• International journal of advanced smart convergence
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• v.13 no.2
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• pp.110-118
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• 2024

This study examines factors influencing nonusers' resistance to the adoption of the metaverse, focusing on propagation mechanisms. It elucidates the role of innovation resistance within the metaverse adoption process. We applied the Innovation Resistance Model in the context of the metaverse and considers three major groups of factors influencing resistance to the metaverse: innovation characteristics (perceived usefulness, compatibility, perceived risk, and complexity), consumer characteristics (personal innovativeness), and propagation mechanisms (mass media, online media, and personal communication). An online survey of college students who do not use the metaverse revealed that perceived usefulness, compatibility, personal innovativeness, and online media were negative predictors of resistance to the metaverse. Conversely, perceived risk, mass media, and personal communication were positive predictors of resistance to the metaverse. Furthermore, innovation resistance was found to play a mediating role in the metaverse adoption process. Drawing upon the findings, we suggested marketing strategies to decrease resistance to the metaverse.

• The Journal of Information Systems
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• v.27 no.2
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• pp.53-75
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• 2018

Purpose The purpose of this study is to provide implications by examining the factors affecting the consumers' innovation resistance and intention to use FIDO technology based on the innovation resistance model. In addition, we investigate the difference between FIDO group using biometric authentication technology and those using knowledge / possessive authentication technology. Design/methodology/approach This study investigated the factors influencing innovation resistance and intention to use based on the innovation resistance model. And the structural equation model was applied to analyze the effect of innovation resistance and intention to use. Findings According to empirical results, this study found that perceived relative advantage (+), perceived risk (+), perceived complexity (+), and existing product attitude(+) influenced innovation resistance, and perceived relative advantage (+), self efficacy(+), and innovation resistance(-) influenced intention to use. In addition, this study found that there is a significant difference between the group using the bio-based authentication technology and the group using the knowledge / possessive based authentication technology.

• The Journal of Information Systems
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• v.25 no.4
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• pp.87-104
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• 2016

Purpose As the smartphone market arrived at its saturation, from world leading information and communications technologies (ICT) businesses to startups, companies are competing to develop innovative wearable device products and suitable contents. Utility, technology, design, price, and various killer contents development targeting every customer's need should be considered for a success in the wearable device market. Design/methodology/approach Prior studies on innovation technology of ICT field have mainly focused on the innovation diffusion theory, expectation confirmation theory, and technology acceptance model, this study suggested the innovation resistance factors of adopting the smart wearable devices based on the innovation resistance model and theory of perceived risk. The model comprises the following two characteristics factors: 1) innovation characteristics which include perceived relative advantages, perceived compatability, perceived complexity, and perceived risk, 2) consumer characteristics which include attitudes towards innovation and existing products (i.e., mobile devices and analog watches). This study developed an extended innovation resistance model to explain the intention to acceptance of wearable devices consumers and collected 284 online survey responses from the non-consumers of the wearable devices. Findings The findings of this study suggest that perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, attitudes towards innovation and attitudes towards existing analog watches affected the innovation resistance which has negative influence on the intention to adoption of wearable devices.

• Knowledge Management Research
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• v.20 no.2
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• pp.59-86
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• 2019

As the era of the 4th Industrial Revolution evolves, not only private companies but also government agencies and institutions in public sector are adopting cloud computing services converged by new information technologies such as IoT, big data, and artificial intelligence to strengthen competitiveness and create new business values. The purpose of this study is to investigate the relationship between innovation characteristics, innovation resistance, and acceptance of innovative technologies from the perspective of cloud computing services in the public sector. In this study, we collected the survey data from 190 employees of IT division in the public sector, and analyzed the causal relationship between innovation characteristics, technostress, innovation resistance, and intention to adopt the cloud computing service that they perceived. As a result of the analysis, we demonstrated that innovation characteristics, technostress have significant effect on innovation resistance and acceptance intention, and that top executive commitment and innovation resistance also have significant effect on acceptance intention. This study provides meaningful practical implications for the staffs preparing for adoption of cloud computing services and the executives who make the final decision in public sector.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.1
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• pp.55-67
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• 2015

This study examines innovation resistance to smart learning, an emerging innovative technology for startups and corporate ventures in the education market. The study explores whether the relative advantage, compatibility and complexity of an innovation, attitudes toward existing learning method(s), and perceived self-efficacy significantly affect innovation resistance. Additionally, the effects of such innovation resistance on future use and the moderating effect according to demographic characteristics are examined. The results of the analysis using a structural equation model showed that all the factors considered (except relative advantage) affects innovation resistance, innovation resistance significantly affects intention to use.

