• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.53-61
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• 2014

This research analyzed the relationship between CFIP and Intention to purchase under M-Commerce circumstances. First of all, CFIP had a negative influence on intention to purchase similar to E-Commerce. Secondly, we found privacy fundamentalist groups to react most sensitive to the degree of CFIP. Finally, Mobile experience did not have influence on the relationship between CFIP and Intention to purchase. This result is different from that of the E-Commerce Study. As such, it requires a more comprehensive research.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.175-184
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• 2014

The purpose of this study is to examine the factors influencing purchase intention of Location-Based Services (LBS) using privacy-trust-behavioral intention model. This model tests various theoretical research hypotheses relating to LBS, privacy-trust-behavioral intention model, and Concern for Information Privacy(CFIP). The target population of this study was LBS users. Data for this study were collected from January 21 to March 20, 2014. The data were gathered from 231 questionnaire respondents with experience using LBS. Among these reponses, 21 were excluded because of missing or inappropriate data. After removing the unsuitable questionnaires, a total of 210 surveys were considered for analysis. The results of hypothesis testing are as follows. First, location awareness positively influence privacy concerns. Second, privacy concerns negatively influence trust. Finally, trust positively influence purchase intention. The results of this study will provide various implication to improve purchase intention of LBS.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.45-59
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• 2015

As many companies have been interested in big data, they have invested a lot of resources to get more customer data. Some companies try to trade the data illegally. In order to collect more customer data, companies provide various incentive programs to customers. However, their results are normally much less than their expectations. This study focuses on exploring the relative importance of the factors which influence customer attitudes to providing his/her personal information. This study conducts a conjoint analysis to assess trade-offs among the five influential factors-monetary reward, concern for data collection, concern for secondary use, concern for unauthorized use, and concern for errors. This study finds that the customer attitude to providing personal information is most influenced by the concern for secondary use. Furthermore, it shows that there are some differences between the light internet user group and the heavy internet user group in the relative importances of these factors. The monetary rewards appeal to the heavy internet users, rather than the light internet users.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.217-236
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• 2015

The purpose of this study is to propose the effective location-based IoT service acceptance model by integrating ELM (Elaboration Likelihood Model) with UTAUT (Unified Theory of Acceptance and Use of Technology). The Partial Least Squares was used to analyze the causal relationships with respect to the effects of central route and peripheral route on acceptance intention. The results shows that central route has more significant impacts on perceived usefulness than peripheral route and CFIP (Concern for Information Privacy) weaken the relationship of acceptance intention and perceived usefulness. Our findings indicate some meaningful implications in the acceptance research of IOT services. First, we noted that the easy of use significantly affects the adoption of location-based IoT service. Furthermore, it is important to build the secured mechanism of privacy protection to adopt of location-based IoT service. Second, we tried to attempt the newly integrated approach to technical acceptance using UTAUT's variables and ELM by Petty and Cacioppo (1986). Finally this research empirically analyzed the adoption case of location-based IoT service which is not well-known yet within our country.