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The Relationship of Actual and Predicted Sales and Profits in New-Product Introductions

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  • Donald S. Tull

Abstract

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Suggested Citation

  • Donald S. Tull, 1967. "The Relationship of Actual and Predicted Sales and Profits in New-Product Introductions," The Journal of Business, University of Chicago Press, vol. 40, pages 233-233.
    • Handle: RePEc:ucp:jnlbus:v:40:y:1967:p:233
    DOI: 10.1086/294974
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    Cited by:

    1. J. Scott Armstrong & Kesten C. Green, 2005. "Demand Forecasting: Evidence-based Methods," Monash Econometrics and Business Statistics Working Papers 24/05, Monash University, Department of Econometrics and Business Statistics.
    2. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    3. Jung, Sang Hoon & Jeong, Yong Jin, 2020. "Twitter data analytical methodology development for prediction of start-up firms’ social media marketing level," Technology in Society, Elsevier, vol. 63(C).
    4. Buehler, Roger & Griffin, Dale, 2003. "Planning, personality, and prediction: The role of future focus in optimistic time predictions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 92(1-2), pages 80-90.
    5. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    6. Gary L. Lilien & Pamela D. Morrison & Kathleen Searls & Mary Sonnack & Eric von Hippel, 2002. "Performance Assessment of the Lead User Idea-Generation Process for New Product Development," Management Science, INFORMS, vol. 48(8), pages 1042-1059, August.
    7. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, University Library of Munich, Germany.

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