• Asian Journal of Business Environment
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• 제11권4호
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• pp.17-29
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• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• 산업경영시스템학회지
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• 제42권2호
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• pp.9-17
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• 2019

In order to deal with high uncertainty and variability in emergency medical centers, many researchers have developed various models for their operational planning and scheduling. However, most of the models just provide static plans without any risk measures as their results, and thus the users often lose the opportunity to analyze how much risk the patients have, whether the plan is still implementable or how the plan should be changed when an unexpected event happens. In this study, we construct a simulation model combined with a risk-based planning and scheduling module designed by Simio LLC. In addition to static schedules, it provides possibility of treatment delay for each patient as a risk measure, and updates the schedule to avoid the risk when it is needed. By using the simulation model, the users can experiment various scenarios in operations quickly, and also can make a decision not based on their past experience or intuition but based on scientific estimation of risks even in urgent situations. An example of such an operational decision making process is demonstrated for a real mid-size emergency medical center located in Seoul, Republic of Korea. The model is designed for temporal short-term planning especially, but it can be expanded for long-term planning also with some appropriate adjustments.

• 아태비즈니스연구
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• 제12권4호
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• pp.13-40
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• 2021

Purpose - The purpose of this study is to predict corporate corruption in emerging markets such as Brazil, Russia, India, and China (BRIC) using different machine learning techniques. Since corruption is a significant problem that can affect corporate performance, particularly in emerging markets, it is important to correctly identify whether a company engages in corrupt practices. Design/methodology/approach - In order to address the research question, we employ predictive analytic techniques (machine learning methods). Using the World Bank Enterprise Survey Data, this study evaluates various predictive models generated by seven supervised learning algorithms: k-Nearest Neighbour (k-NN), Naïve Bayes (NB), Decision Tree (DT), Decision Rules (DR), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Network (ANN). Findings - We find that DT, DR, SVM and ANN create highly accurate models (over 90% of accuracy). Among various factors, firm age is the most significant, while several other determinants such as source of working capital, top manager experience, and the number of permanent full-time employees also contribute to company corruption. Research implications or Originality - This research successfully demonstrates how machine learning can be applied to predict corporate corruption and also identifies the major causes of corporate corruption.

• 동아시아경상학회지
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• 제10권1호
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• pp.47-57
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• 2022

Purpose - Overall social entrepreneurship has a positive effect on the organization's C.S.R. and overall growth. This study aims to identify the effects of social entrepreneurship in startup companies on corporate social responsibility by identifying gaps in the literature and providing feasible solutions to the gaps. Research design, Data, and methodology - The qualitative content analysis that was conducted by this research takes the form of two research designs. The first step to conducting a conceptual content analysis is to choose the level of analysis, specifically words, phrases, word sense and the second step is the relational content analysis by choosing the concept to be examined, only that the analysis entails examining the relationships between concepts Result - According to the investigation of numerous previous literature review, the current authors found out total six solutions and the application of suggested solutions indicated that the use of innovative models, startup organizations can gain a competitive edge against dominant competitors in their industry of operations, Conclusion - Finally, the conclusion of this research indicates through the use of innovative solution models, startup organizations can gain a competitive edge against dominant competitors in their industry of operations and startup companies may range from an increase in reputation to growth in profitability and entrepreneurs' satisfaction.

• 경영정보학연구
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• 제14권2호
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• pp.93-102
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• 2012

네트워크 패러다임의 변화 속에 새로운 제품, 기술, 서비스와 더불어 비즈니스 모델을 제시하는 기업이 새로운 강자로 부상하고 있다. 기업들은 네트워크가 가져온 시공간의 제약 해결 등을 얻기 위해 기존의 비즈니스를 네트워크 공간으로 옮기기 위한 노력을 진행하였으며, 이러한 과정에서 기업들은 전에 없던 새로운 비즈니스 모델을 출현시키고 있다. 본 연구에서는 비즈니스 모델 변화를 위해서는 고객이 아닌 새로운 네트워크 가입자 개념으로 비즈니스 모델에 대한 재해석이 필요함을 강조한다. 비즈니스에 대한 근본적인 변화 없이 네트워크의 특성만을 이용하고자 하는 기업들은 고객의 니즈를 잃어버리는 구조적 관성에 빠질 수 있다. 하지만, 사례 기업은 고객이 원하는 가치가 무엇인가에 주목하였으며, 이를 통해 고객을 새로운 네트워크 가입자의 개념으로 살펴봄으로써 기존 비즈니스 모델을 새롭게 변화시키고 나아가 기업간 관계 형태를 변화시켰다. 본 연구에서는 사례분석을 통해 네트워크 관점에서 비즈니스 모델의 변화과정 및 가치곡선과 고객경험사이클을 적용하여 이에 따른 성과를 설명함으로써 네트워크 관점에서의 비즈니스 모델에 대한 재해석의 필요성을 제시하였다.

