Pengaruh E-Wom dan Brand Image terhadap Repurchase Intention pada Pengguna Aplikasi Dana

Repurchase Intention can be interpreted as the intention to repurchase is a transaction made on a product or service that has been purchased and then makes a repeat purchase. The focus of the research, namely Repurchase Intention, is intended as a customer's decision to reuse the Dana e-wallet. The purpose of the study was to determine the influence of e-wom and brand image on Repurchase Intention on the Dana e-wallet application. The use of quantitative research methods with a sample of 72 respondents obtained from the reach of the questionnaire from Google Form. The data analysis technique is multiple linear regression with SPSS. In terms of percentage, E-WOM has a positive effect on Repurchase Intention. The more customers talk about the Dana application product, the more customers will use it repeatedly and eventually become a habit or even dependent because of its benefits and convenience. The conclusion of the study is that Brand Image has a positive effect on Repurchase Intention. The more famous and has a good brand image, the more customers will reuse the Dana application. A well-known brand will make customers comfortable and safe in using the Dana e-wallet. Suggestions for further research are that researchers can add Artificial Intelligence (AI) factors as research developments.

Authors

Institutions

Publication Details

Journal
Journal of Interdisciplinary Science and Education.
Published
2024-12-23
DOI
https://doi.org/10.70371/jise.v4i2.265
Citations
1
Primary Topic
Consumer Behavior and Marketing Influence
Type
article
Field-Weighted Citation Impact
0.44
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pengaruh E-Wom dan Brand Image terhadap Repurchase Intention pada Pengguna Aplikasi Dana

Edy Susanto, Agustia Handayani, Bahori Ahoen
1 citations
Journal of Interdisciplinary Science and Education.
Consumer Behavior and Marketing Influence
0.44
article

Pengaruh E-Wom dan Brand Image terhadap Repurchase Intention pada Pengguna Aplikasi Dana

Edy Susanto, Agustia Handayani, Bahori Ahoen
article en
1 citations

Abstract

Repurchase Intention can be interpreted as the intention to repurchase is a transaction made on a product or service that has been purchased and then makes a repeat purchase. The focus of the research, namely Repurchase Intention, is intended as a customer's decision to reuse the Dana e-wallet. The purpose of the study was to determine the influence of e-wom and brand image on Repurchase Intention on the Dana e-wallet application. The use of quantitative research methods with a sample of 72 respondents obtained from the reach of the questionnaire from Google Form. The data analysis technique is multiple linear regression with SPSS. In terms of percentage, E-WOM has a positive effect on Repurchase Intention. The more customers talk about the Dana application product, the more customers will use it repeatedly and eventually become a habit or even dependent because of its benefits and convenience. The conclusion of the study is that Brand Image has a positive effect on Repurchase Intention. The more famous and has a good brand image, the more customers will reuse the Dana application. A well-known brand will make customers comfortable and safe in using the Dana e-wallet. Suggestions for further research are that researchers can add Artificial Intelligence (AI) factors as research developments.

Journal of Interdisciplinary Science and Education.Vol. 4(2)
Universitas Patria Artha (ID)
Openalex Percentile: Top 23%
Consumer Behavior and Marketing Influence
0.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.