Choiceflow can be a powerful alternative to zTree and oTree for behavioral economics experiments.
Popular among behavioral economics researchers, zTree (short for Zurich Toolbox For Readymade Economic Experiments) is a commonly used platform used by researchers to design and run behavioral economics and social science experiments. It also has an open source alternative called oTree built using Python and other open source projects. Both these tools can be used to develop and run behavioral economics experiments involving multiple parties and parallel decisioning such as prisoner’s dilemma, public goods game, ultimatum game, Vickrey auctions, and dutch auctions.
While both these platforms offer a compelling set of features with a unique set of pros and cons, the key challenge lies in the fact that they still require a lot of manual set up, programming, and infrastructure setup to support experiments. This is where Choiceflow is different, it’s all about simplicity without sacrificing the sophistication necessary for quality research. This article highlights several key advantages Choiceflow has over zTree and oTree.
About Choiceflow
Choiceflow is an online platform that helps behavioral researchers design, run, and analyze behavioral research experiments. Originally developed as a close collaboration between Deckspire and several marketing and behavioral science researchers at The Wharton School at the University of Pennsylvania, Choiceflow has evolved over the years to become a fully robust platform capable of supporting a variety of behavioral research use cases including organization behavior, leadership research, behavioral economics, and cognitive psychology.
Choiceflow is cloud-based, zTree and oTree are not
While zTree must be locally hosted with a client and server model (and only on a Windows machine) and oTree is quite similar although more flexible, Choiceflow is completely managed and cloud-based (ie. we host it and all you need is a login). Deploying these systems on servers and lab machines, and managing the administration can be cumbersome task even for the most sophisticated of researchers.
Choiceflow offers researchers a modern web interface to design and run their experiments and a JavaScript based API to develop advanced logic. All of the complexity of setting up an experiment infrastructure is completely eliminated and experiments can be run remotely across the world both in lab or within an online participant pool such as Amazon’s Mechanical Turk.
Choiceflow simplifies experimental data management and analysis
Both zTree and oTree require storing data in a database which can be a complex endeavor and cannot be easily modified with evolving needs of the experiment. In addition, not all essential data is tracked by these two systems. Choiceflow comes packaged with a scalable data and analytics tracking system.
By default, Choiceflow automatically tracks user data and interaction data such as participant input, start and end times, click behavior, participant engagement, participant browser information etc. Researchers can easily augment the base set of analytics with custom data and variables to suit their experimental needs.
Choiceflow is all drag-and-drop
While zTree offers a simplified drag-and-drop interface to design studies, oTree definitely falls behind on this front. The less time researchers can spend on writing boilerplate logic for experiments, the more time they can actually spend on higher value-add tasks such as experiment design, analyzing data, and recruiting participants.
Choiceflow, offers a familiar drag-and-drop web interface which allow researchers to rapidly mock up their experiments in PowerPoint or Photoshop and quick import their assets before overlaying the logic on top. This simplifies time to delivery and enables rapid iteration across experiments.
In summary, Choiceflow offers several key benefits over zTree and oTree for behavioral economics researchers. Here’s a quick summary to help you evaluate the choices:
