Manipulating user resistance to large-scale information systems through influence tactics

Ilie, Virginia; Turel, Ofir

doi:10.1016/j.im.2019.103178

Cited by 30 publications

(11 citation statements)

References 96 publications

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“…Similarly, users attach importance to the reliability, accuracy, assurance, and empathy of technologies, resisting those implementations that are limited by slow reactions, low technological quality, and unreliability at critical times, and that ignore users' requests or offer little individualized attention to users ( Alohali et al, 2020 , Chang et al, 2019 ). Existing studies also have integrated the technology acceptance model to verify that perceived difficulty of use (or uselessness) cause user resistance to continuous usage ( Ilie and Turel, 2020 , Jia et al, 2017 ).…”

Section: Literature Reviewmentioning

confidence: 99%

The perils of hotel technology: The robot usage resistance model

Zheng

Wong

2022

International Journal of Hospitality Management

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The COVID-19 outbreak has accelerated the development of service robots. However, service robots in some hotels have been put aside despite successful adoption. This study thus focuses on hotel employees' inhibited continuous usage intention by examining the challenges of benefiting from service robots. A robot usage resistance model (RURM) has been proposed based on the results. In this model, lack of authentic anthropomorphous features and low usability as technological characteristics could influence employees' cognitions toward service robots, while robot-related excessive workloads, techno-insecurity, and techno-uncertainty as psychological stimuli could trigger negative emotional arousal, which in turn fosters employee resistance to service robot continuous usage. This study offers a more solid conceptual investigation into employee resistance to service robot continuous usage, thus allowing the development of strategies to better reap the rewards of hotel service robot usage.

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Section: Literature Reviewmentioning

confidence: 99%

The perils of hotel technology: The robot usage resistance model

Zheng

Wong

2022

International Journal of Hospitality Management

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“…Although overt resistance behavior does not appear against a mandatory system in which users do not have any choice whether they use it or do not use it, covert resistance behavior could still occur [ 19 , 20 ]. Covert resistance behavior might be more dangerous because it causes inappropriate use of EHR systems, which could generate significant risk in a hospital setting [ 15 ]. Hospital management could utilize the findings of this study to implement EHR successfully by reducing user resistance behavior in hospitals.…”

Section: Discussionmentioning

confidence: 99%

“…Acceptance of information systems does not imply that there is no user resistance, especially in the case of mandatory systems. Acceptance or non-acceptance occurs when there is a voluntary system for personal purposes, such as using email or social networks; however, user resistance tends to manifest when there is a mandatory system [ 6 ], such as EHR as well as the large-scale systems that influence the entire hospital workflow [ 6 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Factors associated with nurses' user resistance to change of electronic health record systems

Cho

Kim

Choi

2021

BMC Med Inform Decis Mak

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Background Electronic health record (EHR) systems often face user resistance in hospitals, which results in a failure to acquire their full benefits. To implement the EHR successfully, it is crucial to reduce nurses’ resistance to use the system. This study aimed to investigate the factors associated with nurses’ resistance to use the EHR system. Methods A descriptive correlational study was conducted with nurses working at four university hospitals in Korea using self-administered questionnaires to measure user resistance behavior, resistance to change, perceived usefulness, perceived ease of use, perceived value, colleagues’ opinions, self-efficacy for change, and organizational support for change. Path analysis was performed to examine direct and indirect association with user resistance behavior. Results A total of 223 nurses completed the questionnaires. All seven factors were found to be significantly associated with user resistance, either directly or indirectly. The total effect on user resistance behavior was highest in resistance to change (0.65), followed by perceived usefulness (− 0.33); both had direct but no indirect effects. Conversely, self-efficacy for change (− 0.25), perceived value (− 0.21), colleagues’ opinions (− 0.16), perceived ease of use (− 0.16), and organizational support for change (− 0.05) had indirect but no direct effects. Conclusions The study examined the factors associated with nurses’ user resistance behavior after the implementation of a new EHR system. These findings could help hospitals develop better EHR implementation strategies to reduce user resistance behavior among the nursing staff.

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“…In this line, white goods companies encounter barriers in the implementation of large-scale systems, blocking the agility of the development of new digital-based offers. In information systems studies this is referred to as the resiliency that some internal users have against projects that imply new technologies [ 54 , 55 ]. Consequently, the search for new ways of interacting with the consumers should be one of the premises of value offers [ 56 , 57 ].…”

Section: Discussionmentioning

confidence: 99%

Discovering the Value Creation System in IoT Ecosystems

López

Castillo

Corchado

2021

Sensors

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Internet of Things (IoT) should not be seen only as a cost reduction mechanism for manufacturing companies; instead, it should be seen as the basis for transition to a new business model that monetizes the data from an intelligent ecosystem. In this regard, deciphering the operation of the value creation system and finding the balance between the digital strategy and the deployment of technological platforms, are the main motivations behind this research. To achieve the proposed objectives, systems theory has been adopted in the conceptualization stage, later, fuzzy logic has been used to structure a subsystem for the evaluation of input parameters. Subsequently, system dynamics have been used to build a computational representation and later, through dynamic simulation, the model has been adjusted according to iterations and the identified limits of the system. Finally, with the obtained set of results, different value creation and capture behaviors have been identified. The simulation model, based on the conceptualization of the system and the mathematical representation of the value function, allows to establish a frame of reference for the evaluation of the behaviour of IoT ecosystems in the context of the connected home.

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Manipulating user resistance to large-scale information systems through influence tactics

Cited by 30 publications

References 96 publications

The perils of hotel technology: The robot usage resistance model

The perils of hotel technology: The robot usage resistance model

Factors associated with nurses' user resistance to change of electronic health record systems

Discovering the Value Creation System in IoT Ecosystems

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