IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitmx/v10y2013i05ns0219877013400178.html
   My bibliography  Save this article

Investment Adjustments In Product Market Competition

Author

Listed:
  • TINO SCHÜTTE

    (Faculty of Business Administration and Engineering, Hochschule Zittau/Görlitz University of Applied Science, Theodor-Körner-Allee 16, 02763, Zittau, Germany)

Abstract

Situated in the research field of market structure and strategic behavior, a model is developed, which shows the impacts of investment adjustments on product market competition. Placed in a multi-firm multi-product setting, the consequences of decisions to split budgets in: (i) marketing and development activities and (ii) development expenditures into innovative or imitative activities is investigated. The model is validated with empirical data of the pharmaceutical industry, especially the drug market in Germany. An agent-based modeling and simulation approach is used to explain how the freedom of firms to adjust their investment according to an absolute (individual aspiration level) or relative comparison (success of competitors) can change market performance. The results show that investment strategies adjusted to the behavior of direct competitors outperforms adjustments based on individual aspiration levels.

Suggested Citation

  • Tino Schütte, 2013. "Investment Adjustments In Product Market Competition," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 1-14.
  • Handle: RePEc:wsi:ijitmx:v:10:y:2013:i:05:n:s0219877013400178
    DOI: 10.1142/S0219877013400178
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219877013400178
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219877013400178?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    2. Uwe Cantner & Horst Hanusch, 1998. "Industrie-Evolution," Discussion Paper Series 177, Universitaet Augsburg, Institute for Economics.
    3. Giulio Bottazzi & Giovanni Dosi & Marco Lippi & Fabio Pammolli & Massimo Riccaboni, 2000. "Processes of corporate growth in the evolution of an innovation-driven industry. The case of pharmaceuticals," LEM Papers Series 2000/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Mazzucato,Mariana & Dosi,Giovanni (ed.), 2006. "Knowledge Accumulation and Industry Evolution," Cambridge Books, Cambridge University Press, number 9780521858229.
    5. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    Full references (including those not matched with items on IDEAS)

    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. Gianluca Capone & Franco Malerba & Richard R. Nelson & Luigi Orsenigo & Sidney G. Winter, 2019. "History friendly models: retrospective and future perspectives," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 1-23, March.
    2. Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    3. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    4. J. Silvestre, & T. Araújo & M. St. Aubyn, 2016. "Economic growth and individual satisfaction in an agent-based economy," Working Papers Department of Economics 2016/19, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    5. Deniz Erdemlioglu & Nikola Gradojevic, 2021. "Heterogeneous investment horizons, risk regimes, and realized jumps," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 617-643, January.
    6. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    7. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
    8. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    9. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    10. Klaus Jaffe, 2015. "Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus," Papers 1509.04264, arXiv.org, revised Nov 2015.
    11. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, 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.
    12. repec:hal:spmain:info:hdl:2441/5bnglqth5987gaq6dhju3psjn3 is not listed on IDEAS
    13. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    14. Dirk Helbing & Thomas U. Grund, 2013. "Editorial: Agent-Based Modeling And Techno-Social Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-3.
    15. Frank Westerhoff & Martin Hohnisch, 2010. "Consumer sentiment and countercyclical fiscal policies," International Review of Applied Economics, Taylor & Francis Journals, vol. 24(5), pages 609-618.
    16. Zhang, Hui & Cao, Libin & Zhang, Bing, 2017. "Emissions trading and technology adoption: An adaptive agent-based analysis of thermal power plants in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 23-32.
    17. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    18. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    19. Paul L. Borrill & Leigh Tesfatsion, 2011. "Agent-based Modeling: The Right Mathematics for the Social Sciences?," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 11, Edward Elgar Publishing.
    20. Frank H. Westerhoff, 2006. "Business Cycles, Heuristic Expectation Formation, and Contracyclical Policies," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 8(5), pages 821-838, December.
    21. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2016. "How Inflation Affects Macroeconomic Performance: An Agent-Based Computational Investigation," Macroeconomic Dynamics, Cambridge University Press, vol. 20(2), pages 558-581, March.

    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:wsi:ijitmx:v:10:y:2013:i:05:n:s0219877013400178. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitm/ijitm.shtml .

    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.