• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.249-267
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• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.355-360
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• 2014

Forecasting of emerging technology plays important roles in business strategy and R&D investment. There are various ways for technology forecasting including patent analysis. Qualitative analysis methods through experts' evaluations and opinions have been mainly used for technology forecasting using patents. However qualitative methods do not assure objectivity of analysis results and requires high cost and long time. To make up for the weaknesses, we are able to analyze patent data quantitatively and statistically by using text mining technique. In this paper, we suggest a new method of technology forecasting using text mining and ARIMA analysis.

• Proceedings of the CALSEC Conference
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• 1999.07b
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• pp.729-738
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• 1999

o 기업간 자료교환 서비스 ㆍ 거래 상대에 대한 관리 (BizDesk) ㆍ XML 기반의 문서 Mapping 및 변환 - EDI 지원: ANSI X.12, UN EDIFACT ㆍ 신뢰성 있는 문서 전달: 전송방식에 무관 ㆍ 분석을 위한 데이터 추출 및 저장소 - SQL 7.0, OLAP 서버(중략)

• The Magazine for Energy Service Companies
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• s.19
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• pp.64-67
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• 2002

보고서에 따르면, 에너지 효율화 산업은 지난 10년 동안 매년 $24\%$의 총수익 증가율을 기록하며 급속히 성장했다. 데이터 베이스에 포함된 프로젝트 중 대략 $73\%$가 공공부문 시장으로부터 얻어진 것인데 이는 자료수집 과정에서 있었던 편중 때문이다. 미국의 ESCO시장은 매년 20억불에 달하고 있다.

• The Journal of Bigdata
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• v.1 no.1
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• pp.61-66
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• 2016

With big data analysis, companies use the customized marketing strategy based on customer's information. However, because of the concerns about privacy issue and identity theft, people start erasing their personal information or changing the privacy settings on social network site. Facebook, the most used social networking site, has the feature called 'Likes' which can be used as a tool to predict user's demographic profiles, such as sex and age range. To make accurate analysis model for the study, 'Likes' data has been processed by using Gaussian RBF and nFactors for dimensionality reduction. With random Forest and 5-fold cross-validation, the result shows that sex has 75% and age has 97.85% accuracy rate. From this study, we expect to provide an useful guideline for companies and marketers who are suffering to collect customers' data.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.39-46
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• 2019

The competition for standardization in the enterprise environment starts with the data tier of the back-end and the standard enterprise middle tier is being stabilized by standardization as it is accepted as the Spring Framework. In addition, with the advent of new devices in an increasingly rapid cycle, securing compatibility with web and mobile services has become an important competitive advantage for web service companies. However, companies are unable to secure competent technical personnel appropriate for the rapidly changing environment of the information generation, and the curriculum of educational universities does not reflect the demand of new competency-oriented curriculum. Therefore, in this study, in order to acquire competency-oriented skills required for such an enterprise system platform environment and to develop a curriculum, the system using Spring Data JPA in the Spring Framework environment was implemented through documenting for each analysis and design step. It aims to provide a reference model for the full stack competency-based curriculum and capstone design curriculum that can be applied immediately in the enterprise environment.

• Knowledge Management Research
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• v.22 no.2
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• pp.55-76
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• 2021

The real estate market is a representative imperfectly competitive market. Real estate information is characterized by being collected and utilized in a closed environment, and market participants have to pay a lot of time, effort, and costs to acquire such information. Korea's real estate public data is increasing year by year, but it is scattered by relevant ministries. So it is difficult to search and analyze, and the level of development of the industry using it is low. In the recent 4th industrial revolution, the proptech industry has developed as an industry to efficiently provide necessary information to the real estate market. In this study, based on the case of major companies in the real estate platform field among proptech companies, we looked at the types of information provided to users, and on the contrary, explored ways to utilize the data collected from users. The results of this study are expected to provide theoretical and practical implications for ways to reduce information asymmetry in the real estate market and contribute to the development of the real estate industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.487-493
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• 2019

This study examines the ratio of R&D expenses in intangible assets for pharmaceutical companies, and determines whether these expenses affect the firm value among companies listed on the KOSDAQ. The research subjects included annual R&D expenses of 39 pharmaceutical companies listed on the KOSDAQ between 2011 and 2017. The survey was achieved via "Panel Data Model" with "Tobin Q" as an independent variable, and the ratio of R&D expenses in intangible as a dependent variable. Results of the study conclude that the ratio of R&D expenses in intangible assets of KOSDAQ pharmaceutical companies negatively influence the Tobin Q (Enterprise Value). A large proportion of intangible assets indicates increased R & D investment, and the operating profit is likely to be low due to the high debt ratio, thereby negatively impacting the enterprise value. This study further investigates whether the existing researches are based on researches that identify the total value of R & D expenditure. Results determine a significant relationship between enterprise value and R & D expenditure.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.29-53
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• 2011

This paper analyzes the effects of government-sponsored R&D on firm's employment and management performance, using the panel data of manufacturing firms in the area of Busan, Ulsan and Gyungnam. The paper applies PSM to estimate the treatment effects(ATT) without sample selection bias. The findings show that government-sponsored R&D in the area has positive effects on the participating firms' employment and R&D for several years after completing R&D projects.

• 대한공업교육학회지
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• v.33 no.2
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• pp.232-247
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• 2008

Timely collaboration among businesses is required these days such as in B2B E-Commerce. That is, emergency requests or urgent information among businesses should be processed in an immediate mode. In this paper we investigate the semantics on timing constraints of timely collaboration among businesses in terms of event, data, and action and present ECA rule construction related to the timing constraints and its violation. The prototype is implemented using web-based active functionality component.