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Record W2085086200 · doi:10.1177/1094670503005004005

When Does Commitment Lead to Loyalty?

2003· article· en· W2085086200 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 Service Research · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsBusinessCustomer retentionLoyalty business modelCustomer advocacyMarketingCustomer to customerRelationship marketingOrganizational commitmentCustomer delightLoyaltyCustomer intelligenceService (business)Service qualityPsychologyMarketing managementSocial psychology

Abstract

fetched live from OpenAlex

Customer commitment is now regarded as a key variable in marketing relationships. The article investigates the roles played by different forms of commitment in the relationship between customers and their service provider. It was found that when customer commitment is based on shared values and identification, it has a uniformly positive impact on customer loyalty. When customer commitment is based on switching costs and dependence, it has mixed effects on customer loyalty. In addition, it was found that there were significant interactions between these two forms of commitment on customer loyalty. If we are to understand the role of customer commitment, we must have a solid understanding of the nature of commitment present in the relationship. These findings have important implications for the development and management of service relationships because it is not necessarily the case that more customer commitment is better for either the service provider or the customer.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.106
GPT teacher head0.363
Teacher spread0.257 · 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