracking eliminates information asymmetries, but in such a way that favors insurers exclusively. Furthermore, tracked behaviors and the ability to choose to behave safely are highly correlated with other variables such as income. Therefore, tracking-based insurance relies on and exacerbates existing inequalities and injustices, which undermines the benefits that tracking is supposed to introduce. (shrink)