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Introducing the Bonn Experiment System (BoXS)

Author

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  • Seithe, Mirko

Abstract

Computerised experiments play a vital part in the modern economic and social sciences. As the technology advances, more complex and sophisticated experiments become feasible. Fast internet connections are widely available today and mobile devices have become capable of running complex graphical applications. The Bonn Experiment System (BoXS) was designed to provide a platform for designing and conducting computerised experiments which is both easy to approach and use, as well as flexible in its possible applications. It does not require installation and uses a lean client which runs on Windows, MacOS and Linux and only requires a web browser and a Java Runtime Environment to execute. This paper intends to highlight the main features and limitations of the BoXS and provide some guidance for experimenters getting started with it. It also discusses some of the design decisions and provides in-depth information on technical aspects of the system. The appendix includes both the documentation and full code examples.

Suggested Citation

  • Seithe, Mirko, 2012. "Introducing the Bonn Experiment System (BoXS)," Bonn Econ Discussion Papers 01/2012, University of Bonn, Bonn Graduate School of Economics (BGSE).
    • Handle: RePEc:zbw:bonedp:012012
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    File URL: https://www.econstor.eu/bitstream/10419/74638/1/747435278.pdf
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    Cited by:

    1. Schwerter, Frederik & Zimmermann, Florian, 2020. "Determinants of trust: The role of personal experiences," Games and Economic Behavior, Elsevier, vol. 122(C), pages 413-425.
    2. Both, F. & Adam, M.T.P. & Hariharan, A. & Dorner, V. & Lux, E. & Weinhardt, C., 2016. "A randomized tabu search-based approach for perfect stranger matching in economic experiments," Economics Letters, Elsevier, vol. 145(C), pages 235-238.
    3. Tiziana Medda & Vittorio Pelligra & Tommaso Reggiani, 2021. "Lab-Sophistication: Does Repeated Participation in Laboratory Experiments Affect Pro-Social Behaviour?," Games, MDPI, vol. 12(1), pages 1-14, February.
    4. Shaun P. Hargreaves Heap & Eugenio Levi & Abhijit Ramalingam, 2021. "Group identification and giving: in-group love, out-group hate and their crowding out," MUNI ECON Working Papers 2021-07, Masaryk University, revised Feb 2023.
    5. Chan, Shu Wing & Schilizzi, Steven & Iftekhar, Md Sayed & Da Silva Rosa, Raymond, 2019. "Web-based experimental economics software: How do they compare to desirable features?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 138-160.
    6. Frackenpohl, Gerrit & Pönitzsch, Gert, 2013. "Bundling Public with Private Goods," Bonn Econ Discussion Papers 05/2013, University of Bonn, Bonn Graduate School of Economics (BGSE).
    7. Conrads, Julian & Lotz, Sebastian, 2015. "The effect of communication channels on dishonest behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 58(C), pages 88-93.
    8. Shaun P. Hargreaves Heap & Aikaterini Karadimitropoulou & Eugenio Levi, 2021. "Narrative based information: is it the facts or their packaging that matters?," MUNI ECON Working Papers 2021-08, Masaryk University, revised Feb 2023.

    More about this item

    Keywords

    Experiment System; Software; Experiment Conduction; Java;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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