• Journal of Korea Multimedia Society
• /
• v.19 no.8
• /
• pp.1516-1529
• /
• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• The Journal of Bigdata
• /
• v.3 no.2
• /
• pp.123-130
• /
• 2018

As the demand for analytics technologies in both industry and academia increases, the demand for analytics experts is also increasing. To meet this trend, universities have begun to develop new analytics curriculum and provide courses for training analytics experts. In this study, we surveyed curriculum of master's analytics programs of 9 Korean universities and 20 overseas universities. As a result of comparing the domestic university program with the overseas university programs, the average number of subjects per school program is more than that of the Korean university program, but it was found to be less in terms of diversity of subjects.

• Journal of Distribution Science
• /
• v.21 no.1
• /
• pp.53-63
• /
• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.

• Informatization Policy
• /
• v.28 no.1
• /
• pp.43-63
• /
• 2021

The purpose of this research is to examine the relationships among data literacy, organizational culture, and data analytics maturity and the moderating effects of organizational culture. Analysis of the relationship between data literacy and data analytics maturity shows that the higher the data literacy competency of employees, the higher the organization's data analytics maturity. In examining the relationship between organizational culture and data analytics maturity, it is found that relationship culture and innovation culture are positively related to data analytics maturity. In addition, relationship culture and hierarchy culture show significant moderating effects. Relationship culture shows a synergistic effect, whereas hierarchy culture has a buffer effect between data literacy and data analytics maturity.

• 한국경영정보학회:학술대회논문집
• /
• 2008.06a
• /
• pp.305-311
• /
• 2008

급속히 성장하고 있는 Web Analytics 서비스는 기본적으로 인터넷 상에서 기업간의 거래를 전제로 하며 서비스를 이용하는 고객사의 입장에서는 웹분석 분야 정보시스템 아웃소싱의 한 형태이다. 본 연구는 이러한 거래적 특징들을 바탕으로 경쟁이 치열해지고 있는 Web analytics 서비스 산업에서 고객사의 지속적 이용의도와 이에 영향을 주는 요인들 간의 관계를 실증연구를 통하여 살펴보았다. 연구결과 첫째, 서비스를 이용하는 고객회사들의 지속적 이용의 도는 동기적 요인인 만족도와 이탈억제 요인인 의존도가 동시에 고려됨을 알 수 있었다. 둘째, Web Analytics 서비스 산업에서 고객사의 만족도에 영향을 주는 품질 요인으로는 정보품질만이 통계적으로 유의하였다. 셋째, 거래상대방과의 관계에서 이탈이 고려될 때 이탈을 억제하는 역할을 수행하는 의존도 에 영향을 주는 요인으로는 관계가치, 전환비용, 서비스 이용기간이 의미 있는 것으로 나타났다. 넷째, 동기적 측면에서는 전환경험의 유무에 따라 시스템 품질과 공감성이 만족도에 미치는 영향관계가 다르게 나타났고, 이탈억제 측면에서는 전환경험의 유무에 따라 전환비용이 의존도에 미치는 영향관계에서 차이가 있었다.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2012.05a
• /
• pp.102-105
• /
• 2012

ONVIF is becoming a de factor standard specification for supporting interoperability among network video products, which also supports a specification for video analytics service. A smart IP network camera is an IP network supporting video analytics. In this paper, we present our efforts in integrating ONVIF Video Analytics Service into our currently developing smart IP network camera(SS IPNC; Soongsil Smart IP Network Camera). SSIPNC supports object detection, tracking, classification, and event detection with proprietary configuration protocol and meta data formats. SSIPNC is based on TI' IPNC ONVIF implementation which supports ONVI Core specification, and several ONVIF services such as device service, imaging service and media service, but not video analytics service.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2008.10b
• /
• pp.301-306
• /
• 2008

The World Wide Web (WWW) has continued to grow at very rapid speed in both the sheer volume of traffic and size and the complexity of Web sites. Web Analytics Industry also has been growing rapidly. Web Analytics is to analyze web log files to discover accessing patterns of web pages. In this paper, we identify factors which can affect the continuous usage intention of a firm using services in web analytics services and empirically validate the relationships between the identified factors. For this purpose, we analyze 174 Korea firms. The analysis results show that the satisfaction is significantly associated with service quality and switching cost and the service usage period is not significantly associated with continuous service usage intention. We measure the service quality using SERVQUAL. It turn out that two dimensions of SERVQUAL, reliability and empathy are significantly associated with satisfaction, but another dimension of SERVQUAL, responsibility, is not. Finally, satisfaction is significantly associated with continuous service usage intention.

• Educational Technology International
• /
• v.17 no.2
• /
• pp.175-202
• /
• 2016

Most of the learning analytics research has investigated how quantitative data can affect learning. The information that is provided to learners has been determined by teachers and researchers based on reviews of the previous literature. However, there have been few studies on standard learning activities that are performed in e-learning environments independent of the teaching methods or on learning behavior data that are obtained through learning analytics. This study aims to explore the general learning activities and learning behaviors that can be used in the analysis of learning data. Learning activities and learning behavior are defined in conjunction with the concept of learning analytics to identify the differences between teachers' and learners' learning activities. Learning activities and learning behavior were verified by an expert panel review in an e-learning environment. The differences between instructors and learners in their usage were analyzed using a survey method. As results, 8 learning activities and 29 learning behaviors were validated. The Research has shown that instructors' degree of utilization is higher than that of the learners.

• Journal of KIISE
• /
• v.42 no.12
• /
• pp.1590-1599
• /
• 2015

As a variety of personal medical devices appear, it is possible to acquire a large number of diverse medical contexts from the devices. There have been efforts to analyze the medical contexts via software applications. In this paper, we propose a generic model of medical analytics schemes that are used by medical experts, identify inference methods for realizing each medical analytics scheme, and present guidelines for applying the inference methods to the medical analytics schemes. Additionally, we develop a PoC inference system and analyze real medical contexts to diagnose relevant diseases so that we can validate the feasibility and effectiveness of the proposed medical analytics schemes and guidelines of applying inference methods.

• Spatial Information Research
• /
• v.15 no.3
• /
• pp.311-322
• /
• 2007

Geovisual analytics is the new research area that looks fur the way to enable a truly synergetic work of human and visualization tool in analyzing spatio-temporal data. The research challenge for geovisual analytics is developing new geovisualization tools and enhancing human capabilities to analyse, envision, and reason a lot of spatio-temporal changes. With this research area, geovisual analytics is expected to be a new methodology for developing spatial decision support tools. This research is to integrate T scatter plot with computational method to classify the several patterns of the regional fright generation in Korea. The result of this work shows the capabilities provided by geovisual analytics to support spatial decision making.