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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Management Science and Financial Engineering
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The Korean Operations and Management Science Society
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Volume & Issues
Volume 10, Issue 2 - Nov 2004
Volume 10, Issue 1 - May 2004
Selecting the target year
A Simulation based Approach for Group Decision-Making Support
Kwahk, Kee-Young ; Kim, Hee-Woong ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 1~23
The changing structure of organization and the increasing diversity of business have forced organizations to have abilities to coordinate dispersed business activities. They have required cooperation and coordination among the functional units in the organization which should involve group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative process of group decision-making, they often lack the features supporting the dynamic complexity issue frequently occurring at group decision-making processes. This results in cognitive unfit between the group decision-making tasks and their supporting tools, bringing about mixed results in their effects on group decision-making. This study proposes system dynamics modeling as a group decision-making support tool to deal with the group decision -making tasks having properties of dynamic complexity in terms of cognitive fit theory.
Two-layer Investment Decision-making Using Knowledge about Investor′s Risk-preference： Model and Empirical Testing.
Won, Chaehwan ; Kim, Chulsoo ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 25~41
There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.
Examining Incentives to License Technology in U.S. High-Tech Industries
Kim, Young-Jun ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 43~52
This paper empirically investigates potential factors that might affect firms' incentives to license out technology. The analysis is done with the help of a panel data set of observed licensing transactions involving U.S. public companies in high-technology industries. The important explanatory factors relate to the firm characteristics such as the company's stock of technological knowledge (patent stock). prior involvement in technology licensing. the company size, R&D intensity and capital expenditure. The results suggest that there seems to be significant inter-sectoral differences as well as similarities in determinants of the propensity to transfer technology through licensing agreements.
On Finding an Optimal Departure Time in Time-Dependent Networks
Park, Chan-Kyoo ; Lee, Sangwook ; Park, Soondal ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 53~75
Most existing studies on time-dependent networks have been focused on finding a minimum delay path given a departure time at the origin. There, however, frequently happens a situation where users can select any departure time in a certain time interval and want to spend as little time as possible on traveling the networks. In that case. the delay spent on traveling networks depends on not only paths but also the actual departure time at the origin. In this paper, we propose a new problem in time-dependent networks whose objective is to find an optimal departure time given possible departure time interval at the origin. From the optimal departure time, we can obtain a path with minimum delay among all paths for possible departure times at the origin. In addition, we present an algorithm for finding an optimal departure time by enumerating trees which remain shortest path tree for a certain time interval.
Dynamic Matching Algorithms for Internet-based Logistics Brokerage Agents
Jeong, Keun-Chae ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 77~96
In this paper, we present a dynamic matching methodology for the logistics brokerage agent that intermediates empty vehicles and freights registered to the logistics e-marketplace by car owners and shippers. In this matching methodology, two types of decisions should be made： one is when to match freights and vehicles and the other is how to match freights and vehicles at that time. We propose three strategies for deciding when to match, ie. real time matching (RTM) , periodic matching (PM), and fixed matching (FM) and use Hungarian method for solving the how-to-match problem. In order to compare the performance of the when-to-match strategies, computational experiments are done and the results show that the waiting-and-matching strategies, PM and FM, give better performance than real time matching strategy, RTM. We can expect that the suggested matching methodology may be used as an efficient and effective tool for the brokerage agent in the logistics e-marketplaces.
A Cutting-plane Generation Method for a Variable-capacity (0,1 )-Knapsack Problem with General Integer Variables
Lee, Kyungsik ;
Management Science and Financial Engineering, volume 10, issue 1, 2004, Pages 97~106
In this paper, we propose an effective cut generation method based on the Chvatal-Gomory procedure for a variable-capacity (0,l)-Knapsack problem with two general integer variables. We first derive a class of valid inequalities for the problem using Chvatal-Gomory procedure, then analyze the associated separation problem. Based on the results, we show that there exists a pseudo-polynomial time algorithm to solve the separation problem. By analyzing the theoretical strength of the inequalities which can be generated by the proposed cut generation method, we show that generated inequalties define facets under mild conditions. We also extend the result to the case in which a nontrivial upper bound is imposed on a general integer variable.