Mapping consumer power: an integrative framework for marketing and consumer research
Bibliographic record
Abstract
Purpose To help shape a more cohesive research program in marketing and consumer research, this paper presents a systematic effort to integrate current research on consumer empowerment with highly influential theories of power. A conceptual overview of power consisting of three dominant theoretical models is developed onto which is mapped existing consumer empowerment research. Design/methodology/approach A synthetic review focuses on three perspectives of consumer power: consumer sovereignty, cultural power and discursive power, drawing from sociological, philosophical and economic literature. These models are then applied to consumer research to illuminate research applications and insights. Findings Research of consumer empowerment has grown significantly over the last decade. Yet, researchers drawing from a variety of intellectual and methodological traditions have generated a multitude of heuristic simplifications and mid‐level theories of power to inform their empirical and conceptual explorations. This review helps clarify consumer empowerment, and offers a useful map for future research. Research limitations/implications Researchers in consumer empowerment need to understand the historical development of power, and to contextualize research within conflicting perspectives on empowerment. Originality/value The paper makes several contributions: organizes a currently cluttered field of consumer empowerment research, connects consumer and marketing research to high‐level theorizations of power, and outlines specific avenues for future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.019 | 0.031 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".