The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.
Shackled to the Status Quo: The Inhibiting Effects of Incumbent System Habit, Switching Costs, and Inertia on New System Acceptance
Abstract
Given that adoption of a new system often implies fully or partly replacing an incumbent system, resistance is often manifested as failure of a user to switch from an incumbent technology to a newly introduced one. Thus, a potential source of resistance to adopting a new system lies in the use of an incumbent system. Using the status quo bias and habit literatures as theoretical lenses, the study explains how use of an incumbent system negatively impacts new system perceptions and usage intentions. We argue that habitual use of an incumbent system, rationalization due to perceived transition costs, and psychological commitment due to perceived sunk costs all encourage development of inertia. Inertia in turn fully mediates the impact of these incumbent system constructs on constructs related to acceptance of the new system via psychological commitment based on cognitive consistency and by increasing the importance of normative pressures. Specifically, we hypothesize that inertia leads to decreased perceptions of the ease of use and relative advantage of a newly introduced system and has a negative impact on intentions to use the new system, above and beyond its impact through perceptions. Finally, we hypothesize that inertia moderates the relationship between subjective norm and intention, such that normative pressures to use a new system become more important in the presence of inertia. Empirical results largely support the hypothesized relationships showing the inhibiting effect of incumbent-system habit, transition and sunk costs, and inertia on acceptance of a new system. Our study thus extends theoretical understanding of the role of incumbent system constructs such as habit and inertia in technology acceptance, and lays the foundations for further study of the interplay between perceptions and cognition with respect to the incumbent system and those with respect to a new system.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Compared with the decision to retain a premium subscription, the decision to upgrade represents a departure from the users' status quo”
From What drives subscribing to premium in freemium services? A consumer value‐based view of differences between upgrading to and staying with premium (2020) · cites this paper as Polites & Karahanna, 2012
In the citing paper
“While the intention to retain the premium subscription essentially means continuance of an existing behavior, the intention to upgrade from free to the premium subscription means a departure from the user's status quo (Kim & Kankanhalli, 2009;Polites & Karahanna, 2012).”
From What drives subscribing to premium in freemium services? A consumer value‐based view of differences between upgrading to and staying with premium (2020) · cites this paper as Polites & Karahanna, 2012
In the citing paper
“Moreover, inertia can be divided into two distinct measures: first, cognitive inertia and second, affective inertia (Greenfield 2005; Polites and Karahanna 2012).”
From Health insurance policy renewal: an exploration of reputation, performance, and affect to understand customer inertia (2022) · cites this paper as Polites and Karahanna 2012
Citations
Cites
The publisher hasn’t deposited this paper’s reference list.
Cited by
Sorted by citations
Items 101–200 of 896
Explaining resistance to system usage in the PharmaCloud: A view of the dual-factor model
Hsieh, P.-J., & Lin, W.-S. (2017) · Information & Management · doi:10.1016/j.im.2017.03.008 · Cited by 98
“Prior research has explicitly used the SQB perspective to explain the inhibiting effect of switching costs on user resistance to a new system [10,34,36].”
BackgroundMethodResultInfluentialLee, K., Lee, K. Y., & Sheehan, L. (2020) · Information Systems Frontiers · doi:10.1007/s10796-019-09975-1 · Cited by 95
“On the flip side, the habit of using one system (i.e., email) hindered the acceptance of an alternative system (i.e., Google Docs) by increasing the inertia which reduces the sensitivity to advantage and easiness of the alternative system (Polites and Karahanna 2012).”
BackgroundWang, J., Zheng, B., Liu, H., & Yu, L. (2020) · Information Technology and People · doi:10.1108/itp-10-2018-0483 · Cited by 95
Lee, K., & Joshi, K. (2017) · Information Systems Journal · doi:10.1111/isj.12118 · Cited by 94
“Based on our view, Polites & Karahanna (2012) can be the only study that investigated the role of sunk costs independent from that of transition costs based on SQBP.”
