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

Hyeokseong Lee, Namil Kim, Kiho Kwak, Wonjoon Kim (), Hyungjoon Soh and Kyungbae Park
Additional contact information
Hyeokseong Lee: Graduate School of Innovation and Technology Management, College of Business, KAIST, Daejeon 34141, Korea
Namil Kim: School of Business and Technology Management, College of Business, KAIST, Daejeon 34141, Korea
Kiho Kwak: Graduate School of Management of Technology, Pukyong National University, Busan 48547, Korea
Hyungjoon Soh: Department of Physics, KAIST, Daejeon 34141, Korea
Kyungbae Park: Department of Business Administration, Sangji University, Wonju, Kangwon 26339, Korea

Sustainability, 2016, vol. 8, issue 10, 1-18

Abstract: 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.

Keywords: co-occurrence-based analysis; diffusion model; high-technology industries; industry convergence; newspaper article data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/2071-1050/8/10/1029/pdf (application/pdf)
https://www.mdpi.com/2071-1050/8/10/1029/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:8:y:2016:i:10:p:1029-:d:80499

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().