Bibliographic record
Abstract
Purpose This paper aims to investigate consumer reactions to minority retail employees. The paper argues that despite the persistence of racism and homophobia in society, the vast majority of the population is strongly against these forms of discrimination. Because of the profound negativity of such behavior, the study hypothesizes that consumers will be motivated to see themselves unequivocally as individuals free of prejudice. As a result, rather than treating all people equally, the study proposes that consumers will overcompensate and exhibit favoritism toward a retail employee when the latter is a member of a minority group. Design/methodology/approach This study presents ten studies in which participants evaluated employees who were a member of a minority or majority group. Studies 1a–1d use sexual orientation to contrast reactions to majority or minority bank managers in four countries (USÀ, Germany, Italy and South Korea), whereas Studies 1e and 1f use ethnicity (White vs Black) to examine the same question (UK and Canada). Study 1g offers a single-paper meta-analysis, testing the robustness of the observed effect. Studies 2 and 3 examine the roles of political ideology and its associated values, and Study 4 examines choice of an advisor in an online, but consequential setting. Findings Across several contexts and countries, the study finds a consistent pro-minority bias in evaluations of service employees. The study show that, in the USA, this bias is prevalent among liberals, but not among conservatives. This difference in the impact of political ideology is explained by adherence to traditionalism. Research limitations/implications This paper investigates consumer reactions to gays and Blacks and do not test for consumer reactions to other minority groups. Regarding employees’ sexual orientation, the findings of this study are limited to gay men only. Practical implications To elicit favorable evaluations from customers, managers may consider the match between employees’ sexual orientation or ethnicity and consumers’ liberal beliefs. In particular, managers may want to hire people from those minority groups in areas known for their liberal values. On the other hand, the findings suggest that managers should not worry about their new recruits’ sexual orientation and ethnicity in conservative areas, because the results suggest that conservatives show no favoritism toward employees in response to their group status. Originality/value To the best of the authors’ knowledge, this paper is the first paper in marketing investigating consumer reactions to employees who belong to minority groups. The study reports a pro-minority bias that holds across samples and countries, thereby attesting to the population validity of the hypotheses. Further, the study identifies boundary conditions of the effect of employees’ group status by identifying managerially relevant moderators (i.e. political ideology and traditionalism).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".