Escape or return? Users’ intermittent discontinuance behavior in strong-ties social functions
Authors: 
Min Zhang, Sihong Li, Wen Lin, Yan ZhangAuthors Info & Claims
References
[1]
M.S. Granovetter, The strength of weak ties, Am. J. Sociol. 78 (6) (1973) 1360–1380.
[2]
T. Song, C. Yi, J. Huang, Whose recommendations do you follow? An investigation of tie strength, shopping stage, and deal scarcity, Inf. Manag. 54 (8) (2017) 1072–1083.
[3]
N.C. Krämer, V. Sauer, N. Ellison, The strength of weak ties revisited: further evidence of the role of strong ties in the provision of online social support, Soc. Media Soc. 7 (2) (2021).
[4]
W. He, Q. Qiao, K.K. Wei, Social relationship and its role in knowledge management systems usage, Inf. Manag. 46 (3) (2009) 175–180.
[5]
Q. Zhou, H. Li, B. Li, Employee posts on personal social media: the mediation role of work–life conflict on employee engagement, Curr. Psychol. (2023).
[6]
T. Wang, X.T. Mai, T.D.H. Thai, Approach or avoid? The dualistic effects of envy on social media users’ behavioral intention, Int. J. Inf. Manage. 60 (2021).
[7]
M. Zhang, et al., Users’ health information sharing intention in strong ties social media: context of emerging markets, Libr. Hi Tech. (2021).
[8]
S. Wu, J. Zhang, L. Du, I do not trust health information shared by my parents”: credibility judgement of health (mis) information on social media in China, Health Commun (2022) 1–11.
[9]
X. Shen, Y. Li, Y. Sun, Wearable health information systems intermittent discontinuance: a revised expectation-disconfirmation model, Ind. Manage. Data Syst. 118 (3) (2018) 506–523.
[10]
S. Fu, et al., Social media overload, exhaustion, and use discontinuance: examining the effects of information overload, system feature overload, and social overload, Inf. Process. Manag. 57 (6) (2020).
[11]
Y. Cao, et al., Exploring elderly users’ MSNS intermittent discontinuance: a dual-mechanism model, Telemat. Inform. 62 (2021).
[12]
T. Ravindran, A.C. Yeow Kuan, D.G. Hoe Lian, Antecedents and effects of social network fatigue, J. Assoc. Inf. Sci. Technol. 65 (11) (2014) 2306–2320.
[13]
H.Z. Gao, et al., Social media ties strategy in international branding: an application of resource-based theory, J. Int. Mark. 26 (3) (2018) 45–69.
[14]
T. Zhou, Understanding users' switching between social media platforms: a ppm perspective, Research Anthology on Usage, Identity, and Impact of Social Media On Society and Culture, IGI Global, 2022, pp. 790–803.
[15]
X. Shen, et al., Intermittent continuance of smart health devices: a zone-of-tolerance perspective, in: Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020.
[16]
I.H. Cho, Facebook discontinuance, discontinuance as a temporal settlement of the constant interplay between disturbance and coping, Qual. Quant. 49 (4) (2015) 1531–1548.
[17]
B. Furneaux, M. Wade, An Exploration Of Organizational Level Information Systems Discontinuance Intentions, MIS Quarterly 35 (3) (2011) 573–598.
[18]
W. Soliman, T. Rinta-Kahila, Toward a refined conceptualization of IS discontinuance: reflection on the past and a way forward, Inf. Manage. 57 (2) (2020).
[19]
Z. Zhou, M. Yang, X.L. Jin, Differences in the reasons of intermittent versus permanent discontinuance in social media: an exploratory study in Weibo, in: Proceedings of the 51st Hawaii International Conference on System Sciences, 2018.
[20]
W. Soliman, V.K. Tuunainen, A tale of two frames: exploring the role of framing in the use discontinuance of volitionally adopted technology, Inf. Syst. 32 (3) (2022) 473–519.
[21]
G.L. Polites, E. Karahanna, Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance, MIS Quarterly 36 (1) (2012) 21–42.
[22]
R. Aggarwal, et al., Early to adopt and early to Discontinue: the impact of self-perceived and actual IT knowledge on technology use behaviors of end users, Inf. Syst 6 (1) (2015) 127–144. 2.
