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Journal articles on the topic 'User resistance'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Kim, Hee-Woong, Hock Chuan Chan, and So-Hyun Lee. "User Resistance to Software Migration." Journal of Database Management 25, no. 1 (January 2014): 59–79. http://dx.doi.org/10.4018/jdm.2014010103.

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The demand for software has increased rapidly in the global industrial environment. Open source software (OSS) has exerted significant impact on the software industry. Large amounts of resources and effort have been devoted to the development of OSS such as Linux. Based on the technology adoption model (TAM), the development of Linux as the most well-known OSS with a graphical user interface designed for ease of use and a wide range of functionalities is expected to result in high levels of Linux adoption by individual users. Linux, however, currently controls about 1% of the operating system market for personal computers. The resistance of users to switch to a new operating system remains one of the major obstacles to widespread adoption of Linux among individual users. Based on the integration of the equity implementation model and the TAM, this study examines the formation of user resistance, as well as the effects of user resistance, on the migration to Linux for personal computers. This study discusses the role and effect of user resistance based on the equity implementation model in comparison with the two main determinants in the TAM. This study contributes to the advancement of theoretical understanding of Linux migration and user resistance. The findings also offer suggestions for software communities and practitioners, of OSS in particular, to promote the use of new software by individual users.

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2

Kim, Kyoung-June, and Ki-Dong Lee. "The Effect of Technostress on User Resistance and End-User Performance." Information Systems Review 19, no. 4 (December 31, 2017): 63–85. http://dx.doi.org/10.14329/isr.2017.19.4.063.

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3

Selander, Lisen, and Ola Henfridsson. "Cynicism as user resistance in IT implementation." Information Systems Journal 22, no. 4 (September 23, 2011): 289–312. http://dx.doi.org/10.1111/j.1365-2575.2011.00386.x.

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4

Ali, Mahmood, Li Zhou, Lloyd Miller, and Petros Ieromonachou. "User resistance in IT: A literature review." International Journal of Information Management 36, no. 1 (February 2016): 35–43. http://dx.doi.org/10.1016/j.ijinfomgt.2015.09.007.

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5

Pambudi, Pandu Dwi Luhur. "Analysis of User Resistance Towards Adopting E-Office: A Case from A Governmental Organization." Indonesian Scholars Scientific Summit Taiwan Proceeding 3 (July 7, 2021): 1–7. http://dx.doi.org/10.52162/3.2021105.

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The advancement in information technology is accelerating, affecting many industries. Government entities are one of the industries that have been affected. They adopt information technology (IT) to replace disorganized traditional business processes. This study observes that the IT innovation adoption in an organization will lead to some resistance. We bring a case of IT adoption to replace one part of a manual business process (letter management system) into a digitalized system called E-office in one of Indonesia’s governmental organizations. The adoption of IT causes some resistance within the organization, which motivates us to identify resistances before and during the adoption. We interview a team who oversees handling E-office implementation and discovered two types of resistances in technology adoption: delaying resistances and opposition resistances. Meanwhile, there are two types of behavioral resistances: reluctant compliance resistance and misguided application resistance. This research further provides details on the approaches used by the organization to mitigate resistances before and during the adoption of the E-office project's implementation.

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Daud Norzaidi, Mohd, Siong Choy Chong, and Mohamed Intan Salwani. "Perceived resistance, user resistance and managers' performance in the Malaysian port industry." Aslib Proceedings 60, no. 3 (May 23, 2008): 242–64. http://dx.doi.org/10.1108/00012530810879114.

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7

Muqtadiroh, Feby Artwodini, Amna Shifia Nisafani, Regina Mia Saraswati, and Anisah Herdiyanti. "Analysis of User Resistance Towards Adopting E-Learning." Procedia Computer Science 161 (2019): 123–32. http://dx.doi.org/10.1016/j.procs.2019.11.107.

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8

Haddara, Moutaz, and Henrik Moen. "User resistance in ERP implementations: A literature review." Procedia Computer Science 121 (2017): 859–65. http://dx.doi.org/10.1016/j.procs.2017.11.111.

