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Record W2559044567 · doi:10.1016/j.jom.2016.10.001

Co‐creating value using customer training and education in a healthcare service design

2016· article· en· W2559044567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Operations Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTask (project management)Health careService qualityKnowledge managementService (business)Conceptual modelBusinessCustomer retentionValue (mathematics)Customer serviceMarketingProcess managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract In services, which require significant customer participation to create value, customers who lack the knowledge, skills and motivation necessary to participate effectively can negatively impact service quality and cost outcomes. This paper develops a conceptual model to investigate the effectiveness of utilizing customer training and education (CTE) to improve customer readiness to provide effective behaviors in a professional service. The model was tested using survey data from patients diagnosed with diabetes who received CTE as part of their healthcare service. We found that customers who are taught why they have to perform the tasks, have higher levels of motivation to perform these tasks effectively. Further, as proposed by the customer readiness model, when their task performance is higher, they have improved health and lower healthcare costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.318
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it