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KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association GMUNDEN RETREAT ON NEUROIS 2014 www.kit.edu A NeuroIS Platform for Lab Experiments Marius B. Müller, Anuja Hariharan, Marc T. P. Adam

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KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association

GMUNDEN RETREAT ON NEUROIS 2014

www.kit.edu

A NeuroIS Platform for Lab ExperimentsMarius B. Müller, Anuja Hariharan, Marc T. P. Adam

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Why yet another platform for experiments?

Many platforms already exist

… and even more one time use and single purpose implementations.

Common missing elements:

Integration of bio sensors (and all its requirements)

Easily adaptable and extendable to individual experiment

Offline and online analyses

Decision to create new platform

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Agenda

Objectives & Design

Architecture

Use cases/Demonstration

Evaluation

Limitations & Next steps

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Objectives & DesignMain objectives

Facilitating the creation of lab experiments by reducing development time

Facilitating individual & group interactions in a controlled lab setting

Integrating measurements of bio sensors and logging of physiological data specific to subject events

Ease of event logging and data storage, enabling experiments to scale in time and subject size

Meeting emerging technical requirements in the field of IS research and experimental economics

Design inspirationMicroeconomic Systemby Vernon L. Smith (1976, 1982)

Economic environment

Microeconomic institution

Friedman and Sunder (1994)

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General Platform Architecture

core components

server client

cust

omiz

able

built

-in

experimental design

server(procedure)

client(visualization)

bio sensors

client(recording)

server(control)

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Demonstration: Auction Fever

Experiment Details

Research question: Investigate the process of auction fever in retail auctions and its affects on bidding behavior

Design:2x2 factorial between-subjects designParticipants: 216

Sensors:Measurement of arousal usingECG, EDA & PPG

Platform supportThree groups of three subjects each interact simultaneouslyIntegration of individually chosen avatarsScalability and data preparation

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Demonstration: Auction Workload

Experiment Details

Research question: Understand how IS constructs (arousal and workload) are influenced by auction types and uncertaintyImpact on bidding behavior

Design:2x2 factorial within-subjects designParticipants: 54

Sensors:Measurement of arousal using ECG & EDAMeasurement of workload using EEG

Platform supportSimulate computer agentsSynchronously add triggers to EEG data for various eventsHR and SC data transmitted via bluetooth and stored on client

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Evaluation Process

1) Eeekels(1991) 2) Takeda (1990) 3) Hevner (2004) 4) Cole (2005)

Choose Evaluation

method

• Observational and Descriptive (1)

Choose Evaluation

Type

• Confirmatiory Evaluation (2)• Step 1 : Confirm the solution• Step 2 : Evaluate problem in the solution

Define Metrics

• Utility, Quality, Efficacy (3)• Simplicity, power (4)

Evaluate the evaluation

• Feedback from other IS researchers

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Limitations and Next Iteration

Limitations:Java-APIs not available for other methods (such as fMRIs)

Too rich/not the tool for “simple” surveys

Need to circulate and evaluate tool outside KIT

Combine coding with drag-and-drop UI design methods

• Within own Research Group

• Tested with diff. sensors

Iteration 1

• Other research groups in KIT

• w/o sensors

Iteration 2

• External Research Groups

• Field Experiments

Iteration 3

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Summary & Outlook

Contribution:Stable prototype for implementing experiments with physiological measurements and strategic interactions

Requirements & Objective of research gap for NeuroIS tool specified and met through first iteration

Communication: Distribute as a ready-to-use eclipse workspace

Version controlled source-code repository on Bit Bucket

Tutorials, sample experiments, technical support

Scientific publications

Thank you for your attention!

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Contacts

[email protected]

[email protected]+49 (721) 608 4 8374

[email protected]+49 (721) 608 4 83 82

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Literature

Cole, R.; Purao, S.; Rossi, M.; and Sein, M.K. Being proactive: Where action research meets design research. In D. Avison, D. Galletta, and J.I. DeGross (eds.), Twenty-Sixth International Conference on Information Systems. Atlanta: Association for Information Systems, 2005, pp. 325–336.

Eekels, J., & Roozenburg, N. F. (1991). A methodological comparison of the structures of scientific research and engineering design: their similarities and differences. Design Studies, 12(4), 197-203.

Friedman, D. (1994). Experimental methods: A primer for economists. Cambridge University Press.

Hevner, A.R.; March, S.T.; and Park, J. Design research in information systems research. MIS Quarterly, 28, 1 (2004), 75–105.

Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of management information systems, 24(3), 45-77.

Smith, V. L. (1975). Experimental economics: Induced value theory. University of Arizona, College of Business and Public Administration, Division of Economic and Business Research.

Smith, V. L. (1989). Theory, experiment and economics. The Journal of Economic Perspectives, 151-169.

Takeda, H.; Veerkamp, P.; Tomiyama, T.; and Yoshikawam, H. Modeling design processes. AI Magazine, 11, 4 (Winter 1990), 37–48.