• 유통과학연구
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• 제13권9호
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• pp.47-57
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• 2015

Purpose - The aim of this paper is to investigate the explanatory power of the Pecking-order theory (the cost of financing increases with asymmetric information) among Korean retail firms from the perspective of debt capacity. According to the Pecking-order theory, a firm's first preference is to use internal funds for its capital needs, its next preference is the issuance of debt, and its last preference is the issuance of equity; this is due to the information asymmetry problem between existing shareholders and investors. However, prior empirical studies, such as Lemmon and Zender (2010), argue that the entire sample test for the Pecking-order theory could be misleading due to the different levels of debt issuance capability of each of the individual firms; in fact, they confirm that the explanatory power of the Pecking-order theory improves after taking into account the differences in debt capacity of the U.S. firms they examined. This paper implements a case study approach among Korean retail firms to examine the relationship between debt capacity and the explanatory power of the Pecking-order theory in Korea. Research design, data, and methodology - This study uses the sample of public retail firms on the Korea Composite Stock Price Index (KOSPI) from the time period of 1990 to 2013. We gather related financial and accounting statements from the financial information firm WISEfn. Credit rating information is provided by the Korea Investor Service. We employ the models of Lemmon and Zender (2010) and Son and Kim (2013) to measure a firm's debt capacity. Their logit models use the rating dummy variable as a dependent variable and incorporate other firm characteristics as independent variables to estimate debt capacity. To test the Pecking-order theory, we adopt variants of the financing deficit model of Shyam-Sunder and Myers (1999). In the test of the Pecking-order theory, we consider all of the changes in total debt obligations, current debt obligations, and long-term debt obligations. Results - Our main contribution to the literature is our confirmation of the predicted relationship between debt capacity and the explanatory power of the Pecking-order theory among Korean retail firms. The coefficients on financing deficits become greater as a firm's debt capacity improves. This is consistent with the results of Lemmon and Zender (2010). The coefficients on the square of the financing deficits are also negative for the firms in the largest debt capacity group, which is also consistent with the predictions in prior literature. Conclusions - This study takes a case study approach by examining Korean retail firms. We confirm that the Pecking-order theory explains the capital structure of retail firms more appropriately, after taking into account the debt capacity of each firm. This result suggests the importance of debt capacity consideration in the testing of the Pecking-order theory. Our result also implies that there has been a potential underestimation of the explanatory power of the Pecking-order theory in existing studies.

• Asian-Australasian Journal of Animal Sciences
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• 제27권5호
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• pp.616-627
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• 2014

The Lanyu is a miniature pig breed indigenous to Lanyu Island, Taiwan. It is distantly related to Asian and European pig breeds. It has been inbred to generate two breeds and crossed with Landrace and Duroc to produce two hybrids for laboratory use. Selecting sets of informative genetic markers to track the genetic qualities of laboratory animals and stud stock is an important function of genetic databases. For more than two decades, Lanyu derived breeds of common ancestry and crossbreeds have been used to examine the effectiveness of genetic marker selection and optimal approaches for individual assignment. In this paper, these pigs and the following breeds: Berkshire, Duroc, Landrace and Yorkshire, Meishan and Taoyuan, TLRI Black Pig No. 1, and Kaohsiung Animal Propagation Station Black pig are studied to build a genetic reference database. Nineteen microsatellite markers (loci) provide information on genetic variation and differentiation among studied breeds. High differentiation index ($F_{ST}$) and Cavalli-Sforza chord distances give genetic differentiation among breeds, including Lanyu's inbred populations. Inbreeding values ($F_{IS}$) show that Lanyu and its derived inbred breeds have significant loss of heterozygosity. Individual assignment testing of 352 animals was done with different numbers of microsatellite markers in this study. The testing assigned 99% of the animals successfully into their correct reference populations based on 9 to 14 markers ranking D-scores, allelic number, expected heterozygosity ($H_E$) or $F_{ST}$, respectively. All miss-assigned individuals came from close lineage Lanyu breeds. To improve individual assignment among close lineage breeds, microsatellite markers selected from Lanyu populations with high polymorphic, heterozygosity, $F_{ST}$ and D-scores were used. Only 6 to 8 markers ranking $H_E$, $F_{ST}$ or allelic number were required to obtain 99% assignment accuracy. This result suggests empirical examination of assignment-error rates is required if discernible levels of co-ancestry exist. In the reference group, optimum assignment accuracy was achievable achieved through a combination of different markers by ranking the heterozygosity, $F_{ST}$ and allelic number of close lineage populations.

• 지능정보연구
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• 제22권2호
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• pp.33-56
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• 2016

대부분의 부도 예측에 관한 연구는 재무 변수를 중심으로 통계적 방법 또는 인공지능 기법을 적용하여 부도 예측 모형을 구축하였다. 그러나 재무비율과 같은 회계 정보를 이용한 부도 예측 모형은 재무 제표 결산 시점과 신용평가 시점 간 시차를 고려하지 않을 뿐만 아니라 해당 산업의 경제적 상황과 같은 외부 환경적인 요소를 반영하기 어렵다는 한계점이 존재하였다. 기업의 부도 여부를 예측하기 위해 정량 정보인 재무 변수만을 이용하는 것에 한계가 있음에도 불구하고 정성 정보를 부도 예측 모형에 반영한 연구는 아직 미흡한 실정이다. 본 연구에서는 재무 변수를 이용하는 기존 부도 예측 모형의 성과를 개선하기 위해 빅데이터 기반의 정성 정보를 추가적인 입력 변수로 활용하는 부도 예측 모형을 제안하였다. 제안 모형의 성과 향상은 정성 정보를 예측 모형에 통합시키기에 적합한 형태로 정보의 유형을 변환시킬 수 있는가에 따라 달려있다. 이에 본 연구에서는 정성 정보 처리를 위한 방법으로 빅데이터 분석 기법 중 하나인 텍스트 마이닝(Text Mining)을 활용하였다. 해당 산업과 관련된 경제 뉴스 데이터로부터 경제 상황에 대한 감성 정보를 추출하기 위해 도메인 중심의 감성 어휘 사전을 구축하고, 구축된 어휘 사전을 기반으로 감성 분석(Sentiment Analysis)을 수행하였다. 형태소 분석 등을 포함한 텍스트 전처리 과정을 거쳐 감성 어휘를 추출하고, 각 어휘에 대한 극성 및 감성 점수를 부여하였다. 분석 결과, 전통적 부도 예측 모형에 경제 뉴스 데이터에서 도출한 정성 정보를 반영하는 것은 모형의 성과를 개선하는 것으로 나타났다. 특히, 경제 상황에 대한 부정적 감정이 기업의 부도 여부를 예측하는 데 더욱 효과적임을 알 수 있었다.