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9

Hirschheim, R. "Information Systems and User Resistance: Theory and Practice." Computer Journal 31, no. 5 (May 1, 1988): 398–408. http://dx.doi.org/10.1093/comjnl/31.5.398.

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10

Kang, Yoolee, and Seongcheol Kim. "Understanding User Resistance to Participation in Multihop Communications." Journal of Computer-Mediated Communication 14, no. 2 (January 2009): 328–51. http://dx.doi.org/10.1111/j.1083-6101.2009.01443.x.

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11

Salmon, Stephen R. "User Resistance to Microforms in the Research Library." Preservation, Digital Technology & Culture 42, no. 4 (November 2013): 209–14. http://dx.doi.org/10.1515/pdtc-2013-0031.

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12

Liu, Shan, Yajun Zhang, Kaili Li, and Jing Tan. "Switching costs and benefits affect user resistance in project implementation: Roles of positive emotions and user traditionality." Social Behavior and Personality: an international journal 47, no. 7 (July 18, 2019): 1–10. http://dx.doi.org/10.2224/sbp.6908.

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In this study we investigated how perceived switching costs and benefits influence user resistance as a major cause of information systems project implementation failure, from the perspectives of individual emotions and traditional values. We used structural equation modeling and hierarchical regression analysis to analyze data from 256 potential users of a new information system. Participants were employed by a telecom operator in China. Results indicated that positive emotions played a partial mediating role in the relationship between perceived switching costs and benefits and user resistance. Further, user traditionality moderated the influence of perceived switching costs and benefits on user resistance. These findings have theoretical implications and we suggest practical ways in which managers can alleviate user resistance.

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13

Sung-Ho Jang and Lee Kidong. "Privacy risk of Social network service and User Resistance." E-Business Studies 15, no. 3 (June 2014): 321–34. http://dx.doi.org/10.15719/geba.15.3.201406.321.

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14

Koo, Chulmo, Namho Chung, and Juyeon Ham. "Assessing the User Resistance to Recommender Systems in Exhibition." Sustainability 9, no. 11 (November 7, 2017): 2041. http://dx.doi.org/10.3390/su9112041.

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15

Cheng, Shuang, Sang-Joon Lee, and Kyeong-Rak Lee. "A Study on Chinese User Resistance of Mobile Banking." Journal of Digital Policy and Management 12, no. 1 (January 28, 2014): 105–14. http://dx.doi.org/10.14400/jdpm.2014.12.1.105.

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16

Ngafeeson, Madison N., and Vishal Midha. "An exploratory study of user resistance in healthcare IT." International Journal of Electronic Finance 8, no. 1 (2014): 74. http://dx.doi.org/10.1504/ijef.2014.064003.

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17

Hollanek, Tomasz. "Non-user-friendly." A Peer-Reviewed Journal About 8, no. 1 (August 15, 2019): 184–93. http://dx.doi.org/10.7146/aprja.v8i1.115424.

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User-friendly design makes our use of emerging technologies intuitive and seamless, but it also conceals the new solutions’ influence over how we act, think and plan. In this paper, I analyze the logic of our newly developed ‘touchscreen sensibilities’ to speculate on alternative, ‘non-user-friendly’ design practices that, by invading intuitive interfaces, could make the users aware of their reliance on invisible algorithmic operations to learn and to feel. I revisit Žižek and Pfaller’s conception of ‘interpassivity’ to explore its potential as a means of resisting interactivity and inciting consciousness in contemporary speculative design. The critical interface I envision must defamiliarize consumption, prevent participation, and de-frame perception — make the user experience what lack of control feels like, and do so to encourage resistance.

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18

Lee, Aeri, Jaewon Choi, and Kyung Kyu Kim. "The Determinants of User Resistance to Adopting e-Books : Based on Innovation Characteristics and User Attitude." Journal of Society for e-Business Studies 17, no. 4 (November 30, 2012): 95–115. http://dx.doi.org/10.7838/jsebs.2012.17.4.095.