BackgroundMethodInfluentialZarifis, A., & Cheng, X. (2022) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2022.100739 · Cited by 93
IT Feature Use over Time and its Impact on Individual Task Performance
Benlian, A. (2015) · Journal of the Association for Information Systems · doi:10.17705/1jais.00391 · Cited by 93
“…at pre- or post-adoption stages of IT use), with much of the emphasis being on IT resistance (e.g., Kim & Kankanhalli, 2009), habitual IT use (e.g., Polites & Karahanna, 2012; Limayem, Hirt, & Cheung, 2007) and inhibitors of IT use (e.g., Cenfetelli & Schwarz, 2011), we have little understanding…”
BackgroundHajiheydari, N., Delgosha, M. S., & Olya, H. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120807 · Cited by 92
Vaghefi, I., Qahri‐Saremi, H., & Turel, O. (2020) · Internet Research · doi:10.1108/intr-10-2019-0418 · Cited by 92
The reasons why elderly mobile users adopt ubiquitous mobile social service
Yang, H., & Lin, S.-L. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.12.005 · Cited by 90
Hsieh, P.-J. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121074 · Cited by 88
Determinants of switching intention from web-based stores to retail apps: Habit as a moderator
Iranmanesh, M., Min, C. L., Senali, M. G., Nikbin, D., & Foroughi, B. (2022) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2022.102957 · Cited by 88
Malodia, S., Kaur, P., Ractham, P., Sakashita, M., & Dhir, A. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.03.045 · Cited by 88
Business value of SME digitalisation: when does it pay off more?
Fabian, N. E., Dong, J. Q., Broekhuizen, T., & Verhoef, P. C. (2023) · European Journal of Information Systems · doi:10.1080/0960085x.2023.2167671 · Cited by 88
“…2013; Luo et al., 2012; Proksch et al., 2021; Vial, 2019), and organisational rigidity —that is, an SME’s organisational barrier that reflects the firm’s inability to adapt and innovate (Chan et al., 2019; Fan et al., 2020; Gilbert, 2005; Lucas & Goh, 2009; Polites & Karahanna, 2012; Vial, 2019).”
BackgroundNegative outcomes of ICT use at work: meta-analytic evidence and the role of job autonomy
Karimikia, H., Singh, H., & Joseph, D. (2020) · Internet Research · doi:10.1108/intr-09-2019-0385 · Cited by 85
Extending a TAM–TTF model with perceptions toward telematics adoption
Chen, N. (2019) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-02-2018-0074 · Cited by 80
Liu, L., Liu, R., Lee, M., & Chen, J. (2019) · Internet Research · doi:10.1108/intr-05-2017-0177 · Cited by 80
Exploring factors affecting social e-commerce service adoption: The case of Facebook Gifts
Mamonov, S., & Benbunan‐Fich, R. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.05.005 · Cited by 79
“The effects may be nonlinear (Titah & Barki, 2009) and social inertia can also inhibit technology adoption (Polites & Karahanna, 2012).”
BackgroundModern-day hoarding: A model for understanding and measuring digital hoarding
Sedera, D., Lokuge, S., & Grover, V. (2022) · Information & Management · doi:10.1016/j.im.2022.103700 · Cited by 78
“The PLS-SEM method is well suited for analyzing complex models, which supports the mapping of formative observed variables [87].”
Henderson, C. M., Steinhoff, L., Harmeling, C. M., & Palmatier, R. W. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00744-0 · Cited by 76
“We theoretically justify two distinct behavioral sources, consistency and magnitude of prior consumption (Bolton et al. 2004; Burnham et al. 2003; Polites and Karahanna 2012).”
