ONLINE TEAMWORK AND GROUP DECISION MAKING

[Original published in: Proceedings of Challenges in the European Area: Young Scientist’s 1st International Baku Forum, AZERBIEJAN]

The teamwork in groups consisting of group members from many different locations working at the same time with combined forced on a solution to a problem is a fascinating concept (Rheingold, 1993; Surowiecki, 2005) with promising perspectives and potentially high impact on our day-to-day lives. This concept comes not the least through co-operative and integrative political development in Europe (Cierco, 2013; Palan, 2013) and is supported by increasing possibilities through greater availability of technological infrastructures such as broadband Internet (Czernich, Falck, Kretschmer, & Woessmann, 2011; Kell 2012), an increasingly important topic for business, public organizations, and private individuals. In many fields, this concept is already an integral part of daily life. That the orchestration of such teamwork is a challenge in particular might be safe to say, in particular in the diverse European area. Whereas a wide range of literature is already available on group decision making in “virtual teams” in business-related areas (e.g., Bartelt, Dennis, Yuan, & Barlow, 2013; Sarker, Ahuja, Sarker, & Kirkeby, 2011; Ubell, 2010), not a lot of research is available on online teamwork and group decision making in the private context.

As a first step to inform this understanding, a pilot study on the case of group decision making related to online group stock price predictions was conducted (Endress, 2013). This report presents the results of a pilot experiment on groups’ online group stock price predictions, including the research process, a summary of the results and some preliminary, indicative results from the primary experiment. The overall objectives of the research study are three-fold: to assess the effect of individual and remote group decision-making approaches on stock price predictions; to assess whether a learning effect exists through the feedback loop of an e-Delphi (Dalkey & Helmer-Hirschberg, 1962) process; and to identify the key underlying mechanisms of the individual and the group that influence the decision-making process. A mixed-methods approach using quantitative and qualitative methods aims to gain a more holistic understanding. To some extent, this approach includes the assessment of economic, sociological and other aspects of these group processes. The pilot run was performed with a small group (11 participants) and three financial analysts to benchmark the group over five e-Delphi cycles (five weeks). Each participant in the pilot was asked to provide an estimation of the movement (up or down) over a one-week and three-month period of every share, and to enter a stock price prediction for a three-month period. The pilot run of the group decision-making experiment demonstrated that a mixed-method approach works in this context, but also showed some weaknesses and pitfalls of the planned research design. The pilot run provided some indications that, in certain situations and with careful group design, stock price predictions can be superior to experts’ predictions. Furthermore, a research framework was developed for this study that might provide a basis and starting point for further research in the field of online teamwork and group decision making.

References

Bartelt, V. L., Dennis, A. R., Yuan, L., & Barlow, J. B. (2013). Individual priming priming in virtual team decision-making. Group Decision and Negotiation. doi:10.1007/s10726-012-9333-3

Cierco, T. (2013). The European Union neighbourhood: Challenges and opportunities. Farnham, Surrey; Burlington, VT: Ashgate.

Czernich, N., Falck, O., Kretschmer, T., & Woessmann, L. (2011). Broadband infrastructure and economic growth*. The Economic Journal, 121(552), 505–532. doi:10.1111/j.1468-0297.2011.02420.x

Dalkey, N. C., & Helmer-Hirschberg, O. (1962). An experimental application of the Delphi method to the use of experts. Santa Monica: Rand Corp.

Endress, T. (2013). A pilot study of quality of equity predictions in online communities. International Journal of Innovations in Business, 3(2), 225–240.

Kell, L. (2012, October). World Broadband Statistics Q2 2012. Point Topic Ltd. Retrieved from http://point-topic.com/wp-content/uploads/2013/02/Sample-Report-Global-Broadband-Statistics-Q2-2012.pdf

Palan, R. P. (2013). Global political economy: Contemporary theories. London: Routledge.

Rheingold, H. (1993). The virtual community: Homesteading on the electronic frontier. Reading, Mass.: Addison-Wesley Pub. Co.

Sarker, S., Ahuja, M., Sarker, S., & Kirkeby, S. (2011). The role of communication and trust in global virtual teams: A social network perspective. Journal of Management Information Systems, 28(1), 273–310. doi:10.2753/MIS0742-1222280109

Surowiecki, J. (2005). The wisdom of crowds (1st Anchor Books ed.). New York: Anchor Books.

Ubell, R. (2010). Virtual teams mastering the art and practice of online learning and corporate collaboration.

ONLINE TEAMWORK AND GROUP DECISION MAKING

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