• Asia Marketing Journal
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• v.8 no.3
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• pp.1-11
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• 2006

The Bass model assumes two communication channels: mass-media and word-of-mouth. In this paper, we call the mass-media Type I channel of communications. The word-of-mouth channel means interaction between non-adopters and adopters. Let us call it Type II channel of communications. In the real world, however, the non-adopters who are not aware of the innovation can be affected by communications with other non-adopters who are aware of it. Let us call it Type III channel of communications to differentiate with Type II channel. This paper analyzes the impact of Type III channel on diffusion process. The result shows that exponential growth patterns (for example, the adoption patterns of the blockbuster movies) can be observed when non-adopters are influenced by other non-adopters who aware of the innovation.

• Knowledge Management Research
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• v.9 no.3
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• pp.59-76
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• 2008

Due to rapid increase in number of Internet users, the volume of domestic Internet shopping is expanding dramatically. Although the Internet shopping mall business is steadily growing, it has structural weakness, and in general, the business does not generate profit. In this context, this research identifies characteristics of the Internet shopping non-adopters, and suggests strategies to strengthen competitiveness of domestic Internet shopping malls and to create a new demand. Analysis of MCR data in 2007 showed that out of 4,298 respondents, 2,206 people adopted Internet shopping (51.3%). and 2,092 did not (48.7%). The survey measured 28 items regarding a consumption pattern and a lifestyle of the Internet users, and the analysis result showed that the pattern can be categorized in seven groups. Based on the analysis, the research suggests that the domestic Internet shopping malls adopt strategies to increase consumers' access frequency to tile Internet service, provide high-end goods, diversify transaction methods, make online shopping more convenient, cater to diversified consumer demands based on demographic data, provide price comparison more Internet shopping mails, and provide sufficient and useful information to consumers.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.365-368
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• 2005

While the goal of new IT adoption in small and medium sized firms is to choose an optimal system to fit with their own environments and conditions, that of IT post-adoption usage is to fully implement new IT and maximize their benefits from it. Therefore, the decision-making environments of new IT adoption is definitely different from those of post-adoption. Also, The direct experience of IT usage can provide some learning effect and the change of users' beliefs on new IT. From this point of view, this study attempts to figure out the differences of influencing factors on IOS usage intention between adopters and non-adopters. The results show that there are clear differences of influencing factors between two groups. Non-adopter group shows that perceived financial cost and ability of use have significant influences on IOS usage intention, while relative advantage and perceived risk in adopter group have statistically significant influences on post-adoption usage of IOS.

• Korean Management Science Review
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• v.32 no.3
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• pp.29-36
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• 2015

In this research, we analyze the sensitivity of the network density to the estimates for the Bass model parameters with both theoretical model and a simulation. Bass model describes the process that the non-adopters in the market potential adopt a new product or an innovation by the innovation effect and imitation effect. The imitation effect shows the word of mouth effect from the previous adopters to non-adopters. But it does not divide the underlying network structure from the strength of the influence over the network. With a network based Bass model, we found that the estimate for the imitation coefficient is highly sensitive to the network density and it is decreasing while the network density is decreasing. This finding implies that the interpersonal influence can be under-looked when the network density is low. It also implies that both of the network density and the interpersonal influence are important to facilitate the diffusion of an innovation.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.27-44
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• 2019

The goal of this study is to find why the consumers are reacting slowly or negatively toward smartwatches. Even though, smartwatches provide useful information such as health care and text message, the market was not growing fast as expected, and seems to be stagnant at this point. Thus, the future market predictions are varied. To find out why this may have happened, a Q-method study using non-adopters was conducted. In order to find out depth explanations from each interviewers, the research team chose the Q method and Q sorting to classify the different reasons for non-adopters. Based on the interview, all participants were clustered with into groups with similar patterns of the answers. The research team classified the interview group to three categories 1) Technology Discontent 2) Service Discontent 3) Indifferent. The research team analyzed each category reasoning and logics. Also the team compared the result to the technology chasm as it was proposed by Rogers (1969) to measure the maturity of the consumers.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.135-154
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• 2017

The purpose of the study is to identify the barriers to using mobile health applications based on the Diffusion of Innovations Theory. The study employed a purposive sampling to recruit college students who were non-adopters or rejecters. The study participants were a total of 44 students, who consist of 32 males and 12 females, and paper-based interviews were conducted. The findings of the study indicated that attributes such as relative advantages, complexity, trialability and observability were not considerable factors of impeding the adoption or continuous use of health applications, whereas relative disadvantages and compatibility were. The study suggests that health application developers and service providers minimize relative disadvantages and enhance compatibility of the innovation with consumers' life styles, rather than try to improve relative advantages and complexity, to more effectively encourage non-adopters to try and maintain using the innovation.

