• 한국콘텐츠학회논문지
• /
• 제15권7호
• /
• pp.477-488
• /
• 2015

본 연구는 선행연구를 확장하여 비감사보수가 감사품질에 미치는 영향을 Big4 회계법인과 Non-Big4 회계법인으로 분류하여 분석하였다. 본 연구는 감사서비스와 비감사서비스를 동시에 제공받는 기업들만을 표본으로 선정하였으며 Big4와 Non-Big4 사이에 비감사보수가 감사품질에 미치는 영향에 대한 차이가 있는지를 집중하여 검증하였다. 분석결과 비감사보수는 Non-Big4 회계법인으로부터 감사 받는 기업들의 감사품질과만 유의적인 양(+)의 관련성이 있는 것으로 나타났다. 이는 지역 기업들을 주고객으로 삼고 있는 소형회계법인들의 경우 특정 기업에 대한 경제의존도가 높을 수 있고 따라서 비감사보수가 커질수록 독립성을 훼손할 유인이 크다고 해석할 수 있다. 한편 Big4 회계법인의 경우 비감사보수가 재량적 발생액 절댓값과 음(-)이 관련성이 없는 것으로 나타나 비감사서비스가 전문성을 강화시킨다는 근거는 찾을 수 없었다. 본 연구의 결과는 지속적으로 비감사서비스가 차지하는 비중이 커지는 현 시점에서 규제기관과 자본시장 참여자에게 유용한 통찰력을 제공할 것으로 기대된다.

• 한국항해항만학회지
• /
• 제48권4호
• /
• pp.321-326
• /
• 2024

본 연구는 Big4 회계법인이 해운사를 감사할 경우 이익조정을 경감시키는 역할을 하는지 검증하는 것을 목적으로 한다. 일반적으로 Big4 회계법인이 감사한 기업의 이익조정은 작고 감사품질은 높다고 알려져 있지만, 규모, 산업 등 처한 상황에 따라 다를 수도 있다. 따라서 본 연구는 Big4 회계법인의 감사가 해운사의 이익조정에 미치는 영향을 실증분석한다. Big4 회계법인은 삼일, 삼정, 안진, 한영 등 4대 회계법인이다. 이익조정의 대용치로 재량적발생액을 사용하고, Dechow et al.(1995)이 고안한 수정Jones모형과 Kothari et al.(2005)이 고안한 성과대응모형으로 재량적발생액을 측정한다. 2001년부터 2023년까지 KOSPI에 상장된 해운사를 대상으로 분석한 결과, Big4 회계법인의 감사는 해운사의 이익조정에 유의한 영향을 미치지 않는 것으로 나타났다. 일반적인 경우와 다르게 Big4 회계법인의 감사는 해운사의 이익조정을 경감시키는 역할을 하지 못한 것으로 판단된다. 본 논문은 해운업이라는 특수한 산업에서 감사인의 역할에 관해 연구해 일반적으로 알려진 바와 다른 결과를 도출했다는 점에 의의가 있다. 해운사들은 감사인을 선정할 때 Big4 회계법인의 감사품질이 항상 좋은 것만은 아니라는 점을 고려해야 할 것이다. 또한, 금융감독원 등 감독 당국은 Big4 회계법인의 감사품질에 대한 정확한 이해를 바탕으로 감리·감독에 임해야 할 것이다.

• International Journal of Computer Science & Network Security
• /
• 제22권4호
• /
• pp.340-350
• /
• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• 한국정보통신학회논문지
• /
• 제24권11호
• /
• pp.1562-1565
• /
• 2020

With the development of digital technology, the industrial structure is becoming digitalize. The government selected big data as the key technology of the 4th industrial revolution. Among them, big data is widely used to create new values and services by utilizing vast amounts of information. In order to cultivate professional manpower for the use of big data, various education programs are provided at universities. We intend to develop a curriculum for systematic training of talented people who can acquire knowledge about the three stages of collection, analysis, and application of big data. To this end, subjects are classified into basic competency, technical competency, analysis competency, and business competency based on the big data competency model proposed by the Korea Internet & Security Agency.

