• 한국빅데이터학회지
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• 제7권2호
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• pp.153-172
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• 2022

온라인 쇼핑은 디지털전환(Digital transformation) 수요 및 COVID-19 대유행에 따른 사회적 거리두기 이슈 등에 해결책으로 도소매 서비스 분야의 선두에서 전체 시장을 변화시키고 빠르게 성장해왔다. 온라인 쇼핑 산업의 중심에서 다수를 이루고 있는 소상공인도 이러한 문제를 극복하고 지속적인 성장을 위하여, 정책의 변화 및 시장 동향 정보를 수집하여 마케팅 등 영업 활동에 활용하고 있으나, 한정된 자원과 경쟁 여건에서 본연의 사업에 더욱 밀착된 객관적이고 정제된 정보를 또한 필요로 하고 있다. 이에 본 논문에서는 디지털 전환의 핵심 기술인 빅데이터 정보 수집 및 분석을 통하여 대표적인 온라인 쇼핑몰인 네이버 스마트스토어의 상품 분류, 판매 동향, 소비자 선호도 및 리뷰 정보에서 핵심 변수를 선정하여, 등급별 영향도 및 경쟁자 비교 분석 및 온라인 쇼핑몰 사업 지속성 평가에 활용하는 방안을 마련하여 제안하고자 한다. 빅데이터 기반으로 소상공인이 경쟁자 또는 우수사업자를 벤치마킹하고, 시장의 트렌드 및 소비자 성향을 확인할 수 있다면, 본인의 영업 수준 및 위치를 명확하게 인식하고, 더욱 높은 경쟁력을 확보하기 위하여 자발적으로 노력할 것이다. 아울러 온라인 쇼핑몰 사업자의 지속 가능한 성장을 지표로 확인할 수 있다면, 한 단계 향상된 측정 방안을 보유하게 되므로 더욱 효율적인 정책의 수립 및 리스크관리를 기대할 수 있을 것이다.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1998년도 제13회 하계학술발표회 논문집
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• pp.116-127
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• 1998

The Necessity of Cyber University. Within the rapidly changing environment of global economics, the environment of higher education in the universities, also, has been, encountering various changes. Popularization on higher education related to 1lifetime education system, putting emphasis on the productivity of education services and the acquisition of competitiveness through the market of open education, the breakdown of the ivory tower and the Multiversitization of universities, importance of obtaining information in the universities, and cooperation between domestic and oversea universities, industry and educational system must be acquired. Therefore, in order to adequately cope wi th these kinds of rapid changes in the education environment, operating Cyber University by utilizing various information technologies and its fixations such as Internet, E-mail, CD-ROMs, Interact ive Video Networks (Video Conferencing, Video on Demand), TV, Cable etc., which has no time or location limitation, is needed. Using informal ion and telecommunication technologies, especially the Internet is expected to Or ing about many changes in the social, economics and educational area. Among the many changes scholars have predicted, the development and fixations of Distant Learning or Cyber University was the most dominant factor. In the case of U. S. A., Cyber University has already been established and in under operation by the Federate Governments of 13 states. Any other universities (around 500 universities has been opened until1 now), with the help of the government and private citizens have been able to partly operate the Cyber University and is planning on enlarging step-by-step in the future. It could be seen not only as U. S. A. trying to elevate its higher education through their leading information technologies, but also could be seen as their objective in putting efforts on subordinating the culture of the education worldwide. UTRA University in U. S. A., for example, is already exporting its class lectures to China, and Indonesia regions. Influenced by the Cyber University current in the U.S., the Universities in Korea is willing .to arrange various forms of Cyber Universities. In line with this, at JUNAM National University, internet based Cyber University, which has set about its work on July of 1997, is in the state of operating about 100 Cyber Universities. Also, in the case of Hanam University, the Distant Learning classes are at its final stage of being established; this is a link in the rapid speed project of setting an example by the Korean Government. In addition, the department of education has selected 5 universities, including Seoul Cyber Design University for experimentation and is in the stage of strategic operation. Over 100 universities in Korea are speeding up its preparation for operating Cyber University. This form of Distant Learning goes beyond the walls of universities and is in the trend of being diffused in business areas or in various training programs of financial organizations and more. Here, in the hope that this material would some what be of help to other Universities which are preparing for Cyber University, I would 1ike to introduce some general concepts of the components forming Cyber University and Open Education System which has been established by JUNAM University. System of Cyber University could be seen as a general solution offered by tile computer technologies for the management on the students, Lectures On Demand, real hour based and satellite classes, media product ion lab for the production of the multimedia Contents, electronic library, the Groupware enabling exchange of information between students and professors. Arranging general concepts of components in the aspect of Cyber University and Open Education, it would be expressed in the form of the establishment of Cyber University and the service of Open Education as can be seen in the diagram below.

