Application of theory of planned behavior to study online booking behavior
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The development of the internet has influenced the development of the world economy. Various buying and selling transactions that previously could only be done face-to-face, have now developed into transactions via the internet known as e-business or e-commerce. The hotel room online booking system was created to make it easier for consumers to book rooms 24 hours a day. With the availability of the online booking feature, consumers can access hotel information in detail and more transparently, besides that, consumers can also see reviews which can be used as their consideration in choosing hotels and planning holidays. Traveloka's significant development as an Indonesian online travel agent unicorn plays an important role in accelerating the growth rate of the online travel ecosystem, especially for the domestic market. There are many factors that must be examined in finding information, placing orders, and purchasing online. Therefore, this research is focused on online booking behavior. This study aims to determine the influence between variables based on Theory of Planned Behavior, which consists of attitude toward the online booking behavior, subjective norm, perceived behavioral control, online booking intention and online booking behavior at Traveloka. Data was collected from 133 respondents of domestic tourists who have made online bookings at Traveloka. Data were analyzed using Partial Least Square (PLS) statistics with the Smart PLS 3.0 M3 program to determine the complexity of the relationship between latent variables and their indicators. The results of this study indicate that attitude toward the behavior and subjective norms have a positive and significant effect on online booking intention. Meanwhile, perceived behavioral control has no significant effect on online booking intention. Another finding is that online booking intention and perceived behavioral control are known to have a positive and significant effect on online booking behavior. Traveloka management and marketers are also expected to be able to use the results of this research to evaluate and take corrective action on aspects that are deemed inadequate and manage the ease of use of the application to increase online booking intentions through the Traveloka application.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle