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Record W2029655155 · doi:10.1108/08858620010316831

Customer‐perceived value in industrial contexts

2000· article· en· W2029655155 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 Business and Industrial Marketing · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsBusinessMarketingValue (mathematics)Value propositionEntertainmentUse valueEmpirical researchBusiness valueService (business)Customer retentionCustomer valueCustomer advocacyService qualityEconomicsFinance

Abstract

fetched live from OpenAlex

Although customer‐perceived value is discussed widely in the literature, few empirical studies have been conducted due to an absence of operational measures. Reports on the development of measures and tests two customer‐perceived value structures using data collected from industrial customers of the information technology industry. The findings generally support both structures and provide empirical support for a value proposition with 13 value drivers. Furthermore, results indicate that most of the 13 drivers are assessed in a similar way by industrial customers of three service sectors surveyed, ICE (information, communication, entertainment), distribution and finance. Flexibility and responsiveness – two service‐related benefits – are important value drivers for all the business customers surveyed. Relationship value drivers are assessed the most differently in two of the three sectors studied, finance and ICE (information, communication, entertainment).

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.245
Teacher spread0.202 · 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