• Journal of Environmental Policy
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• v.7 no.4
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• pp.105-134
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• 2008

Local opposition and protest constitute single greatest hurdle to the siting of locally unwanted land uses(LULUs), especially siting of high-level radioactive disposal not only throughout Korea but also throughout the industrialized world. It can be attributed mainly to the NIMBYism, equity problem, and lack of participation. These problems are arisen from rational planning process which emphasizes instrumental rationality. But planning is a value-laden political activity, in which substantive rationality is central. To achieve this goals, we need a sound planning process for siting LULUs, which should improve the ability of citizens to influence the decisions that affects them. By a sound planning process, we mean one that is open to citizen input and contains accurate and complete information. In other word, the public is also part of the goal setting process and, as the information and analyses developed by the planners are evaluated by the public, strategies for solutions can be developed through consensus-building. This method is called as a co-operative siting process, and must be structured in order to arrive at publicly acceptable decisions. The followings are decided by consensus-building method. 1. Negotiation will be held? 2. What is the benefits and risks of negotiation? 3. What are solutions when collisions between national interests and local ones come into? 4. What are the agendas? 5. What is the community' role in site selection? 6. Are there incentives to negotiation. 7. Who are the parties to the negotiation? 8. Who will represent the community? 9. What groundwork of negotiation is set up? 10. How do we assure that the community access to information and expert? 11. What happens if negotiation is failed? 12. Is it necessary to trust each other in negotiations? 13. Is a mediator needed in negotiations?

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.