BackgroundMethodInfluentialYang, H., Zhang, S., Diao, Z., & Sun, D. (2023) · Telematics and Informatics · doi:10.1016/j.tele.2023.102050 · Cited by 76
Jalo, H., & Pirkkalainen, H. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102731 · Cited by 76
“…’ tendency to favor the status quo (Kim & Kankanhalli, 2009; Talke & Heidenreich, 2014), continued use of previous systems due to inertia (Polites & Karahanna, 2012), technology anxiety (Tsai et al., 2019), colleagues ’ attitudes toward the new technology (Kim & Kankanhalli, 2009), and…”
BackgroundWhy do you keep doing that? The biasing effects of mental states on IT continued usage intentions
Steelman, Z. R., & Soror, A. A. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.027 · Cited by 75
“Similarly, even in the case of utilitarian systems, a psychological attachment to the existing system negatively biases the cognitive evaluation of the relative advantage and ease of use of future and alternative system implementations (Polites and Karahanna 2012).”
BackgroundA Dynamic Model of Embeddedness in Digital Infrastructures
Fürstenau, D., Baiyere, A., & Kliewer, N. (2019) · Information Systems Research · doi:10.1287/isre.2019.0864 · Cited by 75
“As part of alternative views on embeddedness, individual users ’ habitual behavior and resistance have been discussed as sources of inertia in the event of replacing information systems (Ciborra and Failla 2000, Eriksson and ˆ Agerfalk 2010, Polites and Karahanna 2012).”
BackgroundResultShankar, A., & Kumari, P. (2019) · International Journal of Nonprofit and Voluntary Sector Marketing · doi:10.1002/nvsm.1662 · Cited by 74
Unlearning Troubled Business Models: From Realization to Marginalization
Mehrizi, M. H. R., & Lashkarbolouki, M. (2016) · Long Range Planning · doi:10.1016/j.lrp.2015.12.005 · Cited by 74
Music as a Service as an Alternative to Music Piracy?
Dörr, J., Wagner, T. M., Benlian, A., & Heß, T. (2013) · Business & Information Systems Engineering · doi:10.1007/s12599-013-0294-0 · Cited by 73
“To date, acceptance studies have solely focused on the intention to use a new service or product, while ignoring other services or products being used by customers (Polites and Karahanna 2012).”
BackgroundMethodTechnology renewal, user resistance, user adoption: status quo bias theory revisited
Shirish, A., & Batuekueno, L. (2021) · Journal of Organizational Change Management · doi:10.1108/jocm-10-2020-0332 · Cited by 72
Online determinants of e-customer satisfaction: application to website purchases in tourism
Pereira, H. G., Salgueiro, M. D. F., & Rita, P. (2016) · Service Business · doi:10.1007/s11628-016-0313-6 · Cited by 72
Investigating switching intention of e-commerce live streaming users
Ye, D., Liu, F., Cho, D., & Jia, Z. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e11145 · Cited by 71
“They describe inertia as users who always utilize the same social media service (Polites and Karahanna, 2012).”
BackgroundMethodLadders to m-commerce resistance: A qualitative means-end approach
Heinze, J., Thomann, M., & Fischer, P. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.059 · Cited by 70
Technology Acceptance Model And The Unified Theory Of Acceptance And Use Of Technology
Venkatesh, V. (2015) · Wiley eBooks · doi:10.1002/9781118785317.weom070047 · Cited by 69
Joerß, T., Hoffmann, S., Mai, R., & Akbar, P. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.02.019 · Cited by 68
Talukder, M. S., Laato, S., Islam, A. K. M. N., & Bao, Y. (2021) · Internet Research · doi:10.1108/intr-10-2020-0586 · Cited by 67
Bölen, M. C. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101439 · Cited by 67
Digital transformation in supply chains: Current applications, contributions and challenges
Özkanlısoy, Ö., & Akkartal, E. (2021) · Business And Management Studies An International Journal · doi:10.15295/bmij.v9i1.1673 · Cited by 65
Liang, H., Wang, N., & Xue, Y. (2022) · Information Systems Research · doi:10.1287/isre.2022.1105 · Cited by 65
Loh, X.-M., Lee, V., Leong, L.-Y., Aw, E. C., Cham, T., Tang, Y.-C., & Hew, J.-J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113726 · Cited by 65
Shi, X., Lin, Z., Liu, J., & Hui, Y. K. (2018) · Information & Management · doi:10.1016/j.im.2018.03.013 · Cited by 65
“Status quo bias is usually shown in the form cognitive lock-in and deliberate inertia – the persistence of an existing behavioral pattern [72].”
