Confirmatory Factor Analysis of Variables Influencing Customer Satisfaction at the Shopee Online Shop

Currently, buying and selling transactions carried out by the public through online shops have increased significantly. This increase occurs because of the ease of transactions, prices that are relatively cheaper than offline stores, and supported by advances in digital marketing technology. In the buying and selling process, customer satisfaction is a very important factor. In order to increase customer loyalty, this study will analyze the variables that influence customer loyalty. The analysis will be carried out using the CFA method. The Confirmatory Factor Analysis technique is one of the powerful techniques in analyzing simple models in seeing the functioning of empirical constructs (factors) in a structural model. CFA can test how well indicator variables can represent related latent variables. The results of the analysis obtained show that there are three indicator variables that have a significant influence on Customer Satisfaction, including Fulfilled consumer expectations for the purchased product (KP1) and Recommendation to other parties (KP2) The Shopee application is able to fulfill consumer desires (KP3) The price given is cheaper than elsewhere, but with the same quality (KP4) The product being sought is easy to obtain (KP5).

Authors

Institutions

Publication Details

Journal
Nusantara Science and Technology Proceedings
Published
2025-05-21
DOI
https://doi.org/10.11594/nstp.2025.4769
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Confirmatory Factor Analysis of Variables Influencing Customer Satisfaction at the Shopee Online Shop

Poppy Alvianolita Sanistasya, Maharani Ikaningtyas, Rosyidatuzzahro Anisykurlillah, Trimono Trimono
Nusantara Science and Technology Proceedings
Technology Adoption and User Behaviour
article

Confirmatory Factor Analysis of Variables Influencing Customer Satisfaction at the Shopee Online Shop

Poppy Alvianolita Sanistasya, Maharani Ikaningtyas, Rosyidatuzzahro Anisykurlillah, Trimono Trimono
article en

Abstract

Currently, buying and selling transactions carried out by the public through online shops have increased significantly. This increase occurs because of the ease of transactions, prices that are relatively cheaper than offline stores, and supported by advances in digital marketing technology. In the buying and selling process, customer satisfaction is a very important factor. In order to increase customer loyalty, this study will analyze the variables that influence customer loyalty. The analysis will be carried out using the CFA method. The Confirmatory Factor Analysis technique is one of the powerful techniques in analyzing simple models in seeing the functioning of empirical constructs (factors) in a structural model. CFA can test how well indicator variables can represent related latent variables. The results of the analysis obtained show that there are three indicator variables that have a significant influence on Customer Satisfaction, including Fulfilled consumer expectations for the purchased product (KP1) and Recommendation to other parties (KP2) The Shopee application is able to fulfill consumer desires (KP3) The price given is cheaper than elsewhere, but with the same quality (KP4) The product being sought is easy to obtain (KP5).

Nusantara Science and Technology Proceedings
University of Pembangunan Nasional Veteran Jawa Timur (ID), Mulawarman University (ID)
Openalex Percentile: Top 86%
Technology Adoption and User Behaviour
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.