Factors Affecting Continuance Intention of AIGC Product

Published: 27 December 2024| Version 1 | DOI: 10.17632/4rcsfbwfzp.1
Contributors:
,
,
, Daoyin Sun

Description

Drawing from data collected from 423 survey samples, our study utilizes the partial least squares (PLS) method to investigate the key factors behind continuance intention. The findings reveal that positive expectancy violation plays a pivotal mediating role between AIGC product attraction (task, affective, and physical attraction) and continuance intention. All three aspects of AIGC product attraction significantly contribute to positive expectancy violation. Notably, task attraction exerts the strongest influence, followed by affective attraction and physical attraction. Moreover, high personal innovativeness enhances the positive impact of affective attraction on positive expectancy violation while diminishing the positive effect of task attraction. The variables and their corresponding abbreviations are as follows: Task Attraction (TA) Affective Attraction (AA) Physical Attraction (PA) Personal Innovativeness (PI) Positive Expectancy Violation (PEV) Continuance Intention (CI)

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Institutions

North China University of Technology

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Artificial Intelligence

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