• Title/Summary/Keyword: patent rearrangement

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Patent Portfolio Composition and New Product Introduction: The Moderating Role of Technological Resource Rearrangement (특허 포트폴리오 구성과 신제품 출시 성과: 특허 재정비 활동의 조절효과를 중심으로)

  • Kim, Nami;Lee, Jongseon
    • Knowledge Management Research
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    • v.19 no.3
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    • pp.63-87
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    • 2018
  • In a rapidly changing technology environment, managing and rearranging the patent portfolios is one of the main sources of competitive advantage for firms. This study analyzes the effects of patent portfolio composition on new product introduction related to resource allocation. This study also looks at the moderating role of rearranging the patent portfolios on new product introduction. Our empirical analysis of the global pharmaceutical industry shows that firms with high-value patent portfolios exhibit a tendency to launch new products, and patent portfolio diversity shows a U-shaped relationship with new product introduction. In addition, the patent portfolio rearrangement positively moderates the relationship between patent portfolio diversity and new product introduction. The results are expected to provide implications for firms' patent portfolio composition and patent portfolio rearrangement related to innovation performance such as new product introduction.

Customer Classification and Market Basket Analysis Using K-Means Clustering and Association Rules: Evidence from Distribution Big Data of Korean Retailing Company (군집분석과 연관규칙을 활용한 고객 분류 및 장바구니 분석: 소매 유통 빅데이터를 중심으로)

  • Liu, Run-Qing;Lee, Young-Chan;Mu, Hong-Lei
    • Knowledge Management Research
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    • v.19 no.4
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    • pp.59-76
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    • 2018
  • With the arrival of the big data era, customer data and data mining analysis have gradually dominated the process of Customer Relationship Management (CRM). This phenomenon indicates that customer data along with the use of information techniques (IT) have become the basis for building a successful CRM strategy. However, some companies can not discover valuable information through a large amount of customer data, which leads to the failure of making appropriate business strategy. Without suitable strategies, the companies may lose the competitive advantage or probably go bankrupt. The purpose of this study is to propose CRM strategies by segmenting customers into VIPs and Non-VIPs and identifying purchase patterns using the the VIPs' transaction data and data mining techniques (K-means clustering and association rules) of online shopping mall in Korea. The results of this paper indicate that 227 customers were segmented into VIPs among 1866 customers. And according to 51,080 transactions data of VIPs, home product and women wear are frequently associated with food, which means that the purchase of home product or women wears mainly affect the purchase of food. Therefore, marketing managers of shopping mall should consider these shopping patterns when they build CRM strategy.