期刊
INFORMATION TECHNOLOGY & PEOPLE
卷 35, 期 1, 页码 46-66出版社
EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/ITP-04-2020-0169
关键词
SNS fatigue; Determinants; Interpretive structural modeling; MICMAC analysis
资金
- Fundamental Research Funds for the Central Universities [NS2020062]
- Young Scientists Fund from Ministry of Education in China Project of Humanities and Social Sciences [20YJC630163]
- National Natural Science Foundation of China [72001106, 91746302]
- China Postdoctoral Science Foundation [2019M650078, 2020T130103]
The purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence. The study revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work-life conflict lead directly to SNS fatigue.
Purpose The purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence. Design/methodology/approach A total of 14 factors influencing SNS fatigue are identified through an extensive literature review. Interpretive structural modeling (ISM) and Matrice d'Impacts Croises Multiplication Applique a un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters. Findings The results revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work-life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue. Originality/value This study represents an initial step toward comprehensively understanding the interrelationships among the factors leading to SNS fatigue and reveals how determinants of SNS fatigue are hierarchically organized, thus extending existing research on SNS fatigue. It also provides logical consistency in the ISM-based model for SNS fatigue by grouping identified factors into dependent and independent categories. Moreover, it extends the applicability of the integration of the ISM and MICMAC approaches to the phenomenon of SNS fatigue.
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