• 산업경영시스템학회지
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• 제23권56호
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• pp.19-34
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• 2000

Impact of business process re-engineering requires the fundamental rethinking of how information systems are analyzed and designed. It is no longer sufficient to establish a monolithic system for fixed business environments. Information systems must be adaptive in nature. This demand is also applied in production domain. Enabling concept for the adaptive information system is reusability. This paper presents a new object-oriented analysis process for creating such reusable software components in production domain, especially for production planning and scheduling. Our process called MeCOMA is based on three meta-models: physical object meta-model, data object meta-model, and activity object meta-model. After the three meta-models are extended independently for a given production system, they are collaboratively integrated on the basis of integration pattern. The main advantages of MeCOMA are (1) to reduce software development time and (2) to consistently build reusable production software components.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.193-202
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• 2021

The article is devoted to current issues of the development of e-commerce, which is gaining more importance in the conditions of widespread quarantine restrictions. As a result, of the research the importance of digitalization as a driver of economic development is substantiated and the main business models of e-commerce and their modifications are examined. The peculiarities of e-commerce in the context of digital economy were analyzed and their current state was established. Identified the main trends in the development of e-commerce at the current stage, which allowed to identify problem areas that require further study and evaluation. Presented the results of the market research of decorative cosmetics, based on which the summarized set of problems that affect the online sales in this segment of the market.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• 한국프랜차이즈경영연구
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• 제3권1호
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• pp.130-143
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• 2012

Franchise store retailing is taking on ever greater roles in business and commerce in China. The diverse product range, small-batch order, high frequency and time-specific requirements inherent in retail logistics make it the most complicated of all categories of logistics. In franchise store retailing, expanding business scales make trans-regional development a trend. Without a well-functioning logistic system, the standardized delivery of products would be held back, impacting trans-regional development strategy and operational costs. Therefore, the efficiency of franchise store retailing largely depends on logistical efficiency. The integrated and streamlined management of franchise stores depends in large measure on their logistical centers. As such, logistical centers constitute the key link and bears on core competitiveness in franchise store retailing. This thesis begins with an analysis of the current developments and four basic logistical models of franchise store retailing in China, proceeds to summarize developmental trends as well as focal issues and proposes an efficiency enhancing plan.

• 아태비즈니스연구
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• 제15권1호
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• pp.145-157
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• 2024

Purpose - In this study, we propose an empirical model for predicting seasoned equity offering (SEO here after) using machine learning methods. Design/methodology/approach - The models utilize the random forest method based on decision trees that considers non-linear relationships, as well as the gradient boosting tree model. SEOs incur significant direct and indirect costs. Therefore, CEOs' decisions of seasoned equity issuances are made only when the benefits outweigh the costs, which leads to a non-linear relationship between SEOs and a determinant of them. Particularly, a variable related to market timing effectively exhibit such non-linear relations. Findings - To account for these non-linear relationships, we hypothesize that decision tree-based random forest and gradient boosting tree models are more suitable than the linear methodologies due to the non-linear relations. The results of this study support this hypothesis. Research implications or Originality - We expect that our findings can provide meaningful information to investors and policy makers by classifying companies to undergo SEOs.

• 인터넷정보학회논문지
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• 제13권2호
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• pp.109-118
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• 2012

본 논문에서는 워크플로우 협력네트워크 지식의 발견 알고리즘을 제안한다. 즉, 워크플로우 인텔리전스 (또는 비즈니스 프로세스 인텔리전스) 기술은 워크플로우 모델들과 그의 실행이력으로부터 일련의 지식을 발견, 분석, 모니터링 및 제어, 그리고 예측하는 세부기법들로 구성되는데, 본 논문에서는 워크플로우 모델을 구성하는 액티버티들과 그들의 수행자들간의 협력네트워크 지식을 "워크 플로우 협력네크워크 지식"라고 정의하고, 그의 발견기법인 정보제어넷(ICN, information control net)기반 워크플로우 협력네트워크 지식 발견 알고리즘을 제안한다. 특히, 제안한 알고리즘의 적용 사례를 통해 특정 워크플로우 모델로부터 해당 워크플로우 협력네트워크 지식을 성공적으로 생성할 수 있음을 증명함으로써 본 논문에서 제안한 알고리즘의 정확성 및 적합성을 검증한다.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.1-10
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• 2020

This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

• International Journal of Contents
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• 제4권3호
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• pp.1-9
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• 2008

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.

• 한국전자거래학회지
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• 제17권3호
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• pp.43-60
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• 2012

본 논문은 개인정보의 법적 및 기술적 특성을 고려한 라이프 사이클 모델들을 각각 검토했다. 그리고, 이를 토대로 국내 IT 기업에 적합한 '개인정보의 동의 관리 기반 모델'을 제안했다. 본 논문에서 제시한 모델은 기존의 모델이 간과하고 있던 '동의'와 '관리' 요소를 모델에 적극 반영했다는 특징이 있다. 본 모델의 타당성은 2가지 방식으로 검증했다. 첫째, IT 기업의 개인정보 라이프 사이클 구성 요소를 파악 후 모델별로 적용하여 '동의 관리' 모델의 우수성을 검증했다. 둘째, 개인정보의 라이프 사이클 전체 프로세스에 '동의'와 '관리' 내용이 포함됨을 입증했다. 본 연구 결과를 활용하면 IT 기업이 개인정보 활용 현황을 분석하고 보호 체계를 마련하는데 기여할 수 있을 것으로 기대된다.

• The Journal of Asian Finance, Economics and Business
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• 제7권4호
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• pp.59-70
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• 2020

The purpose of this study is to construct the ACD model for the block trading volume duration. The ACD model based on the block trading volume duration is referred to as Volume ACD (VACD) in this study. By integrating with GARCH-type models, the VACD based GARCH type models, which include VACD-GARCH, VACD-IGARCH and VACD-FIGARCH models, are set up. This study selects Chunghwa Telecom (CHT) Inc., offering the America Depository Receipt (ADR) in NYSE, to investigate the block trading volume duration in Taiwanese equity market. The empirical results indicate that the long memory in volume duration series increases dependence at level of volatility clustering by VACD (2,1)-FIGARCH (3,d,1) model. Moreover, the VACD (2,1)-IGARCH (1,1) exhibits relatively better performance of prediction on capturing block trading volume duration. This volatility model is more appropriate in this study to portray the change of the CHT Inc. prices and provides more information about the volatility process for investment strategy, which can be a reference indicator of financial asset pricing, hedging strategy and risk management.