Forecasting new product diffusion using both patent citation and web search traffic
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DOI: 10.1371/journal.pone.0194723
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References listed on IDEAS
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Cited by:
- David Lenz & Peter Winker, 2020.
"Measuring the diffusion of innovations with paragraph vector topic models,"
PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
- David Lenz & Peter Winker, 2018. "Measuring the Diffusion of Innovations with Paragraph Vector Topic Models," MAGKS Papers on Economics 201815, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Jinah Yang & Daiki Min & Jeenyoung Kim, 2020. "The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers," Sustainability, MDPI, vol. 12(3), pages 1-17, January.
- Hyoung Jun Kim & Su Jung Jee & So Young Sohn, 2021. "Cost–benefit model for multi-generational high-technology products to compare sequential innovation strategy with quality strategy," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-17, April.
- Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.
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