• Title/Summary/Keyword: Value maximization

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An Investigation on the Effect of Utility Variance on Choice Probability without Assumptions on the Specific Forms of Probability Distributions (특정한 확률분포를 가정하지 않는 경우에 효용의 분산이 제품선택확률에 미치는 영향에 대한 연구)

  • Won, Jee-Sung
    • Korean Management Science Review
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    • v.28 no.1
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    • pp.159-167
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    • 2011
  • The theory of random utility maximization (RUM) defines the probability of an alternative being chosen as the probability of its utility being perceived as higher than those of all the other competing alternatives in the choice set (Marschak 1960). According to this theory, consumers perceive the utility of an alternative not as a constant but as a probability distribution. Over the last two decades, there have been an increasing number of studies on the effect of utility variance on choice probability. The common result of the previous studies is that as the utility variance increases, the effect of the mean value of the utility (the deterministic component of the utility) on choice probability is reduced. This study provides a theoretical investigation on the effect of utility variance on choice probability without any assumptions on the specific forms of probability distributions. This study suggests that without assumptions of the probability distribution functions, firms cannot apply the marketing strategy of maximizing choice probability (or market share), but can only adopt the strategy of maximizing the minimum or maximum value of the expected choice probability. This study applies the Chebyshef inequality and shows how the changes in utility variances affect the maximum of minimum of choice probabilities and provides managerial implications.

Efficient Adaptive Algorithms Based on Zero-Error Probability Maximization (영확률 최대화에 근거한 효율적인 적응 알고리듬)

  • Kim, Namyong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.5
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    • pp.237-243
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    • 2014
  • In this paper, a calculation-efficient method for weight update in the algorithm based on maximization of the zero-error probability (MZEP) is proposed. This method is to utilize the current slope value in calculation of the next slope value, replacing the block processing that requires a summation operation in a sample time period. The simulation results shows that the proposed method yields the same performance as the original MZEP algorithm while significantly reducing the computational time and complexity with no need for a buffer for error samples. Also the proposed algorithm produces faster convergence speed than the algorithm that is based on the error-entropy minimization.

Maximization of Efficiency of IPMSM by Quasi-Newton Method (Quasi-Newton법을 이용한 IPMSM의 효율 최적화 설계)

  • Baek, Sung-min;Park, Byung-Jun;Kim, Yongn-Tae;Kim, Gyu-Tak
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.10
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    • pp.1292-1297
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    • 2018
  • In this paper, efficiency optimization design of 600W class IPMSM was performed by using Quasi-Newton method. The output was limited to 600W to meet the same output as the basic model. The behavior of each variable as the design progressed was judged on the efficiency, which is the target value through correlation analysis. The design variables were set as the width of the stator, the position of the permanent magnet from the end of the rotor, the thickness of the permanent magnet, and the width of the permanent magnet.

A Study on the Management of International Fishery Resources using Cooperative Game Theory (협조적 게임이론을 이용한 국가 간 수산자원관리에 관한 연구)

  • Choi, Jong-Du;Cho, Jung-Hee
    • Ocean and Polar Research
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    • v.30 no.2
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    • pp.173-180
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    • 2008
  • This study demonstrates that cooperative management can provide more benefits than noncooperative management for Korea and Japan fishery. We have studied one management strategy, namely, fishing under joint maximization of net benefits in coastal waters of two countries, using a cooperative game theory. The present net return under non-cooperation amounts to 420,255 million won. However, if two countries cooperate one with another, this figure can get to 2,636,565 million won. We consider this to be an important conclusion as close management relationships have developed between the two countries since the establishment of the EEZ in 1996. The results of the study can also help balance resource conservation and the appropriate catch quota in each country.

Role of Decision Support Systems in Marketing Management

  • Arshi Naim;Kholood Alqahtani
    • International Journal of Computer Science & Network Security
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    • v.24 no.8
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    • pp.153-158
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    • 2024
  • This paper is an extended paper showing the role of Decision Support Systems (DSS) in other fields of Marketing Management (M.Mgnt). DSS facilitates in decision making many M.Mgnt concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model.

