IDEAS home Printed from https://ideas.repec.org/a/eee/streco/v31y2014icp138-148.html
   My bibliography  Save this article

Involuntary technology adoptions: How consumer interdependencies lead to societal change

Author

Listed:
  • Dilaver, Özge

Abstract

It is now well known that the technology adoption decisions of consumers depend on the number of existing adopters (Arthur, 1989) and so, the adoption decisions of consumers are interdependent. This paper investigates the societal implications of two interdependency types that are not adequately addressed in the existing literature: early adoption advantages (EAAs) and institutional change (IC). EAA corresponds to the use-value that agents create with the innovation, if they can adopt it earlier than others. Institutions are shared routines in society following the definition of Veblen (1919) and IC can be regarded as the changes in institutions that are induced by increasing levels of diffusion. In both EAA and IC, the adoption decisions of consumers depend on the number of existing adopters and this paper demonstrates that these interdependencies can lead to involuntary technology adoptions. That is, for some individuals, adoption is a worse state than their initial state before the launch of the innovation. Once it is launched, however, non-adoption becomes an even worse state. Hence, the agents adopt the innovation, albeit not happily. This implies that a society can ‘lock-in’ to inefficient, partially harmful or destructive technologies that entail these particular forms of consumer interdependencies.

Suggested Citation

  • Dilaver, Özge, 2014. "Involuntary technology adoptions: How consumer interdependencies lead to societal change," Structural Change and Economic Dynamics, Elsevier, vol. 31(C), pages 138-148.
  • Handle: RePEc:eee:streco:v:31:y:2014:i:c:p:138-148
    DOI: 10.1016/j.strueco.2014.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0954349X14000526
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.strueco.2014.09.003?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. Farrell, Joseph & Saloner, Garth, 1986. "Installed Base and Compatibility: Innovation, Product Preannouncements, and Predation," American Economic Review, American Economic Association, vol. 76(5), pages 940-955, December.
    2. Jennifer F. Reinganum, 1981. "On the Diffusion of New Technology: A Game Theoretic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(3), pages 395-405.
    3. Joseph Farrell & Garth Saloner, 1985. "Standardization, Compatibility, and Innovation," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 70-83, Spring.
    4. Cowan, Robin & Cowan, William & Swann, Peter, 1997. "A model of demand with interactions among consumers," International Journal of Industrial Organization, Elsevier, vol. 15(6), pages 711-732, October.
    5. Chow, Gregory C, 1989. "Rational versus Adaptive Expectations in Present Value Models," The Review of Economics and Statistics, MIT Press, vol. 71(3), pages 376-384, August.
    6. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
    7. John Foster & Burkhard Flieth, 2002. "Interactive expectations," Journal of Evolutionary Economics, Springer, vol. 12(4), pages 375-395.
    8. Witt, Ulrich, 1996. "Innovations, Externalities and the Problem of Economic Progress," Public Choice, Springer, vol. 89(1-2), pages 113-130, October.
    9. Richard R. Nelson, 2002. "special issue: Bringing institutions into evolutionary growth theory," Journal of Evolutionary Economics, Springer, vol. 12(1), pages 17-28.
    10. Jensen, Richard, 1992. "Innovation Adoption and Welfare under Uncertainty," Journal of Industrial Economics, Wiley Blackwell, vol. 40(2), pages 173-180, June.
    11. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    12. Franco Malerba, 2006. "Innovation and the evolution of industries," Journal of Evolutionary Economics, Springer, vol. 16(1), pages 3-23, April.
    13. Olivier Brette, 2003. "Thorstein Veblen's theory of institutional change: beyond technological determinism," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 10(3), pages 455-477.
    14. Nakayama, Shoichiro & Nakamura, Yasuyuki, 2004. "A fashion model with social interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(3), pages 625-634.
    15. E. Ostrom, 2010. "A Behavioral Approach to the Rational Choice Theory of Collective Action Presidential Address, American political Science Association, 1997," Public administration issues, Higher School of Economics, issue 1, pages 5-52.
    16. Metcalfe, J S, 1994. "Evolutionary Economics and Technology Policy," Economic Journal, Royal Economic Society, vol. 104(425), pages 931-944, July.
    17. David, Paul A, 1985. "Clio and the Economics of QWERTY," American Economic Review, American Economic Association, vol. 75(2), pages 332-337, May.
    18. Malcolm Rutherford, 1984. "Thorstein Veblen and the Processes of Institutional Change," History of Political Economy, Duke University Press, vol. 16(3), pages 331-348, Fall.
    19. Bertaut, Carol C. & Haliassos, Michael, 2005. "Credit cards: Facts and theories," CFS Working Paper Series 2006/19, Center for Financial Studies (CFS).
    20. Hall, Peter A. & Taylor, Rosemary C. R., 1996. "Political science and the three new institutionalisms," MPIfG Discussion Paper 96/6, Max Planck Institute for the Study of Societies.
    21. Simona Cantono & Gerald Silverberg, 2008. "A percolation model of eco-innovation diffusion: the relationship between diffusion, learning economies and subsidies," MERIT Working Papers 2008-025, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    22. Eric Abrahamson & Lori Rosenkopf, 1997. "Social Network Effects on the Extent of Innovation Diffusion: A Computer Simulation," Organization Science, INFORMS, vol. 8(3), pages 289-309, June.
    23. Ulrich Witt, 2001. "special issue: Learning to consume - A theory of wants and the growth of demand," Journal of Evolutionary Economics, Springer, vol. 11(1), pages 23-36.
    24. Williams, Robin & Edge, David, 1996. "The social shaping of technology," Research Policy, Elsevier, vol. 25(6), pages 865-899, September.
    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. Ozge Dilaver, 2015. "From Participants to Agents: Grounded Simulation as a Mixed-Method Research Design," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-15.

