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Open AccessArticle

Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data

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Graduate School of Innovation and Technology Management, College of Business, KAIST, Daejeon 34141, Korea
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School of Business and Technology Management, College of Business, KAIST, Daejeon 34141, Korea
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Graduate School of Management of Technology, Pukyong National University, Busan 48547, Korea
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Department of Physics, KAIST, Daejeon 34141, Korea
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Department of Business Administration, Sangji University, Wonju, Kangwon 26339, Korea
*
Authors to whom correspondence should be addressed.
Academic Editors: JinHyo Joseph Yun and Tan Yigitcanlar
Sustainability 2016, 8(10), 1029; https://doi.org/10.3390/su8101029
Received: 17 June 2016 / Revised: 28 September 2016 / Accepted: 29 September 2016 / Published: 14 October 2016
Firms in high-technology industries have faced great technological and market uncertainty and volatility in the past few decades. In order to be competitive and sustainable in this environment, firms have been pursuing technological innovation, product differentiation, vertical integration, and alliances, which eventually drive industry convergence, defined as the process of blurring boundaries between previously distinct industries. Although industry convergence has greatly affected industrial structure and the economy, little research has investigated this phenomenon, especially its diffusion patterns; thus, it is still unclear which industries are converging more rapidly or have a higher potential for convergence. This paper explores these issues by investigating industry convergence in U.S. high-technology industries, using a large set of newspaper articles from 1987 to 2012. We perform a co-occurrence-based analysis to obtain information on industry convergence and estimate its diffusion patterns using an internal-influence logistic model. We find heterogeneous diffusion patterns, depending on convergent-industry pairs and their wide dispersion. In addition, we find that the potential degree of industry convergence is significantly negatively associated with its growth rate, which indicates that a great deal of time will be required for industry convergence between high-technology industries with this high potential to achieve a high degree of convergence. View Full-Text
Keywords: co-occurrence-based analysis; diffusion model; high-technology industries; industry convergence; newspaper article data co-occurrence-based analysis; diffusion model; high-technology industries; industry convergence; newspaper article data
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MDPI and ACS Style

Lee, H.; Kim, N.; Kwak, K.; Kim, W.; Soh, H.; Park, K. Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data. Sustainability 2016, 8, 1029. https://doi.org/10.3390/su8101029

AMA Style

Lee H, Kim N, Kwak K, Kim W, Soh H, Park K. Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data. Sustainability. 2016; 8(10):1029. https://doi.org/10.3390/su8101029

Chicago/Turabian Style

Lee, Hyeokseong; Kim, Namil; Kwak, Kiho; Kim, Wonjoon; Soh, Hyungjoon; Park, Kyungbae. 2016. "Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data" Sustainability 8, no. 10: 1029. https://doi.org/10.3390/su8101029

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