Inhibitors and Enablers as Dual Factor Concepts in Technology Usage

Cenfetelli, Ronald T.

doi:10.17705/1jais.00059

Cited by 233 publications

(242 citation statements)

References 74 publications

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“…Therefore, first attempts which discussed such an approach could be found in the literature [48]. Nonetheless, it would be necessary to identify different reasons leading to non-adoption, as a status quo bias [42], resistance ( [49]; [7]; [8]) or other inhibitors [16] as fear or threats.…”

Section: Discussion and Future Researchmentioning

confidence: 99%

Technology Adoption by Elderly People – An Empirical Analysis of Adopters and Non-Adopters of Social Networking Sites

Maier

Laumer

Eckhardt

2011

Theory-Guided Modeling and Empiricism in Information Systems Research

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This research paper analyzes the impact of attitudinal, control and normative beliefs on the intention to use social network sites (SNS) by people older than 50. Using the Model of Adoption of Technology in Households (MATH) and the data of 115 social network site adopters and 53 non-adopters it can be shown that the intention of adopters and non-adopters has been influenced by different reasons. Perceived Ease of Use and Normative Beliefs have only a significant impact for adopters. Moreover, this research paper unfolds Fear of Technology as a strong influence factor for non-adopters in regard not to use SNS in their daily routine. The paper concludes with a discussion of an age-sensitive design of SNS in order to address the digital divide.

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Section: Discussion and Future Researchmentioning

confidence: 99%

Technology Adoption by Elderly People – An Empirical Analysis of Adopters and Non-Adopters of Social Networking Sites

Maier

Laumer

Eckhardt

2011

Theory-Guided Modeling and Empiricism in Information Systems Research

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“…A number of previous studies have linked resistance to cognitive (Marakas and Hornik, 1996) and behavioural characteristics (Cenfetelli, 2004;Lapointe and Rivard, 2005;Martinko, Henry and Zmud, 1996), and to social and political factors (Joshi, 1991;Kim and Kankanhalli, 2009;Meissonier and Houzé, 2010;Prasad and Prasad, 2000). However, few studies go beyond consideration of resistance taken from a particular perspective: human, social, technical or organisational.…”

Section: An Integrated Resistance Factor Modelmentioning

confidence: 99%

An innovation resistance factor model

Ishak

Newton

2016

CEB

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The process and implementation strategy of information technology in construction is generally considered through the limiting prism of theoretical contexts generated from innovation diffusion and acceptance. This research argues that more attention should be given to understanding the positive effects of resistance. The study develops a theoretical framing for the Integrated Resistance Factor Model (IRFM). The framing uses a combination of diffusion of innovation theory, technology acceptance model and social network perspective. The model is tested to identify the most significant resistance factors using Partial Least Square (PLS) technique. All constructs proposed in the model are found to be significant, valid and consistent with the theoretical framework. IRFM is shown to be an effective and appropriate model of user resistance factors. The most critical factors to influence technology resistance in the online project information management system (OPIMS) context are: support from leaders and peers, complexity of the technology, compatibility with key work practices; and pre-trial of the technology before it is actually deployed. The study provides a new model for further research in technology innovation specific to the construction industry.

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“…Nonetheless, using technology may not always be beneficial (Featherman 2001;Zhou 2015) and is frequently related to various risks such as unanticipated costs. However, TAM, UTAUT and most other technology acceptance models primarily focus on the advantages of using a technology and leave out the negative factors that discourage usage (Cenfetelli 2004).…”

Section: Net-valence Modelsmentioning

confidence: 99%

Determinants of Intention to Participate in Corporate BYOD-Programs – The Case of Digital Natives –

Weeger

Wang

Gewald

et al. 2015

AMPROC

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Corporations continue to see a growing demand for Bring-Your-Own-Device (BYOD) programs which allow employees to use their own computing devices for business purposes. This study analyses the demand of digital natives for such programs when entering the workforce and how they perceive the benefits and risk associated with BYOD. A theoretical model building on net valence considerations, technology adoption theories and perceived risk theory is proposed and tested. International students from five countries in their final year and with relevant work experience were surveyed. The results show that the intention to enroll in a BYOD program is primarily a function of perceived benefits while risks are widely ignored. Only safety and performance risks proved to contribute significantly to the overall perceived risk. The knowledge acquired from this study is particularly beneficial to IT executives as a guide to deciding whether and how to set up or adjust corporate BYOD initiatives.

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Inhibitors and Enablers as Dual Factor Concepts in Technology Usage

Abstract: Information systems (IS) research has focused extensively on the factors that foster

Cited by 233 publications

References 74 publications

Technology Adoption by Elderly People – An Empirical Analysis of Adopters and Non-Adopters of Social Networking Sites

Technology Adoption by Elderly People – An Empirical Analysis of Adopters and Non-Adopters of Social Networking Sites

An innovation resistance factor model

Determinants of Intention to Participate in Corporate BYOD-Programs – The Case of Digital Natives –

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