• 한국산학기술학회논문지
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• 제17권8호
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• pp.236-250
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• 2016

본 연구는 수도권에 거주하는 일반 소비자를 대상으로 기능성화장품 구매행태를 파악하여 선복화 활용 주름 미백개선 신제품 개발 시 경쟁력 확보를 위한 기초자료로 활용하고자 하였다. 연구결과, 소비자는 주름개선 기능성화장품의 종류 중 세럼을 주로 선호했으며, 1~3개월에 한 번 구매하는 비율이 높았다. 용량은 10~30 ml 미만을 주로 선호했고, 구매비용은 3~5만원 미만을 주로 지출하였다. 미백개선 기능성화장품 역시 세럼을 선호했고, 용량은 30~50 ml 미만을 선호했으며, 구매비용은 3~5만원 미만을 주로 지출하였다. 기능성화장품 형태는 단품을 선호했고 선호도가 높은 주요 구매 장소는 '화장품전문점' 이었고, 선호도가 높은 주요 정보원은 '가족 친구 지인의 추천 및 경험담', 'TV 광고' 등 이었다. 선복화 활용 기능성화장품 세럼 개발시 구매의도 4개 항목 모두 제품 비용이 5만원 이상으로 나타났으며, 가격 지불의사에서도 현재 가격에서 추가로 10~30%까지 지불 할 수 있는 것으로 나타났다. 따라서 화장품 관련 기업 및 산업체는 기능성화장품 관련 신제품 개발 시 소비자의 구매시 요구도를 적용하는 방안과 신제품 판매 활성화를 위해 질 높은 서비스를 제공하는 전문화된 장소 확보 및 직접체험, 다양한 대중매체 활용 SNS 블로그를 통한 구전 효과를 높이고, 천연미백 및 주름개선, 보습효과 등이 검증된 선복화를 활용한 제품을 개발하면 건강과 미용에 관심이 많은 소비자들에게 충분히 어필(appeal)할 수 있을 것으로 사료되었다.

• 벤처창업연구
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• 제19권2호
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• pp.109-124
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• 2024

본 연구는 플랫폼 비즈니스 기반의 스타트업에 대한 투자자의 투자결정요인을 분석하여 투자를 준비하는 플랫폼 스타트업에게 투자자의 관점을 이해하고 사업을 검토하는 데 참고할 수 있는 시사점을 제시하여 플랫폼 스타트업의 투자유치 성공률을 제고 및 플랫폼 생태계 활성화를 목적으로 한다. 투자자의 투자결정요인과 플랫폼 가치평가에 관한 선행연구를 바탕으로 플랫폼 스타트업에 적합한 투자결정요인을 도출한 뒤 AHP 분석기법을 활용하여 각 요인의 중요도를 비교한 결과 가장 높은 중요도를 나타내는 주요 요인은 플랫폼 특성으로 확인되었다. 이는 본 연구에서 선정한 플랫폼 특성인 플랫폼 규모, 핵심 참여집단 확보 여부, 가치 고착 용이성, 확보한 데이터 가치가 플랫폼 스타트업에 대한 투자결정요인으로 적절하다는 것을 시사한다. 플랫폼 스타트업에 대한 투자경험 유무로 투자자 그룹을 나누어 비교한 결과 가장 큰 중요도 차이를 보인 요인은 확보한 데이터 가치였다. 이는 데이터의 가치에 대한 이해도가 투자의사 결정에 있어 주요한 영향을 주고 있음을 시사하며 플랫폼 스타트업은 확보한 데이터의 가치를 증대시킬 수 있는 방안을 마련하고 데이터를 활용하여 자사의 비즈니스에 새로운 가치를 부여할 수 있는지 검토해 보아야 할 필요성이 있다. 기존의 선행연구와 본 연구의 결과를 비교해보면 대부분의 선행연구에서 가장 중요하다고 응답하던 창업자 특성의 중요도가 하위권으로 내려갔으며 플랫폼 스타트업에 적합한 특성들이 높은 중요도를 보였는데 이러한 차이가 나타난 이유는 전체 스타트업에 대한 투자결정요인의 중요도를 분석하던 기존의 선행연구와 달리 본 연구에서는 플랫폼 스타트업이라는 특정한 분야에 투자할 경우로 보다 세분화된 질문을 던졌기 때문이다. 덕분에 기존의 연구와 다른 투자자들의 응답을 이끌어낼 수 있었다. 이처럼 기존 선행연구와의 비교를 통해 플랫폼 스타트업에 대한 투자결정요인은 비플랫폼과는 분명한 차이가 있음을 알 수 있었으며 이는 현재 사용되고 있는 투자결정요인이나 가치평가에 관한 기준이 플랫폼 스타트업을 평가하는데 적합하지 않다는 것을 의미한다. 플랫폼이 비즈니스 생태계에 큰 변화를 일으키며 빠르게 성장하고 있는 가운데 좋은 플랫폼 스타트업을 발견하여 육성하는 것은 국가경쟁력 강화에 있어 반드시 필요한 과업이 될 것이다. 따라서 플랫폼 스타트업에 적합한 투자결정요인을 바탕으로 올바른 가치평가를 실시하여 옥석을 가려내는 것이 중요할 것이다.

• 마케팅과학연구
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• 제19권4호
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• pp.32-43
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• 2009

信任在心理学, 经济学, 社会学中已被广泛研究, 其重要性不仅在市场营销中被强调, 在一般商业原则中也被强调. 供应商和买家之间的关系与过去不同, 过去的关系需要相当大的私人网络优势, 并可能涉及不道德的商业行为. 而在以工业营销成功的为核心的二十一世纪激烈的全球竞争中, 供应商和买家之间的关系是伙伴关系. 在相互合作的高级别信任的基础上, 通过交换的关系, 这会给买家和供应商带来长期的利益, 竞争力增强和交易成本的降低以及其他福利. 尽管现有的研究有信任的重要性, 但是在购买与供应关系中却忽视了信任的作用, 也没有系统地分析信任对关系的影响. 因此, 深入研究, 确定买家和商业服务供应商之间信任和关系绩效之间的联系是绝对需要的. 本研究中的商业服务, 包括那些支持制造业, 正作为下一代经济增长的引擎而吸引着人们的注意. 韩国政府已选择其作为制造业发展的战略领域. 由于商业服务开放市场的需求日趋激烈, 商业服务业的竞争力应该比以往得到更多的提倡. 本研究的目的是探索相互信任对买家和供应商之间的关系绩效的影响. 具体来说, 本研究在商业服务交易中提出了一个关于信任-关系绩效的理论模型, 并实证检验根据模型而提出的假设. 这项研究表明, 研究结果有战略意义. 本研究通过多种方法收集经验数据. 这些方法包括通过电话, 邮件和面试. 作为样本的公司是在韩国供应和购买商业服务的以知识为本的公司. 本研究收集的是二进的基础数据. 每个样本公司对包括购买公司及其相应的供应公司. 并跟踪调查每个公司对的相互信任. 本研究为商业服务的买卖双方提出了信任-关系绩效的模型. 该模型由信任和它的前因和后果. 买家的信任分为对供应公司的信任和对销售人员的信任. 根据Doney 和Cannon (1997)的研究我们在个人水平和组织水平上观察信任. 通常情况下, 买方是信任的受体, 但这项研究我们建议以供应商为观察受体. 因此, 它独特的关注了双边角度的知觉风险. 换言之, 供应商和买家一样, 是信任的主体, 因为交易通常是双边的. 从这个角度来看, 供应商对买家信任和买方对供货商的信赖一样重要. 供应商的信任从某种程度上受它信任的买方公司和买家的影响. 这种使用个人水平和组织水平的信任分类是根据Doney 和Cannon (1997)的研究. 信任影响供应商的选择, 这是一项双向放的工作. 供应商们积极参与供应商选择过程中, 和买家密切的一起工作. 此外, 该过程从某种程度上受每一方信任的合作伙伴的影响. 挑选过程包括一些步骤: 识别, 信息检索, 供应商选择和绩效评价. 作为这一进程的结果, 买家和供应商都进行绩效评估, 并就这些结果为基础, 采取有形或无形的纠正行动. 本研究中使用的关于信任的测量问项是根据Mayer, Davis 和 Schoorman (1995) 以及Mayer和Davis (1999)的研究发展起来的. 根据他们的建议, 有关信任的三个方面的研究包括有能力, 善和完整. 根据商业服务这个背景我们调整了原来的问题. 例如, 如 "他/她的专业能力" 已被改为 "当我们讨论我们的产品时销售人员表现出专业能力. "这项研究使用的测量问项不同于在以往的研究中使用的问项（Rotter 1967; Sullivan和Peterson 1982; Dwyer和Oh 1987. 本研究中有关信任的前因后果的测量问项是根据Doney和Cannon (1997)的研究为基础制定的. 根据商业服务这个背景我们调整了原来的问题. 特别是, 问题被设计为对买家和供应商以解决下列因素: 信誉 (诚信, 客户服务, 良好意愿), 市场地位 (公司规模, 市场份额, 在行业中的地位), 愿意定制（产品, 过程, 交付), 信息共享(专有信息, 个人信息), 愿意保持良好关系, 认为专业, 权威授权, 买方与卖方的相似性, 以及接触频率. 作为信任相应的变量, 我们对关系绩效进行了测试. 关系绩效分为有形的影响, 无形影响, 和副作用. 