The role of the decision-making regime on cooperation in a workgroup social dilemma: An examination of cyberloafing

Corgnet, Brice; Hernán-González, Roberto; McCarter, Matthew W. Article The role of the decision-making regime on cooperation in a workgroup social dilemma: An examination of cyberloafing Games Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Corgnet, Brice; Hernán-González, Roberto; McCarter, Matthew W. (2015) : The role of the decision-making regime on cooperation in a workgroup social dilemma: An examination of cyberloafing, Games, ISSN 2073-4336, MDPI, Basel, Vol. 6, Iss. 4, pp. 588-603, https://doi.org/10.3390/g6040588 This Version is available at: https://hdl.handle.net/10419/167961 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Games 2015, 6, 588-603; doi:10.3390/g6040588 games ISSN 2073-4336 www.mdpi.com/journal/games Article The Role of the Decision-Making Regime on Cooperation in a Workgroup Social Dilemma: An Examination of Cyberloafing Brice Corgnet 1,4, Roberto Hernán-González 2 and Matthew W. McCarter 3,4,* 1 Argyros School of Business and Economics, Chapman University, 1 University Drive, Orange, CA 92866, USA; E-Mail: [email protected] 2 Business School, Nottingham University, Jubilee Campus, Nottingham, NG8 1BB, UK; E-Mail: [email protected] 3 College of Business, University of Texas at San Antonio, 1 UTSA Circle, San Antonio, TX 78249, USA 4 Economic Science Institute, Chapman University, 1 University Drive, Orange, CA 92866, USA * Author to whom correspondence should be addressed; E-Mail: matthew[email protected]; Tel.: +1-210-458-8297; Fax: +1-210-458-4308. Academic Editor: Ananish Chaudhuri Received: 28 July 2015 / Accepted: 29 October 2015 / Published: 5 November 2015 Abstract: A burgeoning problem facing organizations is the loss of workgroup productivity due to cyberloafing. The current paper examines how changes in the decision-making rights about what workgroup members can do on the job affect cyberloafing and subsequent work productivity. We compare two different types of decision-making regimes: autocratic decision-making and group voting. Using a laboratory experiment to simulate a data-entry organization, we find that, while autocratic decision-making and group voting regimes both curtail cyberloafing (by over 50%), it is only in group voting that there is a substantive improvement (of 38%) in a cyberloafer’s subsequent work performance. Unlike autocratic decision-making, group voting leads to workgroups outperforming the control condition where cyberloafing could not be stopped. Additionally, only in the group voting regime did production levels of cyberloafers and non-loafers converge over time. Keywords: autocratic decision-making; cyberloafing; group voting; social dilemma; workgroup performance OPEN ACCESS Games 2015, 6 589 1. Introduction Many of the challenges organizations face when attempting to achieve their goals are social dilemmas: interdependent decisions where an individual attempting to satisfy his or her own interests in the short run conflicts with the collective’s interests in the long run [1]. With the advent of the Internet, a social dilemma that has received increased attention in management studies is cyberloafing, where an employee “uses their company’s Internet access for personal purposes (i.e., web surfing and personal email use) during work hours” [2] (p. 675). In social dilemma terminology, cyberloafing is categorized as a social trap: a situation where an individual indulges in a short-term private benefit (e.g., using the Internet for personal use during work hours) while passing a long-term cost on to the collective; e.g., lost labor and reduced productivity to the workgroup or organization [3]. Surely, employees may use the Internet to cope with stress or to stimulate their creativity [4,5]. While recognizing the inevitable “grey area” between Internet use and abuse (cyberloafing) and acknowledging these caveats [6], we focus on clear cases of cyberloafing, which disrupt work [7] and are thus counterproductive [5]. The costs of cyberloafing to organizations can be substantial. Knights [8], for instance, reports $470 million in lost productivity to U.K. firms from workers taking 15 to 30 min of company time to place a bet using online gambling websites. Another study reports that workers using Facebook and Twitter are interrupted once every 10.5 min by instant messages and tweets, taking about 23 min after using a social media website to refocus their attention entirely back to their work and costing their companies about $4500 per worker every year [9]. These monetary figures leave managers with the task of increasing cooperation from cyberloafers. Van Lange, Balliet, Parks and Van Vugt’s [10] recent review on social dilemmas suggests two decision-making regimes that managers can use to encourage cooperation: autocratic decision-making and group voting. Drawing from normative decision theory [11], we seek to answer the research question: What effects do group decision-making and autocratic decision-making structures have on cyberloafing and subsequent worker performance in workgroups? We address this question in a laboratory environment where workgroups of nine performed a data calculation and entry task while supervised by a monitor. In addition to a