BackgroundMethodInfluentialDogra, N., Bakshi, S., & Gupta, A. (2022) · Journal of Asia Business Studies · doi:10.1108/jabs-02-2021-0066 · Cited by 64
Trust Change in Information Technology Products
McKnight, D. H., Liu, P., & Pentland, B. T. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1831772 · Cited by 64
Liu, Z., Wang, X., Min, Q., & Li, W. (2018) · Information Systems Journal · doi:10.1111/isj.12195 · Cited by 62
“Under low‐effort processing, information is evaluated by relatively automatic heuristics and mental shortcuts (Polites & Karahanna, 2012, 2013).”
MethodHur, J.-Y., Cho, W., Lee, G., & Bickerton, S. H. (2019) · Asian Studies Review · doi:10.1080/10357823.2019.1663786 · Cited by 62
“That is, organisational inertia refers to the inability to enact necessary internal change in response to signi fi cant external change (Polites & Karahanna, 2012).”
BackgroundExplaining resistance intention towards mobile HRM application: the dark side of technology adoption
Shankar, A., & Nigam, A. (2021) · International Journal of Manpower · doi:10.1108/ijm-03-2021-0198 · Cited by 60
Zeng, Z., Li, S., Lian, J.-W., Li, J., Chen, T., & Li, Y. (2021) · Land Use Policy · doi:10.1016/j.landusepol.2021.105629 · Cited by 60
Tams, S. (2022) · MIS Quarterly · doi:10.25300/misq/2022/16359 · Cited by 59
Nel, J., & Boshoff, C. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.12.003 · Cited by 59
Avoiding Trouble: Exploring Environmental Risk Information Avoidance Intentions.
Kahlor, L. A., Olson, H. C., Markman, A. B., & Wang, W. (2018) · Environment and Behavior · doi:10.1177/0013916518799149 · Cited by 59
“RIA is distinct from inertia, which refers to a lack of action to support the status quo (Polites & Karahanna, 2012).”
BackgroundStatus-quo satisfaction and smartwatch adoption: a multi-group analysis
Ghazali, E. M., Mutum, D. S., Pua, M. H.-J., & Ramayah, T. (2020) · Industrial Management & Data Systems · doi:10.1108/imds-10-2019-0576 · Cited by 59
Private land conservation decision-making: An integrative social science model
Epanchin‐Niell, R. S., Jackson‐Smith, D. B., Wilson, R. S., Ashenfarb, M., Dayer, A. A., Hillis, V., Iacona, G. D., Markowitz, E. M., Marquart‐Pyatt, S. T., & Treakle, T. C. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113961 · Cited by 59
Exploring factors influencing educators’ adoption of ChatGPT: a mixed method approach
Hidayat-ur-Rehman, I., & Ibrahim, Y. (2023) · Interactive Technology and Smart Education · doi:10.1108/itse-07-2023-0127 · Cited by 59
Awuah, B., Onumah, J. M., & Duho, K. C. T. (2021) · The Electronic Journal of Information Systems in Developing Countries · doi:10.1002/isd2.12203 · Cited by 59
“These include innovation diffusion theory (IDT), theory of reasoned action, theory of planned behavior, technology acceptance model (TAM), and diffusion of innovation (DOI) model, among others (Rad et al., 2018; Sadoughi et al., 2019; Sharma et al., 2021). Yet, some of these theories are more appropriate at the indivi…”
BackgroundMethodInvoluntary migration in cyberspaces: The case of MSN messenger discontinuation
Fang, Y., & Tang, K. (2016) · Telematics and Informatics · doi:10.1016/j.tele.2016.05.004 · Cited by 58
“Setup cost consistently has been acknowledged in the preceding migration literature as a key component of switching cost and is linked to migration intention (e.g. Bhattacherjee and Park (2013), Polites and Karahanna (2012)).”
