• 제목/요약/키워드: e-Business Pattern

검색결과 129건 처리시간 0.028초

국제 경쟁력과 의류산업의 대응에 관한 연구 (A Study on Apparel Products Performance Effecting the International Marketing Strategies)

  • 김문숙
    • 대한가정학회지
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    • 제32권5호
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    • pp.165-182
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    • 1994
  • Korea's clothing industry which has been country's leading export industry and basic strategical industry is now faced with many difficulties both domestically and internationally. Domestically it is faced with continuing shortage of manpower in both production line and management high labour cost causing increase in price putting more weight on behavior of consumers resulting in change of industrial environment and continuing structural problems of industry itself. Internationally it is faced with strengthening of import regulations and protectionism of developed countries and rapid emergence of underdeveloped countries as leading exporting nations. In reality export plays the most essential role in our economy and is especially sensitive to the external environmental factors. Already economic bloc phonomenon can be seen everywhere and is continuing to accelerate in place such as E. U in Europ, North & South America as NAFTA, and South East Asian contries which recent tendency of economic unity effort is present. These countries of such economic blocs are imposing heavy custom duties reinforcing provision of country origin and acting out strict inspection regulations in order to protect the interest of their own industry. Therefore it is vital to manufacture excellent quality goods For these reasons study in this area has brought attention in Korea as well as worldwide in the recent years. Apparel industry which requires professional technology and ability is the most competitive international business. In order to challenge the international market the high level of intelligence is most required to produce high quality goods. The purpose of this study is to analyze the relationship between functions and roles of marketing and to approach problems in more efficient manner. Apparel industry is composed of various programs such as design pattern making merchandising and textile science. To succeed in the business is to give the highest satisfaction to the targeted market. Hence this study will example the factors that determine the Cost Quality and Performance of apparel products. The study will involve following steps; firstly establish relationship between the quality concept and productivity of apparel products Secondly inquire in to marketing strategy laying stress on apparel production related factors focusing on merchandising marketing production and operations Thirdly prospect 21st century apparel industry focusing on garment production and trade and also other countries structural improvement Fourthly establish the new dimension of competitive factors by grasping the actual circumstance of Korea's apparel industry in the international market. The research method will include; First reality approach method by analysing the present state of industry Second literal analysis such as marketing comparisons between leading apparel exporting countries.

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선박투자자금의 조달구조가 기업의 안정성에 미치는 영향 (The Impact of Capital Structure for Ship Investments on Corporate Stability)

  • 조성순;윤희성
    • 한국항해항만학회지
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    • 제45권6호
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    • pp.276-283
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    • 2021
  • 해운업은 선박투자에 대규모의 자본이 소요되는 한편 시장의 변동성이 극심하기 때문에 투자자금의 조달구조는 기업의 안정성과 직결된다. 지금까지의 해운업 자본구조 연구는 주로 재무제표를 기반으로 자본구조의 결정요인을 도출하는 형태로 진행되었지만 이 연구에서는 접근을 달리하여 과거의 선박가격, 이자율 그리고 부채비중의 변화가 실제 어느 정도의 현금손익으로 이어졌는지 역사적 시뮬레이션을 통해 파악하였다. 연구 결과 현금손익이 0이 되는 손익분기점이 파나막스선은 부채비중 64.38%(부채비율 180.74%), 케이프선은 73.04%(부채비율 270.92%)인 것으로 나타났는데 이는 케이프선에서 추가적인 부채 활용이 가능함을 의미한다. 또한 'Super Boom' 이전과 이후로 구분하여 분석한 결과 선종별로 다른 패턴이 형성되었다. 이를 통해 선종 즉, 영업영역별로 다른 레버리지의 관리가 필요하며 시황 국면에 따라서도 탄력적인 관리가 필요하다는 시사점을 찾을 수 있었다. 이 연구는 해운기업의 입장에서는 기업의 장기적인 안정성을 확보하는 자금조달 구조파악 측면에서, 그리고 해운과 선박금융 정책을 입안하는 정책당국의 입장에서는 해운산업의 건전성을 견인하는 측면에서 실무적인 기여를 할 것으로 기대된다.