control condition, we considered autocratic and group voting regimes. In the autocratic decision-making condition, a monitor would unilaterally decide whether to turn off workers’ access to the Internet in the middle of the experiment. In the group voting condition, a majority vote from workers was used to decide whether workers’ access to the Internet should be turned off. We find that autocratic and group voting structures reduce cyberloafing by over 50%, but only group voting boosts the cyberloafer’s subsequent work productivity by a substantive (and statistically different) amount: 38%. Unlike the autocratic regime, group voting leads to workgroups outperforming the control condition where cyberloafing could not be stopped. The remainder of the paper is outlined as follows. First, we review the literature pertinent to social dilemmas, decision regimes and cyberloafing and state our hypotheses. Second, we summarize our research methodology. Third, we report the results of our hypothesis testing both in terms of statistical and practical significance. Lastly, we conclude with discussing the theoretical and practical implications of our results for social dilemma theory and organizations. Games 2015, 6 590 2. Theoretical Background and Hypotheses Vroom and Yetton’s [11] seminal taxonomy of organizational decision-making regimes outlines two extreme paths that an organization may take when solving a problem. At one extreme is the autocratic decision-making regime where decisions are made by a manager or boss about what those facing the decision situation can do [12]. The motivation behind an autocratic decision-making regime is efficiency. A manager, being aware of a cyberloafing problem, can take steps to avoid collective ruin brought upon by persistent exploiters [13–15]. The effectiveness of Internet abuse detection and disciplining actions within an autocratic decision-making regime rests on general deterrence theory [16–18]. In particular, an autocratic structure allows for a manager to impose an organizational policy that limits Internet access to stop current and future cyberloafers from exploiting other group members [19]. However, the centralized decision rights of an autocratic manager may come at a cost. Most workers value autonomy in their jobs [20] and may feel spite toward those who dictate terms about what they can do [21]. In fact, workers who slack on the job may slack even more out of spite when unilateral actions are taken to force their cooperation [22]. In relation to cyberloafing, losing access to the Internet by an autocratic authority may lead the cyberloafer to not only find something else to pass the time (other than work), but exert even less effort out of spite on the job. Hypothesis 1: After the implementation of the Internet policy, the autocratic decision-making regime will fail to increase individual production by cyberloafers compared to the control condition where cyberloafing cannot be curbed. As a result, workgroup production under an autocratic decision-making structure will fail to surpass that of the control condition. At the other end of Vroom and Yetton’s [11] taxonomy is a group decision-making regime. As a form of employee empowerment [23], a group decision-making regime places decision-making rights in the hands of group members and their manager [24]. As reviewed by Van de Ven and Delbecq [25], group decision-making regimes can vary in the extent to which group members interact. At one extreme, group members may have unstructured discussions about a problem the group faces and develop solutions through conversation. At the other extreme, group members do not converse, but merely vote independently about proposed solutions to a problem. The current research focuses on this second minimal group decision process, which we refer to as a group voting regime. Group voting resembles the democratic leadership style studied by Lewin, Lippitt and White [26]. In relation to cyberloafing, a group voting regime lets workgroups decide through a vote to turn Internet access on or off. Previous work on employee empowerment suggests that a group voting regime increases workgroup performance [27,28]. The reason for this positive relationship may be that shared decision rights among workgroup members give these workers a sense of ownership over their work and trust that each worker will do his or her share of the labor [29]. Furthermore, a group voting regime may positively affect group members who disagree with the majority about what group members can do on the job. Procedural justice research reminds us that workers often value the procedures for reaching an outcome more than the outcome’s value [30]. To capitalize on this asymmetry, the administration may give employees voice over the design of their work; e.g., voting about Internet access [31]. Worker productivity increases after merely giving employees voice about rules on their jobs [27], because choice over elements of work Games 2015, 6 591 increases worker-perceived procedural justice and subsequent work effort [32]. Van den Bos, Vermunt and Wilke’s [33] research on procedural justice suggests that a group member’s commitment and motivation to work will be higher when given voice compared to when not given voice, even when the outcome of a group voting conflicts with that member’s preferences or previous behavior. Hypothesis 2: After the implementation of the Internet policy, the group voting condition will lead to higher levels of individual production among cyberloafers compared to the control and autocratic decision-making conditions. As a result, workgroup production under the group voting condition will be higher than in the control and autocratic conditions. 