Research on Adoption Intention Toward Intelligent Messaging Service: From Self-Determination Theory Perspective
Year: 2025
Type: article
Study design: Observational Study
Abstract: Empowered by artificial intelligence and 5G technologies, intelligent messaging service instead of the existing short messaging service could provide an omni-channel service, thus achieving higher interconnection for mobile users. In this paper, we adopted mixed methods research and explored the psychological factors that affect adoption intention to adopt intelligent messaging services among mobile users based on self-determination theory. After semi-structured interviews, we constructed a partial least squares structural equation model from the perspectives of intrinsic and extrinsic motivations. In addition, openness and perceived complexity were also introduced as an extended dimension. Through an online survey, 548 valid questionnaires were obtained. The results show that intrinsic motivation has a greater effect on adoption intention. Specifically, attitude, perceived autonomy, perceived relatedness, and perceived system quality have significant positive impacts on the adoption intention of intelligent messaging, while perceived complexity has a negative direct impact on adoption intention. Although perceived competence and perceived media richness have no significant effects on adoption intention, an indirect effect on adoption intention through attitude was observed. Notably, perceived interactivity and openness have no effect on adoption intention. Through this study, we aim to provide guidance for developers to focus on mobile users’ psychological needs regarding upgraded interactive channels, which can accelerate the construction of an omni-channel media environment.
Authors: Jianming Wu, Zhiyuan Yu
Institution: Shandong University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,207
Funder: Shandong University
OpenAlex ID: W4409783435