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19

Lee, Ae Ri, and Hyo Young Ahn. "Fintech Users' Information Privacy Concerns and User Resistance: Investigating the Interaction Effect with Regulatory Focus." Journal of the Korea Institute of Information Security and Cryptology 26, no. 1 (February 29, 2016): 209–26. http://dx.doi.org/10.13089/jkiisc.2016.26.1.209.

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20

Ritbumroong, Thanachart, Uthai Tanlamai, and Kamales Santivejkul. "User Resistance to IS Implementation in a Mandatory Use Environment." Change Management: An International Journal 12, no. 4 (2014): 45–60. http://dx.doi.org/10.18848/2327-798x/cgp/v12i04/50746.

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21

Klaus, Tim, J. Ellis Blanton, and Stephen C. Wingreen. "User Resistance Behaviors and Management Strategies in IT-Enabled Change." Journal of Organizational and End User Computing 27, no. 1 (January 2015): 57–76. http://dx.doi.org/10.4018/joeuc.2015010103.

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Information Technology (IT) is often used in organizations as a tool to enable change. However, as organizations switch to different vendors, upgrade their systems, or implement new systems, widespread user resistance is often encountered. Resistant behaviors often occur in these large-scale system implementations because the implementation transforms the jobs of employees and mandates system use. In order to understand resistant behaviors better as well as management strategies to minimize these behaviors, this study uses a focus group and qualitative semi-structured interviews. Based on the data collection, this study first creates a resistant behavior framework and a management strategy framework using a data-driven approach. The findings from the user resistance behaviors are classified into four categories. Also, eight preferred management strategies are identified by users, which are grouped into three categories. Then, the Framework-based Theory of User Resistance is proposed, which examines the causes and moderating forces that affect resistant behaviors. The practical implications of these frameworks also are described.

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22

Jiang, James J., Waleed A. Muhanna, and Gary Klein. "User resistance and strategies for promoting acceptance across system types." Information & Management 37, no. 1 (January 2000): 25–36. http://dx.doi.org/10.1016/s0378-7206(99)00032-4.

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23

Rivard and Lapointe. "Information Technology Implementers’ Responses to User Resistance: Nature and Effects." MIS Quarterly 36, no. 3 (2012): 897. http://dx.doi.org/10.2307/41703485.

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24

Kim, Junghwan, Seongcheol Kim, and Changi Nam. "User resistance to acceptance of In-Vehicle Infotainment (IVI) systems." Telecommunications Policy 40, no. 9 (September 2016): 919–30. http://dx.doi.org/10.1016/j.telpol.2016.07.006.

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25

Shang, Shari S. C. "Dual strategy for managing user resistance with business integration systems." Behaviour & Information Technology 31, no. 9 (September 2012): 909–25. http://dx.doi.org/10.1080/0144929x.2011.553744.

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26

Moran, Dominic. "Antimicrobial resistance in animal agriculture: understanding user attitudes and behaviours." Veterinary Record 181, no. 19 (November 10, 2017): 508–9. http://dx.doi.org/10.1136/vr.j5142.

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27

Saha, Saurav B., Vishwas Uttam, and Vivek Verma. "u-CARE: user-friendly Comprehensive Antibiotic resistance Repository ofEscherichia coli." Journal of Clinical Pathology 68, no. 8 (May 2, 2015): 648–51. http://dx.doi.org/10.1136/jclinpath-2015-202927.

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28

Zhang, Yajun, Peiran Gao, Junwei Zhang, and Lu Lu. "Effect of authoritarian leadership on user resistance to change: evidence from IS project implementation in China." Industrial Management & Data Systems 120, no. 10 (August 28, 2020): 1813–34. http://dx.doi.org/10.1108/imds-11-2019-0619.

