• Title/Summary/Keyword: Market-based Learning

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How to Build a Learning Capability for Innovation? A Framework of Market-Based Learning Process

  • Lee, Hyun Jung;Park, Jeong Eun;Pae, Jae Hyun
    • Asia Marketing Journal
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    • v.17 no.1
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    • pp.27-53
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    • 2015
  • Learning organization has been an important issue in both management and marketing areas. Also learning capability is a key construct of innovation process in a firm. Especially, in marketing context, several researchers have studied market-based learning and its relation with performance. Previous studies have shown that market-based learning has a positive impact on overall firm performance. However, there has been inconsistency in the concept of market-based learning itself and its relationships with antecedents and consequences. Given this conflicting and inconsistent results of previous research, this study has two main objectives. First, this paper proposed a conceptual framework that marketbased learning has two types of processes and each types of market-based learning will generate different types of performance. Second, the mediating role of marketing capability in learning-performance link is proposed. The proposed conceptual framework shows that organizations which have marketbased learning for innovation management can enjoy ambidextrous firm performance on both side of effectiveness and efficiency via marketing capability. Moreover our research model proposes key drivers of market based organizational learning.

The Roles of Market-Based Learning and Customer Orientation in Shaping Effective Selling Behavior and Efforts

  • Park, Jeong Eun;Kim, Seongjin;Lee, Sungho
    • Asia Marketing Journal
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    • v.11 no.2
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    • pp.37-51
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    • 2009
  • Although previous studies have made significant progress in adaptive selling behavior (ASB), few studies have considered salesperson's customer orientation (CO) and learning behavior as determinants of effective sales management (ASB and relationship-making efforts), despite the discussion of important roles of these constructs. The authors test not only the relationships of salesperson's CO and market-based learning behavior to ASB and relationship-making efforts, but also the effects of ASB on relationship-making efforts and performance. The results of the study, which is done with samples of salespeople from Korean companies, indicate that salesperson's CO and market-based learning behavior are identified as significant determinants of ASB. Moreover, both salesperson's ASB and relationship-making efforts have significant effects on sales performance. On the other hand, as per salesperson's relationship-making efforts, salesperson's CO has a positive effect, but salesperson's market-based learning behavior and ASB do not influence his or her relationship-making efforts, which suggest a provocative possibility of conceptualization regarding the relationship between ASB and relationship management efforts.

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Analysis of Trends of Medical Image Processing based on Deep Learning

  • Seokjin Im
    • International Journal of Advanced Culture Technology
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    • v.11 no.1
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    • pp.283-289
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    • 2023
  • AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

The Relationships among Market Orientation, Learning Orientation, IT Support for Resource, IT Support for Strategy, and Performance in Export Firms (수출기업의 시장지향성 및 학습지향성이 성과에 미치는 영향 - 기업의 정보기술 활용을 중심으로 -)

  • Hwang, Kyung-Yun
    • International Commerce and Information Review
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    • v.12 no.1
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    • pp.271-295
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    • 2010
  • In this study, we investigate the relationships among organizational market orientation, learning orientation, information technology(IT) support for firm resource, IT support for strategy, and balanced scorecard(BSC) performance in export firms. The development of the research model is based on the empirical studies of strategy and resource-based view. The data from the survey was analyzed using Partial Least Squares(PLS). The results from the empirical model suggest that IT support for firm resource is effected by market orientation and learning orientation. And, IT support for strategy is enhanced by IT support for firm resource. Finally, BSC performance of export firms is effected by IT support for strategy.

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Supervised Learning-Based Collaborative Filtering Using Market Basket Data for the Cold-Start Problem

  • Hwang, Wook-Yeon;Jun, Chi-Hyuck
    • Industrial Engineering and Management Systems
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    • v.13 no.4
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    • pp.421-431
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    • 2014
  • The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

Suggestions for the Development of RegTech Based Ontology and Deep Learning Technology to Interpret Capital Market Regulations (레그테크 기반의 자본시장 규제 해석 온톨로지 및 딥러닝 기술 개발을 위한 제언)

  • Choi, Seung Uk;Kwon, Oh Byung
    • The Journal of Information Systems
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    • v.30 no.1
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    • pp.65-84
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    • 2021
  • Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