여성복 관련 연구경향 분석 - 2001~2010년까지 학회지 게재논문 중심으로 - (The Analysis on the Trend of the Women's Wear Researches - In Consideration of the Apparel Related Journals Publication Listed on the KCI(Korea Citation Index) from 2001 to 2010 -)

  • 박세희;박진아
    • 복식
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    • 제62권8호
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    • pp.1-18
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    • 2012
  • The purpose of the study was to offer in-depth understanding of the women's wear research trend in South Korea and thus to provide insights from the findings throughout the study to set appropriate directions for further development of women's wear related researches in the clothing and textile study area. The study considered research papers published by the 6 major apparel related journals listed on the KCI(Korea Citation Index) i.e. journals of the Korean Society of Clothing and Textiles(KSCT), the Korean Society of Costume(KSC), the Costume Culture Association (CCA), the Korean Society of Fashion Business(KSFB), the Korean Home Economics Association (KHEA) and the Korean Society for Clothing Industry(KSCI). A total of 380 research papers that were related with women's wear published from 2001 to 2010 were selected for the study and analyzed in the form of descriptive statistics using the SPSS Software ver. 18.0. The analysis was categorized according to the journals, years and research theme. The research themes were divided into various categories such as, clothing construction, textile science, fashion aesthetics and design, costume history and culture, apparel psychology and fashion marketing. The results derived from the research were: (1) the ratio of the research papers on the women's wear to the total papers published from 2001 to 2010 by the 6 subject journals was 380 to 6,815, i.e. 5.6% of the total papers; (2) journal of KSCT published the most women's wear research papers (N=149, 39.2%) and then the rest in order were the journal of CCA (N=69, 18.2%), the journal of KSC (N=68, 17.9%), the journal of KSFB (N=52, 13.7%), the journal of KHEA (N=39, 10.3%) and the journal of KSCI (N=3, 0.7%); (3) the proportions of the research themes for the women's wear study were in the order of the case study in marketing (N=135, 35.5%), body measurements and sizing systems in clothing construction (N=88, 23.2%), fashion design and aesthetics (N=83, 21.8%), pattern-making (N=63, 16.6%), and color study (N=11, 2.9%) and so on.

멀티채널에서의 고객만족제고 인센티브 연구 (Optimal Incentives for Customer Satisfaction in Multi-channel Setting)

  • 김현식
    • 한국유통학회지:유통연구
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    • 제15권1호
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    • pp.25-47
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    • 2010
  • 고객만족제고에 관심을 기울이고 노력을 경주하는 기업이 늘어나면서, 유통업자들에게 고객만족제고 인센티브를 제공함으로써 그들의 고객만족노력을 불러일으키고자 하는 노력 역시 활발해 지고 있다. 이러한 노력은 상호 경쟁하는 멀티채널을 운용하는 기업들 역시 마찬가지이다. 그러나 지금까지의 고객만족제고방안에 관한 연구는 종업원이나 단일유통업자 등단일주체에 초점을 두고 진행되어 왔을 뿐 경쟁이 발생하는 멀티채널 상황에서의 고객만족제고 인센티브에 대해서는 별다른 연구가 이루어지지 않고 있다. 이러한 문제의식에서 출발하여, 본 연구에서는 게임이론에 기반한 수리경제학적 분석을 통해 멀티채널을 운용하는 기업의 고객만족제고방안에 주안점을 두어 제조업자가 두 유통업자를 운용하는 멀티채널 모형을 상정하여 고객만족제고 인센티브를 어떻게 제시하는 것이 바람직한지 규명하였다. 본 연구의 주요결과는 다음과 같다: (1)명성수준이 높을수록 고객만족제고 인센티브 수준을 높이는 것이 바람직하다. (2)멀티채널 사이의 보완적 외부효과가 클수록 고객만족제고 인센티브 수준을 높이는 것이 바람직하다. (3)유통비용이 클수록 멀티채널에서의 고객만족제고 인센티브의 수준은 낮게 제시하는 것이 바람직하다. (4)채널간 경쟁강도가 높을수록 고객만족제고 인센티브 수준을 높이는 것이 바람직하다.

