Service Use Behaviors, Factors and Integrated Marketing Communications Strategies Which Affected the Choice of Personal Loan Service of Bank Customers in Thailand
Notice bibliographique
Résumé
This research was aimed to study service use behaviors in personal loan service of bank customers in Thailand, to analyze factors and integrated marketing communications strategies which affected the choice of personal loan service of bank customers in Thailand. This is a mixed-method research study in which the survey was done with 4000 bank customers who used personal loan service of United Overseas Bank (UOB) and Siam Commercial Bank (SCB) as well as executive panels whereas the qualitative data was collected through interviews with 20 marketing communications staff members of UOB PLC and SCB PLC. The statistical methods were mean score, standard deviation and factor analysis. The survey findings about the behaviors of personal loan service showed that the majority of bank customers have been customers for about 5 years with personal loan credit of between 80,001 and 1,000,000 Baht. They chose to use personal loan service because of the suggestions by bank staff members. The people who influenced their choice the most were themselves. The reason why they chose personal loan service was because the banks had a good image and they were well-known. The average personal loan service behavior was at a high level (=4.31, S.D.=0.53). The results from factor analysis showed that there were 6 independent factors which affected the choice of personal loan service of bank customers in Thailand. The correlations were 0.577-0.981, or at a high level. These 6 factors have the predictive ability of 83.333% and the error is 16.667. The factors could be ranked according to the influence which affected the choice of personal loan service as follows: 1) Marketing through special events, 2) Direct marketing, 3) Sales communications, 4) Sales through staff members, 5) Publicity, 6) Advertisements. The equation for the predictive ability and the indicator is as follows: Y= 0.981(Factor1) + 0.577(Factor 2) + 0.812(Factor 3) + 0.914(Factor 4) + 0.942(Factor 5) + 0.934(Factor 6). The findings from the marketing staff members from those banks through integrated marketing strategies showed that “Above the Line” strategy was used when the banks put up big boards for outdoor display. However, the banks should have more media such as TV or radio spots to attract the attention of the audience. The banks should support TV programs so that customers want to know more about the banks or the products of the banks and that the banks will get more trust from the customers. Regarding the “Below the Line” strategy, the banks should set up booths in department stores to give information to customers and to offer gifts to customers who used the service. There should be more promotional activities and the banks should offer a point system so that customers can collect points and redeem points with rewards or services or discounts to the customers. The banks should have skilled and experienced staff members who can tell about personal loan service so that the customers will get the right information. Moreover, the banks should engage in community activities or local and national events such as Loy Krathong Day or New Year Day in order to attract more customers.
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.
Comment cette classification a été obtenuedéplier
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».