Abstract
The extent to which pricing executives consider consumer perceptions of deception, fairness, and social justice is positioned within an emerging area of research that triangulates the dynamic between legal constraints, ethical considerations, and algorithmic models to make pricing decisions. This paper builds a conceptual model from an analysis of literature describing how companies couple organizational and technology factors into the price-setting process. The legal frameworks of antitrust, data privacy, and antidiscrimination are tethered to the ethical frameworks of deception, fairness, and social justice to form a foundation of relevant organizational factors. A qualitative study is proposed to test the validity of the conceptual model. The primary contribution of this paper is to catalyze practitioner discussion and spur empirical research into the implications of personalized pricing using algorithmic models.
Highlights
Pricing is a tremendously important component of the organizational marketing mix (Borden 1964)
Transdisciplinary research encircles technology factors, ethical considerations, and legal constraints as a triumvirate defining the broad context within which algorithmic models set personalized pricing levels
We identify the relevant literature informing our conceptual model by drawing from the following key theories transcending fields of management, economics, and moral and political philosophy: behavioral theory of the firm (Cyert and March 1992), organizational decision-making theory (March 1994; March and Simon 1993 [1958]), ethical pluralism (James 2016 [1908]; Ross 2002 [1930]), and social contract theory (Hobbes 1982 [1651]; Locke 1980 [1690]; Rawls 1971)
Summary
Pricing is a tremendously important component of the organizational marketing mix (Borden 1964). Businesses race to convert mountains of data into generative insights to improve personalizationcentered retail practices They deploy internally developed and acquired technology factors that enable the marketing function to bridge from customer segmentation to individual personalization. The ethical and legal constructs we have adopted into our concept model are informed by Nissenbaum’s contextual integrity theory, positing that technology-based practices affecting flows of personal data evolve within distinctive contexts of informational norms (Nissenbaum 2010). Transdisciplinary research encircles technology factors, ethical considerations, and legal constraints as a triumvirate defining the broad context within which algorithmic models set (often dynamic) personalized pricing levels. We propose a concept model to suggest how firms reconcile the predictive value of algorithmic decision-making with organizational factors offering human judgment in consideration of consumer ethical interests and the legal and regulatory policy consequences of informational wrongdoing. We approach the literature review as a concatenated activity (Stebbins 2001) that incorporates theoretical sensitivity (Glaser and Strauss 1999) to think “across fields and disciplines .... without letting it stifle [our] creativity or strangle [our] theory” (Charmaz 2014, p. 308)
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