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기업의 SNS 노출과 주식 수익률간의 관계 분석 (The Analysis on the Relationship between Firms' Exposures to SNS and Stock Prices in Korea)

  • 김태환;정우진;이상용
    • Asia pacific journal of information systems
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    • 제24권2호
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    • pp.233-253
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    • 2014
  • Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

장바구니 크기가 연관규칙 척도의 정확성에 미치는 영향 (Effect of Market Basket Size on the Accuracy of Association Rule Measures)

  • 김남규
    • Asia pacific journal of information systems
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    • 제18권2호
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    • pp.95-114
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    • 2008
  • Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

인공지능 기술에 관한 가트너 하이프사이클의 네트워크 집단구조 특성 및 확산패턴에 관한 연구 (Structural features and Diffusion Patterns of Gartner Hype Cycle for Artificial Intelligence using Social Network analysis)

  • 신선아;강주영
    • 지능정보연구
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    • 제28권1호
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    • pp.107-129
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    • 2022
  • 기술경쟁이 심화되고 있는 오늘날 신기술에 대한 선도적 위치의 선점이 중요하다. 선도적 위치의 선점과 적정시점에 기술 획득·관리를 위해 이해관계자들은 지속적으로 기술에 대한 탐색활동을 수행한다. 이를 위한 참고 자료로서 가트너 하이프 사이클(Gartner Hype Cycle)은 중요한 의미가 있다. 하이프 사이클은 기술수명주기(S-curve)와 하이프 수준(Hype Level)을 결합하여 새로운 기술에 대한 대중의 기대감을 시간의 흐름에 따라 나타낸 그래프이다. 새로운 기술에 대한 기대는 기술사업화뿐만 아니라 연구개발 투자의 정당성, 투자유치를 위한 기회의 발판이 된다는 점에서 연구개발 담당자 및 기술투자자의 관심이 높다. 그러나 산업계의 높은 관심에 비해 실증분석을 시도한 선행연구는 다양하지 못하다. 선행문헌 분석결과 데이터 종류(뉴스, 논문, 주가지수, 검색 트래픽 등)나 분석방법은 한정적이었다. 이에 본 연구에서는 확산의 주요한 채널이 되어가고 있는 소셜네트워크서비스의 데이터를 활용하여 'Gartner Hype Cycle for Artificial Intelligence, 2021'의 단계별 기술들에 대한 집단구조(커뮤니티)의 특성과 커뮤니티 간 정보 확산패턴을 분석하고자 한다. 이를 위해 컴포넌트 응집규모(Component Cohesion Size)를 통해 각 단계별 구조적 특성과 연결중심화(Degree Centralization)와 밀도(Density)를 통해 확산의 방식을 확인하였다. 연구결과 기술을 수용하는 단계별 집단들의 커뮤니케이션 활동이 시간이 지날 수록 분절이 커지며 밀도 역시 감소함을 확인하였다. 또한 새로운 기술에 대한 관심을 촉발하는 혁신태동기 집단의 경우 정보확산을 촉발하는 외향연결(Out-degree) 중심화 지수가 높았으며, 이후의 단계는 정보를 수용하는 내향연결(In-degree) 중심화 지수가 높은 것으로 나타났다. 해당 연구를 통해 하이프 사이클에 관한 이론적 기초를 제공할 것이다. 또한 인공지능기술에 대한 기술관심집단들의 기대감을 반영한 정보확산의 특성과 패턴을 소셜데이터를 통해 분석함으로써 기업의 기술투자 의사결정에 새로운 시각을 제공할 것이다.

국내 여성용 인대 사용 실태 및 만족도에 관한 연구 (A Study on the Actual Conditions of and Satisfaction with the Existed Female Dress Forms Usage)

