IDEAS home Printed from https://ideas.repec.org/r/inm/ormksc/v33y2014i3p401-421.html
   My bibliography  Save this item

Prerelease Buzz Evolution Patterns and New Product Performance

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Ho Kim & Juncai Jiang & Norris I. Bruce, 2021. "Discovering heterogeneous consumer journeys in online platforms: implications for networking investment," Journal of the Academy of Marketing Science, Springer, vol. 49(2), pages 374-396, March.
  2. Alexei Parakhonyak & Nick Vikander, 2019. "Optimal Sales Schemes for Network Goods," Management Science, INFORMS, vol. 65(2), pages 819-841, February.
  3. Luo, Anita & Baker, Andrew & Donthu, Naveen, 2019. "Capturing dynamics in the value for brand recommendations from word-of-mouth conversations," Journal of Business Research, Elsevier, vol. 104(C), pages 247-260.
  4. Nguyen, Hang T. & Chaudhuri, Malika, 2019. "Making new products go viral and succeed," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 39-62.
  5. Kim, Ho & Bruce, Norris I., 2018. "Should sequels differ from original movies in pre-launch advertising schedule? Lessons from consumers' online search activity," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 116-143.
  6. Ning Zhong & David A. Schweidel, 2020. "Capturing Changes in Social Media Content: A Multiple Latent Changepoint Topic Model," Marketing Science, INFORMS, vol. 39(4), pages 827-846, July.
  7. Amaradri Mukherjee & Ronn J. Smith & Scot Burton, 2023. "The effect of positive anticipatory utility on product pre‑order evaluations and choices," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 551-569, May.
  8. 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.
  9. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
  10. Beth L. Fossen & David A. Schweidel, 2019. "Social TV, Advertising, and Sales: Are Social Shows Good for Advertisers?," Marketing Science, INFORMS, vol. 38(2), pages 274-295, March.
  11. Schulz, Petra & Shehu, Edlira & Clement, Michel, 2019. "When consumers can return digital products: Influence of firm- and consumer-induced communication on the returns and profitability of news articles," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 454-470.
  12. Alexei Parahonyak & Nick Vikander, 2024. "Strategic Use of Product Delays to Shape Word-of-Mouth Communication," Economics Series Working Papers 1032, University of Oxford, Department of Economics.
  13. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
  14. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
  15. Andrea Schöndeling & Alexa B. Burmester & Alexander Edeling & André Marchand & Michel Clement, 2023. "Marvelous advertising returns? A meta-analysis of advertising elasticities in the entertainment industry," Journal of the Academy of Marketing Science, Springer, vol. 51(5), pages 1019-1045, September.
  16. Pengyuan Wang & Guiyang Xiong & Jian Yang, 2019. "Frontiers: Asymmetric Effects of Recreational Cannabis Legalization," Marketing Science, INFORMS, vol. 38(6), pages 927-936, November.
  17. Kim, Ho & Hanssens, Dominique M., 2017. "Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 57-74.
  18. Maximilian Matthe & Daniel M. Ringel & Bernd Skiera, 2023. "Mapping Market Structure Evolution," Marketing Science, INFORMS, vol. 42(3), pages 589-613, May.
  19. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
  20. Mark B. Houston & Ann-Kristin Kupfer & Thorsten Hennig-Thurau & Martin Spann, 2018. "Pre-release consumer buzz," Journal of the Academy of Marketing Science, Springer, vol. 46(2), pages 338-360, March.
  21. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
  22. Davide Christian Orazi & Bhoomija Ranjan & Yimin Cheng, 2023. "Non-face emojis in digital marketing: Effects, contingencies, and strategic recommendations," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 570-597, May.
  23. Chang Liu & Shouming Chen & Qiuyue Shao, 2019. "Do CEO Rhetorical Strategies Affect Corporate Social Performance? Evidence from China," Sustainability, MDPI, vol. 11(18), pages 1-21, September.
  24. Shijie Lu & Koushyar Rajavi & Isaac Dinner, 2021. "The Effect of Over-the-Top Media Services on Piracy Search: Evidence from a Natural Experiment," Marketing Science, INFORMS, vol. 40(3), pages 548-568, May.
  25. Rex Yuxing Du & Tsung-Yiou Hsieh, 2023. "Leveraging Online Search Data as a Source of Marketing Insights," Foundations and Trends(R) in Marketing, now publishers, vol. 17(4), pages 227-291, August.
  26. Rasul, Tareq & Lim, Weng Marc & Dowling, Michael & Kumar, Satish & Rather, Raouf Ahmad, 2022. "Advertising expenditure and stock performance: A bibliometric analysis," Finance Research Letters, Elsevier, vol. 50(C).
  27. Vasu Unnava & Ashwin Aravindakshan, 2021. "How does consumer engagement evolve when brands post across multiple social media?," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 864-881, September.
  28. Young-Jin Lee & Kellie B. Keeling & Andrew Urbaczewski, 2019. "The Economic Value of Online User Reviews with Ad Spending on Movie Box-Office Sales," Information Systems Frontiers, Springer, vol. 21(4), pages 829-844, August.
  29. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
  30. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
  31. Venkatesh Shankar & Sohil Parsana, 2022. "An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1324-1350, November.
  32. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.