• Information Systems Review
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• v.9 no.1
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• pp.67-84
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• 2007

In diffusing an information systems(IS), the provider of the IS can be more effective if they can identify user groups who can adopt the system early. By focusing on the user groups, system providers can encourage them to adopt the IS. After the early adopters adopt an IS, the diffusion of the system to other groups can be easier by early adopters' voluntary advertisement and help in adopting the IS. Instead of discrete choice methods which are usually used for this purpose, we suggest a decision tree method. Compared to discrete choice methods, this method is more accurate for prediction and can easily identify non-linear segments of groups. By testing the data of adopters of an IS in agricultural business, we show the excellence of this method in identifying target groups to focus on. This method would help system providers to diffuse their systems by starting from early adopters.

• Information Systems Review
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• v.8 no.3
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• pp.21-38
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• 2006

The major objectives of this study are to identify the key organizational factors that facilitate and/or inhibit the IS outsourcing in Korean hospitals, and to analyze the differences between adopter & non-adopters and successful ones and not-successful ones. In order to achieve the research objectives, we derived comprehensive lists of potential facilitators and inhibitors from the past research, and conducted a field survey on 135 hospitals in metropolitan area. The analysis results suggest that organizational, financial and strategic factors are the most important facilitators, while organizational, psychological, vendor-related and environmental factors are the most important inhibitors. In addition, it was found that factors differentiating adopters and non-adopters are organizational factor(facilitator) and environmental factor(inhibitor) while strategic factor is a differentiating one between successful hospitals and unsuccessful ones.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.545-550
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• 2007

The aim of this paper is to find out whether there is a difference in adopting and/or diffusing the information and communication technology (ICT) between countries. If there is, what are the primary factors that keep some countries from adopting and diffusing ICT while others do? To analyze the above problem, we adopted the Unified Theory of Acceptance and Use of Technology (UTAUT) suggested by Venkatesh et al. (2003), which consists of effort expectancy, performance expectancy and social influence. We also use the innovation diffusion functions, which are known to have the S-shape and are made up of the introduction, growth, maturity and decline phases. We do not, however, consider the decline phase, because the ICT that we are considering is not believed to be in that phase. Therefore, we researched how the three factors affect adoption in the three phases. We selected the cellular phone as the ICT, because it is considered to be the most popularly used ICT and its technology has been developing rapidly. We surveyed the cellular phone adopters in Korea, and the U.S. for 15 years from 1989 to 2003. Korea, and the U.S. represent newly developed and developed countries, respectively. For the data analysis, a survival analysis was used, as it could explain the characteristics of the potential adopters or non-adopters. We found that the ICT diffusion patterns, as well as the ICT diffusion factors, of the two countries were different. Therefore, we believe that the results of our research can be used in building strategies on reducing the digital divide gaps between countries.

• The Journal of Information Systems
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• v.24 no.4
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• pp.83-97
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• 2015

Purpose: Traditionally, information technology acceptance have been considered one of the most important research issues. However non-acceptance, which was main objective of acceptance theories, have not been included in main research area by communities of information systems. This study is to identify the factors influencing non-acceptance of information technology and suggest a total research model for explaining the phenomena of non-acceptance. Design/methodology/approach: Grounded theory was adopted as a principal research method. which is an inductive technique of interpreting qualitative data about a social phenomenon to build theories about that phenomenon. Data were collected by depth interview and open question on potential non-adopters during 3 months. The collected data were coded by two main coding paradigm in ground theory, open coding and axis coding. Findings: Factors influencing non-acceptance, status quo, imitation, value evaluation, and concerning risk were extracted from open coding. These factors were integrated into system 1 thinking and system 2 thinking, which were from axis coding. More specifically, status quo and imitation are system 1 thinking which are more responsive and emotional thinking and value evaluation and concerning risk are system 2 thinking which are more rational and reasoning thinking.