• Journal of Families and Better Life
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• v.23 no.3 s.75
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• pp.217-230
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• 2005

The purpose of this study was to examine factors related to the purchase of cash-value life insurance of households. Based on human capital and bequest motive theories of the demand for life insurance, this study developed a conceptual model of the demand for life insurance of households. In addition, in order to capture the beneficiaries' preference and expected lifetime utility, expected future financial needs were included in the conceptual model. Using Heckit analysis, the model was estimated by two stages. The results supported that human capital, bequest motives and expected future financial needs were significant factors on both decision to have insurance and the mont of insurance. Specifically, if the household's head expected to have a higher potential in the future, the household was more likely to have insurance. If a household had dependents, the household was more likely to have insurance. As income or monthly expenditure increased, the probability of haying insurance and the amount of the insurance increased However, savings or social insurance were positively related to the purchase of insurance.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.314-318
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• 2010

Predicting Alpha-helicies, Beta-sheets and Turns of a proteins secondary structure is a complex non-linear task that has been approached by several techniques such as Neural Networks, Genetic Algorithms, Decision Trees and other statistical or heuristic methods. This project introduces a new machine learning method by combining Bayesian Inference with offline trained Multilayered Perceptron (MLP) models as the likelihood for secondary structure prediction of proteins. With varying window sizes of neighboring amino acid information, the information is extracted and passed back and forth between the Neural Net and the Bayesian Inference process until the posterior probability of the secondary structure converges.

• Journal of Korea Technology Innovation Society
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• v.8 no.1
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• pp.94-115
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• 2005

The purpose of this study is to evaluate the economic value of a biotechnology in the middle of R&D and to examine strategies to manage a variety of risks and uncertainties intrinsic in research and development of biotechnologies through economic valuation in consideration of technological and industrial characteristics of the technology. To do this, this study analyzes the probability of commercial success of the technology development in qualitative terms, evaluates the quantitative value of the technology on the basis of a determined model, and proposes the implications on R&D strategy. In concrete, this study analyzes the economic value of the technology by constructing a decision tree reflecting the characteristics of the R&D process of the technology and draw the implications on the future R&D strategies of the technology.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1155-1162
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• 2004

This research proposes a new risk analysis method in order to guarantee successful performance of construction projects. The proposed risk analysis methods consists of four phases. First step, AHP model can help contractors decide whether or not they bid for a project by analysing risks involved in the project. Second step, the influence diagraming, decision tree and Monte Carlo simulation are used as tools to analyze and evaluate project risks quantitatively. Third step, Monte Carlo simulation is used to assess risk for groups of activities with probabilistic branching and calendars. Finally, Fuzzy theory suggests a risk management method for construction projects, which is using subjective knowledge of an expert and linguistic value, to analyze and quantify risk. The result of study is expected to improve the accuracy of risk analysis because three factors, such as probability, impact and exposure, for estimating membership function are introduced to quantify each risk factor. Consequently, it will help contractors identify risk elements in their projects and quantify the impact of risk on project time and cost.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.408-416
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• 2005

Quality of service (QoS) provision is an important and indispensable function for multi-service wireless networks. In this paper, we present a new scheduling/admission control frame­work, including an efficient rate-guaranteed opportunistic scheduling (ROS) scheme and a coordinated admission control (ROS­CAC) policy to support statistic QoS guarantee in multi-service wireless networks. Based on our proposed mathematical model, we derive the probability distribution function (PDF) of queue length under ROS and deduce the packet loss rate (PLR) for individual flows. The new admission control policy makes admission decision for a new incoming flow to ensure that the PLR requirements of all flows (including the new flow) are satisfied. The numerical results based on ns-2 simulations demonstrate the effectiveness of the new joint packet scheduling/admission control framework.

• Korean Management Science Review
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• v.32 no.2
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• pp.125-143
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• 2015

When studying the film industry, researchers have seldom addressed the dynamic interaction between marketing information and word of mouth in the motion picture industry mainly because of the limitation of traditional research methodologies. This study explores integration and competition among important variables influencing on audience's choice on movie selection, particularly by using a new method of agent-based modeling including competitive environment. Decision process of moviegoer composed of transition probability based on multinomial logit model, considering marketing and box-office information, critique, and word of mouth from other moviegoers. After validating the fitness of market share among released movies, this study conducted a set of simulation experiments considering several variables such as market size, change of weight between variables, and movie performance under competition. Propositions are derived from the simulation results is also suggested for future research.

• Journal of Technology Innovation
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• v.10 no.2
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• pp.69-90
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• 2002

This paper investigates the determinants of the firm's decision to carry out innovative activities in terms of the resource-based view(RBV) in strategic management. Two types of resources are distinguished: tangible(financial autonomy, firm size, capital intensity) and intangible(human resource, entrepreneurship, and commercial resource). R&D intensity and patent statistics are used as proxies for innovative activity. Specific hypotheses about their effect on the probability of a firm carrying out innovative activities are derived and tested on a sample of 337 listed firms in Korean manufacturing industry for the year 1999, using the logistic regression model. Empirical findings suggest that firm size and human resource are the main determinants of firm's internal innovative activities. The results show that the hypotheses concerning financial autonomy, debt ratio, capital intensity, entrepreneurship, and commercial resource are rejected.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.395-398
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• 2004

It is effective and desirable for a proper customer relational management(CRM) to send an email of product sales' advertisement bills for the prospective customers rather than to send spam mails for non specific customers. This study identifies the prospective customers with high probability to buy the specific products using Artificial Neural Network(ANN) and Induction Rule(IR) technique. We suggest an integrated model, IRANN of ANN and IR of decision tree program C5.0 and, also compare and analyze the accuracy of ANN, IR, and IRANN each other.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.104-118
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• 2003

It has been criticized that conventional human reliability analysis (HRA) methodologies for probabilistic safety assessment (PSA) have been focused on the quantification of human error probability (HEP) without detailed analysis of human cognitive processes such as situation assessment or decision-making which are crticial to successful response to emergency situations. This paper introduces a new human reliability analysis (HRA) methodology, AGAPE-ET (A guidance And Procedure for Human Error Analysis for Emergency Tasks), focused on the qualitative error analysis of emergency tasks from the viewpoint of the performance of human cognitive function. The AGAPE-ET method is based on the simplified cognitive model and a taxonomy of influencing factors. By each cognitive function, error causes or error-likely situations have been identified considering the characteristics of the performance of each cognitive function and influencing mechanism of PIFs on the cognitive function. Then, overall human error analysis process is designed considering the cognitive demand of the required task. The application to an emergency task shows that the proposed method is useful to identify task vulnerabilities associated with the performance of emergency tasks.