[23]
B. Furneaux, M. Wade, Impediments to information systems replacement: a calculus of discontinuance, J. Manag. Inf. Syst. 34 (3) (2017) 902–932.
[24]
I. Vaghefi, H. Qahri-Saremi, O. Turel, Dealing with social networking site addiction: a cognitive-affective model of discontinuance decisions, Internet Res. 30 (5) (2020) 1427–1453.
[25]
Y. Man, M. Ng, Twitter intermittent and permanent discontinuance: a multi-method approach to study innovation diffusion, Comput. Hum. Behav. 138 (2023).
[26]
S.C.S. Abraham, G. Hayward, Understanding discontinuance: towards a more realistic model of technological innovation and industrial adoption in Britain, Technovation 2 (1984) 209–231.
[27]
J.J.H. Zhu, Z. He, Perceived characteristics, perceived needs, and perceived popularity adoption and use of the internet in China, Communic. Res. 29 (2002) 466–495.
[28]
C. York, J. Turcotte, Vacationing from Facebook: adoption, temporary discontinuance, and readoption of an innovation, Commun. Res. Rep. 32 (1) (2015) 54–62.
[29]
Y.M.M. Ng, Re-examining the innovation post-adoption process: the case of Twitter discontinuance, Comput. Hum. Behav. 103 (2020) 48–56.
[30]
Y. Feng, L. Li, A. Zhao, A Cognitive-emotional model from mobile short-form video addiction to intermittent discontinuance: the moderating role of neutralization, Int. J. Human–Comput. Interact. (2022) 1–13.
[31]
S. Bhatia, N. Singh, F. Liébana-Cabanillas, Intermittent continued adoption of digital payment services during the COVID-19 induced pandemic, Int. J. Human–Comput. Interact. (2022) 1–15.
[32]
Y.M.M. Ng, Twitter intermittent and permanent discontinuance: a multi-method approach to study innovation diffusion, Comput. Human Behav. 138 (2023).
[33]
S. Fu, H. Li, Y. Liu, Why discontinue Facebook usage? An empirical investigation based on a push–pull–mooring framework, Ind. Manage. Data. Syst. 121 (11) (2021) 2318–2337.
[34]
A. Dhir, et al., Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression, Int. J. Inf. Manage. 40 (2018) 141–152.
[35]
Z. Tang, L. Chen, An empirical study of brand microblog users’ unfollowing motivations: the perspective of push-pull-mooring model, Int. J. Inf. Manage. 52 (2020).
[36]
I. Chang, C. Liu, K. Chen, The push, pull and mooring effects in virtual migration for social networking sites, Inf. Syst. J. 24 (4) (2014) 323–346.
[37]
J.M. Tsai, M.J. Cheng, H.H. Tsai, S.W. Hung, Y.L. Chen, Acceptance and resistance of telehealth: the perspective of dual-factor concepts in technology adoption, Int. J. Inf. Manage. 49 (2019) 34–44.
[38]
B. Moon, Paradigms in migration research: exploring moorings as a schema, Prog. Hum. Geogr. 19 (4) (1995) 504–524.
[39]
Y. Sun, et al., Understanding users' switching behavior of mobile instant messaging applications: an empirical study from the perspective of push-pull-mooring framework, Comput. Hum. Behav. 75 (2017) 727–738.
[40]
J.K. Burgoon, S.B. Jones, Toward a theory of personal space expectations and their violations, Hum. Commun. Res. 2 (2) (1976) 131–146.
[41]
W.A. Afifi, S. Metts, Characteristics and consequences of expectation violations in close relationships, J. Soc. Pers. Relat. 15 (3) (1998) 365–392.
[42]
J.K. Burgoon, Interpersonal expectations, expectancy violations, and emotional communication, J. Lang. Soc. Psychol. 12 (1–2) (1993) 30–48.
[43]
J.W. Hong, Q. Peng, D. Williams, Are you ready for artificial Mozart and Skrillex? An experiment testing expectancy violation theory and AI music, New Media Soc. 23 (7) (2021) 1920–1935.
[44]
S. Tomasi, C.D. Han, J. Otto, Expectancy violation in a Facebook group: what is your response?, Inf. Technol. People. 35 (4) (2022) 1428–1442.
[45]
Y. Guo, et al., Information avoidance behavior on social network sites: information irrelevance, overload, and the moderating role of time pressure, Int. J. Inf. Manage. 52 (2020).