BackgroundCapturing Value in Platform Business Models That Rely on User-Generated Content
Subramanian, H., Mitra, S., & Ransbotham, S. (2021) · Organization Science · doi:10.1287/orsc.2020.1408 · Cited by 58
Traditional-bank customers' digital-only bank resistance: evidence from South Africa
Nel, J., & Boshoff, C. (2021) · International Journal of Bank Marketing · doi:10.1108/ijbm-07-2020-0380 · Cited by 58
Shiu, J. Y. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102547 · Cited by 57
Silić, M. (2018) · Computers & Security · doi:10.1016/j.cose.2018.09.012 · Cited by 56
Polites, G. L., Serrano, C. I., Thatcher, J. B., & Matthews, K. D. (2018) · European Journal of Information Systems · doi:10.1080/0960085x.2018.1457194 · Cited by 56
“To avoid respondent fatigue, we measured habit using a short form measure based on Polites and Karahanna (2012) and Limayem et al. (2007).”
Self-citationStatus quo bias and shoppers’ mobile website purchasing resistance
Nel, J., & Boshoff, C. (2020) · European Journal of Marketing · doi:10.1108/ejm-02-2018-0144 · Cited by 56
Gan, C., Li, H., & Liu, Y. (2023) · Information Technology and People · doi:10.1108/itp-05-2022-0403 · Cited by 56
Trial-Period Technostress: A Conceptual Definition and Mixed-Methods Investigation
Maier, C., Laumer, S., Thatcher, J. B., Wirth, J., & Weitzel, T. (2022) · Information Systems Research · doi:10.1287/isre.2021.1047 · Cited by 56
Miremadi, I., Khoshbash, M., & Saeedian, M. (2023) · Research Policy · doi:10.1016/j.respol.2023.104781 · Cited by 55
Kim, D., & Lee, H. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.04.011 · Cited by 55
Early Changes in Billing and Notes After Evaluation and Management Guideline Change
Apathy, N. C., Hare, A. J., Fendrich, S. J., & Cross, D. A. (2022) · Annals of Internal Medicine · doi:10.7326/m21-4402 · Cited by 54
“Incorporating changes that reduce the time and burden associated with provider documentation will likely require additional time, planning, organizational commitment, and technical support to implement and sustain (30).”
BackgroundInbound open innovation and radical innovation capability
Shi, X., & Zhang, Q. (2018) · Journal of Organizational Change Management · doi:10.1108/jocm-07-2017-0262 · Cited by 54
Social network migration and anonymity expectations: What anonymous social network apps offer
Gerhart, N., & Koohikamali, M. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.01.030 · Cited by 53
On-demand service platforms pro/anti adoption cognition: Examining the context-specific reasons
Delgosha, M. S., & Hajiheydari, N. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.031 · Cited by 53
Chen, L., Hsieh, J. J. P.-A., & Rai, A. (2022) · Information Systems Research · doi:10.1287/isre.2021.1097 · Cited by 53
Unraveling Human-AI Teaming: A Review and OutlookPreprint
Lou, B., Lu, T., Raghu, T. S., & Zhang, Y. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5211067 · Cited by 52
The distinct roles of dedication-based and constraint-based mechanisms in social networking sites
Kim, B., & Min, J. (2015) · Internet Research · doi:10.1108/intr-11-2013-0253 · Cited by 52
Formation and Effect of Social Media Usage Habit
Hu, T. “., Stafford, T. F., Kettinger, W. J., Zhang, X. “., & Dai, H. (2017) · Journal of Computer Information Systems · doi:10.1080/08874417.2016.1261378 · Cited by 52
“Despite insights on the nature of IS habit (e.g., [15, 22, 30]), the context-specific and theory-driven investigations in this direction are still rare [27].”
