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Functional Regression: A New Model for Predicting Market Penetration of New Products

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  1. Ashish Sood & Gerard J. Tellis, 2009. "Do Innovations Really Pay Off? Total Stock Market Returns to Innovation," Marketing Science, INFORMS, vol. 28(3), pages 442-456, 05-06.
  2. Guiyang Xiong & Sundar Bharadwaj, 2014. "Prerelease Buzz Evolution Patterns and New Product Performance," Marketing Science, INFORMS, vol. 33(3), pages 401-421, May.
  3. Ashish Sood & V Kumar, 2018. "Client profitability of diffusion segments across countries for multi-generational innovations: The influence of firm, market, and cross-national differences," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 49(9), pages 1237-1262, December.
  4. Blanquero, R. & Carrizosa, E. & Jiménez-Cordero, A. & Martín-Barragán, B., 2019. "Functional-bandwidth kernel for Support Vector Machine with Functional Data: An alternating optimization algorithm," European Journal of Operational Research, Elsevier, vol. 275(1), pages 195-207.
  5. Oliver Schaer & Nikolaos Kourentzes & Robert Fildes, 2022. "Predictive competitive intelligence with prerelease online search traffic," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3823-3839, October.
  6. Sam K. Hui & Tom Meyvis & Henry Assael, 2014. "Analyzing Moment-to-Moment Data Using a Bayesian Functional Linear Model: Application to TV Show Pilot Testing," Marketing Science, INFORMS, vol. 33(2), pages 222-240, March.
  7. Marlene A. Smith & Murray J. Côté, 2022. "Predictive Analytics Improves Sales Forecasts for a Pop-up Retailer," Interfaces, INFORMS, vol. 52(4), pages 379-389, July.
  8. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
  9. Rutger D. van Oest & Harald J. van Heerde & Marnik G. Dekimpe, 2010. "Return on Roller Coasters: A Model to Guide Investments in Theme Park Attractions," Marketing Science, INFORMS, vol. 29(4), pages 721-737, 07-08.
  10. Prabhakaran, Thara & Lathabai, Hiran H. & Changat, Manoj, 2015. "Detection of paradigm shifts and emerging fields using scientific network: A case study of Information Technology for Engineering," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 124-145.
  11. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
  12. Slaets, Leen & Claeskens, Gerda & Silverman, Bernard W., 2013. "Warping Functional Data in R and C via a Bayesian Multiresolution Approach," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 55(i03).
  13. Anderl, Eva & Becker, Ingo & von Wangenheim, Florian & Schumann, Jan Hendrik, 2016. "Mapping the customer journey: Lessons learned from graph-based online attribution modeling," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 457-474.
  14. Lemmens, A. & Croux, C. & Stremersch, S., 2012. "Dynamics in international market segmentation of new product growth," Other publications TiSEM 306086bd-670f-48d2-97d1-3, Tilburg University, School of Economics and Management.
  15. Lemmens, Aurélie & Croux, Christophe & Stremersch, Stefan, 2012. "Dynamics in the international market segmentation of new product growth," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 81-92.
  16. Rha, Hyungmin & Kao, Ming-Hung & Pan, Rong, 2020. "Design optimal sampling plans for functional regression models," Computational Statistics & Data Analysis, Elsevier, vol. 146(C).
  17. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
  18. Meade, Nigel & Islam, Towhidul, 2021. "Modelling and forecasting national introduction times for successive generations of mobile telephony," Telecommunications Policy, Elsevier, vol. 45(3).
  19. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
  20. Goia, Aldo & May, Caterina & Fusai, Gianluca, 2010. "Functional clustering and linear regression for peak load forecasting," International Journal of Forecasting, Elsevier, vol. 26(4), pages 700-711, October.
  21. Fan-Osuala, Onochie & Zantedeschi, Daniel & Jank, Wolfgang, 2018. "Using past contribution patterns to forecast fundraising outcomes in crowdfunding," International Journal of Forecasting, Elsevier, vol. 34(1), pages 30-44.
  22. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
  23. Dazhou Lei & Hao Hu & Dongyang Geng & Jianshen Zhang & Yongzhi Qi & Sheng Liu & Zuo‐Jun Max Shen, 2023. "New product life cycle curve modeling and forecasting with product attributes and promotion: A Bayesian functional approach," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 655-673, February.
  24. Natasha Zhang Foutz & Wolfgang Jank, 2010. "Research Note—Prerelease Demand Forecasting for Motion Pictures Using Functional Shape Analysis of Virtual Stock Markets," Marketing Science, INFORMS, vol. 29(3), pages 568-579, 05-06.
  25. Timmermans, Catherine & Delsol, Laurent & von Sachs, Rainer, 2011. "Using Bagidis in nonparametric functional data analysis: predicting from curves with sharp local features," LIDAM Discussion Papers ISBA 2011020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  26. Timmermans, Catherine & Delsol, Laurent & von Sachs, Rainer, 2013. "Using Bagidis in nonparametric functional data analysis: Predicting from curves with sharp local features," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 421-444.
  27. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
  28. Ashish Sood & Gerard J. Tellis, 2011. "Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies," Marketing Science, INFORMS, vol. 30(2), pages 339-354, 03-04.
  29. Slaets, Leen & Claeskens, Gerda & Hubert, Mia, 2012. "Phase and amplitude-based clustering for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2360-2374.
  30. Phillip M. Yelland & Shinji Kim & Renée Stratulate, 2010. "A Bayesian Model for Sales Forecasting at Sun Microsystems," Interfaces, INFORMS, vol. 40(2), pages 118-129, April.
  31. Ahmed, M.S. & Attouch, M.K. & Dabo-Niang, S., 2018. "Binary functional linear models under choice-based sampling," Econometrics and Statistics, Elsevier, vol. 7(C), pages 134-152.
  32. Sang-Gun Lee & Eui-bang Lee & Chang-Gyu Yang, 2014. "Strategies for ICT product diffusion: the case of the Korean mobile communications market," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 65-81, March.
  33. Thompson, Ann-Marie K., 2010. "Golder's historical method in research in marketing," Journal of Business Research, Elsevier, vol. 63(12), pages 1269-1272, December.
  34. Ashish Sood & Gareth M. James & Gerard J. Tellis & Ji Zhu, 2012. "Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder," Marketing Science, INFORMS, vol. 31(6), pages 964-979, November.
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