Co-creating educational consumer journeys: A sensemaking perspective
Bibliographic record
Abstract
Abstract To date, customer education has been framed in terms of one-way information provision, at odds with much of the literature on meaning co-creation. Drawing on an ethnography of a specialty coffee purveyor, we show how staff and consumers co-create educational consumer journeys through the deployment of seven practices: auditing, realignment, marrying competing logics, negotiating scripts, evangelizing, expanding collective knowledge, and impression management. These practices require staff and consumers to enact three different educational roles (educator, student, and peer), which are necessary for the co-creation and extension of consumer journeys. The roles, practices and the journeys themselves emerge iteratively through sensebreaking, sensegiving, and sensemaking processes among staff, consumers and the servicescape. Our findings frame customer education as a dynamic process in which meaning is co-created between participants. Furthermore, the cues and touchpoints needed for meaning-making shift as power relations between participants change. Managerially, these findings highlight the potential of co-created educational consumer journeys to expand established market categories.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.043 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".