인도의 투자환경과 우리나라 기업의 대인도 투자현황 및 투자 관리 방안에 관한 연구

남경두(Nam Kyung-Doo),한준우(Han Joon-Woo) 한국상품학회 2004 商品學硏究 Vol.- No.31

This research is to study how Korean firms should manage FDI risks, and also to examine the various ways of the risk management when investing in India. In the case of company trait, the scale of the company, its export share and the age of the firm when investing in India do have an effect on the risk. The risk level is lower when the company is large, exports more and has a long history operating in India. As for the management of company trait, the Korean firms investing in India should assess the risk, increase export share and pay close attention to the risk at the beginning stage of the investment. In the case of industry trait, the risk is being affected by the diversification of the business, as well as the items and dispersion of production line. As for the management of industry trait, Korean firms investing in India are advised to disperse business sites and production lines, to diversify handling items as well as buying sources. In the case of investment environment trait, the risk is increased when the country risk is high, market situation is unstable and labor is unrest. As for the management of environment trait, Korean firms investing in India should acquire investment insurance, manage labor properly and adjust to the different cultures in India. It has been revealed that India's social environment such as caste, religion, and culture are very different from Korea's. As a result, it might be difficult to maintain a good relationship with an Indian business partner. India's potential is estimated to be very high, however the corruption level of government officials is also pretty high and the government's policies are unpredictable.

한·중 소비자의 스마트폰 채택 관련 지각된 선택행동에 대한 비교연구

남경두(Kyung-Doo Nam),조현준(Hyun-Jun Cho),서진(Jin Seo),이진우(Jin-Woo Lee) 한국관세학회 2011 관세학회지 Vol.12 No.4

Based on the TAM model, this study reviews factors affecting consumers’ perceived choice and attitudes toward using smartphones. The independent variables are classified into smartphone-specific characteristics (function & properties, security, and applications), perceived cost, and social influence. The parameters are composed of ease of use, usefulness, and satisfaction. In order to compare Chinese consumers with Korean ones, this paper empirically tests survey data for 318 residents in Beijing and Seoul. As for the result of hypothesis testing, usefulness as well as satisfaction appear to have statistically significant influences on the purchase intention in both China and Korea. But in the case of Korea, the influence of satisfaction appears larger; in China the usefulness appears to have greater influence. As for Korean consumers, the interest in the application appears relatively larger, whereas Consumers in China are found to respond more strongly to the perceived costs. Accordingly, among the traditional 4P marketing mix factors, the product factor should be more noted for Korean consumers, whereas the price factor should be relatively more important for Chinese ones.

국제마케팅 분석을 위한 뉴럴네트웍의 응용

남경두(Kyung Doo Nam) 건국대학교 경제경영연구소 1996 상경연구 Vol.21 No.1

In the fiercely competitive global marketplace of the 1990s, nothing is more powerful than information or knowledge about customers’ individual practices and preferences. Accordingly, international marketers are collecting mountains of data to forecast marketing requirements ; the search is on for social, economic, and consumer trends within specific international markets. Given that good information is the key to effective marketing decisions, the international marketer with better information will surely have a competitive advantage. The purpose of this paper is to demonstrate the potential of neural networks(NNs) for international marketing analysis. Neural networks are computer-based simulations of living nervous systems which simulate the intuition and judgement necessary for unstructured decision problems faced by top-level international marketing managers. Some potential applications of neural networks to international marketing are discussed. Also, the potential of using neural networks in lieu of traditional statistical methods in forecasting airline passenger traffic is explored. Neural networks offer great potential for improvements in solving a host of marketing problems, particularly problems characterized by “fuzzy” data such as many problems faced in the global marketplace. A few considerations that have proved useful in international marketing analysis are presented. First, neural networks require great quantities of historical data for learning. So, be certain to have enough data on hand to satisfy NN requirements. Second, use the neural networks to solve those problems for which they are best adapted. Generally, the neural networks perform well when no theoretical model or underlying mathematical function which can be easily determined is available. Finally, competitive-minded international markets will find neural networks, an excellent alternative to traditional statistical techniques for the many real-world problems to which NNs apply.

부동산 분석을 위한 뉴럴네트웍의 응용

남경두(Kyung Doo Nam) 건국대학교 경제경영연구소 1997 상경연구 Vol.22 No.2

This study shows the potential of neural networks for real estate analysis. Also, the study compares the performance of neural networks with that of time series regression analysis as illustration of the appropriate use of real estate analysis. Neural networks are computer-based simulations of living nervous systems and have a mathematical basis. Neural networks learn from experiences, generalize from previous examples to new ones, and abstract essential characteristics from noisy and incomplete inputs. It is required that a user have sufficient expertise to decide the number of neurons in the hidden layers, the learning rate, and the momentum. The selection of these factors is problem-dependent and, at this time, there are no established methods for identifying the appropriate values. Generally, using a small number of neurons in the hidden layer increases the number of iterations required to train the neural network and reduces the predictive ability of the neural network. On the other hand, the use of too many neurons in the hidden layer extends the training time and allows the neural network to memorize rather than generalize the training data. The performance of the neural network is affected by its training time. During the first part of training, the performance of the neural network on the training data and testing data improves. During the next part of training, the performance of the neural network on the training data improves continuously. However, the performance of the neural network on the testing data may become worse because the neural network may memorize the training data, and it may cause nongeneralization of predictive ability of the neural network on the testing data. The empirical results for the data of housing price index are that the neural networks performed better than time series regression on the basis of MAD(mean absolute deviations). Also, the F-tests showed that there were statistical differences between them at 0.05 significance level.

