• 제목/요약/키워드: Competitive Advantage of Information Technology

검색결과 248건 처리시간 0.024초

한국 산업보안교육 프로그램의 정립에 관한 연구 (A Study on the Establishment of Industrial Security Education Programs in Korea)

  • 최선태;유형창
    • 시큐리티연구
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    • 제25호
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    • pp.185-208
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    • 2010
  • 이 연구는 현재 한국 산업보안교육과정의 개선과 보안교육 프로그램에 대하여 제시하였다. 현대인은 세상의 급격한 변화에 대응해야 하는 불안전한 세상에서 살고 있다. 전반적으로 현대인의 생활, 사회, 경제, 국제관계 그리고 보안리스크는 점차적으로 더 복잡성이 더해가고 있다. 이와 더불어 현대인의 업무형태, 교통수단, 여가, 그리고 통신수단은 급격하게 변화하고 있다. 우리가 살고 있는 세상은 과거의 변화의 추세로서 미래의 변화를 예측하는 것을 불가능하게 한다. 이러한 불안전한 세상에서의 현대의 모든 활동에서의 실제적인 결정에는 안전성을 우선하게 되었다. 글로벌 환경은 과거와는 다르게 급격한 변동성이 증가하여 산업보안에 대한 사회적인 기대는 모든 면에서 증가하고 있다. 세계화의 복잡성, 공공의 기대감, 법적인 규제의 요구조건, 다국적에 걸친 이슈, 재판관한상의 이슈, 범죄, 테러리즘, 앞선 정보기술, 사이버 공격, 전염병 등은 새로운 보안리스크 환경을 조성하였으며, 현대인의 삶에 큰 장애물로 등장하였다. 이러한 새로운 보안리스크에 대응하기 위하여 산업보안전문가의 양성이 필요하다. 그러나 대학교육이 보안전문가의 양성에 얼마나 밀접하게 관련되어 있는가? 아쉽게도 오늘날의 대학학위는 취업이나 더 향상된 기회를 보장하지는 못하지만, 지금까지는 실제적으로 대학교육은 더 좋은 직업을 구하는데 최상의 방법이다. 마찬가지로 보안교육과 경험은 좋은 직업을 찾는데 최고의 고려대상이며, 여기에 훈련 또한 중요한 고려요소이다. 현대기업에서의 보안업무는 다양한 리스크로부터 기업을 보호하는 업무에서 비즈니스 경쟁 우위를 확보하기 위한 새로운 원천으로 변화되고 있다. 따라서 보안 분야의 교육의 미래는 지속적인 성장에 비례하여 유망한 산업분야가 되었다. 오늘날 현대인들은 과거와 다르게 일상생활에서 보안에 대하여 더욱 민감하게 의식하면서 생활하고 있으므로, 여기에 가장 부합하는 전문교육과정과 대학교육에서는 새로운 위협요인에 대응하는 산업보안교육 프로그램이 수립되어야 한다.

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Computer Aided Innovation 역량이 연구개발역량에 미치는 효과: 국내 중소기업을 대상으로 (The Effects of the Computer Aided Innovation Capabilities on the R&D Capabilities: Focusing on the SMEs of Korea)

  • 심재억;변무장;문효곤;오재인
    • Asia pacific journal of information systems
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    • 제23권3호
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    • pp.25-53
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    • 2013
  • This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

호텔기업의 CRM 시스템 구축이 고객성과에 미치는 영향에 관한 연구 (A Study on the Effects of CRM System Installment in Customer Performance of Hotel Business)

  • 김정승
    • 마케팅과학연구
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    • 제11권
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    • pp.147-163
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    • 2003
  • 최근 들어 호텔 기업은 환경변화에 신속히 대처하고 경쟁우위 제고를 위해서 기업 겸영에 정보기술을 도입하는 것이 필수적인 부분이 되었다. 이에 따라 많은 호텔 기업들은 정보기술을 전략적으로 활용하기 위한 노력의 일환으로써, CRM(고객관계관리 ; customer relationship management)시스템을 구축하고 있다. CRM 시스템 도입이 호텔기업의 핵심적인 전략시스템으로 자리를 잡아가고, 도입에 따른 고객성과를 밝히기 위해서 본 논문에서는 CRM 시스템 구축이 고객성과에 미치는 영향을 규명하는 연구를 시도하였다. 본 연구를 위하여 CRM 시스템 구축요인과 고객성과에 대한 기존의 연구 결과를 토대로 문제해결을위한 가설을 설정하였으며, 이를 실증적으로 검증하기 위하여 현재 CRM 시스템을 운용하고 있는 특급호텔의 CRM 시스템 구축과 관련이 있는 종사자들을 대상으로 설문조사를 실시하였다. 본 연구의 결과들을 요약하면 첫째, CRM 구축 요인이 CRM 고객 성과에 영향을 미치는 것으로 조사되었다. 즉, 조직적 특성 요인, 경영환경 요인, 정보지향성 및 기술적 요인이 CRM 고객 성과에 영향을 미치는 것으로 나타났다. 본 연구를 시행하면서 나타난 한계점과 향후 연구과제는 다음과 같다. 첫째, CRM의 고객성과에 영향을 미치는 요인들은 기존의 선행연구를 검토하여 추출하였으나, 추가적인 변수들에 대한 고려가 필요하다고 판단된다. 둘째, CRM 시스템이 국내 기업들에 보급된 지 불과 2-3년 밖에 지나지 않아 선행연구들이 지극히 부족한 상태이고, 실증적 분석 연구 또한 부족하여 본 연구의 통계분석 결과를 기존 연구와 비교하여 해석하기에는 한계가 있다. 특히 호텔산업을 중심으로 한 선행연구가 전무한 상태여서 여러 가지 CRM 시스템의 고객 성과에 대한 선행 변수를 조사해 보았으나, 아직까지 선행연구의 부족으로 차후에 그 측정수단에 대한 연구가 앞으로 계속적으로 이루어져야 할 것이다. 향후 연구에서는 이런 문제점을 고려하여 보다 정밀한 이론적 검토와, 우리 나라 전 지역의 호텔을 대상으로 CRM 시스템의 구축현황과 문제점에 대해서 좀 더 세밀히 고찰하는 것이 필요할 것이다.

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시스템 다이내믹스 기법을 활용한 온라인 쇼핑몰의 전략에 관한 연구 : 소비자의 구매 및 재구매 행동을 중심으로 (A Study for Strategy of On-line Shopping Mall: Based on Customer Purchasing and Re-purchasing Pattern)

  • 이상근;민석기;강민철
    • Asia pacific journal of information systems
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    • 제18권3호
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    • pp.91-121
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    • 2008
  • Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

키워드 네트워크 분석을 이용한 NPD 연구의 진화 및 연구동향 (A Study on Recent Research Trend in New Product Development Using Keyword Network Analysis)

  • 편제범;정의범
    • 한국산업정보학회논문지
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    • 제23권5호
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    • pp.119-134
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    • 2018
  • 오늘날 기업은 기술의 급속한 발전, 고객의 다양한 요구로 인해 높은 불확실성과 경쟁 상황에 놓여 있다. 이러한 기업 환경 속에서 지속적인 경쟁우위와 미래 성장 동력을 확보하는 방안 중 가장 중요한 것이 NPD (신제품 개발)와 관련된 문제로, 이는 기업과 학계에 매우 중요한 이슈이다. 이에 본 연구는 NPD 분야의 기존 연구 흐름과 앞으로의 동향을 파악하여 NPD와 관련된 실무자와 연구자들에게 새로운 가치를 제공하고자 한다. 이를 위해 본 연구는 Scopus 데이터베이스를 활용하여 해외 저명한 저널에 게재된 논문의 키워드를 수집하여 키워드 네트워크 분석을 실시하였다. 이를 통해 NPD 분야의 기존 연구 흐름을 파악할 수 있었고, 각 키워드 간의 연결 관계와 시간의 흐름에 따른 변화를 바탕으로 구체적인 연구주제들의 변화 과정을 제시하였다. 또한, NPD 분야에서 선호되는 키워드를 바탕으로 앞으로의 연구 동향을 제시하였다. 본 연구를 통해 NPD 키워드 네트워크는 멱함수 법칙의 분포를 따르고 있는 좁은 세상 네트워크이고, 키워드의 선호에 의해서 링크가 형성되어 네트워크의 성장이 이루어졌음을 확인할 수 있었다. 또한, 컴포넌트 분석 및 중심성분석을 통해 NPD 키워드 네트워크에서는 주로 Innovation(혁신), New Product Innovation(신제품 혁신), Risk Management(리스크 관리), Concurrent engineering(동시공학), Research and Development(연구개발), Product Life Cycle Management(제품 수명주기 관리) 등과 같은 키워드들이 중심성이 높음을 확인하였다. 한편, 시간의 흐름에 따른 키워드의 선호적 연결의 변화를 살펴본 결과, Innovation(혁신), New Product Introduction(신제품 출시), Project Management(프로젝트 관리) 등의 주제를 중심으로 i) 공급업체와 NPD 협업, ii) 시장의 불확실성을 고려한 NPD, iii) 기술 경영 및 지식경영 분야와 통섭을 고려한 NPD, iv) 중소기업 관점의 NPD 등과 같은 주제의 연구가 요구됨을 확인하였다. 본 연구의 분석 결과는 NPD의 연구 동향, 다른 분야와의 학제간 연구를 위한 새로운 연구주제를 결정하는데 유용하게 쓰일 수 있다.

경제구조 전환기에서 새로운 비즈니스 영역의 창출 : 강소기업의 성공함정과 신시장 개척 (The Exploration of New Business Areas in the Age of Economic Transformation : a Case of Korean 'Hidden Champions' (Small and Medium Niche Enterprises)

  • 이장우
    • 중소기업연구
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    • 제31권1호
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    • pp.73-88
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    • 2009
  • 본 연구는 우리나라 대표적인 강소기업들을 대상으로 심층적 사례조사를 실시하여 새로운 비즈니스 영역의 창출에 필요한 정책적 과제를 도출하고자 했다. 이를 통해 경제 구조적전환기에 금융위기가 가중된 경영환경 속에서 과연 중소기업들이 어떻게 신시장을 개척하고 신성장동력을 지속적으로 유지할 수 있는지에 관해 답변해보고자 했다. 24개 강소기업들에 관한 심층적 전략분석을 토대로 이들의 성공유형과 잠재된 실패요인(성공함정)들을 조사했으며, 그 결과 한국 강소기업의 8가지 유형을 제시했다. 또한 이들의 생존비결과 그에 따른 문제점을 살펴봄으로써 향후 지속적인 경쟁력 유지를 위해 고려해야 할 당면과제들을 도출했다. 이러한 조사결과들을 토대로 우리나라 강소기업들이 신성장동력을 지속적으로 확보하기 위한 전략대안과 정책적 지원방안에 관해서 논의하였다. 이와 함께 '저탄소 녹색성장'의 국가비전에 대해서도 중소기업을 위한 기회창출이라는 차원에서 논의하였다.

빅데이터 도입의도에 미치는 영향요인에 관한 연구: 전략적 가치인식과 TOE(Technology Organizational Environment) Framework을 중심으로 (An Empirical Study on the Influencing Factors for Big Data Intented Adoption: Focusing on the Strategic Value Recognition and TOE Framework)

  • 가회광;김진수
    • Asia pacific journal of information systems
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    • 제24권4호
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    • pp.443-472
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    • 2014
  • To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

국제프랜차이징 연구요소 및 연구방향 (Research Framework for International Franchising)

  • 김주영;임영균;심재덕
    • 마케팅과학연구
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    • 제18권4호
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    • pp.61-118
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    • 2008
  • 본 연구는 국내외 프랜차이즈의 해외진출에 대한 연구들을 바탕으로 국제프랜차이징연구의 전체적인 연구체계를 세워보고, 연구체계를 형성하고 있는 연구요인들을 확인하여 각 연구요소별로 이루어지는 연구주제와 내용을 살펴보고, 앞으로의 연구주제들을 제안하고자 한다. 주요한 연구요소들은 국제프랜차이징의 동기 및 환경 요소과 진출의사결정, 국제프랜차이징의 진입양식 및 발전전략, 국제프랜차이징의 운영전략 및 국제프랜차이징의 성과이다. 이외에도 국제프랜차이징 연구에 적용할 수 있는 대리인이론, 자원기반이론, 거래비용이론, 조직학습이론 및 해외진출이론들을 설명하였다. 또한 국제프랜차이징연구에서 보다 중점적으로 개발해야 할 질적, 양적 방법론을 소개하였으며, 마지막으로 국내연구의 동향을 정리하여 추후의 연구방향을 종합적으로 정리하였다.

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