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The Effects of Communication on the Partnership Solution to the Commons

There is more than a verbal tie between the words common, community, and communication.

-John Dewey

Abstract

Organizing individual appropriators into output sharing groups has been found to effectively solve the tragedy of the commons problem. We experimentally investigate the robustness of this solution by introducing different channels of communication that naturally arise from group competitions. In the absence of communication, we confirm that output sharing can introduce sufficient free riding to offset over-harvesting and results in full efficiency. Allowing local communication within output-sharing groups substantially decreases this efficiency enhancement because it reduces free riding and boosts between-group competition. Yet the efficiency level is still significantly higher than that achieved when global communication is allowed among all appropriators in a conventional common pool resource without output sharing. The efficiency-reducing effect of local communication is mitigated when random partners instead of fixed partners are sharing output over time, and is nearly eliminated when random partners are formed with users who belong to different communication groups.

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Fig. 1

Notes

  1. 1.

    Note that throughout this paper we use the term “communication” to mean “non-binding and costless communication”.

  2. 2.

    Most studies have examined the effect of communication in inter-group games with fixed groups and a fixed prize (Rapoport and Bornstein 1989; Schram and Sonnemans 1996; Cason et al. 2012; Leibbrandt and Sääksvuori 2012; Zhang 2012). Sutter and Strassmair (2009) examine the impact of communication in a group tournament in which the prize is not fixed and is paid by the losing team and shared equally in the winning team. They find that free riding dominates when teams cannot communicate or can only communicate with members of other teams. Communication within teams, on the other hand, increases individual contributions and efficiency. Contrary to theirs, in our experiment incentives are not monotonic as higher group contributions may lead to lower efficiency due to the congestion externality and the non-linear payoff of the CPR.

  3. 3.

    In this context a treatment is a specific combination of levels of the factors in the experiment [see “Treatment” in Statistics and Probability Dictionary (Stat Trek 2017)].  Factors are variables that have two or more discrete levels.  For example, in this experiment output sharing is a factor that can take on a Boolean value of true or false.  Similarly, local communication also is a factor that can take on a Boolean value of true or false.  For the CPR treatment both output sharing and local communication factors are false. All of the factors used in this study along with their combinations (i.e. treatments) will be described below and are summarized in Table 1.

  4. 4.

    Janssen et al. (2010) introduce chat-room communication into a CPR setting in which it is possible to destroy the CPR by over appropriation. Chat-room communication is successful in forestalling destruction of the CPR and raising profit. This result is similar to the results reported by Muller and Vickers (1996) who use face-to-face communication. Bochet et al. (2006) compare different forms of communication in public goods laboratory experiments and find little difference between the effects of face-to-face communication and verbal communication through a chat room.

  5. 5.

    Prior to the first decision round, individuals are given 4 min to send messages. Prior to the second and third decision rounds, individuals are given 3 min to communicate. Prior to the fourth round this is set at 2 min and from the fifth through the fifteenth rounds, communication is limited to 1 min. These time limits were based on debriefing subjects after several pilot sessions.

  6. 6.

    See section 1 of Appendix III for a derivation of the equilibrium results. See Schott et al. (2007) for the derivation of the optimal effort to allocate to appropriation from the common pool.

  7. 7.

    There is no unique individual extraction effort. See section 2 of Appendix III for this derivation.

  8. 8.

    Adding an additional observation to the data for the basic CPR treatment, the Fixed-Partners treatment and the Random-Partners treatment reported in Schott et al. (2007) does not affect the results obtained by Schott et al. (2007) that the system effort for each treatment is not different from the predicted values. In all cases the p values for the statistical tests are greater than 0.10 regardless of whether the additional observation is added.

  9. 9.

    All reported p values are based on two-sided tests unless otherwise stated. One-sided tests are used only when the prediction implies a direction for the change.

  10. 10.

    A test comparing the data for the mean system efforts of the two treatments supports the null hypothesis that there is no difference between the two means (F test, \(p = 0.299\), Mann–Whitney U test, \(p = 0.343\)).

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Correspondence to Stephan Schott.

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Buckley, N.J., Mestelman, S., Muller, R.A. et al. The Effects of Communication on the Partnership Solution to the Commons. Environ Resource Econ 70, 363–380 (2018). https://doi.org/10.1007/s10640-017-0124-9

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Keywords

  • Common pool resources
  • Output sharing
  • Partnership solution
  • Communication
  • Competition
  • Group behavior
  • Partners and strangers
  • Experiments

JEL Classification

  • Q20
  • C92
  • C72