• Title/Summary/Keyword: competition model

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Assessing Bank Competition in Nepal Using Panzar-Rosse Model

  • BUDHATHOKI, Prem Bahadur;RAI, Chandra Kumar;RAI, Arjun
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.759-768
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    • 2020
  • The purpose of this study is to assess the state of competition in Nepalese banking over the period from 2010 to 2019. This study employs panel data and a non-structural Panzar-Rosse model to measure the degree of competition in the Nepalese banking industry. The first reduced-form equation is applied to gauge competition, and the second model is used to test the long-run equilibrium in the banking market. The finding reveals that the Nepalese banking market is equilibrium in the long-run. It implies that the factor prices do not affect ROA in the long-run. The result of the H-statistic shows that the Nepalese banking system is operating under the state of perfect competition and is shifted from monopolistic competition to perfect competition. The reduced-form model reveals that the interest income is positive and significantly affected by factor prices. Similarly, the macroeconomic variable GDP growth is positively related to interest income. On the contrary, the bank's specific factors risk and the number of bank branches are inversely associated with the regressand. The outcomes of the study may be advantageous to the policymakers, especially to Nepal Rastra Bank to implement monetary policy and M&A policy for the stability and growth of the financial system of Nepal.

Computable General Equilibrium Analysis of Energy Markets with Imperfect Competition and Scale Economy (불완전경쟁 및 규모의 경제가 에너지 산업에 미치는 영향)

  • Park, Chang Won;Kim, Gene Uhc
    • Environmental and Resource Economics Review
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    • v.11 no.2
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    • pp.291-319
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    • 2002
  • This Paper investigates imperfect competition and economy of scale on Korean energy markets based on computable general equilibrium model. Some industries like energy sector have exhibited that their economies have strong economies of scale and imperfect competition. Thus these industrial organization facts should be incorporated into CGE model. In our model, non-competitive markets are adopted and compare these results with convention perfect competition model.

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Forecasting Model of Container Transshipment Traffic Volume in Northeast Asia (동북아시아 환적물동량 예측모델 연구)

  • Lee, Byoung-Chul;Kim, Yun-Bae
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.4
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    • pp.297-303
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    • 2011
  • Major ports in Northeastern Asia engage in fierce competition to attract transshipment traffic volume. Existing time series analyses for analyzing port competition relationships examine the types of competition and relations through the signs of coefficients in cointegration equations using the transshipment traffic volume results. However, there are cases for which analyzing competing relationships is not possible based on the results of the transshipment traffic volume data differences and limitations in the forecasting of traffic volume. Accordingly, we used the Lotka-Volterra (L-V) model,also known as the ecosystem competitive relation model, to analyze port competition relations for the long-term forecast of South Korean transshipment traffic volume.

Forecasting Next Generation Technology Using Lotka-Volterra Competition Model and Factors for Technology Substitution (기술대체 영향요인과 Lotka-Volterra 경쟁 모형을 이용한 차세대 기술 예측)

  • Kim, Hyein;Jeong, Yujin;Yoon, Byungun
    • Journal of Korea Technology Innovation Society
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    • v.20 no.4
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    • pp.1262-1287
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    • 2017
  • Recently, forecasting for next-generation technologies have influenced the competitiveness of companies. However, in previous studies, only extract factors influencing the adoption of technology have been investigated. Also, there are few researches on the importance of each decision factors or the competition between technologies. In this research, Lotka-Volterra model is used to confirm the technological competition in the new technology choice timing when the competition is intensified due to the emergence of new technologies. For purpose of this study, estimate the LVC model based on the data of the past competition and then derived the factors affecting the technology of competition and substitution from the literature survey. After that, we confirmed the factor value between the past and the present technology competition. The difference between the factor values derived from the previous step is used to revise the model estimated from the past data base. At this stage, regression analysis is used to derive the importance of each factor and use it as the weight. Through the correction model, the competitiveness is identified through 1:1 comparison with competition candidate technology and existing dominant design technology. In this research, we quantitatively propose the possibility that a specific technology can become a dominant design in the next generation, based on the difference in factor values and importance. This results will help the company's R&D strategy and decision making.

A Neural Network Combining a Competition Learning Model and BP ALgorithm for Data Mining (데이터 마이닝을 위한 경쟁학습모텔과 BP알고리즘을 결합한 하이브리드형 신경망)

  • 강문식;이상용
    • Journal of Information Technology Applications and Management
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    • v.9 no.2
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    • pp.1-16
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    • 2002
  • Recently, neural network methods have been studied to find out more valuable information in data bases. But the supervised learning methods of neural networks have an overfitting problem, which leads to errors of target patterns. And the unsupervised learning methods can distort important information in the process of regularizing data. Thus they can't efficiently classify data, To solve the problems, this paper introduces a hybrid neural networks HACAB(Hybrid Algorithm combining a Competition learning model And BP Algorithm) combining a competition learning model and 8P algorithm. HACAB is designed for cases which there is no target patterns. HACAB makes target patterns by adopting a competition learning model and classifies input patterns using the target patterns by BP algorithm. HACAB is evaluated with random input patterns and Iris data In cases of no target patterns, HACAB can classify data more effectively than BP algorithm does.

