IDEAS home Printed from https://ideas.repec.org/p/ags/cuaewp/18803.html

Product Life Cycle Model Of Cowpea Based Products In Ghana

Author

Listed:
  • Nyankori, James Cyprian Okuk
  • Wabukawo, Veronica
  • Sakyi-Dawson, Esther
  • Sefa-Dedeh, Sam

Abstract

An exploratory market study of cowpea products in Ghana using data from case studies of consumers, personal interviews of processors and market surveillance of retail outlets indicated that the cowpea processing industry has low milling capacity, low production level, and few small operators most of whom have been in the business for less than six years. Cowpea flour, the main value added product, is typically sold in bulk or unbranded small packages through retail and wholesale outlets and directly to consumers including individuals, institutions and the catering industry. Although a high proportion of processors are aware of the new cowpea utilization technologies, only a low percentage have capacity expansion plans within the next two years. A large majority is uncertain and a small percentage has no expansion plans in the next two years. Cowpea products are widely consumed but are facing increasing competition from soybean especially in weaning mixes. However, there are several dishes using cowpea flour produced in the household and these provide a varied nutritious diet and have added desirable attributes which include easy cooking, availability, and favorable taste. The cowpea products industry is a nascent industry, apparently in stage two of the product life cycle, the introduction stage, which is characterized by a limited number of competing firms, low profitability, and high prices. The full impact of new utilization technologies will be realized over several years following substantial private capital investments in processing, marketing and strategic promotional activities.

Suggested Citation

  • Nyankori, James Cyprian Okuk & Wabukawo, Veronica & Sakyi-Dawson, Esther & Sefa-Dedeh, Sam, 2002. "Product Life Cycle Model Of Cowpea Based Products In Ghana," Working Papers 18803, Clemson University, Department of Agricultural and Applied Economics.
    • Handle: RePEc:ags:cuaewp:18803
    DOI: 10.22004/ag.econ.18803
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/18803/files/sp052402.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.18803?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    2. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2002. "Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint," Management Science, INFORMS, vol. 48(2), pages 187-206, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Srinivasan, Sunderasan, 2007. "The Indian solar photovoltaic industry: a life cycle analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(1), pages 133-147, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Berkowitz, J. & Birgean, I. & Kilian, L., 1999. "On the Finite-Sample Accuracy of Nonparametric Resampling Algorithms for Economic Time Series," Papers 99-01, Michigan - Center for Research on Economic & Social Theory.
    2. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    3. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2011. "Note: A Reply to "New Product Diffusion Decisions Under Supply Constraints"," Management Science, INFORMS, vol. 57(10), pages 1811-1812, October.
    4. repec:hum:wpaper:sfb649dp2006-021 is not listed on IDEAS
    5. Daniel Grabowski & Anna Staszewska-Bystrova & Peter Winker, 2020. "Skewness-adjusted bootstrap confidence intervals and confidence bands for impulse response functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 5-32, March.
    6. 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).
    7. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    8. Zhiling Guo & Jianqing Chen, 2018. "Multigeneration Product Diffusion in the Presence of Strategic Consumers," Information Systems Research, INFORMS, vol. 29(1), pages 206-224, March.
    9. Lim, Wei Shi & Tang, Christopher S., 2006. "Optimal product rollover strategies," European Journal of Operational Research, Elsevier, vol. 174(2), pages 905-922, October.
    10. Surya Pathak & P. V. Sundar Balakrishnan, 2025. "The paradox of product scarcity: Catalyzing the speed of innovation diffusion," Journal of the Academy of Marketing Science, Springer, vol. 53(3), pages 804-824, May.
    11. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    12. Ye, Yi & Nie, Jiajia & Guo, Qiang, 2025. "Economic analysis of energy procurement under price cap policy," Energy Economics, Elsevier, vol. 148(C).
    13. Vahideh Manshadi & Sidhant Misra & Scott Rodilitz, 2020. "Diffusion in Random Networks: Impact of Degree Distribution," Operations Research, INFORMS, vol. 68(6), pages 1722-1741, November.
    14. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.
    15. Teck-Hua Ho & Shan Li & So-Eun Park & Zuo-Jun Max Shen, 2012. "Customer Influence Value and Purchase Acceleration in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 236-256, March.
    16. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    17. Leeb, Hannes & Pötscher, Benedikt M., 2008. "Can One Estimate The Unconditional Distribution Of Post-Model-Selection Estimators?," Econometric Theory, Cambridge University Press, vol. 24(2), pages 338-376, April.
    18. Kartik Hosanagar & Peng Han & Yong Tan, 2010. "Diffusion Models for Peer-to-Peer (P2P) Media Distribution: On the Impact of Decentralized, Constrained Supply," Information Systems Research, INFORMS, vol. 21(2), pages 271-287, June.
    19. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    20. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    21. Ciccarone Giuseppe & Giuli Francesco & Marchetti Enrico, 2020. "Prospect Theory and sentiment-driven fluctuations," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-25, January.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:cuaewp:18803. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dacleus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.