Exploring the Factors Influencing Continuous Usage Intention of Academic Social Network Sites￼
Exploring the Factors Influencing Continuous Usage Intention of Academic Social Network Sites
Yuqi Wang, Zhiwei Yang, Qingshan Zhou, and Dickson Kak Chiu
Academic social network sites (ASNS) have become a new form of academic service for educators, researchers and students in the social media age. ASNS have many prominent features of academic communication and social networks. What are the differences among Adoption, Use, and Continuous Use? What factors can influence continuous usage intention of ASNS? And in what way do the factors influence users’ continuous usage intention of ASNS?
—What are the differences among Adoption, Use, and Continuous Use?—
ASNS help academic users to obtain literature resources and establish academic social relationships, and recently there has been widespread usage of ASNS in China. Notably, there are further deficiencies in research on the influence factors of usage intention of ASNS:
- Existing research does not consciously distinguish among adoption, use, and continuous use.
- Existing research has mainly concentrated on scholars in the United States, Britain and India, but less on Chinese scholars, even though the ASNS have been widely used in China.
Our study targets Chinese scholars, aiming to explain influencing factors and mechanisms for ASNS continuous usage intention from a theory perspective, and to reveal user behaviors of obtaining academic services. This research mainly focuses on the impact of user adoption on usage intention, which demonstrates influencing factors and communicate patterns for user adoption to provide evidence for improving service efficiency.
This study takes perceived usefulness, satisfaction and social identity as direct influencing variables that affect the continuous usage intention of ASNS based on expectancy confirmation model of information systems (ECM-IS). Expectation confirmation is the antecedent variable in terms of perceived usefulness and satisfaction. To enhance the explanatory power of our model, this study adds external factors, including referent network size and perceived interactivity as the antecedent variables affecting user satisfaction and social identity.
The following hypotheses are suggested by this model:
H1a. Expectation confirmation positively affects the perceived usefulness of ASNS users.
H1b. Expectation confirmation positively affects the perceived interactivity of ASNS users.
H1c. Expectation confirmation positively affects the satisfaction of ASNS users.
H2a. Perceived usefulness positively affects the satisfaction of ASNS users.
H2b. Perceived usefulness positively affects the continuous usage intention of ASNS.
H3. Satisfaction positively affects the continuous usage intention of ASNS.
H4a. Social identity positively affects the satisfaction of ASNS users.
H4b. Social identity positively affects the continuous usage intention of ASNS.
H5a. Perceived interactivity positively affects the social identity of ASNS users.
H5b. Perceived interactivity positively affects the satisfaction of ASNS users.
H6a. Referent network size positively affects the social identity of ASNS users;
H6b. Referent network size positively affects the satisfaction of ASNS users.
This study conducts structural equation model analysis based on the 361 valid questionnaire surveys, which are obtained through two channels: one is the groups from colleges or universities, the other one is the ResearchGate users from six representative major Chinese academic institutions.
The results of the path coefficients and the corresponding levels of significance shows that except these three paths: perceived interactivity -> satisfaction, perceived usefulness -> continuous intention, and social identification -> continuous intention, the other path coefficients all reach the significance level of 0.05. Thus, the results support hypotheses H1a, H1b, H1c, H3, H4a, H4b, H5a, H6a, and H6b, while hypotheses H2b, H4b, and H5b are not supported (seen on Fig. 2). In addition, the results of the path coefficient, significance level, and variance interpretation ratio (R2) of the corrected model show that the variance interpretation ratio of each path coefficient and internal factor variable changes slightly, and the significance level of all path coefficients reaches 0.01 (seen on Fig. 3).
All the results show that satisfaction, expectation confirmation, perceived usefulness, referent network size, social identity, and perceived interactivity have significant positive effects on the continuous intention to use ASNS. This study demonstrates that the theoretical model based on ECT-IS integrates perceptual interactivity, referent network size, and social identity can better explain the continuous usage intention of ASNS. In general, the theoretical model construct in this study can well explain the influencing factors and mechanism of continuous usage intention of ASNS. The applicability of ECT in information systems is confirmed, and a new theoretical model adapts to the situation of ASNS is constructed based on this theory. The model reveals that two variables, expectation confirmation and referent network size, can largely explain and predict users’ continuous intention to use ASNS, which is of great significance in both theory and practice.
At the theoretical level, this study contributes to the study of user behavior in ASNS in several ways. First, as an emerging application of information and Internet technology for academic communication, ASNS has general attributes of information systems and can be interpreted by a unified theoretical framework (such as ECT-IS). Second, the successful introduction of social identity reflects the new characteristics of ASNS that differs from traditional academic communication tools (such as digital libraries, online databases, etc.). The research also shows that perceived interactivity and referent network size are the main antecedent variables of social identity, which reveal the source of social identity. Further, the referent network size is an important variable that affects ASNS users’ continuous intention. Referent network size affects social identity and satisfaction, then indirectly affects users’ continuous intention. This strongly demonstrates the socialization characteristics of ASNS. Finally, the overall analysis of our research model demonstrated that the two external dependent variables of referent network size and expectation confirmation could explain and predict the ASNS users’ continuous intention. This study provides a clear and concise theoretical explanation to understand ASNS users’ continuous intention.
At the practical level, our findings provide insights for stakeholders, including scholars, academic librarians, and platform providers, to understand the influencing factors of scholars’ ASNS behavior and adopt new service methods.
This is a translation of an original article:
Yang, Z., Zhou, Q., Chiu, D.K.W. and Wang, Y. (2022), “Exploring the factors influencing continuous usage intention of academic social network sites”, Online Information Review, Vol. 46 No. 7, pp. 1225-1241. https://doi.org/10.1108/OIR-01-2021-0015
Cite this article in APA as: Wang, Y., Yang, Z., Zhou, Q., & Chiu, D. K. (2022, November 7). Exploring the factors influencing continuous usage intention of academic social network sites. Information Matters, Vol. 2, Issue 11. https://informationmatters.org/2022/10/exploring-the-factors-influencing-continuous-usage-intention-of-academic-social-network-sites/