• Journal of Information Technology Applications and Management
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• v.18 no.4
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• pp.169-181
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• 2011

The study developed the ideas of innovation resistance attitude in view of innovation delay, rejection, and objection. Authors developed the idea of innovation resistance attitudes of customers in view of innovation diffusion process. The study categorized the idea of resistance such as delay, rejection, and objection. The study hired the structural equation modeling to evaluate the relationships among the consumers' subjective variables such as incongruence, uncertainty, perceived performance, peer usage, and tradition orientation those were factored out by the survey test. These measured variables were analyzed into the innovation resistance related latent variables. The study provides the basic treatment to introduce new technologies and products to the superficially resisting customers. Those resisting customers might be future late adopters. The research results provide the basic arguments for prerequisite treatment to introduce smart phone in the global market place.

• The Korean Journal of Franchise Management
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• v.11 no.4
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• pp.7-15
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• 2020

Purpose: The purpose of this study is to clarify the role of decoupling between job characteristics, innovation behavior, and innovation resistance in order to seek ways for companies to survive and grow continuously through innovation activities in various uncertain situations. Research design, data and methodology: A total of 263 valid questionnaires were collected and used for analysis for employees working at the company. For the analysis, simple and multiple regression analysis, and 3-step mediated regression analysis were conducted using SPSS 24.0 and AMOS 24.0. Results: First, it was found that skill variety, task identity, autonomy, and feedback increase decoupling, and decoupling increases innovation resistance. In addition, it was confirmed that decoupling had a mediating effect between job characteristics and innovation resistance excluding task significance. Finally, it was found that task significance and feedback increase innovation behavior, and decoupling and task identity increase innovation resistance, but feedback can alleviate innovation resistance. Conclusions: As a result of the analysis, the fact that job characteristics excluding task importance have a positive effect on decoupling means that there are two sides of job characteristics perceived by employees. In other words, it means that the results of analysis on the jobs that the company assigns to its members may not be effective. In addition, decoupling, a phenomenon that seems to be accepting on the outside, but perceives that it is negative on the inside, means that there is a possibility to reject innovation. Therefore, prior to carrying out innovation activities, companies should give clear job specifications and meanings for the job and give them autonomy when assigning jobs to their members. In order to provide appropriate feedback, the company must design, operate, and provide feedback. It was found that there was a need to review the overall effectiveness. In addition, efforts such as strengthening corporate-level fairness, maintaining psychological contracts, and realizing authentic leadership should be preceded to reduce decoupling.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.627-648
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• 2012

The Purpose of current study is to empirically examine the impact of innovation resistance management practices on technological innovation activities and its performance. Drawing upon literature review, innovation resistance management practices are conceptualized and the measurement items of independent and dependent variables are developed. Survey-based data for this study was collected from 300 Korea manufacturers. The results of structural equation modeling analysis are as follows. First, innovation resistance management practices significantly affected on technological innovation activities and its performance. Second, technological innovation activities affected on its performance. Therefore, in order to make high innovation performance, corporate have to properly implement the innovation resistance management practices.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.61-73
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• 2014

While past studies on e-books have mainly focused on the uses and gratifications (UG) and technology acceptance model(TAM), this study rather analysed the innovation resistance factors of adopting the e-book based on the innovation resistance model. The research model comprises of two factors: 1) innovation characteristics which include relative advantages, compatability and complexity, 2) user characteristics which encompass attitudes towards innovation and existing products (i.e., paper books). Using online survey questionnaire, this study examined the effects of those innovation and user characteristics on the innovation resistance, and the relationship between innovation resistance and intention of adoption. The results showed that complexity and attitude towards existing products affected the innovation resistance which has negative influence on the intention of adoption. Accordingly, it is necessary to improve the ease of use in the whole process from purchase to reading experiences, and highlight e-books' own interactive features and functions which are perceived as different from paper-book user experience.

• Human Ecology Research
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• v.57 no.2
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• pp.171-183
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• 2019

Convergence between technology and financial services is ubiquitous and widespread. Virtual banks represent an important aspect of financial markets that can generate value added for consumers and enhance the quality of financial services. This study explores the effect of innovation characteristics (relative advantage, compatibility, and perceived risk), consumer characteristics (status quo bias), and social mechanisms (network externality: complementarity, numbers of peers) on consumers' adoption intention and resistance to virtual banks. This study adopted an innovation resistance model with two dependent variables: adoption intention and resistance to virtual banks. An online self-administered survey was conducted and 532 or non-users of virtual banks aged 20 to 69 years old were analyzed. Frequency analysis, descriptive analysis, and hierarchical multiple regression indicated that status quo bias, relative advantage, perceived risk, complementarity, and number of peers insignificantly influence the adoption intention regarding virtual banks. Furthermore, status quo bias, relative advantage, perceived risk, and number of peers insignificantly influence the resistance to virtual banks. Female respondents have a lower adoption intention and higher resistance to virtual banks than male respondents. The findings suggest that the innovation resistance model can be useful in understanding consumers'adoption and resistance behavior as well as reveal that innovation characteristics, consumer characteristics, and social mechanism are important antecedent variables of the innovation adoption decision.