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PurposeUser resistance to change has been identified as a significant cause of information system (IS) implementation failure. Previous studies have proposed antecedents of user resistance to change. However, whether project leadership (e.g. authoritarian leadership) can lead to user resistance to change remains unclear. By drawing on project leadership, affective event theory and contingency theory of leadership, the authors address this void by empirically examining whether authoritarian leadership can lead to user resistance to change through the mediation of negative emotion and whether the magnitude of this mediation depends on the power distance level.Design/methodology/approachThis study examines the authors’ research model that integrates authoritarian leadership, negative emotion, power distance and user resistance to change using data from a matched-pair survey of 278 users and their supervisors involved in IS project implementation in China.FindingsNegative emotion plays a mediating role in the relationship of authoritarian leadership and user resistance to change. In addition, power distance moderates the relationship between authoritarian leadership and negative emotion and the indirect effect of authoritarian leadership on user resistance to change in IS project implementation through negative emotion.Originality/valueThe authors’ research provides a comprehensive understanding of the antecedents of user resistance to change in IS project implementation and ultimately contributes to the IS project implementation literature and practice.

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29

Crewe, Albert V., Deborah L. Clayton, David A. Crewe, and Katarzyna Moscicka. "User-friendly field emission." Proceedings, annual meeting, Electron Microscopy Society of America 47 (August 6, 1989): 114–15. http://dx.doi.org/10.1017/s0424820100152549.

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We introduced the field emission source into electron microscopy twenty five years ago but in spite of the obvious advantages of such a source it was not an instant success. In fact it is only in recent years that the use of field emission has become significant, and even now it is only for high performance, high cost instruments.The reasons for customer resistance are not hard to find. Firs t there is the need for a UHV system, a necessity which brings with it a significant increase in cost and also the need for new expertise and training since UHV systems use different hardware and different maintenance procedures.Next there is the need for knowledge and experience with field emission and its peculiar characteristics. Tips need to be “flashed” and the operator needs to be able to recognize the symptoms which signal that need.

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30

Femdal, I., and I. R. Knutsen. "Dependence and resistance in community mental health care-Negotiations of user participation between staff and users." Journal of Psychiatric and Mental Health Nursing 24, no. 8 (August 3, 2017): 600–609. http://dx.doi.org/10.1111/jpm.12407.

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31

Song, Seong-Beom, Ju-Young Kang, and Sang-Gun Lee. "Analyzing Impact Factors of User Resistance to Accepting Paid Mobile Application." Journal of the Korea Contents Association 13, no. 4 (April 28, 2013): 361–75. http://dx.doi.org/10.5392/jkca.2013.13.04.361.

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32

강민구, 송영렬, and 박종미. "The Effects Resistance of User of IT Characteristics and Personal Characteristics." E-Business Studies 11, no. 3 (September 2010): 155–80. http://dx.doi.org/10.15719/geba.11.3.201009.155.

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33

Campbell, Robert Hugh, and Mark Grimshaw. "User Resistance to Information System Implementations: A Dual-Mode Processing Perspective." Information Systems Management 33, no. 2 (February 24, 2016): 179–95. http://dx.doi.org/10.1080/10580530.2016.1155951.

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34

Cheng, Shuang, Sang-Joon Lee, and Kyeong-Rak Lee. "User Resistance of Mobile Banking in China: Focus on Perceived Risk." International Journal of Security and Its Applications 8, no. 2 (March 31, 2014): 167–72. http://dx.doi.org/10.14257/ijsia.2014.8.2.17.

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35

Klaus, Tim, and J. Ellis Blanton. "User resistance determinants and the psychological contract in enterprise system implementations." European Journal of Information Systems 19, no. 6 (December 2010): 625–36. http://dx.doi.org/10.1057/ejis.2010.39.

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36

Ilie, Virginia, and Ofir Turel. "Manipulating user resistance to large-scale information systems through influence tactics." Information & Management 57, no. 3 (April 2020): 103178. http://dx.doi.org/10.1016/j.im.2019.103178.

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37

Lee, Hwansoo, Dongwon Lim, and Hangjung Zo. "Personal Information Overload and User Resistance in the Big Data Age." Journal of Intelligence and Information Systems 19, no. 1 (March 31, 2013): 125–39. http://dx.doi.org/10.13088/jiis.2013.19.1.125.