• 한국전자거래학회지
• /
• 제18권4호
• /
• pp.301-314
• /
• 2013

IT기술의 발전은 기존의 컴퓨터 환경과 더불어 수많은 모바일 환경 및 사물 인터넷환경을 통해 사람의 삶을 편리하게 하고 있다. 이러한 모바일과 인터넷 환경의 등장으로 데이터가 급속히 폭증하고 있으며, 이러한 환경에서 데이터를 경제적인 자산으로 활용 가능한 Big Data 환경과 서비스가 등장하고 있다. 그러나 Big Data를 활용한 서비스는 증가하고 있지만, 이러한 서비스를 위해 발생되는 다량의 데이터에는 보안적 문제점이 있음에도 불구하고 Big Data의 보안성에 대한 논의는 미흡한 실정이다. 그리고 기존의 Big Data에 대한 보안적인 측면의 연구들은 Big Data의 보안이 아닌 Big Data를 활용한 서비스의 보안이 주를 이루고 있다. 이에 따라서 본 연구에서는 Big Data의 서비스 산업의 활성화를 위하여 Big Data의 보안에 대한 연구를 하였다. 세부적으로 AHP 기법을 활용한 Big Data 환경에서 보안관리를 위한 구성요소를 파악하고 그에 대한 우선순위를 도출하였다.

• 한국IT서비스학회지
• /
• 제11권4호
• /
• pp.277-294
• /
• 2012

The purpose of this research is to analyze big data structure and various objects in big data industry based on ecological perspective. Big data is rapidly emerging as a highly valuable resource to secure competitiveness of enterprise and government. Accordingly, the main issues in big data are to find ways of creating economic value and solving various problems. However big data is not systematically organized, and hard to utilize as it constantly expands to related industry such as telecommunications, finance and manufacturing. Under this circumstance, it is crucial to understand range of big data industry and to which stakeholders are related. The ecological approach is useful to understand comprehensive industry structure. Therefore this study aims at confirming big data structure and finding issues from interaction among objects. Results of this study show main framework of big data ecosystem including relationship among object elements composing of the ecosystem. This study has significance as an initial study on big data ecosystem. The results of the study can be useful guidelines to the government for making systemized big data ecosystem and the entrepreneur who is considering launching big data business.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2017년도 춘계 학술논문 발표대회
• /
• pp.93-94
• /
• 2017

This study have derived the big issue of overseas construction through big data analysis. For identification of big issues on overseas construction, domestic online articles, 30 daily newspapers like the JoongAng Ilbo, 7 construction related articles including construction economy and 1,759 local newspapers and small media companies were analyzed from October 1st, 2015 to September 30th, 2016. 13,884 cases in total were used for big data analyses and big issue candidates were identified. The analysis result is as shown below. First, looking into major issues on overseas construction for a year, construction orders in the Middle East decreased because of the drop in oil prices. Accordingly, there were discussions on concerns and crises we may face as profitabilities worsened in overseas construction. Second, analyzing main concern based on 8 key words on overseas construction among construction issues for the last one year, it was found as following: Region (29.4%), Business environment (21.4%), Group (15.8%), Profitability (14.5%), Policy and Institution (7.8%), Market environment (4.2%), Business (project) (4.15%), and Education (3.2%). Third, among 30 issues on 8 key words, 10 key issues that are likely to spread and continue were identified. Then, a semantic network map among key words and centrality were analyzed.

• 대한안전경영과학회지
• /
• 제14권4호
• /
• pp.229-238
• /
• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• Asian Journal of Innovation and Policy
• /
• 제8권1호
• /
• pp.58-72
• /
• 2019

The wave of the 4th Industrial Revolution was announced by Schwab Klaus at the 2016 World Economic Forum in Davos, and prospects and measures with the future society in mind have been put in place. With the launch of the Moon Jae-in administration in May 2017, Korea has shifted all of its interest to Big Data, which is one of the most important features of the 4th Industrial Revolution. In this regard, this study focuses on the role of the public sector, explores related issues, and identifies an agenda for determining the demand for ways to foster Big Data ecosystem, from an objective perspective. Furthermore, this study seeks to establish priorities for key Big Data issues from various areas based on importance and urgency using a Delphi analysis. It also specifies the agenda by which Korea should exert national and social efforts based on these priorities in order to demonstrate the role of the public sector in reinforcing the Big Data ecosystem.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권4호
• /
• pp.41-50
• /
• 2020

The paper aims to investigate auditors, auditing firms and other external factors that affect quality of information technology audit in Vietnam. We conducted 2 types of data collections including direct and on survey. For direct survey, we sent directly to auditors at the training classes organized by State Securities Exchanges Commission. An online survey was established and Google doc link was provided to the Big4 and non-Big4 auditors. We received 138 survey responses in that 90 auditors came from Big4 and 48 auditors from non-Big4 firms. The data are analyzed using a factor analysis and compare means approaches to illustrate the potential IT audit quality factors and identify differences between two groups of auditors. The results show that independence and accounting knowledge and audit skills are the most important factors. And since external auditors perform many assurance services, the independence is critical. The result also shows that the auditors need to have enough competent and professional skills when conducting an audit, especially within an IT environment that requires high quality. The findings suggest a similar pattern of two groups in the context of Vietnam and some factors of auditors and auditing firms appear to have a statistically significant impact on quality of IT audit.