Understanding determinants of social networking service fatigue: an interpretive structural modeling approach. Issue 1 (22nd December 2020)

• Record Type: Journal Article
• Authors: Xiao, Lin; Pan, Ting; Mou, Jian; Huang, Lihua
• Is Part Of: Information technology & people. Volume 35:Issue 1(2022)
• Page Start: 46
• Page End: 66
• Publication Date: 2020-12-22
• Subjects: SNS fatigue -- Determinants -- Interpretive structural modeling -- MICMAC analysis; Information technology -- Periodicals; Management information systems -- Periodicals; Human-computer interaction -- Periodicals; 004
• DOI: 10.1108/ITP-04-2020-0169
• Languages: English
• ISSNs: 0959-3845

Abstract

Abstract : 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 Croisés Multiplication Appliqué à 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.