BackgroundA dedication-constraint model of consumer switching behavior in mobile payment applications
Gong, X., Liu, X., & Xiao, Z. (2022) · Information & Management · doi:10.1016/j.im.2022.103640 · Cited by 52
Understanding dark side of online community engagement: an innovation resistance theory perspective
Kumar, A., Shankar, A., Tiwari, A. K., & Hong, H. (2023) · Information Systems and e-Business Management · doi:10.1007/s10257-023-00633-3 · Cited by 51
“Performance barrier raises the expectation of adverse outcomes, resulting in an unfavorable attitude and negatively influencing the user’s desire to use the new technology (Khanra et al. 2021; Polites and Karahanna 2012; Benlian and Hess 2011).”
Liu, Z., Zhao, Y., Chen, S., Song, S., Hansen, P., & Zhu, Q. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2020.102396 · Cited by 51
Nugraha, K., Arief, M., Abdinagoro, S. B., & Heriyati, P. (2022) · Sustainability · doi:10.3390/su141912506 · Cited by 51
Compulsive technology use: Compulsive use of mobile applications
Clements, J. A., & Boyle, R. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.05.018 · Cited by 50
Xiang, K., Xu, C., & Wang, J. (2021) · Psychology Research and Behavior Management · doi:10.2147/prbm.s303239 · Cited by 50
“Psychological transformation costs and fixed consumption have a negative impact on the substitution of willingness to consume tourism.(48,49) To ensure the accuracy of the model and hypothesis construction, two mediating variables were introduced into this study: crisis and safety risk perception and sustainable consu…”
BackgroundSave Face or Save Life: Physicians’ Dilemma in Using Clinical Decision Support Systems
Liang, H., & Xue, Y. (2021) · Information Systems Research · doi:10.1287/isre.2021.1082 · Cited by 50
Tsai, P., & Tang, J. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103535 · Cited by 50
You, Y., He, Y., Chen, Q., & Hu, M. (2020) · Information & Management · doi:10.1016/j.im.2020.103410 · Cited by 50
Oschinsky, F. M., Stelter, A., & Niehaves, B. (2021) · Government Information Quarterly · doi:10.1016/j.giq.2021.101611 · Cited by 50
Fit for purpose: engineering principles for selecting an appropriate type of data exchange standard
Rosenthal, A. S., Seligman, L., Allen, M. D., Chapman, A. P., & Zhu, H. (2014) · Information Systems and e-Business Management · doi:10.1007/s10257-014-0238-3 · Cited by 49
“Finally, it is usually hard to trade political versus technical costs, and the interactions between technology and politics can take a long time to diagnose (Markus 1983; Polites and Karahanna 2012).”
BackgroundPark, M., Jun, J., & Park, H. (2017) · Quality Innovation Prosperity · doi:10.12776/qip.v21i3.983 · Cited by 48
Why discontinue Facebook usage? An empirical investigation based on a push–pull–mooring framework
Fu, S., Li, H., & Liu, Y. (2021) · Industrial Management & Data Systems · doi:10.1108/imds-12-2020-0709 · Cited by 48
“Inertia when using social media ensures that users attach and adhere to current social media usage patterns, even if they are unsatisfied with the social media platform and/or if better alternatives exist to which they could change (Polites and Karahanna, 2012).”
BackgroundKim, B., Kang, M., & Jo, H. (2014) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2014.888501 · Cited by 47
“Polites and Karahanna (2012) observed that habitual IS users do not generally reevaluate their behavior; rather, they simply continue with their existing behavioral pattern.”
BackgroundHo, K. Y., Ke, W., Liu, H., & Chau, P. Y. K. (2020) · MIS Quarterly · doi:10.25300/misq/2020/14246 · Cited by 46
Interrogating and redefining the concept of consumer inertia
Cui, R., Xin, S., & Li, Z. (2020) · Journal of Consumer Behaviour · doi:10.1002/cb.1849 · Cited by 46
Determinants of dynamic process of emerging ICT adoption in SMEs – actor network theory perspective
Eze, S. C., Chinedu-Eze, V. C., & Bello, A. O. (2018) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-02-2018-0019 · Cited by 45
“It was further revealed by previous studies that if these new applications can be easily understood and used regardless of the skills acquired, it will be adopted (Chau, 1996; Hong et al. , 2011; Awa et al. , 2012; Polites and Karahanna, 2012).”
