The Nature and Implications of Consumers’ Experiential Framings of Failure in High-Risk Service Contexts
Bibliographic record
Abstract
Many services, particularly those related to health care, can be considered high-risk in that despite service providers’ best efforts, consumers may not attain the outcomes they hope to achieve. Recent research highlights how cultural models regarding service providers influence the ways consumers experience and respond to failure. What bears investigating is how these cultural models and consumers’ related framings of failure shape consumer experience in high-risk contexts. Analyzing data from informants engaged with various types of infertility services, we develop a typology of four consumer experiential framings of failure that explore their experiences across three dimensions. These are as follows: the implicit cultural model that shapes relationships with service providers, the implicit cultural model regarding goal pursuit, and consumers’ tacit understandings regarding their appropriate courses of action in response to failure. We link each distinct type of experiential framing to consumers’ distinct set of expectations related to service recovery. And we offer insights for service providers on how to manage their relationships with consumers and (in the tradition of transformative services research) how to enhance consumer well-being.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".