Prof. Peter P. Zubcsek (Warrington College)

Program

• Date: 20.11.2014
  Time: 10am - 12noon
  Location: Ludwigstr. 28, VG, Room 211b

"Behavioral Science Research on and with Mobile Devices"

Over the last two decades, researchers have developed many tools that help them investigate consumer behavior. Internet research tools have allowed researchers to reach more demographically and geographically diverse populations, and allowed for an increasing array of interactivity. However, these tools have increasingly focused on pull technology, resulting in systems that are constrained in terms of the factors that they can control and/or manipulate. They are, for example, unable to address fundamental questions about the effects of time and delay, because those variables are now out of the researcher’s control. Similarly, it is not possible to schedule research interactions to occur immediately after the participant has visited a certain location or area, because that information is unknown to the researcher.

We are developing a collaborative research system, mLab, which will circumvent many of these constraints. The solution is a client-server platform wherein the client applications run on smartphones. By utilizing mobile technology, the system will enable researchers to interact with participants over time, controlling when, where and under what conditions participants receive particular questions. In this system, researchers can control the events that are used to send notifications to participants’ mobile devices. Participants then receive instructions and (multimedia) stimuli and respond to questions relevant for that particular event. Researchers can specify for any given study, the questions to be received at 9AM, noon, and 3PM; exactly 90 minutes after a prior survey has been completed, etc. The result will be a system that possesses many of the same characteristics of a traditional web-based research platform while also allowing control over time and location.

In my talk, I will discuss the advantages of and challenges pertaining to our novel methodology, and I will also present some preliminary results on data collected via behavioral experiments hosted on the mLab platform.