3. Method 3.1. Sample Participants were 220 students recruited from a subject pool of about 2000 undergraduate and graduate students at a university in the Western United States. Participants received a $7 show-up fee plus the opportunity to earn more money for participation in a 2.5-h experiment. We conducted 6 sessions in the control and group voting conditions and 10 sessions in the autocratic condition. Participants earned $32.50 on average, which includes the show-up fee. Our participants thus earned on average $13 per hour, which compares to average earnings of data-entry clerks in the United States, which were $13.37 per hour ± $2.75 [34] at the time of the study. 3.2. Design and Procedure We employed a one-way factorial design with three conditions: a control condition, an autocratic decision-making condition and a group voting condition. Each participant was randomly assigned to one of the three conditions summarized in Table 1. In the control condition, participants could use the Internet at any time during the experiment. In the other two conditions, Internet access could be turned off after the second period. In the autocratic decision-making condition, one of the participants, the monitor, decided unilaterally whether to turn off or maintain Internet access. In the group voting condition, Internet access was turned off if the majority of workers (five out of nine) voted to do so. 3.2.1. Instruction Period Upon arrival at the laboratory, participants were directed to private cubicles and asked to read a set of computerized instructions. Since the instructions were somewhat involved [35], participants had 20 min to read them, with a timer displayed on a large screen at the front of the laboratory. The instructions indicated that they were one of ten members of a workgroup; the workgroup would undertake a 1 h and 40-min task, broken up into five 20-min periods. Each member would work on the task, separately and in isolation, but their earnings would be calculated based on group performance. Games 2015, 6 592 Table 1. Summary of conditions. Condition Description No. of Sessions (Participants) Control Internet access was maintained by the experimenter after Period 2. 6 (60) Autocratic decision-making condition The monitor unilaterally decided whether to turn off or maintain Internet access after Period 2. 10 (100) Group voting condition Workers voted on whether to turn off or maintain Internet access after Period 2. The decision selected by the majority of workers was implemented. 6 (60) Three minutes before the end of the instruction period, the experimenter announced the time remaining and handed out a printed summary of the instructions. None of the participants asked questions or requested extra time. At the end of the instruction period, the experiment was launched from the experimenter’s room. All conditions involved the same number of participants (nine workers and one monitor), so as to be able to compare production patterns across conditions. The person who was assigned the role of monitor kept this role for the entire experiment. We conducted six sessions of 10 participants for all conditions, but the autocratic decision-making condition, for which we conducted a total of 10 sessions. More sessions were conducted for the autocratic decision-making condition so as to collect more observations on voting decisions, since, in this case, only the monitor voted on future Internet access, leaving us with only one vote per session. 3.2.2. Software The experiment was conducted using the Virtual Organizations software developed by CYDeveloper LLC. The software facilitates a multi-party team task, controlled centrally by an experimenter. 3.2.3. The Work Task Adapted from previous research using summation tasks [36], the work task was a particularly long and laborious task intended to resemble the monotony that can accompany organizational life and prompt Internet usage. The task required summing up tables of 36 numbers without using a pen, scratch paper or calculator (see Figure 1). Participants could sum as many tables as they wanted so that the work task was never interrupted during a period. After completion of a table, and whether the summation was correct or not, a new table appeared on the screen. Each table had six rows and six columns of randomly-generated numbers between zero and ten. Before providing the grand total, participants had to provide a separate subtotal for all of the 12 rows and columns. Calculating these subtotals did not directly generate earnings, but could help participants compute the grand total, which generated a 40¢ profit to the group only if the grand total was correct. If the grand total was incorrect, a 20¢ penalty was deducted from group production. So that participants could not sabotage other group members’ production, penalties only applied when the worker who completed the table