A New Fast EM Algorithm (새로운 고속 EM 알고리즘)

  • 김성수;강지혜
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.10
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    • pp.575-587
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    • 2004
  • In this paper. a new Fast Expectation-Maximization algorithm(FEM) is proposed. Firstly the K-means algorithm is modified to reduce the number of iterations for finding the initial values that are used as the initial values in EM process. Conventionally the Initial values in K-means clustering are chosen randomly. which sometimes forces the process of clustering converge to some undesired center points. Uniform partitioning method is added to the conventional K-means to extract the proper initial points for each clusters. Secondly the effect of posterior probability is emphasized such that the application of Maximum Likelihood Posterior(MLP) yields fast convergence. The proposed FEM strengthens the characteristics of conventional EM by reinforcing the speed of convergence. The superiority of FEM is demonstrated in experimental results by presenting the improvement results of EM and accelerating the speed of convergence in parameter estimation procedures.

Learning and Propagation Framework of Bayesian Network using Meta-Heuristics and EM algorithm considering Dynamic Environments (EM 알고리즘 및 메타휴리스틱을 통한 다이나믹 환경에서의 베이지안 네트워크 학습 전파 프레임웍)

  • Choo, Sanghyun;Lee, Hyunsoo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.5
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    • pp.335-342
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    • 2016
  • When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.

The Influence of Customer Satisfaction on Market Value of the Corporate (고객만족도가 기업가치에 미치는 영향)

  • Bae, Jungho;Lee, Hee-Tae
    • Journal of Distribution Science
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    • v.16 no.10
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    • pp.55-64
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    • 2018
  • Purpose - The most important goal of corporate management is the maximization of firm value in the market. Executives of companies are making effort to increase corporate value and initiate various management strategies, which is to develop the products or service with value. Through these efforts, consumer satisfaction grows and loyalty increases, which leads to the positive change of customer satisfaction index. The purpose of this research is to find out the abnormal return after the KCSI(Korean Customer Satisfaction Index) is announced. Research design, data, and methodology - This research data is collected from 11 years' stock price in KOSPI market and KCSI. The authors analyze the abnormal return triggered by the announcement of KCSI through the event study. Results - First, newly enlisted companies in the KCSI show statistically significant short-term abnormal rate of return. Second, the value of the customer satisfaction index is not the level of customer satisfaction but the direction of the change in the CSI. Conclusion - Customer satisfaction has the important intangible asset in the marketing area. However, firms' investment for CS is not an easy decision, because of the difficulty to measure the effect on corporate market value. This research investigates the change of the market value after the announcement of KCSI. Based on the results, firms have to keep trying to increase KCSI relative to the previous year. And the small company has to struggle for being newly listed in the KCSI.

Modeling the Relationship between Expected Gain and Expected Value

  • Won, Eugene J.S.
    • Asia Marketing Journal
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    • v.18 no.3
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    • pp.47-63
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    • 2016
  • Rational choice theory holds that the alternative with largest expected utility in the choice set should always be chosen. However, it is often observed that an alternative with the largest expected utility is not always chosen while the choice task itself being avoided. Such a choice phenomenon cannot be explained by the traditional expected utility maximization principle. The current study posits shows that such a phenomenon can be attributed to the gap between the expected perceived gain (or loss) and the expected perceived value. This study mathematically analyses the relationship between the expectation of an alternative's gains or losses over the reference point and its expected value, when the perceived gains or losses follow continuous probability distributions. The proposed expected value (EV) function can explain the effects of loss aversion and uncertainty on the evaluation of an alternative based on the prospect theory value function. The proposed function reveals why the expected gain of an alternative should exceed some positive threshold in order for the alternative to be chosen. The model also explains why none of the two equally or similarly attractive options is chosen when they are presented together, but either of them is chosen when presented alone. The EV function and EG-EV curve can extract and visualize the core tenets of the prospect theory more clearly than the value function itself.

Optimal k Value for the Profit Maximizing in the k out of n : open & close Systems

  • Oh, Chung Hwan;Lee, Jong Chul
    • Journal of Korean Society for Quality Management
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    • v.21 no.1
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    • pp.144-151
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    • 1993
  • This Paper shows a special case of the optimization criterion is to make the maximum profit in the system reliability of the k out of n open & close structure. Especially, the number of the optimal k is determined for the profit maximization in system reliability by deriving several properties of the optimal k out of n systems in one of four possible styles(closed & opened).

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