• 한국의류산업학회지
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• 제23권3호
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• pp.358-369
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• 2021

This study aims to classify the dimensions of the sales information of secondhand clothing goods on the C2C secondhand trading platform and to systematically analyze the components of each dimension. To this end, the NVivo 12.0 qualitative data analysis software was used. The content analysis showed that the sales information of secondhand clothing goods was classified into four dimensions: detailed information of the sale goods, information specific to secondhand clothing goods, seller opinion information, and service information. The components of each dimension were as follows. The detailed information of the sale goods included size, sale price, item, design, brand name, material, color, wearing season, fit, gender, etc. The information specific to secondhand clothing goods included the number of times the item was worn, its purchase history, and product condition. Seller opinion information included product review, sales motivation, notes for the transaction, coordination proposal, and usage proposal. The service information included the transaction mode, exchange·return·refund, and promotion. The frequency analysis showed that the highest frequencies were sale goods(37.47%), information specific to secondhand clothing goods(24.63%), seller opinion information(20.54%), and service information(17.37%). This study will help C2C secondhand trading platform managers or sellers establish clear standards for presenting sales information and developing ideas toward constructing differentiated platform contents.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.43-50
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• 2020

Disclosure level in interim financial reporting is important for information users to make business decisions. This has received much attention from the information users. The article is aimed at determining the factors of financial ratios, which impact on the disclosure level in interim financial reporting. The authors use the ordinary least squares to test. The sample consists of 418 VN100 over a 6-year period from 2014 to 2019. The results show that there are four factors that positively impact on the disclosure level in interim financial reporting: Enterprise size (SIZE); Liquidity (LIQI); Sales growth (GROW) and Profitability (ROE). The article proposes some policy recommendations to contribute to improving disclosure level in interim financial reporting. Accordingly, State Securities Commission of Vietnam should strengthen the regular inspection of VN100's disclosure level in interim financial reporting and also should enforce strict sanctions or may consider delisting in cases of listed enterprises with incomplete disclosure. The managers of VN100 need to raise the sense of responsibility of information providers to ensure adequate information in interim financial reporting. Investors should also pay attention to the financial ratios of VN100 such as firm size, return-on-equity, liquidity, and sales growth to get useful information and ensure sound business decisions.

• 한국조리학회지
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• 제20권6호
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• pp.175-189
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• 2014

본 연구는 정보공개서의 재무자료를 이용하여 외식 프랜차이징 기업의 기업 특성과 성과를 관한 기초적인 정보를 제공하는데 목적이 있었다. 이에 본 연구에서는 2013기준 169개의 정보공개서를 바탕으로 프랜차이징의 규모, 마케팅역량, 운영특성과 성과에 관해 다중회귀분석으로 검증하였다. 첫째, 프랜차이징 규모와 성과에서 직영점수는 매출액, 당기순이익, 총점포수에 유의하였고, 가맹점수는 총점포수에만 유의한 것으로 나타났다. 둘째, 마게팅 역량 변수와 성과에서는 광고비는 매출액, 총점포수, 판촉비는 매출액, 당기순이익, 총점포수에 유의하였고, 광고비는 당기순이익에 유의하지 않게 나타났다. 마지막으로 운영특성과 성과에서는 사업기간 만이 매출액, 당기순이익, 총점포수에 유의하였고, 브랜드 수는 성과에 영향이 없었다. 본 연구의 가치로는 정보공개서를 이용하여 기타 외식 프랜차이징 기업의 규모, 마케팅역량, 운영특성 변수와 성과를 검증하는데 의의가 있었다. 시사점으로는 외식프랜차이징 기업의 재무성과에 영향을 주는 변수로는 직영점수, 광고비, 판매촉진비, 업력 등이 재무성과에 기여하였고, 비재무성과에는 광고비, 가맹점수 등에서 영향력이 높게 나타나, 기업의 경쟁의 위치에 따라 전략적 선택이 필요함을 시사해주고 있다. 한편, 횡단적 연구방법은 본 연구의 한계점으로 추후 연구에서는 이를 보완하여 종적인 패널데이터를 이용하여 연구한다면 더욱 가치 있는 연구가 될 것으로 사료된다.