BackgroundWhy do consumers continue to use OTT services?
Yoon, J., & Kim, H. (2023) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2023.101285 · Cited by 45
Intensifying to Cease: Unpacking the Process of Information Systems Discontinuance1
Mehrizi, M. H. R., Modol, J. R., & Nezhad, M. Z. (2019) · MIS Quarterly · doi:10.25300/misq/2019/13717 · Cited by 44
Li, A., Sun, Y., Guo, X., Guo, F., & Guo, J. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2020.102458 · Cited by 44
Investigating senders’ switching intention to smart lockers: An extension of push-pull-mooring model
Chen, L., Wu, P., Dou, Y., & Wu, Y. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103414 · Cited by 44
Zamani, E. D., & Pouloudi, A. (2020) · Information Systems Journal · doi:10.1111/isj.12315 · Cited by 44
“Therefore switching to something more appealing is easier, less risky and with lower switching costs overall (Polites & Karahanna, 2012).”
BackgroundFox, G., Mooney, J. G., Rosati, P., & Lynn, T. (2021) · Agriculture · doi:10.3390/agriculture11121283 · Cited by 44
“This has resulted in a shift in focus towards understanding individuals’ behaviors after the initial adoption of a new technology, often with an emphasis on understanding why individuals discontinue use [20,21].”
BackgroundCheon, Y., Choi, S. K., Kim, J., & Kwak, K. T. (2014) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2014.05.002 · Cited by 43
Facilitator and inhibitor factors: Adopting e-government in a dual model
Rey‐Moreno, M., Felício, J. A., Molina, C. M., & Moreno, R. R. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2017.11.015 · Cited by 43
Soliman, W., & Tuunainen, V. K. (2021) · Information Systems Journal · doi:10.1111/isj.12355 · Cited by 43
“…dependent variable is captured either quantitatively , typically measured on an 1-to-7 scale, such as discontinuance intentions, switching intentions, and so on (e.g., Polites & Karahanna, 2012), or qualitatively , as a binary decision, such as reject, quit, unadopt, and so on (e.g., Goode, 2005).”
BackgroundChawla, U., Verma, B., & Mittal, A. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102482 · Cited by 42
Should I adopt an integrated virtual clinic? A dual‐factor theory perspective
Shankar, A., Kumar, A., Yadav, R., Misra, P., & Pani, S. K. (2023) · Journal of Consumer Behaviour · doi:10.1002/cb.2202 · Cited by 42
Soror, A. A., Steelman, Z. R., & Turel, O. (2021) · Information Technology and People · doi:10.1108/itp-11-2019-0603 · Cited by 42
Inan, D. I., Hidayanto, A. N., Juita, R., Andiyani, K., Hariyana, N., Tiffany, P., Pertiwi, T. P. T., & Kurnia, S. (2022) · Case Studies on Transport Policy · doi:10.1016/j.cstp.2022.05.017 · Cited by 42
Metadata
- Authors
- Polites, G. L., & Karahanna, E.
- Affiliations
- Bucknell University (US)
- University of Georgia (US)
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2012-03-01
- Volume
- 36
- Issue
- 1
- Pages
- 21-42
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W4401611614
- Cited by
- 215
- References
- 0
- Citations by year
- 2026: 27 · 2025: 56 · 2024: 27 · 2023: 26 · 2022: 11 · 2021: 16 · 2020: 9 · 2019: 12 · 2018: 10 · 2017: 8 · 2016: 3 · 2015: 3 · 2013: 4 · 2012: 1
- FWCI
- 5.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- MIS Quarterly (publishedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Keywords
- technology adoption, status quo bias, habit, inertia, switching costs, sunk costs, resistance to change, technology acceptance, perceived ease of use, relative advantage, intention to use, subjective norms, normative pressure, cognitive consistency, psychological commitment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review