소프트웨어 불법복제에 영향을 미치는 환경 요인에 기반한 국가 분류Country Clustering Based on Environmental Factors Influencing on Software Piracy
- Other Titles
- Country Clustering Based on Environmental Factors Influencing on Software Piracy
- Authors
- 서보밀; 심준호
- Issue Date
- Dec-2017
- Publisher
- 한국정보시스템학회
- Keywords
- Software Piracy; Classification of Countries; Economic Factors; Social Factors; Technical Factors; Data-Driven Approach
- Citation
- 정보시스템연구, v.26, no.4, pp 227 - 246
- Pages
- 20
- Journal Title
- 정보시스템연구
- Volume
- 26
- Number
- 4
- Start Page
- 227
- End Page
- 246
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2151
- DOI
- 10.5859/KAIS.2017.26.4.227
- ISSN
- 1229-8476
2733-8770
- Abstract
- Purpose: As the importance of software has been emphasized recently, the size of the software market is continuously expanding. The development of the software market is being adversely affected by software piracy. In this study, we try to classify countries around the world based on the macro environmental factors, which influence software piracy. We also try to identify the differences in software piracy for each classified type.
Design/methodology/approach: The data-driven approach is used in this study. From the BSA, the World Bank, and the OECD, we collect data from 1990 to 2015 for 127 environmental variables of 225 countries. Cronbach's α analysis, item-to-total correlation analysis, and exploratory factor analysis derive 15 constructs from the data. We apply two-step approach to cluster analysis. The number of clusters is determined to be 5 by hierarchical cluster analysis at the first step, and the countries are classified by the K-means clustering at the second step. We conduct ANOVA and MANOVA in order to verify the differences of the environmental factors and software piracy among derived clusters.
Findings: The five clusters are identified as underdeveloped countries, developing countries, developed countries, world powers, and developing country with large market. There are statistically significant differences in the environmental factors among the clusters. In addition, there are statistically significant differences in software piracy rate, pirated value, and legal software sales among the clusters.
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