ItemArticle

Predicting Consumers' Usage Intention Towards User-Generated Content: A Hybrid SEM-ANN Approach

Title
Predicting Consumers' Usage Intention Towards User-Generated Content: A Hybrid SEM-ANN Approach
Creator
Mathur, Smriti; Tewari, Alok; Shrivastava, Avinash K.; Verma, Vimal Chandra; Vishnoi, Sushant Kumar; Sharma, Preeti
Description
With the change in the communication pattern, end-users are engaging in creating content and referring to the content created by other users while making purchase decisions. This research aims at modelling factors affecting consumers' usage intention (UI) towards user-generated content (UGC) using Need for Cognition (NfC) as a moderator of the proposed relationships. The factors affecting consumers' UI involve perceived usefulness (PU), source credibility (SC), information quality (IQ) and NfC. Further, a novel attempt has been made by using the neural network approach to assess the predictive accuracy of the model. A structured questionnaire was used to collect data from 298 consumers through a survey. Data were analysed using two-stage structural equation modelling (SEM) and artificial neural network (ANN). All the independent variables viz., PU, SC, IQ and NfC significantly affect attitude towards UGC, which in turn affects UI. Results of multi-group analysis and a series of chi-square difference tests reveal that a NfC significantly moderates the relationship between PU and attitude, as well as that between SC and attitude. The root mean square error values from the neural network analysis suggest that the models show good predictive accuracy. This study provides a novel assessment of the usage of a hybrid SEM-ANN approach for understanding of UGC by incorporating NfC as a moderator in shaping consumers' attitudes and intentions to use UGC. 2025 World Scientific Publishing Co.
Source
Journal of Information and Knowledge Management;Volume;24;Issue;1;Article No.;2450106;
Date
01-01-2025
Publisher
World Scientific
Subject
attitude; information quality; moderation; need for cognition; neural network; perceived usefulness; source credibility; usage intention; User-generated content
Coverage
Mathur S., School of Business and Management, Christ University, Delhi NCR Campus, U.P., Ghaziabad, India; Tewari A., School of Management, Babu Banarasi das University, U.P., Lucknow, India; Shrivastava A.K., International Management Institute Kolkata, West Bengal, Kolkata, India; Verma V.C., BBA Department, Siddharth University, U.P., Siddharth Nagar, India; Vishnoi S.K., Department of Marketing, Institute of Management Studies, U.P., Ghaziabad, India; Sharma P., School of Business Studies, Sharda University, U.P., Greater Noida, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 2196492;
Format
online
Language
English
Type
Article

Citation

Mathur, Smriti; Tewari, Alok; Shrivastava, Avinash K.; Verma, Vimal Chandra; Vishnoi, Sushant Kumar; Sharma, Preeti, “Predicting Consumers' Usage Intention Towards User-Generated Content: A Hybrid SEM-ANN Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/23024.

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