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38

Swerdfager, Thomas. "Theorizing resistance: Foucault, Cross-Cultural Psychiatry, and the User/Survivor Movement." Philosophy, Psychiatry, & Psychology 23, no. 3-4 (2016): 289–99. http://dx.doi.org/10.1353/ppp.2016.0033.

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39

Fan, Peng-Fei, Sang-Joon Lee, and Kyeong-Rak Lee. "Study on Chinese User Resistance of SNS : Focus on Renren Wang." Journal of Digital Convergence 12, no. 2 (February 28, 2014): 183–91. http://dx.doi.org/10.14400/jdc.2014.12.2.183.

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40

Ishak, Siti Salwa Mohd, and Sidney Newton. "Testing a Model of User Resistance Towards Technology Adoption in Construction Organizations." International Journal of Innovation and Technology Management 15, no. 06 (December 2018): 1950002. http://dx.doi.org/10.1142/s0219877019500020.

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Drawing upon diffusion of innovation (DoI) theory, technology acceptance models (TAMs), social network perspective and resistance literature, the study developed and tested a model, named integrated resistance factor model (IRFM), which integrates four key elements i.e. resistance indicators, support network factors, experience and disposition factors and the integration and accessibility factors. The study investigated if the model applies in a selected technology, namely online project information management systems (OPIMS). The IRFM was tested with partial least square (PLS) techniques and results from the [Formula: see text] analysis of the whole PLS structural model were significant and the data were coherence with the proposed model [Formula: see text]. These results indicated that user resistance to technology innovation can be predicted using the IRFM.

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41

Ngafeeson, Madison N., and Joseph A. Manga. "The Nature and Role of Perceived Threats in User Resistance to Healthcare Information Technology." International Journal of Healthcare Information Systems and Informatics 16, no. 3 (July 2021): 21–45. http://dx.doi.org/10.4018/ijhisi.20210701.oa2.

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The efforts of the United States government in the past 15 years have included harnessing the power of health information technology (HIT) to improve legibility, lessen medical errors, keep costs low, and elevate the quality of healthcare. However, user resistance is still a barrier to overcome in order to achieve desired outcomes. Understanding the nature of resistance is key to successfully increasing the adoption of HIT systems. Previous research has showed that perceived threats are a significant antecedent of user resistance; however, its nature and role have remained vastly unexplored. This study uses the psychological reactance theory to explain both the nature and role of perceived threats in HIT-user resistance. The study shows that perceived helplessness over process and perceived dissatisfaction over outcomes are two unique instances of perceived threats. Additionally, the results reveal that resistance to healthcare information systems can manifest as reactance, distrust, scrutiny, or inertia. The theoretical and practical implications of the findings are discussed.

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42

Klaus, Tim, Stephen C. Wingreen, and J. Ellis Blanton. "Resistant Groups in Enterprise System Implementations: A Q-Methodology Examination." Journal of Information Technology 25, no. 1 (March 2010): 91–106. http://dx.doi.org/10.1057/jit.2009.7.

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This paper is an initial investigation into types of user resistance and the management strategy expectations of users in a mandatory adoption setting. Despite its relationship to adoption, relatively little is known about user resistance. User resistance is investigated in the Enterprise System (ES) environment because the complexity and richness of ES leads users to manifest a large range of resistant behaviors and beliefs. Using Concourse Theory and Q-methodology, ES users are interviewed followed by the development of a Q-sort questionnaire, which was distributed to ES users. The results reveal eight user groups and address the management strategies preferred by each group. The results have implications for both research in the field of user resistance and adoption, and practitioners involved in system implementation.

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43

Kim and Kankanhalli. "Investigating User Resistance to Information Systems Implementation: A Status Quo Bias Perspective." MIS Quarterly 33, no. 3 (2009): 567. http://dx.doi.org/10.2307/20650309.