[46]
S. Zhang, et al., Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services, Inf. Manag. 53 (7) (2016) 904–914.
[47]
P. Karr-Wisniewski, Y. Lu, When more is too much: operationalizing technology overload and exploring its impact on knowledge worker productivity, Comput. Hum. Behav. 26 (5) (2010) 1061–1072.
[48]
S. Utz, N. Muscanell, Social Media and Social capital: Introduction to the Special Issue, MDPI, 2015, pp. 420–424.
[49]
S. Saegert, Crowding: cognitive overload and behavioral constraint, Environ. Res. 2 (1973) 254–260.
[50]
R. Pennington, B. Tuttle, The effects of information overload on software project risk assessment, Decis. Sci. 38 (3) (2007) 489–526.
[51]
C. Maier, et al., The effects of technostress and switching stress on discontinued use of social networking services: a study of Facebook use, Inf. Syst. J. 25 (3) (2015) 275–308.
[52]
S. Zhang, et al., Get tired of socializing as social animal? An empirical explanation on discontinuous usage behavior in social network services, in: PACIS 2015 Proceedings, 2015.
[53]
A.R. Lee, S.M. Son, K.K. Kim, Information and communication technology overload and social networking service fatigue: a stress perspective, Comput. Hum. Behav. 55 (2016) 51–61.
[54]
E. Smets, et al., The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue, J. Psychosom. Res. 39 (3) (1995) 315–325.
[55]
L.F. Bright, H.S. Lim, K. Logan, Should I Post or Ghost?”: examining how privacy concerns impact social media engagement in US consumers, Psychol. Mark. 38 (10) (2021) 1712–1722.
[56]
W. Gao, et al., The dark side of ubiquitous connectivity in smartphone-based SNS: an integrated model from information perspective, Comput. Hum. Behav. 84 (2018) 185–193.
[57]
P.B. Lowry, J. Cao, A. Everard, Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: the case of instant messaging in two cultures, J. Manag. Inf. Syst. 27 (4) (2011) 163–200.
[58]
A. Burns, et al., Examining the relationship of organizational insiders' psychological capital with information security threat and coping appraisals, Comput. Hum. Behav. 68 (2017) 190–209.
[59]
E. Ghazali, et al., Constructing online switching barriers: examining the effects of switching costs and alternative attractiveness on e-store loyalty in online pure-play retailers, Electron. Mark. 26 (2) (2016) 157–171.
[60]
Y.H. Chen, C.J. Keng, Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platform, Internet Res. (2018).
[61]
L. Xue, G. Ray, A.B. Whinston, Strategic investment in switching cost: an integrated customer acquisition and retention perspective, Int. J. Electron. Commer. 11 (1) (2006) 7–35.
[62]
W. Samuelson, R. Zeckhauser, Status quo bias in decision making, J. Risk Uncertain. 1 (1) (1988) 7–59.
[63]
Y. Huang, W. Miao, Re-domesticating social media when it becomes disruptive: evidence from China's “super app” WeChat, Mob. Media Commun. 9 (2) (2021) 177–194.
[64]
CNNIC. (2021). The 48th China Statistical Report on Internet development http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202109/t20210915_71543.htm, Accessed December 15, 2021.
[65]
W.T. Bielby, R.M. Hauser, Structural equation models, Annu. Rev. Sociol. 3 (1) (1977) 137–161.
[66]
Hair Jr, J.F., et al., A primer on partial least squares structural equation modeling (PLS-SEM), (2021).
[67]
A.S. Putra, et al., Leadership in the Innovation Era: transactional or Transformational Style?, Int. J. Social Manag. Stud. 1 (1) (2020) 89–94.
[68]
J.C. Anderson, D.W. Gerbing, Structural equation modeling in practice: a review and recommended two-step approach, Psychol. Bull. 103 (3) (1988) 411.
[69]
S. Petter, D. Straub, A. Rai, Specifying formative constructs in information systems research, MIS Quarterly 31 (4) (2007) 623–656.
[70]
D. Gefen, D. Straub, A practical guide to factorial validity using PLS-Graph: tutorial and annotated example, Commun. Assoc. Inf. Syst. 16 (1) (2005) 5.
