MétaCan
Menu
← Back to cohort
Record W3045986999 · doi:10.17722/ijme.v15i1.1145

Structural Equation Model of Guests’ Satisfaction of Inland Resorts in Region xii

2020· article· en· W3045986999 on OpenAlexvenueno aff
Menchu Dalumpines Estaris

Bibliographic record

VenueInternational Journal of Management Excellence · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsStructural equation modelingLoyaltyLoyalty business modelCustomer satisfactionMarketingService qualityBusinessQuality (philosophy)Service (business)Relationship marketingData collectionMathematicsMarketing managementStatistics

Abstract

fetched live from OpenAlex

The ultimate goal of this research undertaking was to determine the best fit model involving the following exogenous variables: service quality, customer loyalty, and green marketing practices to endogenous variable – guests’ satisfaction. For the purpose of data collection, a survey questionnaire was administered to the various Inland Resorts in Region XII, Philippines with 417 visited guests. Structural equation modelling was used to find the best fit model. Results revealed that service quality, customer loyalty and green marketing practices show a significant relationship with guest satisfaction. However, the three identified exogenous variables service quality, customer loyalty and green marketing practices emerged as key predictors of guests’ satisfaction considering its observed variables as depicted in the final and best fit model of this study.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.060
GPT teacher head0.304
Teacher spread0.244 · 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 designObservational
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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Management Excellence→Same topicDigital Marketing and Social Media→French-language works237,207→