• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.46-50
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• 2013

In insurance statistics, the sum of homogeneous insurance is often needed. The sum is called individual risk model which is a fundamental model in risk analysis for insurance. This paper first presents an individual risk model based on the uncertainty theory. Then its uncertainty distribution is provided. Finally, its arithmetic is shown by a numerical example.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.177-193
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• 2003

This paper examines empirically if the increase of funding uncertainty in government supported R&D institutes(GSRIs) in Korean cause managers to use more effective management control practices. Recently government introduced a new government R&D budget management system, based on competition, named PBS(Project Base System). Government requires GSRIs to be self-supporting and compete for funding from government. The introduction of new budget management system named PBS, has resulted in the increase of funding uncertainty in GSRIs. According to institutional theory, government organizations gain legitimacy by conforming to external expectations regarding management control practices, In contrast, contingency theory proposes that management control practices are driven by the fit between the technical features of the environment and the management control practices. The contingency literature provides that one external factor expected to motivate government managers to use more efficient control practices is the presence of competition and funding uncertainty. This paper use both theoretical perspective to develop hypotheses and examine the influence of funding environment on management control practices. Results show that the more institutionalized environment, the more managers in GSRIs rely on bureaucratic mode of control for conforming to external requirements, and the greater the funding uncertainty, the more managers use results and personal modes of control to improve research team performance.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.327-348
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• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.176-182
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• 2012

This paper presents a new approach to risk comparison in uncertain environment. Based on the uncertainty theory, some uncertain risk measures and risk comparison rules are proposed. Afterward the bridges are built between uncertain risk measures and risk comparison rules. Finally, several comparable examples are given.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.902-907
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• 2005

This study was undertaken to develop a comprehensive scheduling method which applied the core concept(DBR) of TOC to PERT, and to combine Monte Carlo Simulation to revise the uncertainties of activities then to eliminate project duration uncertainty. Most of the project duration overlooks the fact that in spite of minimizing the project duration, the uncertainty of constrained resources still puts the reliability of project duration in jeopardy. For the contractor, however, the most important thing is to comply the project scheduling with the planning to reduce the uncertainty of the project activities, operational interaction and project duration. In order to demonstrate that the model can be used in construction project, the scheduling of a steel-structure project was used as a case study to verify the validity of this model.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.1-18
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• 2011

The present study provides a theoretical investigation on pioneering advantage based on reference dependence and loss aversion effect under prospect theory (Kahneman and Tversky, 1979). Behavioral explanations for pioneering advantage are provided from two different perspectives: one based on the prototypicality and the other on the utility uncertainty of the option. A pioneer brand creates the product category and makes a strong impression in customers' mind, and thus becomes the most representative or prototypical option of the category. In addition, the pioneer brand becomes the first option to be experienced by the majority of consumers in the product category, thus has the lowest level of utility uncertainty compared with the late movers. This study integrates the previous accounts for pioneering advantage by showing that consumers have higher preferences for the most prototypical and the least uncertain option based on loss aversion and reference dependence effect. This study suggests that firms should carefully analyze the consumers' loss aversion and perceived uncertainty and prototypicality of their products in order to develop effective market entry strategies.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.15-28
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• 2014

Evaluation of the implementation and performance of a firm's green supply chain management (GSCM) is an ongoing process. Balanced scorecard is a multi-criteria evaluation concept that highlights implementation and performance measures. The literature on the framework is abundant literature but scarce on how to build a hierarchical framework under uncertainty with dependence relations. Hence, this study proposes a hybrid approach, which includes applied interpretive structural modeling to build a hierarchical structure and uses the analytic network process to analyze the dependence relations. Additionally, this study applies the fuzzy set theory to determine linguistic preferences. Twenty dependence criteria are evaluated for a GSCM implemented firm in Taiwan. The result shows that the financial aspect and life cycle assessment are the most important performance and weighted criteria.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.135-145
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• 1998

There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.18-25
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• 2012

IChinese postman problem is one of the classical combinatorial optimization problems with many applications. However, in application, some uncertain factors are frequently encountered. This paper employs uncertain programming to deal with Chinese postman problem with uncertain weight Within the framework of uncertainty theory, the concepts of expected shortest route, ${\alpha}$-shortest route, and distribution shortest route are proposed. After that, expected shortest model, and ${\alpha}$-shortest model are constructed. Taking advantage of properties of uncertainty theory, these models can be transf-ormed into their corresponding deterministic forms, which can be solved by classical algorithm..

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.43-61
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• 2015

The valuation of patents is very important, since technology competitiveness is crucial for firms to maintain global competitiveness. But, the patent valuation is difficult and challenging because of the uncertainty affecting their returns. Hence, we propose a patent valuation method by incorporating game theory into the real option model, which can not only potentially recognizes the effect of uncertainty on patent value, but also consider investment decision in a competitive market, as a game between firms. With the model, we can consider dynamic strategy involving an option of patent leveraging strategies enabling the firm to switch among compete, cooperate, or wait modes under different demand or competitive advantage condition.