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Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models

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  1. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
  2. Rui Pascoal & Jorge Marques, 2011. "Fitting Broadband Diffusion by Cable Modem in Portugal," GEMF Working Papers 2011-20, GEMF, Faculty of Economics, University of Coimbra.
  3. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
  4. Mingxing Wu & Liya Wang & Ming Li, 2015. "An approach based on the Bass model for analyzing the effects of feature fatigue on customer equity," Computational and Mathematical Organization Theory, Springer, vol. 21(1), pages 69-89, March.
  5. Chien, Chen-Fu & Chen, Yun-Ju & Peng, Jin-Tang, 2010. "Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle," International Journal of Production Economics, Elsevier, vol. 128(2), pages 496-509, December.
  6. 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.
  7. Seo-Hoon Kim & SungJin Lee & Seol-Yee Han & Jong-Hun Kim, 2020. "Scenario Analysis for GHG Emission Reduction Potential of the Building Sector for New City in South Korea," Energies, MDPI, vol. 13(20), pages 1-19, October.
  8. Namwoon Kim & Dae Ryun Chang & Allan D. Shocker, 2000. "Modeling Intercategory and Generational Dynamics for A Growing Information Technology Industry," Management Science, INFORMS, vol. 46(4), pages 496-512, April.
  9. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Technology diffusion model with change in adoption rate and repeat purchases: a case of consumer balking," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 29-36, February.
  10. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2019. "Modeling Technological Substitution by Incorporating Dynamic Adoption Rate," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-24, February.
  11. Amir Heiman & Bruce P. McWilliams & David Zilberman, 2022. "Adoption of Innovations: Comparing the Imitation and the Threshold Models," Foundations and Trends(R) in Marketing, now publishers, vol. 17(1), pages 1-57, June.
  12. Annafari, Mohammad Tsani, 2013. "Multiple subscriptions of mobile telephony: Explaining the diffusion pattern using sampling data," Telecommunications Policy, Elsevier, vol. 37(10), pages 930-939.
  13. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  14. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
  15. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
  16. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
  17. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
  18. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
  19. Riikonen, Antti & Smura, Timo & Kivi, Antero & Töyli, Juuso, 2013. "Diffusion of mobile handset features: Analysis of turning points and stages," Telecommunications Policy, Elsevier, vol. 37(6), pages 563-572.
  20. Park, Sang Yong & Kim, Jong Wook & Lee, Duk Hee, 2011. "Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects," Energy Policy, Elsevier, vol. 39(6), pages 3307-3315, June.
  21. Gupta, Ruchita & Jain, Karuna, 2016. "Competition effect of a new mobile technology on an incumbent technology: An Indian case study," Telecommunications Policy, Elsevier, vol. 40(4), pages 332-342.
  22. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
  23. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
  24. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).
  25. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
  26. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
  27. V. Kumar & Trichy V. Krishnan, 2002. "Multinational Diffusion Models: An Alternative Framework," Marketing Science, INFORMS, vol. 21(3), pages 318-330, July.
  28. Lee, Sang-Gun & Trimi, Silvana & Kim, Changsoo, 2013. "The impact of cultural differences on technology adoption," Journal of World Business, Elsevier, vol. 48(1), pages 20-29.
  29. Rajkumar Venkatesan & Trichy V. Krishnan & V. Kumar, 2004. "Evolutionary Estimation of Macro-Level Diffusion Models Using Genetic Algorithms: An Alternative to Nonlinear Least Squares," Marketing Science, INFORMS, vol. 23(3), pages 451-464, August.
  30. Debabrata Talukdar & K. Sudhir & Andrew Ainslie, 2002. "Investigating New Product Diffusion Across Products and Countries," Marketing Science, INFORMS, vol. 21(1), pages 97-114, February.
  31. 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.
  32. Baur, Lucia & Uriona M., Mauricio, 2018. "Diffusion of photovoltaic technology in Germany: A sustainable success or an illusion driven by guaranteed feed-in tariffs?," Energy, Elsevier, vol. 150(C), pages 289-298.
  33. Kim, Moon-Soo & Kim, Ho, 2007. "Is there early take-off phenomenon in diffusion of IP-based telecommunications services?," Omega, Elsevier, vol. 35(6), pages 727-739, December.
  34. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
  35. Hailin Zhang & Xina Yuan & Tae Ho Song, 2020. "Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 589-608, September.
  36. Negahban, Ashkan & Smith, Jeffrey S., 2018. "Optimal production-sales policies and entry time for successive generations of new products," International Journal of Production Economics, Elsevier, vol. 199(C), pages 220-232.
  37. Ye Li & Clemens Kool & Peter-Jan Engelen, 2020. "Analyzing the Business Case for Hydrogen-Fuel Infrastructure Investments with Endogenous Demand in The Netherlands: A Real Options Approach," Sustainability, MDPI, vol. 12(13), pages 1-22, July.
  38. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
  39. Kaijie Zhu & Ulrich W. Thonemann, 2004. "An adaptive forecasting algorithm and inventory policy for products with short life cycles," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(5), pages 633-653, August.
  40. Wu, Xiang & Xiong, Jie & Li, Haitao & Wu, Han, 2019. "The myth of retail pricing policy for developing organic vegetable markets," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 8-13.
  41. Guidolin, Mariangela & Guseo, Renato, 2014. "Modelling seasonality in innovation diffusion," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 33-40.
  42. Ashutosh Jha & Debashis Saha, 2022. "Mobile Broadband for Inclusive Connectivity: What Deters the High-Capacity Deployment of 4G-LTE Innovation in India?," Information Systems Frontiers, Springer, vol. 24(4), pages 1305-1329, August.
