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Behavioral biases in new product forecasting

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  • Tyebjee, Tyzoon T.

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  • Tyebjee, Tyzoon T., 1987. "Behavioral biases in new product forecasting," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 393-404.
    • Handle: RePEc:eee:intfor:v:3:y:1987:i:3-4:p:393-404
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    Citations

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    Cited by:

    1. Rotheli, Tobias F., 2005. "The illusion of over-optimism in survey data: the case of manufacturers' selling prices," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 34(2), pages 151-159, March.
    2. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    3. Benjamin R. Handel & Kanishka Misra, 2015. "Robust New Product Pricing," Marketing Science, INFORMS, vol. 34(6), pages 864-881, November.
    4. 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).
    5. Belvedere, Valeria & Goodwin, Paul, 2017. "The influence of product involvement and emotion on short-term product demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 652-661.
    6. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    7. Thomassey, Sebastien & Happiette, Michel & Castelain, Jean Marie, 2005. "A short and mean-term automatic forecasting system--application to textile logistics," European Journal of Operational Research, Elsevier, vol. 161(1), pages 275-284, February.
    8. 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.
    9. Harvey, Nigel & Koehler, Derek J. & Ayton, Peter, 1997. "Judgments of Decision Effectiveness: Actor-Observer Differences in Overconfidence," Organizational Behavior and Human Decision Processes, Elsevier, vol. 70(3), pages 267-282, June.
    10. Daniel Feiler & Jordan Tong, 2022. "From Noise to Bias: Overconfidence in New Product Forecasting," Management Science, INFORMS, vol. 68(6), pages 4685-4702, June.
    11. 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.
    12. 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.
    13. 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.
    14. Segelod, Esbjorn, 2000. "A comparison of managers perceptions of short-termism in Sweden and the U.S," International Journal of Production Economics, Elsevier, vol. 63(3), pages 243-254, January.
    15. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    16. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.

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