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Environmental options and technological innovation: an evolutionary game model

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  • Angelo Antoci
  • Simone Borghesi
  • Marcello Galeotti

Abstract

This paper analyzes the effects on economic agents’ behavior of an innovative environmental protection mechanism that the public administration of a tourist region may adopt to attract visitors while protecting the environment. On the one hand, the public administration sells to the tourists an environmental call option that gives them the possibility of being (partially or totally) reimbursed if the environmental quality in the region turns out to be unsatisfactory. On the other hand, it offers the firms that adopt an innovative, non-polluting technology an environmental put option that allows them to get a reimbursement for the additional costs imposed by the new technology if the environmental quality is sufficiently good. The aim of the paper is to study the dynamics that arise with this financial mechanism from the interaction between the economic agents and the public administration in an evolutionary game context. The evolution of visitors’ and firms’ behavior is modeled in the paper using the so-called replicator dynamics, according to which a given choice spreads across the population as long as its expected payoff is greater than the average payoff. From the model it emerges that such dynamics may lead either to a welfare-improving attractive Nash equilibrium, in which all firms adopt the environmental-friendly technology, or to a Pareto-dominated equilibrium with no technological innovation and no tourism. As shown in the paper, the attraction basin of the virtuous equilibrium will be maximum if total reimbursement is offered by the public administration to the visitors, and will be minimum if a simple entrance ticket is imposed on the tourists with no chance of reimbursement. Copyright Springer-Verlag 2013

Suggested Citation

  • Angelo Antoci & Simone Borghesi & Marcello Galeotti, 2013. "Environmental options and technological innovation: an evolutionary game model," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 247-269, April.
    • Handle: RePEc:spr:joevec:v:23:y:2013:i:2:p:247-269
    DOI: 10.1007/s00191-011-0238-0
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    References listed on IDEAS

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    1. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    2. Perrings, Charles, 1989. "Environmental bonds and environmental research in innovative activities," Ecological Economics, Elsevier, vol. 1(1), pages 95-110, February.
    3. Perrings,Charles, 1987. "Economy and Environment," Cambridge Books, Cambridge University Press, number 9780521340816, September.
    4. Costanza, Robert & Perrings, Charles, 1990. "A flexible assurance bonding system for improved environmental management," Ecological Economics, Elsevier, vol. 2(1), pages 57-75, April.
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    Citations

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    Cited by:

    1. Angelo Antoci & Marcello Galeotti & Davide Radi, 2011. "Financial Tools for the Abatement of Traffic Congestion: A Dynamical Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 38(3), pages 389-405, October.
    2. Esther Blanco & Javier Lozano, 2015. "Ecolabels, uncertified abatement, and the sustainability of natural resources: an evolutionary approach," Journal of Evolutionary Economics, Springer, vol. 25(3), pages 623-647, July.
    3. Gianluca Iannucci & Federico Martellozzo & Filippo Randelli, 2022. "Sustainable development of rural areas: a dynamic model in between tourism exploitation and landscape decline," Journal of Evolutionary Economics, Springer, vol. 32(3), pages 991-1016, July.
    4. Zi Tang & Minsi Zhang, 2023. "Evolutionary game analysis of energy saving behavior of tourism enterprises under carbon emission constraints," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 49-54.
    5. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.
    6. Fabio Castelli & Marcello Galeotti & Giovanni Rabitti, 2019. "Financial Instruments for Mitigation of Flood Risks: The Case of Florence," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 462-472, February.
    7. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    8. Simone Borghesi, 2020. "Satisfied or Reimbursed: An Innovative Index-Based Mechanism for the Environmental Protection of a Tourist Region," Sustainability, MDPI, vol. 12(21), pages 1-8, October.
    9. Juan M. Hernández & Jacques Bulchand-Gidumal & Manuel Chica, 2022. "The Role of the Tourism Network in the Coordination of Pandemic Control Measures," Sustainability, MDPI, vol. 14(23), pages 1-17, December.

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    More about this item

    Keywords

    Environmental bonds; Call and put options; Technological innovation; Evolutionary dynamics; C62; C70; G10; H23; Q55; Q58;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy

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