incorrectly had produced a positive amount sufficient to bear the penalty. After completing a table, participants learned whether their answers were correct and how much money they earned. At the end of each period, participants learned the total amount of money generated by all Games 2015, 6 593 participants’ efforts on the work task. Individual earnings were calculated such that each participant obtained an equal share of 10% of workgroup production similar to a gainsharing plan. The gainsharing design feature induces interdependence among participants, as their performance on the task not only affects their individual earnings, but also the other participants’ earnings. The current setting is a social dilemma, as each member of the group can increase overall performance at their own cost of effort. Figure 1. Sample work task. In addition to the work task earnings, participants received a fixed wage of $2.40 per period, which was obtained by clicking on a yellow box at the bottom of the participants’ screens. The fixed wage was implemented to mimic real work environments in which pay for performance is only limited to a portion of the wage. In our experiments, about half of total pay was earned on the work task, while the remainder corresponded to fixed pay. 3.2.4. Internet At any point during the experiment, all participants were told they could switch from the work task to Internet browsing. Within the bounds of university policy, participants could use the Internet however they liked, including email. Their confidentiality was assured and maintained, but the software tracked the exact amount of time spent on each activity. Although participants could not complete the work task while browsing the Internet, switching was quick and easy. Through the action menu, participants returned to either the last Internet page or the last number table that they had seen. If participants chose the Internet, the work task window was replaced by an Internet window (embedded in the software; see Figure 2). Students were not allowed to bring cell phones into the lab, so that Internet browsing, if any, was embedded into the experimental platform. At the end of the second period, depending on the condition, Internet access was either maintained or removed. In the control condition, Internet access was maintained after the second period. In the group voting and autocratic decision-making conditions, organizational members decided on whether Internet access should be turned off after Period 2. Therefore, even if the Internet were turned off, participants could still loaf on the job by sitting idle. Games 2015, 6 594 Figure 2. Embedded Internet screen. 3.2.5. Monitoring In all conditions, one of the 10 participants referred to as “C” (the rest of the workers were referred to as “Bs”) was given the ability to watch everyone else, and everyone else was aware of this ability. If the monitor selected the monitoring option from the action menu, he or she used a separate screen to choose whom to monitor (anywhere from one to all other participants) and to actually perform the monitoring. For each selected participant, a column in a table listed their activities (e.g., switched to Internet, provided a subtotal), their current earnings and their percentage contribution to the workgroup total (see Figure 3). For example, the first row in Figure 3 informs the monitor that Participant B13 just switched to the Internet screen and that B13 had produced 40¢ on the task thus far (that is, after 13 min and 18 s of the 20-min period). The production of Participant B13 corresponded to 33% of workgroup production (120¢) thus far. Participants who were being monitored saw the figure of an eye and a text message indicating that “C is watching you”, independently of the activity they were undertaking. The figure and message resemble the common practice of notifying employees when they visit restricted websites. Notification systems are becoming popular, as illustrated by the team application developed by the largest online marketplace: oDesk. oDesk allows employers to overtly monitor freelancers via webcams (the analogue of our eye image), which take frequent pictures that are immediately sent back to the employer. Participants could spend as much or as little time as they wanted on the various activities (work task, Internet and monitoring), each of which was undertaken on a separate screen. To switch activities, participants simply chose the corresponding option from a drop-down menu at the bottom-right of their screens. 3.2.6. Voting In the autocratic decision-making condition, the monitor unilaterally decided whether to turn off or maintain Internet access after Period 2. In the group voting condition, all workers (excluding the Games 2015, 6 595 monitor) voted on whether to turn off or maintain Internet access after Period 2. The details of the voting process were described to participants during the instruction period. Figure 3. Monitoring screen with a zoom on Participant B13. 