Project Selection and Competitive Cheap Talk: An Experimental Study

2019 ◽  
Author(s):  
John Hamman ◽  
Miguel Martinez-Carrasco ◽  
Eric Schmidbauer
Keyword(s):  
Experimental Study ◽  
Cheap Talk ◽  
Project Selection

scholarly journals Cheap Talk Games with Two-Senders and Different Modes of Communication

Games ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 18
Author(s):  
Esra E. Bayindir ◽  
Mehmet Y. Gurdal ◽  
Ayca Ozdogan ◽  
Ismail Saglam
Keyword(s):  
Experimental Study ◽  
Information Transmission ◽  
Cheap Talk ◽  
Experimental Results ◽  
The Third ◽  
Logistic Regressions ◽  
Cheap Talk Games ◽  
The One ◽  
High Payoff

This paper deals with the effects of different modes of communication in a costless information transmission environment with multiple senders. To this aim, we present a theoretical and experimental study of three Cheap Talk games, each having two senders and one receiver. The communication of senders is simultaneous in the first, sequential in the second and determined by the receiver in the third game (the Choice Game). We find that the overcommunication phenomenon observed with only one sender becomes insignificant in our two-sender model regardless of the mode of communication. However, as to the excessive trust of the receiver, our results are not distinguished from those in the one-sender model. Regarding the Choice Game, our logistic regressions on experimental results suggest that the receiver is more likely to select simultaneous play if the previous play was simultaneous and the receiver earned the high payoff and much more likely to select simultaneous play if the messages were nonconflicting.

scholarly journals Cheap Talk with Multiple Strategically Interacting Audiences: An Experimental Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0163783
Author(s):  
Xinyu Li ◽  
Ronald Peeters
Keyword(s):  
Experimental Study ◽  
Cheap Talk

scholarly journals Scaling up a Project Portfolio Selection Technique by using Multiobjective Genetic Optimization

2014 ◽  
Vol 7 (4) ◽  
pp. 60-74
Author(s):  
Márcio De Oliveira Barros ◽  
Hélio Costa ◽  
Fábio Vitorino Figueiredo ◽  
Ana Regina Cavalcanti Rocha
Keyword(s):  
Genetic Algorithm ◽  
Experimental Study ◽  
Portfolio Selection ◽  
Heuristic Search ◽  
Large Scale ◽  
Random Search ◽  
Project Selection ◽  
Project Portfolio ◽  
Selection Technique ◽  
Project Portfolio Selection

This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of the candidate projects, which turns to be unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four real-world project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure (random search). A second experimental study evaluates the best parameter settings to perform the heuristic search. Experimental results show evidence that the project selection technique can be used in large-scale scenarios and that the genetic algorithm presents better results than simpler search strategies.

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