The Influence of Mobile Commerce on Consumer Behavior: A FCM-RF-DNN Analysis

For m-commerce vendors, the difficulty is to decipher what factors impact customer actions in the ubiquitous mobile setting. In addition, companies are attempting to incorporate social media into their mobile approach in some way. This proposed approach to the findings of a qualitative exploratory study regarding the use of social media and smartphones within the framework of mobile commerce. Keep in mind the order of importance while doing data preprocessing, feature selection, and training the model. The usual steps in getting data ready for processing, such as cleaning it, identifying users and sessions, and finding episodes. The IS-DT suggested method's implementation technique is utilized in feature selection. Unified FCM-RF-DNN models need to be trained after features have been retrieved. Two state-of-the-art approaches, RF and DNN, are outperformed by the suggested approach. Following the implementation of the method, accuracy improved by 96.13%.

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Published
2024-08-23
DOI
https://doi.org/10.1109/iacis61494.2024.10721778
Primary Topic
Technology Adoption and User Behaviour
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article
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The Influence of Mobile Commerce on Consumer Behavior: A FCM-RF-DNN Analysis

Amit Chauhan, Vidhya Prasanth, Suman Dahiya, Nawab Akram et al.
Technology Adoption and User Behaviour
article

The Influence of Mobile Commerce on Consumer Behavior: A FCM-RF-DNN Analysis

Amit Chauhan, Vidhya Prasanth, Suman Dahiya, Nawab Akram, Valarmathi Periyasamy, Hemanand Chittapragada
article en

Abstract

For m-commerce vendors, the difficulty is to decipher what factors impact customer actions in the ubiquitous mobile setting. In addition, companies are attempting to incorporate social media into their mobile approach in some way. This proposed approach to the findings of a qualitative exploratory study regarding the use of social media and smartphones within the framework of mobile commerce. Keep in mind the order of importance while doing data preprocessing, feature selection, and training the model. The usual steps in getting data ready for processing, such as cleaning it, identifying users and sessions, and finding episodes. The IS-DT suggested method's implementation technique is utilized in feature selection. Unified FCM-RF-DNN models need to be trained after features have been retrieved. Two state-of-the-art approaches, RF and DNN, are outperformed by the suggested approach. Following the implementation of the method, accuracy improved by 96.13%.

Magadh University (IN), Universal Engineering College (IN), M. Kumarasamy College of Engineering, Christ University (IN)
Decent work and economic growth
Openalex Percentile: Top 79%
Technology Adoption and User Behaviour
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The Influence of Mobile Commerce on Consumer Behavior: A FCM-RF-DNN Analysis — Amit Chauhan, Vidhya Prasanth, et al. · (2024) | TGRS Research Map | TGRS