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Strategic formation of collaborative networks

Philip Solimine, Luke Boosey

TL;DR

The paper investigates how endogenous network formation and information structure influence voluntary collaboration. Using a lab experiment where groups choose contributions and who to share with, the authors show that providing detailed information about others' sharing drives higher contributions, more links, and coordination on efficient, decentralized structures through direct reciprocity. A panel structural model reveals how trust and two forms of reciprocity (overall and positive) shape behavior, with heterogeneity captured via PCA; counterfactuals indicate increasing positive reciprocity yields the most robust efficiency gains across information settings. The work contributes to network public goods, structural estimation on dynamic networks, and social-preference literature, offering actionable insights for platform design to promote collaboration through targeted information and reciprocity-promoting policies.

Abstract

We examine behavior in an experimental collaboration game that incorporates endogenous network formation. The environment is modeled as a generalization of the voluntary contributions mechanism. By varying the information structure in a controlled laboratory experiment, we examine the underlying mechanisms of reciprocity that generate emergent patterns in linking and contribution decisions. Providing players more detailed information about the sharing behavior of others drastically increases efficiency, and positively affects a number of other key outcomes. To understand the driving causes of these changes in behavior we develop and estimate a structural model for actions and small network panels and identify how social preferences affect behavior. We find that the treatment reduces altruism but stimulates reciprocity, helping players coordinate to reach mutually beneficial outcomes. In a set of counterfactual simulations, we show that increasing trust in the community would encourage higher average contributions at the cost of mildly increased free-riding. Increasing overall reciprocity greatly increases collaborative behavior when there is limited information but can backfire in the treatment, suggesting that negative reciprocity and punishment can reduce efficiency. The largest returns would come from an intervention that drives players away from negative and toward positive reciprocity.

Strategic formation of collaborative networks

TL;DR

The paper investigates how endogenous network formation and information structure influence voluntary collaboration. Using a lab experiment where groups choose contributions and who to share with, the authors show that providing detailed information about others' sharing drives higher contributions, more links, and coordination on efficient, decentralized structures through direct reciprocity. A panel structural model reveals how trust and two forms of reciprocity (overall and positive) shape behavior, with heterogeneity captured via PCA; counterfactuals indicate increasing positive reciprocity yields the most robust efficiency gains across information settings. The work contributes to network public goods, structural estimation on dynamic networks, and social-preference literature, offering actionable insights for platform design to promote collaboration through targeted information and reciprocity-promoting policies.

Abstract

We examine behavior in an experimental collaboration game that incorporates endogenous network formation. The environment is modeled as a generalization of the voluntary contributions mechanism. By varying the information structure in a controlled laboratory experiment, we examine the underlying mechanisms of reciprocity that generate emergent patterns in linking and contribution decisions. Providing players more detailed information about the sharing behavior of others drastically increases efficiency, and positively affects a number of other key outcomes. To understand the driving causes of these changes in behavior we develop and estimate a structural model for actions and small network panels and identify how social preferences affect behavior. We find that the treatment reduces altruism but stimulates reciprocity, helping players coordinate to reach mutually beneficial outcomes. In a set of counterfactual simulations, we show that increasing trust in the community would encourage higher average contributions at the cost of mildly increased free-riding. Increasing overall reciprocity greatly increases collaborative behavior when there is limited information but can backfire in the treatment, suggesting that negative reciprocity and punishment can reduce efficiency. The largest returns would come from an intervention that drives players away from negative and toward positive reciprocity.

Paper Structure

This paper contains 22 sections, 2 theorems, 18 equations, 6 figures, 7 tables.

Table of Contents

  1. Introduction
  2. Network provision of public goods
  3. Structural estimation from network data
  4. Social preferences for trust and reciprocity
  5. Outline of the paper.
  6. Conceptual Framework
  7. Experimental Design
  8. Reduced-Form Results
  9. Contributions and links
  10. Efficient Structure
  11. Individual Costs
  12. Reciprocity
  13. Centralization
  14. Structural Estimation
  15. Structural Model
  16. ...and 7 more sections

Key Result

Proposition 1

The unique Nash equilibrium of the sharing game (under Assumption asn:boundedmpcr) is $c_i = 0$ and $N_i = \emptyset$.

Figures (6)

  • Figure 1: Dynamics of key outcomes
  • Figure 2: Dependence graphs for a two-player game.
  • Figure 3: Scree plot of the eigenvalues determining reciprocity characteristics
  • Figure 4: Results of counterfactual uniform increases to trust
  • Figure 5: Results of counterfactual uniform increases to overall reciprocity
  • ...and 1 more figures

Theorems & Definitions (7)

  • Proposition 1
  • proof
  • Definition 1
  • Definition 2
  • Definition 3
  • Proposition 2
  • proof