How Algorithms Constrain Consumer Experience
Ashok Kumar Kaliyamurthy & Hope Jensen Schau
Abstract
Prior literature is yet to explain how algorithms systematically constrain consumer experience (CX). To address this issue, we conducted a multi-method ethnographic study of consumers using fitness tracking software. We draw on the information science literature to demonstrate that the constitutive properties of information technology (IT) that underlie algorithms result in a set of restrictive fundamental interactional mechanisms imposed through algorithmic logics of legibility (what is selectively registered as input), visibility (what is selectively represented in output), and legitimacy (normative commitments embedded in input and output choices). We find that these mechanisms systematically constrain the distinct dimensions of the CX construct by eliciting consumption work. Consumers perform cognitive work to think through algorithmic limitations, practical work to accommodate those limitations, relational work to clarify algorithmic misrepresentation, and affective work to deal with algorithmic delegitimization. We make two contributions. First, our emergent framework not only demonstrates how algorithms systematically constrain CX, but is also more broadly relevant to consumer research because it enables accounting for the agency of IT. Second, we provide a corrective to the passive, emotion focused, view of CX by demonstrating how the consumption work of accommodating algorithmic limitations constrains the distinct dimensions of the CX construct.
4 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.37 × 0.4 = 0.15 |
| M · momentum | 0.60 × 0.15 = 0.09 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.