예비무역인의 영어학습동기가 영어학습전략 사용에 미치는 영향에 관한 실증 연구

남경두(Kyung Doo Nam),김현정(Hyun Jung Kim),김지혜(Ji Hye Kim) 한국무역연구원 2015 무역연구 Vol.11 No.2

The purpose of this study is to investigate the differences and correlation between English learning motivation and English learning strategies of two groups of Korean university students categorized as future trade experts and non-trade experts. This study focused on business education and training program sponsored and operated by the korean government for 7 years for the purpose of fostering future trade specialists known as GTEP(Global Trade Experts Incubation Program) and defined GTEP participants as future trade experts. The test for English learning motivation which was set up with 8 questions consisting of 4 internal motivations and 4 external motivations, was made under the special conditions of the GTEP curriculum. Oxford's test(1990) was applied in the analysis of learning strategies. Participants of this study consisted of 266 university students categorized into two groups: 133 future trade experts and 133 non-trade experts. In terms of motivation, results showed future trade experts having higher internal/external motivations than non-trade experts. In the analysis of strategies, the future trade experts group showed a correlation between both learning motivations and learning strategies while the non-trade experts group showed a correlation only between internal motivation and strategies. One interesting finding is that the negative correlation between external motivation and strategies was found in the future trade experts group. These results indicate that GTEP has led to advanced English proficiency in the case of future trade experts. But, there still remains some tasks that need to be done to help students internalize their learning motivations and stimulate the usage of English learning strategies.

예비무역인의 인터넷무역 전문지식과 활용방법이 무역성과에 미치는 영향에 관한 실증연구

남경두(Kyung-Doo Nam),김병유(Byung-Yu Kim),권윤희(Yun-Hee Kwon) 국제e-비즈니스학회 2012 e-비즈니스 연구 Vol.13 No.5

우리나라 기업의 대인도 투자 리스크 관리에 관한 실증적 연구

남경두(Kyung-Doo Nam),한준우(Joon-Woo Han) 한국무역학회 2004 貿易學會誌 Vol.29 No.2

Application of Artificial Neural Networks for Statistical Quality Control

Nam, Kyung-Doo(남경두) 대한경영학회 1999 大韓經營學會誌 Vol.21 No.-

한국 무역업체의 알리바바 무역e-Marketplace 활용동기 및 성과에 관한 실증연구

남경두(Kyung-Doo Nam),김종환(Jong Hwan Kim) 한국관세학회 2011 한국관세학회 학술대회 Vol.2011 No.12

Performance Comparison of Neural Networks and Univerariate Linear Regression Models in the Presence of an Outlier

Kyung Doo Nam(南炅杜) 건국대학교 경제경영연구소 1995 商經硏究 Vol.20 No.1

최근에 컴퓨터의 발달에 따라 컴퓨터를 기본으로 한 여러 가지 통계분석방법이 개발되고 있다. 전통적인 통계분석의 약점을 보완한 새로운 컴퓨터 인공지능기법 중에 하나가 뉴럴네트웍(Neural Network)이다. 뉴럴네트웍은 인공지능(Artificial Intelligence)테크닉의 한 분야로서 인간의 두뇌기능을 근거로 한 컴퓨터 시스템이다. Wasserman에 의하면 뉴럴네트웍은 인간처럼 경험으로부터 배울 수 있고, 과거의 패턴으로부터 새로운 패턴을 이끌 수 있으며, 이상값 또는 Noisy Data로부터 어떤 근본적인 특성을 도출할 수도 있다. 뉴럴네트웍은 전통적인 통계기법처럼 전제가 되는 가정을 요구하지 않는다. 예를 들면 과거의 자료로 통계적 방법에 의해 어떤 변수를 다른 변수로 예측하는 과정을 회귀분석이라고 한다. 그러나 이 회귀분석의 시행은 다음과 같은 회귀모형의 측정오차에 대한 전제조건이 충족되어야 한다. ① 측정오차들은 서로 독립이 되어야 한다. ② 측정오차들은 정규분포를 가져야 한다. ③ 측정오차들의 분산은 일정해야 한다. 또한 뉴럴네트웍은 기존 통계분석처럼 복잡한 수학공식이나 이론적 근거의 이해를 요구하지 않는다. 전통적인 통계분석방법에 비해서 뉴럴네트웍은 다음과 같은 경우에 장점을 보인다. ① 주어진 Data의 패턴이 비선형일 경우 ② 주어진 통계모델의 가정이 위반될 경우 ③ 주어진 Data에 이상값 또는 부적절한 Data가 존재할 경우 ④ On-line 의사결정이 필요한 경우 일반적으로 기존 통계분석방법이 주어진 Data 분석방법에 부적당한 경우 뉴럴네트웍은 여러 가지 통계적 예측분석에 유용하게 쓰일 수 있다. 이에 본 연구에서는 새로운 통계적 경영분석을 위한 뉴럴네트웍을 소개하고, 응용분야로서 이상값의 존재하에서 뉴럴네트웍과 단순회귀분석의 수행을 비교한다. 실증분석결과에 의하면 이상값의 존재하에서 표본의 크기가 증가될 때 뉴럴네트웍은 단순회귀분석보다 더 좋은 수행결과를 보여주었다. 그러나 표본의 크기가 작을 때 뉴럴네트웍은 회귀분석과 마찬가지로 이상값에 의하여 영향을 받았다.