有形的影响包括财务业绩;无形的影响, 包括关系的改善, 网络开发, 以及内部员工的满意度;副作用包括既不是有形影响也不是无形影响的影响. 我们联系了350对公司, 105对公司答复了我们. 由于不完整我们删除了5对公司, 105对公司被用于数据分析. 用于数据分析的回应率为30%(三百五十零分之一百零五), 高于工业营销的平均回复比率. 至于回复的公司的特点, 大多数的公司运作的商业服务既为买方(85.4%)也为供应商(81.8%). 大部分买家是做消费品贸易(76%), 而供应商的大部分(70%)是做工业品贸易. 这可能意味着买家的过程是购入材料, 部件和组件从而生产消费品成品. 正如他们对他们与合作伙伴关系的长度的报告表示, 供应商比买家有更长的商业关系. 假设1测试买方-供应方特点对信任的影响. 销售人员的专业度(t=2.070, p<0.05)和权威授权(t=2.328, p<0.05)积极影响买方对供应方的信任. 另一方面, 权威授权(t=2.192, p<0.05)积极影响供应方对买方的信任. 对买方和供应方来说, 权威授权的程度对保持对彼此的信任有关键作用. 假设2测试买卖双方关系特点对信任的影响. 买家倾向于信任供应方, 因为供应方总是尽全力联系买方(t=2.212, p<0.05)这种倾向性在供应方方面也表现得很强(t=2.591, p<0.01). 另一方面, 供应商对买方的信任是由于供应商感知买家与自己的相似性(t=2.702, p<0.01). 这一发现证实了Crosby, Evans, 和Cowles(1990)的研究结果. 他们的结果表明供应方和买方通过商务或私务的定期会议来建立彼此的联系. 假设3测试信任对感知风险的影响. 结果表明无论对买方还是供应方, 信任越低, 感知风险就越大(买方: t =-6.621, p<0.01; 供应方: t=-2.437, p<0.05). 有趣的是, 这一趋势已被证明对买方更强. 这种较高水平的感知风险的一个可能的解释是在商业服务交易中买方通常比供应方感知到更大的风险. 为此, 有必要对供应商对买方实施减少风险的战略. 假设4测试信任对信息搜集. 根据结果, 对供应方和买方, 与预期相反, 信任取决于他们合作伙伴的名誉(买方t=2.929, p<0.01; 供应方t=2.711, p<0.05). 这一发现表明, 具有良好信誉的供应商往往是可信的. 以往的经验并没有显示出任何与买家或供应商信任的重要关系. 假设5测试信任对供应方/买方选择的影响. 与买方不同, 当供应方认为以往与买方的交易重要时, 供应方倾向信任买方(t=2.913 p<0.01). 但是, 本研究并没有现实资源忠诚和买方对供应方的信任之间有显著关系. 假设6测试的是信任对关系绩效的影响. 对买方和供应方, 当财务表现被报告提高时, 他们比较信任他们的合作伙伴(买方: t=2.301, p<0.05;供应方: t=3.692, p<0.01). 有趣的是, 这种趋势在供应方比较明显. 类似的, 当竞争力被报告提高时, 买卖双方比较信任他们的合作伙伴(买方t=3.563, p<0.01 ; 供应方t=3.042, p<0.01). 对供应方来说, 当对买方信任时效率和生产力会提高(t=2.673, p<0.01). 其他绩效指标与信任没有显著关系. 这项研究结果有一定的战略意义. 首先和最重要的是, 以信任为基础的交易对供应商和买家而言都是有益的. 根据研究证实, 通过努力建立和保持相互信任可以使财务表现提高. 同样, 可以通过同样的努力提高竞争力. 第二, 以信任为基础的交易能够减少购买情况中的感知风险. 这对供应商和买家都有启示. 人们普遍认为, 在一个高度参与的采购情况中买家感知到更高的风险. 为了减少风险, 以往的研究已建议供应商制定降低风险的策略. 而本研究的特点是从双边角度关注知觉风险. 换言之, 供应商也容易存在风险, 特别是当他们提供的服务, 需要非常先进的技术, 操作和维护. 因此, 购买者和供应商必须一起密切合作解决问题. 因此, 相互信任在问题解决过程中起着关键作用. 第三, 在这项研究中发现, 销售人员有更多的授权, 他或她越被信任. 这一发现从战术角度看是非常重要的. 建立信任是一个长期的任务, 然而, 当互信尚未开发, 供应商能够通过授权销售人员做出某些决定来克服遇到的问题, 这一结论也适用于供应商.

• 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.