    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. repec:bla:jecsur:v:12:y:1998:i:2:p:131-76 is not listed on IDEAS
    2. den Hartigh, E. & Langerak, F. & Commandeur, H.R., 2002. "The Effects of Self-Reinforcing Mechanisms on Firm Performance," ERIM Report Series Research in Management ERS-2002-46-MKT, 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.
    3. Andrea Marchini & Chiara Riganelli & Francesco Diotallevi & Bianca Polenzani, 2021. "Label information and consumer behaviour: evidence on drinking milk sector," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-24, December.
    4. Papachristos, George, 2017. "Diversity in technology competition: The link between platforms and sociotechnical transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 291-306.
    5. Nathalie Lazaric & Vanessa Oltra, 2012. "Sustainable Consumption in an Evolutionary Framework: How to Foster Behavioural Change?," Chapters, in: Blandine Laperche & Nadine Levratto & Dimitri Uzunidis (ed.), Crisis, Innovation and Sustainable Development, chapter 3, Edward Elgar Publishing.
    6. Carrillo-Hermosilla, Javier, 2006. "A policy approach to the environmental impacts of technological lock-in," Ecological Economics, Elsevier, vol. 58(4), pages 717-742, July.
    7. Giovanni Dosi & Richard Nelson, 2013. "The Evolution of Technologies: An Assessment of the State-of-the-Art," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(1), pages 3-46, June.
    8. Nicholas Economides, 1997. "The Economics of Networks," Brazilian Electronic Journal of Economics, Department of Economics, Universidade Federal de Pernambuco, vol. 1(0), December.
    9. Pekka Sääskilahti, 2016. "Buying Decision Coordination and Monopoly Pricing of Network Goods," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 25(2), pages 313-333, April.
    10. Cowan, Robin & Cowan, William & Swann, Peter, 1997. "A model of demand with interactions among consumers," International Journal of Industrial Organization, Elsevier, vol. 15(6), pages 711-732, October.
    11. Albert Faber & Koen Frenken, 2008. "Models in evolutionary economics and environmental policy: Towards an evolutionary environmental economics," Innovation Studies Utrecht (ISU) working paper series 08-15, Utrecht University, Department of Innovation Studies, revised Apr 2008.
    12. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    13. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    14. Greaker Mads & Heggedal Tom-Reiel, 2010. "Lock-In and the Transition to Hydrogen Cars: Should Governments Intervene?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-30, May.
    15. Michihiro, Kandori & Rob, Rafael, 1998. "Bandwagon Effects and Long Run Technology Choice," Games and Economic Behavior, Elsevier, vol. 22(1), pages 30-60, January.
    16. van de Kaa, Geerten & de Vries, Henk J., 2015. "Factors for winning format battles: A comparative case study," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 222-235.
    17. Liangjie Zhao & Wenqi Duan, 2014. "Simulating the Evolution of Market Shares: The Effects of Customer Learning and Local Network Externalities," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 53-70, January.
    18. Grazia Cecere & Nicoletta Corrocher & Cédric Gossart & Muge Ozman, 2014. "Lock-in and path dependence: an evolutionary approach to eco-innovations," Journal of Evolutionary Economics, Springer, vol. 24(5), pages 1037-1065, November.
    19. Kenneth Arrow, 2000. "Increasing returns: historiographic issues and path dependence," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 7(2), pages 171-180.
    20. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    21. Heli Koski & Tobias Kretschmer, 2004. "Survey on Competing in Network Industries: Firm Strategies, Market Outcomes, and Policy Implications," Journal of Industry, Competition and Trade, Springer, vol. 4(1), pages 5-31, March.

    More about this item

    Keywords

    Innovation diffusion; Technological change; Institutional change; Early adoption advantages; Interdependency;
    All these keywords.

    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory

    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:eee:streco:v:31:y:2014:i:c:p:138-148. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/525148 .

    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.