• 벤처창업연구
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• 제13권2호
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• pp.1-13
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• 2018

본 연구는 기존연구들을 분석하여 벤처기업의 성공개념을 정리하고 통합적 성공요인 모형을 도출하였다. 성공요인으로는 크게 창업자/팀 요인과 기업요인, 환경 요인 및 창업과정 요인으로 구분하여 각 요인들의 하위 구성요인들을 규명하였고, 기업성과로는 지표의 계량화 여부에 따라 정성/정량적 성과를 측정하거나 응답자의 주관적 평가 여부에 따라 주관/객관적 성과를 측정하는 것으로 통합모형을 설계하였다. 한국 벤처기업에 대한 실증분석으로는 성공 요인 중 하나인 벤처기업의 일반적 특성(업종, 규모, 소재지, 발전단계, 업력)을 주변에서 용이하게 수집할 수 있는 2차 자료를 활용하여 살펴보았다. 분석결과, 2016년 동안 기업의 평균 매출액이 가장 많은 업종은 음식료/섬유/(비)금속이며, 당기순이익이 가장 큰 업종은 컴퓨터/반도체/전자부품, 매출액 증가율이 가장 큰 업종은 정보통신/방송서비스와 소프트웨어 개발, 매출액 당기순이익률이 가장 큰 업종은 에너지/의료/정밀이었다. 종사자규모 측면에서 100인 이상 종사자의 벤처기업이 매출액과 당기순이익이 가장 많았으나, 일반적으로 종사자수와 매출액 및 당기순이익은 높은 상관관계를 보이기 때문에 이러한 결과는 큰 의미가 없으며, 오히려 매출액 증가율이나 매출액 당기순이익률이 의미가 있을 수 있는데, 특히 50~99인의 벤처기업이 이들 지표가 높았다. 소재지 측면에서 매출액이 가장 많은 지역은 서울/인천/경기였고, 당기순이익이 가장 큰 지역은 광주/전라/제주와 서울/인천/경기가 거의 비슷하였다. 매출액 증가율과 매출액 당기순이익률이 가장 큰 지역은 광주/전라/제주였다. 기업의 발전단계와 기업성과와의 관계에서는 예상대로 성숙기와 쇠퇴기의 매출액이 가장 많았다. 당기순이익도 성숙기가 가장 많았으며, 매출액 증가율은 창업기, 초기성장기, 고도성장기, 성숙기, 쇠퇴기의 순으로 전형적인 패턴을 보이고 있었다. 업력 측면에서는 매출액과 당기순이익이 가장 많은 업력은 21년 이상이었고, 창업 3년 이하가 가장 높은 매출액 증가율을 보였으며, 4~10년이 가장 높은 매출액 당기순이익률을 보였다. 연구의 논의사항에서 이들 분석결과에 대한 해석과 시사점들을 제시하였다. 본 연구는 벤처기업의 통합적 성공요인 모형을 제시하고, 한국 벤처기업의 경영성과를 분석함에 있어서 2차 자료의 활용방안을 실증적으로 보여줌으로써 여러 가지 유용한 시사점을 제시하고 있다.

• Asia pacific journal of information systems
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• 제18권2호
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• pp.95-114
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• 2008

Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

• 한국주거학회논문집
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• 제11권1호
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• pp.37-44
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• 2000

The purpose of this research is to examine the evolution of low-cost sales housing and give suggestions for the future housing for the 21st century. This paper investigates the trends of low-cost suburban housing since world War II, as examplified by the Levitt housing in the Northeastern regions of the States. This research analyzes the trends of 14 variables including total floor area. lot size, living room size, kitchen size, mean bedroom size, master bedroom size, number of bedrooms, number of bathrooms, family room, garage, number of story, appliances and features, values, and values per sq ft. Nine entry-level houses were chosen as cases for comparative purpose at different points in time from 1940's to 1990's. This research finds that house sizes have been grown until 1960s, but this trend has reversed with shrinking economy and changing family lifestyles. The trend for smaller housing equipped with several features and convenient equipments will be continued for the next decades to come.