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44

Gobbin, Renzo. "The role of cultural fitness in user resistance to information technology tools." Interacting with Computers 9, no. 3 (January 1998): 275–85. http://dx.doi.org/10.1016/s0953-5438(97)00031-3.

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45

Kim, Hee-Woong. "The Effects of Switching Costs on User Resistance to Enterprise Systems Implementation." IEEE Transactions on Engineering Management 58, no. 3 (August 2011): 471–82. http://dx.doi.org/10.1109/tem.2010.2089630.

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46

Kim, Dong-hyu, and Heejin Lee. "Effects of user experience on user resistance to change to the voice user interface of an in‑vehicle infotainment system: Implications for platform and standards competition." International Journal of Information Management 36, no. 4 (August 2016): 653–67. http://dx.doi.org/10.1016/j.ijinfomgt.2016.04.011.

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47

Li, Jing, Yabo Dong, Shengkai Fang, Haowen Zhang, and Duanqing Xu. "User Context Detection for Relay Attack Resistance in Passive Keyless Entry and Start System." Sensors 20, no. 16 (August 9, 2020): 4446. http://dx.doi.org/10.3390/s20164446.

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In modern cars, the Passive Keyless Entry and Start system (PKES) has been extensively installed. The PKES enables drivers to unlock and start their cars without user interaction. However, it is vulnerable to relay attacks. In this paper, we propose a secure smartphone-type PKES system model based on user context detection. The proposed system uses the barometer and accelerometer embedded in smartphones to detect user context, including human activity and door closing event. These two types of events detection can be used by the PKES to determine the car owner’s position when the car receives an unlocking or a start command. We evaluated the performance of the proposed method using a dataset collected from user activity and 1526 door closing events. The results reveal that the proposed method can accurately and effectively detect user activities and door closing events. Therefore, smartphone-type PKES can prevent relay attacks. Furthermore, we tested the detection of door closing event under multiple environmental settings to demonstrate the robustness of the proposed method.

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48

Yoo, Jaeheung, Saesol Choi, Yujong Hwang, and Mun Y. Yi. "The Role of User Resistance and Social Influences on the Adoption of Smartphone." Journal of Organizational and End User Computing 33, no. 2 (July 2021): 36–58. http://dx.doi.org/10.4018/joeuc.20210301.oa3.

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This study examines the factors affecting users' adoption of the smartphone as an innovative device. Prior studies on the acceptance of computing devices have primarily focused on the impact of the technological benefits and characteristics. Meanwhile, there is a lack of research approaching user resistance, which hinders the diffusion of an innovation. In particular, the smartphone is a highly communication-oriented device that people's attitude and evaluation critically influence its further diffusion. However, few studies have validated this link in the smartphone adoption context. Therefore, this study has attempted to build a research model that explains factors affecting user's resistance to smartphone adoption by integrating technological and social antecedents forming the resistance, and empirically analyzes the data obtained through a survey. As a result, the relative complexity and relative advantages presented in the theory of innovation diffusion had a direct impact on the user's resistance.

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49

Schwalm, Robert C., and Linda C. Carlson. "On the Loss and Restoration of End User Acceptance." Proceedings of the Human Factors Society Annual Meeting 33, no. 13 (October 1989): 797–801. http://dx.doi.org/10.1177/154193128903301306.

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This paper identifies, through a case study, some of the specific factors contributing to the erosion of user acceptance during the redesign of an automated system and the specific steps taken to restore user acceptance. Among the factors contributing to a shift in user attitude are resistance to a new computer environment, a temporary emphasis during design on computer (vs user) issues, less frequent user reviews, and concerns about job security. Steps taken to restore user acceptance include increased contact with end users, familiarizing users with the computer environment, and clarification of system and user roles.

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50

Lin, Tung-ching, Shiu-li Huang, and Shun-Chi Chiang. "User Resistance to the Implementation of Information Systems: A Psychological Contract Breach Perspective." Journal of the Association for Information Systems 19, no. 4 (April 2018): 306–32. http://dx.doi.org/10.17705/1jais.00493.

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