  • 박진아;이혜영;최진희
    • 한국의류학회지
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    • 제30권3호
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    • pp.378-385
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    • 2006
  • 콘크리트포장에 초기균열을 일으키는 중요한 인자 중 하나는 콘크리트 내부의 초기온도이다. 따라서 콘크리트포장의 초기균열 발생원인을 연구하기 위해서는 초기온도를 계측하여 분석하는 일이 필요하다. 본 논문에서는 초기균열이 발생하는 슬래브 장소와 초기균열의 발생시간이 초기온도패턴에 어떤 영향을 받는지를 검증하였고 더불어, 줄눈부에서 발생하는 균열의 발생시점과 시공시간과의 관계도 알아보았다. 본 논문을 위해서 "중부내륙고속도로 여주-충주간 제 1공구 시험도로 건설공사구간 STATION 1+400$\sim$1+700" 지점에서 시험시공이 이루어졌으며, 시공 후 72시간 동안 i-Button(온도계측센서)을 이용하여 온도계측을 시행하였으며, 초기균열의 거동은 Demec gauge를 사용하였으며, 초기균열 및 줄눈부 균열은 육안으로 확인하였다. 초기온도패턴과 초기균열의 분석 결과, 콘크리트의 초기온도패턴은 슬래브에 초기균열이 발생하는 위치와 시각에 영향을 주는 것으로 나타났다 초기균열균열은 온도낙차폭이 가장 큰 슬래브에서 발생하였으며, 그 시각은 슬래브의 온도가 급강하하는 새벽이었다. 또한, 콘크리트 슬래브의 거동이 인근 줄눈부에 발생한 초기균열에 따라 영향을 받으며. 줄눈부에 발생한 균열의 발생시기가 서로 다를 경우에 균열의 거동이 달라질 수 있다는 가능성이 제시되었다. 그 외에도, 오전에 시공한 슬래브에서의 균열 발생률이 오후에 시공한것보다 더 큰 것으로 나타났으며, 균열의 발생 간격이 큰 균열이 그렇지 않은 균열보다 더 큰 균열틈을 보였다.

서비스혁신 연구 동향: 국내 및 해외 주요 학술지를 중심으로 (A Review of Service Innovation Research: A Comparison of Domestic and International Research Papers)

  • 유현선
    • Asia pacific journal of information systems
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    • 제24권4호
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    • pp.577-610
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    • 2014
  • Although service innovation is not a new concept, innovation research in general tends to focus on technological innovation by manufacturing firms. With this view, innovation studies focus on product(e.g., goods) and process(e.g., product systems) innovation, ignoring service innovation and its inherent opportunities. Since major economy has been transformed to service economy, service innovation is considered a new effective way to sustain and gain a competitive advantage. Service innovation is no longer regarded merely as a side activity to product innovation; it has become a main research topic in its own right, accompanied by an increasing focus on services. While the number of service innovation studies has increased dramatically in the past 30 years in international research, few studies have been performed in domestic studies because domestic service innovation research began from the middle of 2000. In addition, there are no comprehensive literature reviews describing the evolution of service innovation research in both international and domestic studies because of the heterogeneities of service industry and multidiscipline characteristics of service innovation studies. To bridge this research gap, the purpose of this paper is to perform an extensive literature review and synthesis to enable a critical review of extant research on service innovation and trace its evolution, which will establish a foundation for further studies. By reviewing 169 articles (136 international papers; 33 domestic papers) published between 2000 and 2014 (in past 15 years), primarily in leading service, innovation and management information systems journals, this study analyzes the progression of service innovation research according to the four aspects such as number of studies, topics, methodologies and target industries. Overall, the view of service innovation has evolved, from a complement of traditional product innovation to a multidimensional, all-encompassing concept that entails several functions, both within and outside the firms. The results showed that domestic research still stays at the formation phase of service innovation studies although international research is in the maturity or multidimensional phase. We found increasing recent activities pertaining to service innovation, resulting from the increasing interest in services innovation across various industries and the links of new topics to the service innovation concept in both international and domestic studies. However, the main focus of service innovation research showed a different propensity between international and domestic studies: the former mainly focuses on a much more diversified pattern, emphasizing the linkages between service innovation and business strategy while the latter mainly focuses on the service innovation process(system) and service design. In addition, there are many case studies in domestic studies while many empirical studies in international studies. Domestic studies should increases the understanding of the interplay between service innovation and product innovation within manufacturing firms. Furthermore, rather than focusing on intrinsic distinctions between service innovation and product innovation, researchers should strive to develop and conceptualize service innovation in domestics studies. The present research also provides useful implications for practitioners. First, this study contributes to expand the current understanding of service innovation research by performing an extensive literature review. Second, tracing and comparing the progression and trends of service innovation research between international and domestic studies, this study showed the similarities and differences between them, which provide practical guidance on future research directions and research agenda. Third, this study performed literature review establishing the analysis system in the initial stage and using them to analyze articles, which is leading to explain the research review of service innovation more systematically and objectively. Finally, this study suggests the domestic researchers their future interests and topics of service innovation research.

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.