  43. Dong, Changgui & Sigrin, Benjamin & Brinkman, Gregory, 2017. "Forecasting residential solar photovoltaic deployment in California," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 251-265.
  44. Yongchao Zeng & Peiwu Dong & Yingying Shi & Yang Li, 2018. "On the Disruptive Innovation Strategy of Renewable Energy Technology Diffusion: An Agent-Based Model," Energies, MDPI, vol. 11(11), pages 1-21, November.
  45. Lechman, Ewa & Popowska, Magdalena, 2022. "Harnessing digital technologies for poverty reduction. Evidence for low-income and lower-middle income countries," Telecommunications Policy, Elsevier, vol. 46(6).
  46. James, Waters, 2015. "Do vegetarian marketing campaigns promote a vegan diet?," MPRA Paper 66737, University Library of Munich, Germany.
  47. Xiao, Yu & Han, Jingti, 2016. "Forecasting new product diffusion with agent-based models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 167-178.
  48. Koray Cosguner & P. B. (Seethu) Seetharaman, 2022. "Dynamic Pricing for New Products Using a Utility-Based Generalization of the Bass Diffusion Model," Management Science, INFORMS, vol. 68(3), pages 1904-1922, March.
  49. Jacob Goldenberg & Oded Lowengart & Daniel Shapira, 2009. "Zooming In: Self-Emergence of Movements in New Product Growth," Marketing Science, INFORMS, vol. 28(2), pages 274-292, 03-04.
  50. Jacob Goldenberg & Barak Libai & Eitan Muller & Renana Peres, 2006. "Blazing Saddles: the early and mainstream markets in the High-Tech product life cycle," Israel Economic Review, Bank of Israel, vol. 4(2), pages 85-108.
  51. Marszk, Adam & Lechman, Ewa, 2019. "New technologies and diffusion of innovative financial products: Evidence on exchange-traded funds in selected emerging and developed economies," Journal of Macroeconomics, Elsevier, vol. 62(C).
  52. Hlavinka, Alexander N. & Mjelde, James W. & Dharmasena, Senarath & Holland, Christine, 2016. "Forecasting the adoption of residential ductless heat pumps," Energy Economics, Elsevier, vol. 54(C), pages 60-67.
  53. Arkadiusz Kijek & Tomasz Kijek, 2010. "Modelling of innovation diffusion," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(3-4), pages 53-68.
  54. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
  55. Alex Bentley & Paul Ormerod, 2009. "Tradition And Fashion In Consumer Choice: Bagging The Scottish Munros," Scottish Journal of Political Economy, Scottish Economic Society, vol. 56(3), pages 371-381, July.
  56. repec:gdk:wpaper:34 is not listed on IDEAS
  57. Franses, Ph.H.B.F., 2003. "On the Bass diffusion theory, empirical models and out-of-sample forecasting," ERIM Report Series Research in Management ERS-2003-034-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  58. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
  59. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
  60. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
  61. 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.
  62. Bacha, Radia & Gasmi, Farid, 2022. "The broadband diffusion process and its determinants in Algeria: A simultaneous estimation," TSE Working Papers 22-1309, Toulouse School of Economics (TSE).
  63. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
  64. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
  65. Venkatesan, Rajkumar & Kumar, V., 2002. "A genetic algorithms approach to growth phase forecasting of wireless subscribers," International Journal of Forecasting, Elsevier, vol. 18(4), pages 625-646.
  66. Tunstall, Thomas, 2015. "Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale," Energy, Elsevier, vol. 93(P1), pages 580-588.
  67. Waters, James, 2013. "Variable marginal propensities to pirate and the diffusion of computer software," MPRA Paper 46036, University Library of Munich, Germany.
  68. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
  69. Park, Sang-June & Lee, Yeong-Ran & Borle, Sharad, 2018. "The shape of Word-of-Mouth response function," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 304-309.
  70. Theoharakis, Vasilis & Vakratsas, Demetrios & Wong, Veronica, 2007. "Market-level information and the diffusion of competing technologies: An exploratory analysis of the LAN industry," Research Policy, Elsevier, vol. 36(5), pages 742-757, June.
  71. Y. Li & C.J.M. Kool & P.J. Engelen, 2016. "Hydrogen-Fuel Infrastructure Investment with Endogenous Demand: A Real Options Approach," Working Papers 16-12, Utrecht School of Economics.
  72. Chang, Byeong-Yun & Li, Xu & Kim, Yun Bae, 2014. "Performance comparison of two diffusion models in a saturated mobile phone market," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 41-48.
  73. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
  74. Zhang, Shoutong Thomas, 2016. "Firm valuation from customer equity: When does it work and when does it fail?," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 966-970.
  75. Marshall, Pablo & Dockendorff, Monika & Ibáñez, Soledad, 2013. "A forecasting system for movie attendance," Journal of Business Research, Elsevier, vol. 66(10), pages 1800-1806.
  76. Carlos A. Arbelaez-Velasquez & Diana Giraldo & Santiago Quintero, 2022. "Analysis of a Teleworking Technology Adoption Case: An Agent-Based Model," Sustainability, MDPI, vol. 14(16), pages 1-14, August.
  77. Gil Appel & Eitan Muller, 2021. "Adoption patterns over time: a replication," Marketing Letters, Springer, vol. 32(4), pages 499-511, December.
  78. 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.
  79. Shun-Chen Niu, 2006. "A Piecewise-Diffusion Model of New-Product Demands," Operations Research, INFORMS, vol. 54(4), pages 678-695, August.
  80. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
  81. 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.
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  89. Sung Yong Chun & Minhi Hahn, 2008. "A diffusion model for products with indirect network externalities," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 357-370.
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