• Title/Summary/Keyword: e-Learning Business

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Team Project Activity and Satisfaction in Business Education (경영학 수업에서 팀 프로젝트활동과 수업만족에 관한 연구)

  • Suk, Yeung-Ki
    • Journal of Digital Convergence
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    • v.12 no.7
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    • pp.217-227
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    • 2014
  • Since 2010, the universities in Korea have been faced severe difficulties on the selection of students and on the delivery of high quality education services, as the number of students is reduced and the college entrance rate is declined. To solve these problems, the universities have introduced the various and professional education services such as team-based projects, case study, e-learning, action learning, etc. The purpose of this study is to examine the effect of team-based project learning on the student's satisfaction in business education. The 4 factors(team cohesiveness, teamwork, team performance and goal achievement) are measured by using questionnaire survey and data are collected from 134 students(34 teams) for 4 subjects. The results show that the structure of team cohesiveness${\rightarrow}$teamwork${\rightarrow}$student's satisfaction is statistically significant, and that team performance and goal achievement are not significant. The student's satisfaction in team-based project learning would highly be related with team cohesiveness.

Innovation Patterns of Machine Learning and a Birth of Niche: Focusing on Startup Cases in the Republic of Korea (머신러닝 혁신 특성과 니치의 탄생: 한국 스타트업 사례를 중심으로)

  • Kang, Songhee;Jin, Sungmin;Pack, Pill Ho
    • The Journal of Society for e-Business Studies
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    • v.26 no.3
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    • pp.1-20
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    • 2021
  • As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

Design and Implementation of SMIL Authoring Tool for E-Learning Item Metadata (E-Learning용 문항 메타데이터 작성을 위한 SMIL 저작도구 설계 및 구현)

  • Lee, Dong-Su;Kim, Chul-Hyun;Park, Seung-Beom;Lee, Sang-Jun;Kim, Byung-Ki
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.05a
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    • pp.296-299
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    • 2008
  • E-Learning 환경에서 학습자에게 보다 정확한 맞춤형 교육 시스템을 제공하기 위하여 평가 문항 및 학습 문항의 난이도, 변별도 등과 같은 문항 정보 활용이 필요하다. 본 논문에서는 문항 난이도, 변별도의 수치를 메타데이터에 저장하고, 평가 문항 및 학습 문항을 저작할 수 있는 템플릿(Templates) 및 GUI(Graphical User Interface) 기반의 SMIL(Synchronized Multimedia Integration Language) 저작도구를 설계 구현 하였다. 구현한 시스템은 SMIL 문법을 모르는 교수자가 문항 난이도, 변별도를 메타데이터에 저장하고, 학습 문항을 쉽게 저작하는데 효율적이다. 또한 저작된 문항은 XML(Extensible Markup Language) 기반 메타데이터를 활용함으로서 다른 플랫폼과의 통합 관리 및 재사용에 용이하다.

A Decision Monitoring System for Machine Learning Based Dispatcher of Manufacturing Lines (제조라인의 학습기반 디스패처를 위한 디스패치 의사결정 평가 시각화시스템)

  • Huh, Jaeseok;Park, Jonghun
    • The Journal of Society for e-Business Studies
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    • v.25 no.1
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    • pp.1-12
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    • 2020
  • Recently, research using machine learning have shown remarkable results in various domains, leading to the fact that leaning-based dispatchers have intrigued interest in both academia and industry. To improve the performance of the dispatcher, each dispatch decision needs to be evaluated in detail. However, existing studies on visualization techniques for manufacturing lines have mainly focused on illustrating the performance indicators or abnormal patterns. In this paper, we propose a monitoring system that displays a variety of information about the manufacturing line along with alternatives at the time of each dispatching decision being made. Furthermore, the proposed system effectively represents the cause of the idle time of resources and the change of the performance index over time.

