• Asia pacific journal of information systems
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• 제33권4호
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• pp.1036-1042
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• 2023

• 산업경영시스템학회지
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• 제42권4호
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• pp.84-90
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• 2019

Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

• Asia pacific journal of information systems
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• 제30권4호
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• pp.847-878
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• 2020

In the era of disruptive change, a data-driven approach is vital to Human Resource Management (HRM) of any leading organization, for it is used to gain a competitive advantage. HR analytics (HRA) has emerged as innovative technologies since advanced analytics, i.e., predictive or prescriptive analytics, were widely used in the High Performing Organizations (HPOs). Therefore, many organizations elevate themselves to become HPOs through Data Science on the "people side." This paper proposes a systematic literature review using the Literature Weighted Scoring (LWS) to develop a conceptual framework based on three adoption theories, which are the Technology-Organization-Environment (TOE), Diffusion of Innovation (DOI), and Unified Theory of Acceptance and Use of Technology (UTAUT). The results show that a total of 13 theory-derived factors are determined as influential factors affecting HRA adoption, and the top three factors are "Quantitative Self-Efficacy," "Top Management Support," and "Data Availability." The conceptual framework with hypotheses is proposed to provide a foundation for further studies on organizational HRA adoption.

• 한국IT서비스학회지
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• 제16권1호
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• pp.1-26
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• 2017

Keeping good, talented people is one of the most significant factors in a company's success. HR analytics is an important area for applying big data analysis techniques to human resources. It provides organizational insight that enables effective management of employees, allowing management to reach their business goals quickly and efficiently. Job satisfaction and employee turnover analysis are the keys to HR analytics. Job review web services have been becoming popular. Because people exchange information about job satisfaction and turnover through these web services, useful information about HR Analytics is accumulated on the job review web sites. In this paper, we identified factors of employee retention by analyzing a Job Satisfaction/Retention group, and the factors of employee turnover by analyzing a Job Unsatisfaction/Turnover group. In order to do this, we first classified employees according to whether their self-reported job satisfaction or turnover was true. We collected and analyzed data from Jobplanet, a popular job review site. Through dominance analysis and LDA topic modeling, we found major factors, topics, and keywords of the classified groups by IT, service, and manufacturing domains. Our approach is a novel model to apply the analysis of reviews and text mining to the HR domain, and it will be practically helpful for setting new strategies that improve job satisfaction.

• Asia pacific journal of information systems
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• 제30권4호
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• pp.879-918
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• 2020

One of the challenges faced by Talent Acquisition teams today pertains to the acquisition of human resources by matching job descriptions and skillsets desired. It is more so in the case of competitive sectors like the Indian IT sector. There can be various channels for Talent Acquisition and accordingly, the cost and benefits might vary. However, the consequences of a mismatch have an impact on the quality of deliverables, high recruitment expenses and loss of revenue for the organization. With increased and diverse sources of data that are available to organizations today, there is ample opportunity to apply analytics for informed decision making in this field. This paper reveals useful insights that help streamline the Talent Acquisition process in the Indian IT Industry. The paper adopts a data-centric approach to examine the critical determinants for efficient and effective Talent Acquisition process in IT organizations. Selected supervised machine learning algorithms are applied for the analysis of the dataset. The study is likely to help organizations in reassessing their talent acquisition strategy with respect to key parameters like expected cost to company (CTC), candidate sourcing channels and optimal joining period.

• 기록학연구
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• 제45호
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• pp.83-120
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• 2015