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A Dynamic Analysis on the Competition Relationships in Korean Stock Market Using Lotka-Volterra Model (Lotka-Volterra 모형을 이용한 국내 주식시장의 경쟁관계 동태적 분석)

  • Lee, Sung Joon;Lee, Deok-Joo;Oh, Hyungsik
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.1
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    • pp.14-20
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    • 2003
  • The purpose of this paper is an attempt to analyze the dynamic relationship between KSE and KOSDAQ, two competing markets in Korean stock market, in the viewpoint of competition. Lotka-Volterra model, one of well-known competitive diffusion model, is adopted to represent the competitive situations of Korean stock market and it is estimated using daily empirical index data of KSE and KOSDAQ during 1997~2001. The results show that there existed a predator-prey relationship between two markets in which KSE acted as a predator right after the emergence of KOSDAQ. This interaction was altered to a symbiotic relationship and finally to the pure competition relationship. We also perform an equilibrium analysis of the estimated Lotka-Volterra equations and, as a result, it is found that there is a market index equilibrium point that would be stable in the latest relationship.

Echelon Base Stock Policy with Outside Competition in a Two-Stage Supply Chain (외부 경쟁을 고려한 두 단계 공급체인에서의 단계기본재고수준의 결정)

  • Kim, Nam-Young
    • Journal of the Korean Operations Research and Management Science Society
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    • v.30 no.4
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    • pp.71-81
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    • 2005
  • This Paper focuses on the effects of outside competition on an optimal echelon base stock level in a two stage supply chain. This is new in that we have been studying the effects of inside competition within a supply chain up to now. It is known that the optimal echelon base stock level with inside competition within a supply chain is less than the global optimal echelon base stock level without inside competition. This is due to the ' public goods ' nature of inventory. That is, more inventory is better, but one wants the other to invest more, thus resulting in under-investment. However, this phenomenon becomes weaker as outside competition increases. We show that as outside competition becomes stronger, the ' public goods ' effects decrease and the optimal echelon base stock level increases. If the level of competition is sufficiently high, the optimal echelon base stock level goes even higher than the global optimal echelon base stock level. We develop a theoretical model for the analysis and conduct a numerical analysis.

ALMOST PERIODIC SOLUTION FOR A n-SPECIES COMPETITION MODEL WITH FEEDBACK CONTROLS ON TIME SCALES

  • Li, Yongkun;Han, Xiaofang
    • Journal of applied mathematics & informatics
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    • v.31 no.1_2
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    • pp.247-262
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    • 2013
  • In this paper, using the time scale calculus theory, we first discuss the permanence of a $n$-species competition system with feedback control on time scales. Based on the permanence result, by the Lyapunov functional method, we establish sufficient conditions for the existence and uniformly asymptotical stability of almost periodic solutions of the considered model. The results of this paper is completely new. An example is employed to show the feasibility of our main result.

Development of Fashion Retailing Store Type Attractiveness (FaRSTA) -Indirect Estimates Approach with Multiple Scale Items- (패션리테일링 점포유형별 쇼핑유인력(FaRSTA) 모델 개발에 대한 연구 -다속성 간접평가법 활용-)

  • Park, Jin Je;Lee, Jin Hwa
    • Journal of the Korean Society of Clothing and Textiles
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    • v.37 no.1
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    • pp.76-89
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    • 2013
  • The exploration of the interaction effect among the components of attractiveness is impossible; therefore, this study uses an indirect estimates approach with multiple scale items that can measure the interaction effect among the components of attractiveness to solve the problem of direct estimates. Previous studies focused on intra-store type competition as their subjects; subsequently, this study dealt with intra-store type competition as well as inter-store type competition in the competing and selecting activities among fashion retailing stores with different business models (such as department stores, road brand stores, discount stores, outlets and internet shopping malls). This study suggests a generalized model for shopping attractiveness of stores and proposes a fashion retailing store type attractiveness (FaRSTA) model instead of a simple relative importance between store selection standards.

A Measurement Way of Competition Power of Container Port: AHP and DEA Approach (컨테이너항만의 경쟁력 측정방법:AHP와 DEA접근)

  • 박길영;오성동;박노경
    • Journal of Korea Port Economic Association
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    • v.21 no.1
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    • pp.133-151
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    • 2005
  • The purpose of this paper is to investigate the international competition power between Korean ports and Chinese ports according to the port efficiency scores of DEA(Data Envelopment Analysis) by newly introducing the priority vector of AHP(Analytic Hierarchy Process) to the DEA method. Empirical analysis shows the followings: First, there was not big changes of DEA rankings when we use the input-oriented CCR and BCC models after introducing the AHP priority vectors to the input variables. Yantian Port's competition power was declined, but that of Busan Port was up in the BCC model. Second, there was some changes of DEA rankings when we use the output-oriented CCR and BCC models after introducing the AHP priority vectors to the output variables. Rankings of Dalian, Qingdao, Shanghai Ports were up. But Shekou, Yantian Ports showed the declined ranking position in the CCR model. In the BBC model, rankings of Shanghai and Busan Ports were up. But those of Shekou and Yantian Ports were declined. The main policy implication based on the findings of this study is that The Ministry of Maritime Affairs & Fisheries in Korea and China should introduce AHP and DEA approaches when they measure the international competition power by using the porrt efficiency scores of DEA.

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