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Big Data, Little Individual: Considering the Human Side of Big Data

Published online by Cambridge University Press:  17 December 2015

Michael N. Karim*
Affiliation:
Fors Marsh Group, LLC, Arlington, Virginia
Jon C. Willford
Affiliation:
Department of Organizational Sciences and Communication, The George Washington University
Tara S. Behrend
Affiliation:
Department of Organizational Sciences and Communication, The George Washington University
*
Correspondence concerning this article should be addressed to Michael N. Karim, Fors Marsh Group, LLC, 1010 North Glebe Road, Number 510, Arlington, VA 22201. E-mail: mkarim@forsmarshgroup.com

Extract

Guzzo, Fink, King, Tonidandel, and Landis (2015) provide a clear overview of the implications of conducting research using big data. One element we believe was overlooked, however, was an individual-level perspective on big data; that is, what impact does this sort of data collection have on the individuals being studied? As psychologists, the ethics and impact of big data collection from workers should be at the forefront of our minds. In this reply, we use years of research on electronic monitoring and tracking to provide evidence that an individual-level perspective is an essential part of the discussion surrounding industrial–organizational psychology and big data. Specifically, we examine electronic performance monitoring (EPM) literature to identify how the widespread, pervasive collection of employee data affects employees’ attitudes and behaviors.

Type
Commentaries
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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References