Predicting Reports of Theft in Businesses via Machine Learning

  • JungIn, Seo;JeongHyeon, Chang
    • International Journal of Advanced Culture Technology
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    • v.10 no.4
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    • pp.499-510
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    • 2022
  • This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

The Effect of Chat GPT's e-Service Quality on Learning Performance through Perceived Value and Innovation (Chat GPT의 e-서비스 품질이 지각된 가치와 혁신성을 통해 학습성과에 미치는 영향)

  • Park Chol-Hoon;Cho Ara;Chae Young il
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.707-719
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    • 2023
  • In the Fourth Industrial Revolution era, AI technologies, such as Chat GPT, have moved beyond assisting to actively analyzing data and providing solutions. This research assessed Chat GPT's e-service quality's influence on perceived value, innovativeness, and subsequent learning outcomes. Findings revealed that while ease of use and responsiveness weren't significant, safety and reliability were positively related to perceived value and innovativeness. A negative correlation was found between trustworthiness and perceived value. Users who saw Chat GPT as valuable and innovative experienced enhanced learning. The study emphasizes the need for guidelines in deploying Chat GPT academically. Given Chat GPT's recent introduction, further nuanced research is necessary.

The Effects of Franchise's Learning Orientation and Relationship Marketing Orientation on the Job Satisfaction (프랜차이즈 조직의 학습지향성과 관계마케팅지향성이 직무만족에 미치는 영향)

  • Hwang, Yoon-Yong;Seo, Chang-Sun;Choi, Soow-A
    • Journal of Distribution Science
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    • v.11 no.6
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    • pp.51-58
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    • 2013
  • Purpose - Nowadays, more than ever before, fierce competition, deep market segmentation, short product life cycles, and intensifying customer needs are putting increasing pressure on franchise's organizations to satisfy their customers by creating market-oriented relationships with and enhancing their market knowledge of them. One way that this might be achieved is by establishing deep ties (i.e., job commitment and job satisfaction) with their employees. Therefore, the purpose of this study is to examine how two important constructs of franchises' strategic efforts, LO (learning orientation) and RMO (relationship marketing orientation), affect job satisfaction, given the mediating role of job commitment. A franchise system comprises a set of contractual arrangements by which mutual obligations are performed. An organizational learning goal motivates employees to improve their abilities and master the tasks they perform. Relationship marketing, in addition, is to identify, establish, maintain, and enhance relationships with customers and other stakeholders to ensure that the objectives of all parties are met and this is done through the mutual exchange of promises. In a relationship marketing orientation, then, a firm creates, maintains, and enhances a strong relationship with its customers by sustaining long-term ties. This study was designed to examine the evolution of various theoretical approaches to franchise systems in order to determine whether theories about firms have significantly affected the franchise system. To this end, the authors developed a structural model consisting of several constructs. Previous studies have suggested that franchises' learning and relationship marketing orientations are important occupational immersion dimensions driving job satisfaction. Research design, data, methodology - We empirically tested a process of how the learning orientation and the relationship marketing orientation influence job commitment and job satisfaction using survey data drawn from 150 responding franchisees who were interviewed about their individual tendencies. Results - The results of this study provide empirical evidence that learning orientation, relationship marketing orientation, and job commitment all influence franchisees' job satisfaction. The results of this study indicate that, first, learning orientation had a significant effect on job satisfaction; second, relationship marketing orientation was positively related to job commitment; third, job commitment had a significant effect on job satisfaction. We also found that relationship marketing orientation and job satisfaction were mediated by job commitment. Conclusions - The findings of this study confirm the importance of learning orientation and relationship marketing orientation in maintaining a positive marketing relationship between franchiser and franchisee from to the perspective of the market. This indicates that franchiser support such as educational programs provided by the franchiser will help franchisees attain higher business management achievement and satisfaction. Moreover, a positive relationship between franchisees and consumers can be maintained through tie effects. Our findings also suggest that learning orientation plays a critical role in job satisfaction within the franchise system.

