• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1036-1042
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• 2023

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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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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• v.30 no.4
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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.

• Journal of Information Technology Services
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• v.16 no.1
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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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• v.30 no.4
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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.

• The Korean Journal of Archival Studies
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• no.45
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• pp.83-120
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• 2015

Record Information Services is an aggressive action of connecting documentaries focusing on the information needs of user. However, recent studies on the parliament's written information service recognize the necessity that it should segment the user's information requests, and provide personalized service, but have not discussed for specific cases or measures. While the importance of Web services written with the proliferation of information and popularization of the Web is emerging right to know but, it is not being performed properly by lack of sufficient manpower and budget along with lack of recognition in hands-on sites upon the user analysis. So, while increasing the efficiency of the hands-on workers of Record Information Services, the introduction of analytical tools that can be utilized in low budget agencies is needed. Web analytics is to analyze the behavior by analyzing Web logs which web users have left you visit the site. To estimate the behavior they want to request information of the analyzed Web user aims to provide a Web service, the Web service further continued improvement. There are several types that include among them Google Analytics offering a variety of analysis items for free and all over the world, many people are already using. This study introduces a Google Analytics web analytics focused and proposes a service improvement plan with specific web user segmentation analyzes the cases of Korea Democracy Foundation of Open Archives introduces them to the actual institutions.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Journal of The Korean Society of Integrative Medicine
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• v.5 no.1
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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.

• Journal of the Korean Society of Safety
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• v.32 no.3
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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.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.173-200
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• 2015

This study is to seek a development plan in the borrowed book and current condition of operation of J-do provincial library. Based on library use card issuer 30,072 people and the number of lending books 705,447(2012 to 2013) of J-do provincial library, it was to analyzed elemental and comparative research for library development plan and user satisfaction. Method of analysis used SPSS statistics 21. This confirmed provincial library user's library user behavior and usage pattern of data. Based on the results of analytics, it indicated a development plan of J-do provincial library.