[71]
S. Petter, D. Straub, A. Rai, Specifying formative constructs in information systems research, MIS Quarterly (2007) 623–656.
[72]
N.P. Podsakoff, Common method biases in behavioral research: a critical review of the literature and recommended remedies, J. Appl. Psychol. 885 (879) (2003) 10–1037.
[73]
M.K. Lindell, D.J. Whitney, Accounting for common method variance in cross-sectional research designs, J. Appl. Psychol. 86 (1) (2001) 114.
[74]
Collier, J.E., Applied structural equation modeling using AMOS: basic to advanced techniques: routledge, 2020.
[75]
M. Wetzels, G. Odekerken-Schröder, C. Van Oppen, Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration, MIS Quarterly 33 (1) (2009) 177–195.
[76]
K.K.-K. Wong, Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS, Mark. Bull. 24 (1) (2013) 1–32.
[77]
C. Nitzl, J.L. Roldan, G. Cepeda, Mediation analysis in partial least squares path modeling: helping researchers discuss more sophisticated models, Ind. Manage. Data Syst. 116 (9) (2016) 1849–1864.
[78]
X. Zhao, J.G. Lynch Jr, Q. Chen, Reconsidering Baron and Kenny: myths and truths about mediation analysis, J. Consum. Res. 37 (2) (2010) 197–206.
[79]
C.C. Ragin, The Comparative method: Moving beyond Qualitative and Quantitative Strategies, University of California Press, 1987.
[80]
C.C. Ragin, The Comparative Method, University of California Press, 2014.
[81]
I.O. Pappas, et al., The interplay of online shopping motivations and experiential factors on personalized e-commerce: a complexity theory approach, Telemat. Inform. 34 (5) (2017) 730–742.
[82]
C.Q. Schneider, C. Wagemann, Standards of good practice in qualitative comparative analysis (QCA) and fuzzy-sets, Comp. Sociol. 9 (3) (2010) 397–418.
[83]
P.C. Fiss, Building better causal theories: a fuzzy set approach to typologies in organization research, Acad. Manage. J. 54 (2) (2011) 393–420.
[84]
J. Choi, J. Jung, S.W. Lee, What causes users to switch from a local to a global social network site? The cultural, social, economic, and motivational factors of Facebook's globalization, Comput. Hum. Behav. 29 (6) (2013) 2665–2673.
[85]
A.G. Sutcliffe, J.F. Binder, R.I.M. Dunbar, Activity in social media and intimacy in social relationships, Comput. Hum. Behav. 85 (2018) 227–235.
[86]
S.A. Zahra, Contextualizing theory building in entrepreneurship research, J. Bus. Venturing. 22 (3) (2007) 443–452.
[87]
W. Hong, F.K. Chan, J.Y. Thong, L.C. Chasalow, G. Dhillon, A framework and guidelines for context-specific theorizing in information systems research, Inf. Syst. Res. 25 (1) (2014) 111–136.
Recommendations
Twitter intermittent and permanent discontinuance: A multi-method approach to study innovation diffusion
AbstractEarly studies tend to follow a simple, generic approach to define intermittent discontinuance and permanent discontinuance without considering the unique life cycle, turnover rate, and user base of one innovation. This study uses a multi-method ...
Highlights- An expanded methodological repertoire of diffusion study with trace and survey data.
- Introduces an innovation-specific benchmark to define adopters and discontinuers.
- Permanent discontinuers report lower levels of Twitter ...
An empirical study of brand microblog users’ unfollowing motivations: The perspective of push-pull-mooring model
Highlights- Dissatisfaction with information quality shows a positive influence on unfollowing intention.
AbstractBrand microblogs (BMs) have been increasingly utilized by companies to facilitate communication and foster deeper relationships with their customers. In addition to attracting new followers, retaining existing followers is equally, if ...
Understanding the effects of eWOM social ties on purchase intentions: A moderated mediation investigation
Highlights- Strong-tie eWOM and weak-tie eWOM both facilitate consumer purchase intentions.
AbstractElectronic word-of-mouth (eWOM) social ties have been well recognized to exert influence on consumer decision making. However, the underlying mechanism through which eWOM social ties impart influence remains unclear. ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2023.
Publisher
Elsevier Science Publishers B. V.
Netherlands
Publication History
Published: 14 March 2024
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Jan 2025