The Effects of Learning Transfer on Perceived Usefulness and Perceived Ease of Use in Enterprise e-Learning - Focused on Mediating Effects of Self-Efficacy and Work Environment - (지각된 유용성과 사용용이성이 기업 이러닝 교육의 학습전이에 미치는 영향에 관한 연구 -자기효능감과 업무환경의 매개효과를 중심으로-)

  • Park, Dae-Bum;Gu, Ja-Won
    • Management & Information Systems Review
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    • v.37 no.3
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    • pp.1-25
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    • 2018
  • This research performed the empirical test for the effects of learning transfer on perceived usefulness, perceived ease of use, self-efficacy and work environment using 390 employees who have experienced e-learning in domestic and foreign companies. Analyzed the mediating effects of self-efficacy and work environment in addition to direct effect of each factor on learning transfer. The results showed that perceived usefulness and perceived ease-of-use of e-learning learner had a positive(+) effect on self-efficacy and a positive influence on supervisor and peer support and organizational climate. Self-efficacy showed a positive effect on learning transfer, and supervisor support, peer support and organizational climate had a positive influence on learning transfer as well. Perceived usefulness also had a positive effect on learning transfer. However, perceived ease-of-use had no significant effect on learning transfer. As a result of the mediating effect analysis, self-efficacy and work environment were analyzed to have mediating effects between perceived usefulness, perceived ease of use, and learning transfer. The implications of this study are as follows. First, this study designed a new research model that reflects factors influencing the effect of learning transfer on acceptance of e-learning that is common in corporate education. It has derived a research model of perceived usefulness and perceived ease-of-use, which were used as mediating variables for external characteristics factors, as independent variables, using self-efficacy and work environment as mediating variables, which were studied as external factors. Second, most of the studies on technology acceptance model and learning transfer are conducted in a single country. The reliability was enhanced by testing the study models using different samples from 26 countries. Third, perceived usefulness and ease-of-use in existing studies have been considered as key determinants of acceptance intention and learning transfer. This study explored the mediating effects of learner and environmental factors on the accepted information technology and strengthened and supplemented the path of learning transfer of perceived usefulness and ease-of-use. In addition, based on the sample analysis of various countries used in this study, it is expected that future international comparative studies will be possible.

Proposal of Artificial Intelligence Convergence Curriculum for Upskilling of Financial Manpower : Focusing on Private Bankers and Robo-Advisors

  • KIM, JiWon;WOO, HoSung
    • Fourth Industrial Review
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    • v.2 no.1
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    • pp.19-32
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    • 2022
  • Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

The empirical study on e-learning quality and its relevant constructs (이러닝 품질과 관련 변인에 대한 실증연구)

  • Lee, Misook
    • Journal of Korean Society for Quality Management
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    • v.45 no.4
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    • pp.917-932
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    • 2017
  • Purpose: This study aims to identify the most important quality construct among system quality, information quality, and service quality, which are integrated as the second-order construct; perceived quality, and to investigate the relationship between perceived quality, learner satisfaction, learner enjoyment, switching cost, and learner loyalty. Method: Data were collected from learners who had taken e-learning course, and the analysis was conducted in two phases. The first phase described demographic characteristics using SPSS23.0; the second phase involved the second order CFA of perceived quality and the analysis of measurement model and structural model through AMOS 23.0. Results: (1) The explanatory power of system quality, information quality, and service quality appears to be almost equal; (2) Perceived quality positively influences only both learner satisfaction and switching cost; (3) Only learner satisfaction positively influences learner loyalty and switching cost negatively influences learner loyalty. Conclusion: Learner enjoyment does not play an important role in this study, which could be extrapolated in regard to the characteristics of sample. The respondents are over high school students, who emphasize on the acquisition of knowledge rather than enjoyment. Additionally, the result implies that respondents show low loyalty in the high switching cost.