• Title/Summary/Keyword: the value chain external network activity

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The Effect of Technology Startups' Value Chain Internal and External Network Activities on Competitive Advantage Through Dynamic Capabilities (기술창업기업의 가치사슬내부 및 외부 네트워크 활동이 동적역량을 매개로 경쟁우위에 미치는 영향)

  • Hong, Inki;Kim, Hyung-Jun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.5
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    • pp.17-30
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    • 2022
  • It has been verified in several studies that dynamic capabilities has a very important effect on the competitive advantage of technology startups. And the network has an important influence on this dynamic capability. This is even more important for start-ups that lack the resources and knowledge. Networks that directly and significantly affect dynamic capabilities have been studied mainly the value chain internal. However, network activities of start-ups are conducted not only with the value chain internal networks but also with the value chain external networks. Therefore, it is necessary to study the effect of the value chain internal and external network activity of start-ups on the dynamic capabilities, but prior studies are lacked. In this study, We make a model that encompass the value chain internal and external network for technology startups, and a study was conducted to demonstrate the effect on dynamic capabilities and competitive advantage. As a result of the study, value chain internal network activity directly and significantly affected dynamic capabilities, and value chain external network activity did not directly significantly affect dynamic capacity. And dynamic capabilities had a significant effect on competitive advantage. As confirmed through additional research, value chain external network activity affects value chain internal network activity, and through this, dynamic capabilities are strengthened, and positively affect competitive advantage.. The intensity of value chain external network activity was not significant to dynamic capabilities and the diversity of value chain external network activity had a significant effect on the competitive advantage by double mediating the value chain internal network activity and dynamic capability. Through this study, it is confirmed that the value chain internal networks is important in order for startups to strengthen their dynamic capabilities and increase their competitive advantage, and that both strong and diversified the value chain internal networks positively affects competitive advantage by enhancing dynamic capabilities.

A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

  • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.67-88
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    • 2018
  • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.