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Record W3089569213 · doi:10.5267/j.msl.2020.9.040

The effect of experience quality, perceived value, happiness and tourist satisfaction on behavioral intention

2020· article· en· W3089569213 on OpenAlexvenueno aff
Sulfi Abdul Haji, Surachman Surachman, Kusuma Ratnawati, MintartiRahayu MintartiRahayu

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessPsychologyTourismSocial psychologyValue (mathematics)Nonprobability samplingQuality (philosophy)Affect (linguistics)Sample (material)GeographyMathematicsMedicinePopulation

Abstract

fetched live from OpenAlex

This research aims at examining and determining the effect of experience quality on tourists’ behavioral intention either directly or by perceived value, happiness, and tourist satisfaction. The sample in this research includes 227 tourists visiting Dodola Island using purposive sampling technique. The analytical method to test the hypothesis in this research is SEM-PLS. The results show that Experience Quality, Tourist Satisfaction, and Happiness had positive and significant effects on Tourists’ Behavior Intention. Meanwhile, Perceived value did not have any significant effect on Tourist Behavioral Intention as Perceived Value was not able to act as a mediator on the effect of Experience Quality on Behavioral Intention. On the other hand, Perceived Value variable had a positive and significant effect on Tourist Satisfaction. Therefore, the increase in Tourist Satisfaction sourced from Perceived Value could affect behavioral intention. The results of further research also show that Tourist Satisfaction and Happiness could partially mediate the effect of Experience Quality on Behavioral Intention.

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 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.341
Teacher spread0.315 · 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 teacher head, 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

Citations30
Published2020
Admission routes1
Has abstractyes

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