기록정보서비스는 이용자들의 행태를 관찰하고 그들의 정보요구를 파악하여 그에 맞는 기록정보에 연결하고 안내해주는 적극적인 행위이다. 그러나 국내 기록정보서비스에 대한 연구는 이용자를 세분화하여 개인화된 서비스를 제공해야 한다는 당위성을 인정하지만 구체적인 사례나 방안에 대해서는 논의되지 않고 있다. 웹의 대중화와 알 권리의 확산으로 웹기록정보서비스의 중요성이 대두되고 있지만, 현재 우리나라 대부분의 기록관리기관에서는 실무 현장에서의 인식이 부족하고 인력과 예산의 불충분으로 웹로그분석을 실시하지 못하고 있다. 그래서 기관의 기록정보서비스 담당자의 업무 효율성을 높여주면서 예산이 부족한 기관에서 활용될 수 있는 분석 도구의 도입이 필요하다. 웹애널리틱스는 사이트에 방문한 웹이용자가 남긴 웹로그를 분석하여 행태를 분석하는 것이다. 그 종류에는 여러 가지가 있는데 그 중에서도 구글애널리틱스는 무료로 다양한 분석 항목을 제공하고 있어 전 세계 많은 인구가 이미 사용하고 있다. 본 연구에서는 구글애널리틱스를 중심으로 웹애널리틱스를 소개하고 이를 실제 기관에 도입한 민주화운동기념사업회 사료관의 사례를 분석하여 구체적인 웹이용자 세분화와 서비스 개선 방안을 제시하고자 한다.

• 지능정보연구
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• 제28권3호
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• pp.161-183
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• 2022

여론조사는 유권자들의 투표행위를 예측하고, 그 행위에 영향을 준다는 점에서 선거운동의 강력한 수단이자, 언론의 가장 중요한 기사거리로 자리잡고 있다. 하지만, 여론조사가 활발할수록 후보자들의 공약과 정책을 검증하기 보다 당선 가능성이나 지지도에 관한 조사만 반복적으로 실시하는 등 선거 캠페인에 관한 효과 측정에서 유권자들의 마음을 제대로 반영하지 못하는 경우가 많다. 여론조사의 선거 결과에 대한 부실한 예측이 언론사의 권위를 실추시켰다 하더라도, 어느 후보가 최종 승리할지에 대해 인간의 본능적인 궁금증을 풀어줄 명백한 대안이 없기 때문에 사람들은 여론조사에 대한 관심을 쉽게 놓지 못한다. 이에, 온라인 빅데이터를 통해 인사이트를 발굴하는 환경을 제공하는 썸트렌드의 '유튜브 분석' 기능을 활용하여 20대 대선에 대한 여론을 회고적으로 파악해 보고자 한다. 본 연구를 통해 간단한 유튜브 데이터 분석 결과만으로도 실제 여론(혹은 여론조사 결과)에 근접한 결과를 쉽게 도출하고, 성능이 좋은 여론 예측모형을 구축할 수 있음을 확인하였다.

• 대한통합의학회지
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• 제5권1호
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• pp.19-24
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• 2017

Purpose : The purpose of this study was to find out the difference motion of hip, knee and ankle joint during walking according to using walker on older people. Method : Korean older people of 34 subjects was participated in this study. Participants was measured joint motion on hip, knee and ankle joint during both conditions (walking with walker and without walker). The measured data were analyzed using independent t-test to investigate the difference of joint motion on the both condition. The statistical analyses were performed using Predictive Analytics Soft Ware (PASW) for windows(Ver. 19) and p-value less than .05 were considered significant for all cases. Result : The study showed that more joint motion on hip flexion and ankle pronation is increased by using walker. And hip extension, knee external rotation and ankle plantar flexion is decreased by using walker. Conclusion : This study suggest that using walker on older people was change the motion of the lower limb joint during walking. Therefore, It is necessary to develop a new walker that can reduce dependency and ensure stability on older people during walking.

• 한국안전학회지
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• 제32권3호
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• pp.83-89
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• 2017

A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

• 한국문헌정보학회지
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• 제49권1호
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• pp.173-200
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• 2015

이 연구는 J도 도립도서관의 대출과 운영현황을 조사 분석하여 향후 발전방안을 모색하는데 있다. 이를 위해 도서관 이용증 발급자 30,072명과 대출건수(2012~2013년) 705,447건을 분석하였으며, 도서관 발전계획 및 이용자 만족도를 조사하여 이를 비교분석하였다. 분석방법은 SPSS 21.0을 사용하였다. 이를 통해 도립도서관 이용자의 도서관 이용 행태 및 자료 이용 패턴 등을 확인하였으며, 분석 결과를 기반으로 도립도서관의 발전방안을 제시하였다.