A Case Study on the Opportunity Realization Process of the i-KAIST Venture: Entrepreneurial Intent, Organizational Learning, and Technology/Market Domain Shifts (기업가적 의지, 조직학습, 기술/시장 변화에 의한 대학발 창업 벤처기업의 기회실현 과정: i-KAIST 탐색적 사례연구)

  • Kwon, Sang Jib;Baek, Seoin;Kim, Hee Tae;Chang, Hyun Joon;KIm, Seong Jin
    • Knowledge Management Research
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    • v.14 no.5
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    • pp.55-79
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    • 2013
  • This study primarily focused on the opportunity realization process of a korean venture firm based on university. This research examined the relationship between entrepreneurial intent and organizational learning produced in a sustainable opportunity realization process with technology/market domain shifts. Therefore, this research explores the determinants of sustainable growth of a venture firm at the organizational level and suggests optimal solutions for promoting entrepreneurial intent and opportunity realization for many entrepreneurs. The results showed that CEO's entrepreneurial intent is a key driving factor that can positive impacts on opportunity recognition and organizational learning based on university's expertise. Furthermore, the orientation of a entrepreneur can affect venture's technology/market domain shift through the advanced technological knowledge of university. In conclusion, this research sheds light on the growth of a venture firm based on university suggesting more customized solutions for many entrepreneurs. Implications for the results and the future directions are discussed.

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FOREX Web-Based Trading Platform with E-Learning Features

  • Yong, Yoke Leng;Lieu, Shang Qin;Ngo, David;Lee, Yunli
    • Journal of Multimedia Information System
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    • v.4 no.4
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    • pp.271-278
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    • 2017
  • There has been an influx of traders and researchers eager to gain a better understanding of the market due to the rapid growth of the FOREX market. Traders with varying degree of experience are also often inundated with information, analysis methods as well as trading rules when making a trading decision on buying/selling a currency exchange pair. Thus, this paper reviews the current computational tools and analysis methods used within the FOREX trading community and proposes the development of a web-based trading platform with e-learning features to support beginners. Novice traders could also benefit from the use of the proposed e-learning trading platform as it helps them gain valuable knowledge and navigate the FOREX market in real-time. Even experienced traders would find it useful as the platform could be used for actual trading and acts as a reference point to understand the reasoning behind the certain technical analysis implementation that are still unclear to them.

Development of Export Volume and Export Amount Prediction Models Based on Supervised Learning (지도학습 기반 수출물량 및 수출금액 예측 모델 개발)

  • Dong-Gil Na;Yeong-Woong Yu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.2
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    • pp.152-159
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    • 2023
  • Due to COVID-19, changes in consumption trends are taking place in the distribution sector, such as an increase in non-face-to-face consumption and a rapid growth in the online shopping market. However, it is difficult for small and medium-sized export sellers to obtain forecast information on the export market by country, compared to large distributors who can easily build a global sales network. This study is about the prediction of export amount and export volume by country and item for market information analysis of small and medium export sellers. A prediction model was developed using Lasso, XGBoost, and MLP models based on supervised learning and deep learning, and export trends for clothing, cosmetics, and household electronic devices were predicted for Korea's major export countries, the United States, China, and Vietnam. As a result of the prediction, the performance of MAE and RMSE for the Lasso model was excellent, and based on the development results, a market analysis system for small and medium sellers was developed.

A Study on the Advancement of Korean Companies into Chinese e-Learning Market (국내 기업의 중국 이러닝 시장 진출 방안 연구)

  • Lee, In-Sook
    • Journal of Digital Contents Society
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    • v.14 no.2
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    • pp.263-274
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    • 2013
  • As the numbers of Internet users and the growth of education market along with the generalization of distance study increase, e-Learning industry in China is growing rapidly more than 20% each year. However, domestic e-Learning industry for entry to the Chinese market is showing inadequate result even though its potential growth in China and their scale of industry is near about 3 trillion won. A type of this industry is combined with Information Technology (IT) and education industry and their complex factors need to be considered because of the country's education policy and ICT infrastructure. In addition to these factors, sometimes main agents can be the government or a private organization and they form different circumstances each other. Therefore, it is required to have an in-depth study of the entering the Chinese market based on an accurate analysis for Chinese education and culture. In this research, it will focus on the current state of e-Learning market in Korea and China after studying the e-Learning system through the existing reference research. Moreover, this research will propose a method of the entry for the Chinese e-Leaning market through a case study from domestic and foreign companies.