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Grey theory analysis of online population and online game industry revenue in Taiwan

Author

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  • Chang, Tsung-Sheng
  • Ku, Cheng-Yuan
  • Fu, Hsin-Pin

Abstract

This study examines the relationship between the number of Internet users and the amount of online game revenues in Taiwan. We collected the number of Internet users, online game players, and revenues of Taiwan's online game industry during the period of 2003–2010 for analysis. The grey forecasting GM(1,1) model, a simple analysis method, was used to predict the growth trend of these three values, and to examine the relationships among them. The results indicate that there is still room for Taiwan's online game industry to expand its customer base and thus increase future revenues. The findings can help to understand supply and demand in Taiwan's online games market, and provide a reference for both academics and practitioners. Since the Greater China area, including Taiwan, Hong Kong, Macau and Mainland China, has a similar culture and also a huge potential market, the research results in this paper may be helpful for international game companies interested in entering or expanding in this market.

Suggested Citation

  • Chang, Tsung-Sheng & Ku, Cheng-Yuan & Fu, Hsin-Pin, 2013. "Grey theory analysis of online population and online game industry revenue in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 80(1), pages 175-185.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:1:p:175-185
    DOI: 10.1016/j.techfore.2012.06.009
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    Citations

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    Cited by:

    1. Liu, Chuang-Chun, 2016. "Understanding player behavior in online games: The role of gender," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 265-274.
    2. Hua’an Wu & Bo Zeng & Meng Zhou, 2017. "Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption," IJERPH, MDPI, vol. 14(11), pages 1-12, November.
    3. Oliviero A. Carboni & Paolo Russu, 2018. "Measuring and forecasting regional environmental and economic efficiency in Italy," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 335-353, January.
    4. Maya Malinda & Jo-Hui Chen, 2022. "The forecasting of consumer exchange-traded funds (ETFs) via grey relational analysis (GRA) and artificial neural network (ANN)," Empirical Economics, Springer, vol. 62(2), pages 779-823, February.
    5. Czerny Małgorzata & Firkowska-Jakobsze Zuzanna & Hońko Stanisław, 2019. "A Comparability of Information in the Financial Statements of Gaming Companies," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(4), pages 27-44, December.
    6. Natnael Nigussie Goshu & Surafel Luleseged Tilahun, 2016. "Grey theory to predict Ethiopian foreign currency exchange rate," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 2(2), pages 95-116.
    7. Thanh Tuyen Tran & Lai Wang Wang, 2014. "Vietnamese Milk Industry Forecasting: A Grey System Theory Case of Vinamilk," International Journal of Asian Social Science, Asian Economic and Social Society, vol. 4(6), pages 779-790, June.

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