• East Asian Economic Review
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• 제16권2호
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• pp.205-225
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• 2012

I use panel data of sales by the foreign subsidiaries of the U.S. MNCs to examine whether trading blocs create more or less FDI and the impacts on FDI of the extended market size created by forming blocs. By employing a region-fixed effects model, I find that countries forming trading blocs attract more FDI, particularly from non-member countries, but that FDI does not always increase with the market size of the blocs. As the market size increases, FDI increases only for large blocs. However, these findings are sensitive to model specifications. A policy implication is that a country considering forming or joining a trading bloc with a view to attract FDI may want to form a trading bloc with a country or countries with a large market size.

• 품질경영학회지
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• 제42권3호
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• pp.477-496
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• 2014

Purpose: This paper has examined the impact of open innovation business model in technology commercialization with the data from 30 companies of manufacturing firms in South Korea. Methods: The findings provide support for distinguishing five hypotheses relating to development time, IP management, sales, firm size and R&D intensity. To test the hypotheses, data were collected using via e-mail and fax. Small and medium-sized (less than 300 employees) and large industrial firms were chosen for this study. Results: The result shows that openness in its business model is positively associated with successful technology commercialization. Conclusion: The major findings and the implications are: First, as the business model gets more open, development period of technology will be more favorable which gets benefit from rising costs of innovation. Second, as the business model gets more open, large portion of sales are created from new products. Thus, the problem of shorter product life in the market which affects large portion of market revenue can be solved through an open business model. Third, in general, R&D intensity, firm size and the level of IP management affect determination of business model types. The findings also suggest that companies need to increasingly address their external technology exploitation process instead of focusing on their internal innovation processes.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.177-184
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• 2020

This paper analyzes factors affecting corporate investment decisions in economic groups listed on the Vietnam stock market. The panel data of the research sample includes 39 economic groups listed on the Vietnam stock market from 2009 to 2019. The Generalized Least Square (GLS) is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, the investment rate is a dependent variable. Cash-flow (CF), Investment opportunities (ROA), Fixed capital intensity (FCI), Leverage (LEV), Sales growth (GR), Size (SZ), Business risk (RISK) are independent variables in the study. The model results show that cash flow and sales growth have the same impact on investment decisions of economic groups in Vietnam. In addition, investment opportunities have a negative impact on the capital investment decisions of economic groups. The remaining factors include fixed capital intensity, leverage, firm size, and business risks that have a weak and insignificant impact on capital investment decisions of economic groups in Vietnam. The findings of this article are useful for business administrators, and helping business managers make the right financial decisions. Besides, the research results are also meaningful to money management agencies. The authors recommend that the State Bank of Vietnam should maintain a sustainable monetary policy.

• 한국빅데이터학회지
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• 제5권1호
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• pp.147-154
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• 2020

오늘날 빅데이터로부터 유의미한 결과를 도출하는 연구가 활발히 진행되고 있다. 본 논문에선 빅데이터의 데이터의 영역들을 파티션(partition)으로 설정하고 각 파티션들의 대표 값을 계산하여 변수들 사이의 상관관계를 분석 할 수 있는 파티션 기반 빅데이터 분석 알고리즘을 제안한다. 본 논문에선 파티션의 크기조절이 가능한 파티션 기반 빅데이터 분석 알고리즘의 파티션 크기 변화에 따른 시각화 결과를 비교분석하였다. 제안한 파티션 기반 빅데이터 분석 알고리즘을 검증하기 위해 의류 회사 'A'의 빅데이터를 분석하여 온도와 판매 가격 변화에 따른 상품의 판매량 변화를 분석하고 시각화하여 유의미한 결과를 얻을 수 있었다.