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Record W1972545148 · doi:10.1080/13606710701546835

Reframing the service environment in the fitness industry

2007· article· en· W1972545148 on OpenAlexaffabout
Eric MacIntosh, Alison Doherty

Bibliographic record

VenueManaging Leisure · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsWestern University
Fundersnot available
KeywordsClubMarketingOrganizational cultureCognitive reframingService (business)BusinessService qualityPublic relationsPsychologySocial psychology

Abstract

fetched live from OpenAlex

Understanding how to be competitive within the fitness industry requires a fundamental awareness of the service environment at the club level. To date, research on the fitness industry has placed considerable focus on the notion of service quality, particularly such elements as equipment, programmes, facilities and ancillary services, and its role in client satisfaction and retention. Recent research suggests that an organization's culture – the values, beliefs and assumptions that reflect how things are done within an organization – may be perceived outside the organization as well. The objective of the study was to examine the relationships between what have thus far been identified as key service elements for fitness organizations, organizational culture values, and the attitudes and intentions of client members from one private fitness company operating in Canada. Findings showed that both the service elements and the corporate values were significantly associated with members' satisfaction and intentions to stay. The findings suggest that what has typically been conceptualized as the service environment of fitness clubs should be revised to include organizational culture elements.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.019
Scholarly communication0.0120.005
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.248
Teacher spread0.222 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations51
Published2007
Admission routes2
Has abstractyes

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