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Interpretive structural modeling (ISM) and Matrice d'Impacts Crois\u00e9s Multiplication Appliqu\u00e9 \u00e0 un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>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\u2013life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1108\/itp-04-2020-0169","type":"journal-article","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T21:11:38Z","timestamp":1608585098000},"page":"46-66","source":"Crossref","is-referenced-by-count":19,"title":["Understanding determinants of social networking service fatigue: an interpretive structural modeling approach"],"prefix":"10.1108","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2259-6357","authenticated-orcid":false,"given":"Lin","family":"Xiao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5756-0744","authenticated-orcid":false,"given":"Ting","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6497-9105","authenticated-orcid":false,"given":"Jian","family":"Mou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihua","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"issue":"2","key":"key2022011705540130700_ref501","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.jsis.2015.03.001","article-title":"Linking dimensions of social media use to job performance: the role of social capital","volume":"24","year":"2015","journal-title":"Journal of Strategic Information Systems"},{"key":"key2022011705540130700_ref001","article-title":"Structural analysis with the MICMAC method and actor's strategy with MACTOR method","volume-title":"Futures Research Methodology","year":"1999"},{"key":"key2022011705540130700_ref002","unstructured":"Audienceproject (2019), \u201cApp and social media usage\u201d, available at: https:\/\/www.audienceproject.com\/resources\/insight-studies\/app-social-media-usage (accessed October 2019)."},{"issue":"4","key":"key2022011705540130700_ref502","doi-asserted-by":"crossref","first-page":"831","DOI":"10.2307\/41409963","article-title":"Technostress: technological antecedents and implications","volume":"35","year":"2011","journal-title":"MIS Quarterly"},{"key":"key2022011705540130700_ref003","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.chb.2014.11.048","article-title":"Too much Facebook? 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