• KDI Journal of Economic Policy
• /
• v.33 no.3
• /
• pp.121-161
• /
• 2011

We study incentive structures of public developers and land owners in the process of public expropriations using a sequential game model. In the model, we show that there is an incentive for the public developer to give more compensation than just compensation that are defined by law. Also the model shows that there is an incentive for the land owners to revolt strategically against the public expropriation. Then an ideal authority delegation model is introduced to resolve the problems, where an independent appraiser determines the compensation for the expropriation. In the real world, improving the independence of appraisal process is critical to make the system closer to the ideal authority delegation model. So this paper concludes by making a few policy suggestions to improve the current appraisal system.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.11
• /
• pp.257-270
• /
• 2022

This paper analyzes the effect of profit incentives within the setting of bounty open source project. A simple decision-making model based on classical utility maximization is presented for open source developers that includes income effects from the bounty prize. We then simulate the decisions of multiple developers to assess the effect from the bounty prize. Our result shows that learning costs can greatly reduce the software quality improvement benefit from bounty project. It also suggests that open source projects can benefit more when they have multiple small bounty projects than a single large bounty project since it reduces the learning cost and the opportunity cost for the open source developers.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.800-807
• /
• 2009

The limited public funds available for infrastructure projects have led governments to consider private entities' participation in long-term contracts for finance, construction, and operation of these projects to share risks and rewards between the public and the private. Because these projects have complicated risk evolutions, diverse contractual forms for each project member to hedge risks involved in a project are necessary. In light of this, Build-Operate-Transfer(BOT) model is considered as effective to accomplish Public Private Partnerships(PPPs) with a characteristic of an ownership-reversion. In BOT projects, the government has used such an incentive system as minimum revenue guarantee(MRG) agreement to attract the private's participation. Although this agreement turns out critical in success of BOT project, there still exist problematic issues in a financial feasibility analysis since the traditional capital budgeting theory, Net Present Value(NPV) analysis, has failed to evaluate the contingent characteristic of MRG agreement. The purpose of this research is to develop real option model based on option pricing theory so as to provide a theoretical framework in valuing MRG agreement in BOT projects. To understand the applicability of the model, the model is applied to the example of the BOT toll road project and the results are compared with that by NPV analysis. Finally, we found that the impact of the MRG agreement is significant on the project value. Hence, the real option model can help the government establish better BOT policies and the developer make appropriate bidding strategies.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.129-139
• /
• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.