• 패션비즈니스
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• 제22권4호
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• pp.30-46
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• 2018

The purpose of the study was to suggest certain measurements of the skirt block pattern drafting process for the Korean female fashion models, with the aim to improve its fit. For this purpose, the study carried out an analysis of the lower body features of a dress form developed for the study. This form was representative of Korean female fashion models' body features. The study performed a cross-sectional analysis at waist and hip levels and measured the angles from the frontal and lateral silhouettes of the dress forms. The comparisons of the skirt block patterns developed through draping by the use of 2 types of the dress forms developed and existed and through drafting according to the current patternmaking method have led to noticeable findings in terms of implementation of the skirt block drafting process for the Korean female fashion models. The results of the study are as follows: (1) the vertical lengths between the levels at the front waist point and the side waist point in the patterns are 0.7cm; (2) the vertical length between the levels at the front waist point and the back waist point in the back panel is 0.7cm; (3) the horizontal lengths between the perpendicular line from the side hip point and the side waist point in patterns are within a range of 2.0 to 2.2cm; (4) the horizontal length between the original and the adjusted back waist points moved into the waist line, in a range of 0.0 to 1.0cm, differs whether the center back line would be folded or sewn.

• 지능정보연구
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• 제29권4호
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• pp.287-308
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• 2023

ChatGPT는 2022년 11월에 서비스를 시작한 후 급격하게 사용자 수가 늘어나며 인공지능의 역사에서 큰 전환점을 가져올 정도로 사회 곳곳에 많은 영향을 미치고 있다. 특히 ChatGPT와 같은 거대언어모델의 추론 능력은 프롬프트 엔지니어링 기법을 통해 빠른 속도로 그 성능이 발전하고 있다. 인공지능을 워크플로우에 도입하려고 하는 기업이나 활용하려고 하는 개인에게 이와 같은 추론 능력은 중요한 요소로 고려될 수 있다. 본 논문에서는 거대언어모델에서 추론을 가능하게 한 문맥내 학습에 대한 이해를 시작으로 하여 프롬프트 엔지니어링의 개념과 추론 유형 및 벤치마크 데이터에 대해 설명하고, 이를 기반으로 하여 최근 거대언어모델의 추론 성능을 급격히 향상시킨 프롬프트 엔지니어링 기법들에 대해 조사하고 발전과정과 기법들 간의 연관성에 대해 상세히 알아보고자 한다.

• 아태비즈니스연구
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• 제15권2호
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• pp.207-222
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• 2024

Purpose - This study investigates whether the lagged price difference ratio between preferred and common stocks is related to the return and closing price of the preferred stock using three panel models. Design/methodology/approach - As a first step, we use a two-way fixed effect panel model with stationary preferred stock returns as a dependent variable. For robustness, we then apply the autoregressive distributed lag model (ARDL) and error correction model (ECM) with nonstationary closing prices of the preferred stocks as a dependent variable and compare the results of each model. The ARDL and ECM models provide an advantage of estimating a long-run equilibrium equation together if a long-run relationship exists between the two time-series variables compared to the fixed effect model. Findings - Our sample consists of 107 preferred stocks with at least four years of daily observations as of the end of December 2023. The coefficients of the error correction terms in the ARDL and ECM models are highly statistically significant, approximately -0.08. This indicates that the disequilibrium between the closing prices of common and preferred stocks adjusts by about 8% per day toward equilibrium. In all three models, the price difference ratio on day t-1 was statistically significant in explaining the preferred stock returns or closing prices on day t, implying that trading based on the previous day's price difference ratio is effective for one day. Research implications or Originality - Furthermore, the returns on preferred stocks are higher for firms with a lower proportion of foreign investors or a lower foreign market capitalization of preferred stocks. This suggests that foreign investors with informational advantages do not actively engage in profit-taking by trading preferred stocks, thus not narrowing the price difference. In summary, the recent surge in preferred stock prices is likely driven mainly by the irrational behavior of retail investors.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.761-771
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• 2020

This study discusses the role of Board Monitoring Effectiveness (BME) on managers' decisions regarding the business strategies that fit the external business environmental conditions by using a contingency analysis approach. Furthermore, this study will examine how fit strategies affect Sustainability Reporting (SR) of listed companies on the Indonesia Stock Exchange (IDX) from 2014 to 2017. This study uses Conditional Mixed Process (CMP) technique. This CMP method is claimed to be more efficient in analyzing the TSL models. This study found that in highly uncertain conditions, BME had a positive influence on the probability of managers to choose prospector and defender strategies rather than analyzers. These results indicate that BME shows positive impact on the contingency fit between business strategies and environmental uncertainty. In addition, the study documents that only prospectors have a positive impact on SR, however this study failed to document that defenders have positive impact on SR. Meanwhile the unexpected result is analyzers have a significantly positive effect on SR. This study is the first study to investigate the role of BME in contingency fit between business strategies and environmental uncertainties and how it produces effects up to the level of SR.

• 한국멀티미디어학회논문지
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• 제18권9호
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• pp.1105-1117
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• 2015

During the last decade, the business infrastructure has become digital with increased interconnections among products, processes, and services. Across many firms spanning different industries and sectors, digital technologies are fundanmentally transforming business stratiges, business processes, firm capabilities, productes and services, and key interfirm relationships in extended business networks. With the emergence of smartphones, the paradigm of the ICT industry is rapidly changing as the line between global and local markets are being blurred. In the changing global environment, although some game companies are accelerating the improvement of their global competitiveness and cases of successes of venture enterprises by developing biosimilar technology are being discovered, majority of ICT companies are focusing on limited marketing activities to get subcontracts or projects from large companies. Thus the aim of this study is to find out how digital ecosystems evolve and how business models and strategies have changed of individual companies according to the evolution of the digital ecosystems.