Aiello, J. R., & Kolb, K. J. (1995). Electronic performance monitoring and social context: Impact on productivity and stress. Journal of Applied Psychology, 80 (3), 339353. doi:10.1037/0021-9010.80.3.339CrossRefGoogle ScholarPubMed
Aiello, J. R., & Svec, C. M. (1993). Computer monitoring of work performance: Extending the social facilitation framework to electronic presence. Journal of Applied Social Psychology, 23 (7), 537548. doi:10.1111/j.1559-1816.1993.tb01102.xGoogle Scholar
Alder, G. S. (2001). Employee reactions to electronic performance monitoring: A consequence of organizational culture. The Journal of High Technology Management Research, 12 (2), 323342. doi:10.1016/S1047-8310(01)00042-6CrossRefGoogle Scholar
Alder, G. S., & Ambrose, M. L. (2005). An examination of the effect of computerized performance monitoring feedback on monitoring fairness, performance, and satisfaction. Organizational Behavior and Human Decision Processes, 97 (2), 161177. doi:10.1016/j.obhdp.2005.03.003Google Scholar
Alge, B. (2001). Effects of computer surveillance on perceptions of privacy and procedural justice. Journal of Applied Psychology, 86, 797804. doi:10.1037/0021-9010.86.4.797Google Scholar
American Psychological Association. (2010). Ethical principles of psychologists and code of conduct. Retrieved from http://www.apa.org/ethics/code/principles.pdfGoogle Scholar
Ante, S. E., & Weber, L. (2013, October 22). Memo to workers: The boss is watching. The Wall Street Journal. Retrieved from http://online.wsj.com/news/articles/SB10001424052702303672404579151440488919138Google Scholar
Bhave, D. P. (2014). The invisible eye? Electronic performance monitoring and employee job performance. Personnel Psychology, 67 (3), 605635. doi:10.1111/peps.12046Google Scholar
Bowman, R. (2014, February 11). Is new truck-monitoring technology for safety—or spying on drivers? Forbes. Retrieved from http://www.forbes.com/sites/robertbowman/2014/02/11/is-new-truck-monitoring-technology-for-safety-or-spying-on-driversGoogle Scholar
Executive Office of the President, President's Council of Advisors on Science and Technology. (2014). Report to the President: Big data and privacy. Retrieved from https://www.whitehouse.gov/sites/default/files/microsites/ostp/PCAST/pcast_big_data_and_privacy_-_may_2014.pdfGoogle Scholar
Foster, D. (2009). Secure, online, high-stakes testing: Science fiction or business reality? Industrial and Organizational Psychology, 2 (1), 3134. doi:10.1111/j.1754-9434. 2008.01103.xCrossRefGoogle Scholar
Guzzo, R. A., Fink, A. A., King, E., Tonidandel, S., & Landis, R. S. (2015). Big data recommendations for industrial–organizational psychology. Industrial and Organizational Psychology: Perspectives on Science and Practice, 8 (4), 491508.Google Scholar
Karim, M. N., & Behrend, T. S. (2015, April). Feedback and the self-regulatory process in monitored learning environments. In Young, C. K. & Beier, M. E. (Chairs), Integrating technology and training: New developments and frontiers. Symposium presented at the 30th Annual Conference of the Society for Industrial and Organizational Psychology, Philadelphia, PA.Google Scholar
Karim, M. N., Kaminsky, S. E., & Behrend, T. S. (2014). Cheating, reactions, and performance in remotely proctored testing: An exploratory experimental study. Journal of Business and Psychology, 29 (4), 555572. doi:10.1007/s10869-014-9343-zCrossRefGoogle Scholar
Lohr, S. (2013, April 20). Big data, trying to build better workers. The New York Times. Retrieved from http://www.nytimes.com/2013/04/21/technology/big-data-trying-to-build-better-workers.htmlGoogle Scholar
McGregor, J. (2014, December 18). Fitness trackers chase after the corporate market. The Washington Post. Retrieved from http://www.washingtonpost.com/blogs/on-leadership/wp/2014/12/18/fitness-trackers-chase-after-the-corporate-marketGoogle Scholar
McNall, L. A., & Roch, S. G. (2007). Effects of electronic monitoring types on perceptions of procedural justice, interpersonal justice, and privacy. Journal of Applied Social Psychology, 37 (3), 658682. doi:10.1111/j.1559-1816.2007.00179.xCrossRefGoogle Scholar
McNall, L. A., & Roch, S. G. (2009). A social exchange model of employee reactions to electronic performance monitoring. Human Performance, 22 (3), 204224. doi:10.1080/08959280902970385Google Scholar
McNall, L. A., & Stanton, J. M. (2011). Private eyes are watching you: Reactions to location sensing technologies. Journal of Business and Psychology, 26 (3), 299309. doi:10.1007/s10869-010-9189-yGoogle Scholar
Stanton, J. M. (2000). Reactions to employee performance monitoring: Framework, review, and research directions. Human Performance, 13 (1), 85113. doi:10.1207/S15327043HUP1301_4CrossRefGoogle Scholar
Stanton, J. M., & Barnes-Farrell, J. L. (1996). Effects of electronic performance monitoring on personal control, task satisfaction, and task performance. Journal of Applied Psychology, 81 (6), 738745. doi:10.1037/0021-9010.81.6.738Google Scholar
Stanton, J. M., & Julian, A. L. (2002). The impact of electronic monitoring on quality and quantity of performance. Computers in Human Behavior, 18 (1), 85101. doi:10.1016/S0747-5632(01)00029-2CrossRefGoogle Scholar
Stone, E. F., Gueutal, H. G., Gardner, D. G., & McClure, S. (1983). A field experiment comparing information-privacy values, beliefs, and attitudes across several types of organizations. Journal of Applied Psychology, 68 (3), 459468. doi:10.1037/0021-9010.68.3.459Google Scholar
Thompson, L. F., Sebastianelli, J. D., & Murray, N. P. (2009). Monitoring online training behaviors: Awareness of electronic monitoring hinders e-learners. Journal of Applied Social Psychology, 39 (9), 21912212. doi:10.1037/0021-9010.68.3.459Google Scholar
Watson, A. M., FosterThompson, L., Rudolph, J. V., Whelan, T. J., Behrend, T. S., & Gissel, A. L. (2013). When big brother is watching: Goal orientation shapes reactions to electronic monitoring during online training. Journal of Applied Psychology, 98 (4), 642657. doi:10.1037/a0032002Google Scholar
Wells, D. L., Moorman, R. H., & Werner, J. M. (2007). The impact of the perceived purpose of electronic performance monitoring on an array of attitudinal variables. Human Resource Development Quarterly, 18 (1), 121138. doi:10.1002/hrdq.1194Google Scholar
Willford, J. C., Howard, R. H., Cox, M. J., Badger, J. M., & Behrend, T. S. (2015, April). A latent class analysis of electronic performance monitoring practices. Paper presented at the 30th Annual Conference of the Society for Industrial and Organizational Psychology, Philadelphia, PA.Google Scholar