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Demand forecasting for new media services with consideration of competitive relationships using the competitive Bass model and the theory of the niche

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  • Seol, Hyeonju
  • Park, Gwangman
  • Lee, Hakyeon
  • Yoon, Byungun

Abstract

New broadcasting services such as Internet protocol TV (IPTV) have been totally revolutionizing the broadcasting industry; thus, the prediction of the degree of diffusion of new media services is a major topic of interest for both governments and providers. This paper proposes a new approach towards demand forecasting for new services with no data and with consideration of competitive relationships with existing services. The underlying model of the proposed approach is the competitive Bass model, which is the most widely used competitive diffusion model. The competition coefficients of the model are estimated by introducing the theory of the niche. The theory of the niche, which originates from ecology, has often been used as a framework for examining competition patterns in the media industry. This study develops a new integrated measure, competitive superiority, by modifying and combining the two conventional measures of the theory of the niche, viz., niche overlap and niche superiority. The competition coefficients are then obtained by adjusting the values of competitive superiority to be incorporated in the model based on the relationship between competition and imitation effects. A case of Korean digital broadcasting services is presented to illustrate the proposed approach.

Suggested Citation

  • Seol, Hyeonju & Park, Gwangman & Lee, Hakyeon & Yoon, Byungun, 2012. "Demand forecasting for new media services with consideration of competitive relationships using the competitive Bass model and the theory of the niche," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1217-1228.
    • Handle: RePEc:eee:tefoso:v:79:y:2012:i:7:p:1217-1228
    DOI: 10.1016/j.techfore.2012.03.002
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    Cited by:

    1. Shuai, Jing & Zhao, Yujia & Shuai, Chuanmin & Wang, Jingjin & Yi, Tian & Cheng, Jinhua, 2023. "Assessing the international co-opetition dynamics of rare earth resources between China, USA, Japan and the EU: An ecological niche approach," Resources Policy, Elsevier, vol. 82(C).
    2. Zhang, Xiaoxing & Gao, Changyuan & Zhang, Shuchen, 2022. "The niche evolution of cross-boundary innovation for Chinese SMEs in the context of digital transformation——Case study based on dynamic capability," Technology in Society, Elsevier, vol. 68(C).
    3. Ying Sun & Jianzhong Xu, 2021. "Evaluation Model and Empirical Research on the Green Innovation Capability of Manufacturing Enterprises from the Perspective of Ecological Niche," Sustainability, MDPI, vol. 13(21), pages 1-21, October.
    4. Wenjing Shen & Izak Duenyas & Roman Kapuscinski, 2014. "Optimal Pricing, Production, and Inventory for New Product Diffusion Under Supply Constraints," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 28-45, February.
    5. Lingjun Wang & Ying Wang & Jian Chen, 2019. "Assessment of the Ecological Niche of Photovoltaic Agriculture in China," Sustainability, MDPI, vol. 11(8), pages 1-17, April.
    6. Li, Xishu & Yin, Ying & Manrique, David Vergara & Bäck, Thomas, 2021. "Lifecycle forecast for consumer technology products with limited sales data," International Journal of Production Economics, Elsevier, vol. 239(C).
    7. Lingjun Wang & Yuanyuan Li, 2022. "Research on Niche Improvement Path of Photovoltaic Agriculture in China," IJERPH, MDPI, vol. 19(20), pages 1-25, October.
    8. Amal Abdel Razzac & Linda Salahaldin & Salah Eddine Elayoubi & Yezekael Hayel & Tijani Chahed, 2017. "A Game Theoretical Real Options Framework for Investment Decisions in Mobile TV Infrastructure," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-34, August.
    9. Najmeh Madadi & Azanizawati Ma’aram & Kuan Yew Wong, 2017. "A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1300992-130, January.
    10. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    11. Xie, Xuemei & Wang, Hongwei, 2021. "How to bridge the gap between innovation niches and exploratory and exploitative innovations in open innovation ecosystems," Journal of Business Research, Elsevier, vol. 124(C), pages 299-311.
    12. Lee, Youseok & Kim, Sang-Hoon & Cha, Kyoung Cheon, 2021. "Impact of online information on the diffusion of movies: Focusing on cultural differences," Journal of Business Research, Elsevier, vol. 130(C), pages 603-609.
    13. Ling Ding & Jinxi Wu & Ziyou Ma & Jialu Mai, 2022. "Regional Niche and Spatial Distribution of Foreign Investment in China from 2012 to 2021," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    14. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    15. Ling Ding & Di Cao & Taohua Ouyang & Jin-xi Wu, 2018. "Promoting the Development of Enterprise Niche: Case Study on China’s Organizational Ambidexterity," Sustainability, MDPI, vol. 10(10), pages 1-14, October.

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