3.3. Measures Individual production is defined as the total monetary amount (in U.S. Dollars) generated by a participant’s answers on the work task. Workgroup production is defined as the sum of the individual production of the nine workers in the organization. Internet usage is defined as the percentage of a participant’s total time that was spent on the Internet screen. Internet usage was considered cyberloafing in this case, because time spent on the Internet was time away from the work task, costing money for participants and their colleagues. We confirm this interpretation of Internet usage in our organizational setting in which it is shown, for example, that a worker’s accuracy on the summation task typically decreased after spending time browsing the Internet [37]. This would not be the case if workers used the Internet to take a break and restore concentration with the objective of increasing productivity thereafter. 4. Results 4.1. Periods 1–2: Internet Access on We start by analyzing the first two periods of the experiment during which Internet access was available in all conditions. Average Internet usage across conditions was equal to 13.9% (SD = 0.20) of workers’ available time (see Table 2). This is similar to the on-the-job Internet usage, for non-work purposes, of about 13% reported in the 2005 report by American Online and Salary.com [38]. Our cyberloafing rate is also a little less than half the rate [39] of the study of Wagner and colleagues’ [40] that measures cyberloafing behaviorally in a classroom setting. Games 2015, 6 602 10. Van Lange, P.A.M.; Balliet, D.; Parks, C.D.; van Vugt, M. Social Dilemmas: The Psychology of Cooperation; Oxford University Press: Oxford, UK, 2014. 11. Vroom, V.H.; Yetton, P.W. Leadership and Decision-making; University of Pittsburgh Press: Pittsburgh, PA, USA, 1973. 12. Van Vugt, M.; Jepson, S.F.; Hart, C.M.; de Cremer, D. Autocratic leadership in social dilemmas: A threat to group stability. J. Exp. Soc. Psychol. 2004, 40, 1–13. 13. Chen, X.-P.; Bachrach, D.G. Tolerance of free-riding: The effects of defection size, defection pattern, and social orientation in a repeated public goods dilemma. Organ. Behav. Hum. Decis. Processes 2003, 90, 139–147. 14. Hardin, G. The tragedy of the commons. Science 1968, 162, 1243–1248. 15. Hardin, G. Living on a lifeboat. BioScience 1974, 24, 561–568. 16. Straub, D.W. Effective IS security: An empirical study. Inf. Syst. Res. 1990, 1, 255–276. 17. Straub, D.W.; Nance, W.D. Discovering and disciplining computer abuse in organizations: A field study. MIS Q. 1990, 14, 45–60. 18. Straub, D.W.; Welke, R.J. Coping with systems risk: Security planning models for management decision making. MIS Q. 1998, 22, 441–469. 19. Ugrin, J.C.; Pearson, J.M. The effects of sanctions and stigmas on cyberloafing. Comput. Hum. Behav. 2013, 29, 812–820. 20. Laschinger, H.K.S.; Finegan, J.; Shamian, J. The impact of workplace empowerment, organizational trust on staff nurses’ work satisfaction and organizational commitment. Health Care Manag. Rev. 2001, 26, 7–23. 21. Lawrence, T.B.; Robinson, S.L. Ain’t misbehavin: Workplace deviance as organizational resistance. J. Manag. 2007, 33, 378–394. 22. Tripp, T.M.; Bies, R.J. Getting Even: The Truth about Workplace Revenge—And How to Stop It; Wiley: New York, NY, USA, 2009. 23. Martin, S.; Liao, H.; Campbell, E.M. Directive versus empowering leadership: A field experiment comparing the impact on task proficiency and proactivity. Acad. Manag. J. 2012, 56, 1372–1395. 24. Somech, A. The effects of leadership style and team process on performance and innovation in functionally heterogeneous teams. J. Manag. 2006, 32, 132–157. 25. Van de Ven, A.H.; Delbecq, A.L. The effectiveness of nominal, Delphi, and interacting group decision making processes. Acad. Manag. J. 1974, 17, 605–621. 26. Lewin, K.; Lippitt, R.; White, R.K. Patterns of aggressive behavior in experimentally created “social climates.” J. Soc. Psychol. 1939, 10, 271–299. 27. Lawler, E.E.; Hackman, J.R. Impact of employee participation in the development of pay incentive plans: A field experiment. J. Appl. Psychol. 1969, 53, 467–471. 28. Srivastava, A.; Bartol, K.M.; Locke, E.A. Empowering leadership in management teams: Effects on knowledge sharing, efficacy, and performance. Acad. Manag. J. 2006, 49, 1239–1251. 29. Huang, X.; Iun, J.; Liu, A.; Gong, Y. Does participative leadership enhance work performance by inducing empowerment or trust? The differential effects on managerial and non-managerial subordinates. J. Organ. Behav. 2010, 31, 122–143. 30. Folger, R.; Konovsky, M.A. Effects of procedural and distributive justice on reactions to pay raise decisions. Acad. Manag. J. 1989, 32, 115–130. Games 2015, 6 603 31. Lind, E.A.; Tyler, T.R. The Social Psychology of Procedural Justice; Plenum: New York, NY, USA, 1988. 32. Caza, A.; McCarter, M.W.; Northcraft, G.B. Performance benefits of reward choice: A procedural justice perspective. Hum. Resour. Manag. J. 2015, 25, 184–199. 33. Van den Bos, K.; Vermunt, R.; Wilke, H.A.M. Procedural and distributive justice: What is fair depends more on what comes first than on what comes next. J. Personal. Soc. Psychol. 1997, 72, 95–104. 34. Salary Wizard. Available online: http://swz.salary.com/SalaryWizard/Data-Entry-Clerk-I-JobDescription.aspx. (accessed on 2 November 2015). 35. Decision-making and Cooperation in a Workgroup Social Dilemmas. Available online: http://www. sites.google.com/site/voInternetpolicy. 2015. (accessed on 2 November 2015). 36. Eriksson, T.; Poulsen, A.; Villeval, M.C. Feedback and incentives: Experimental evidence. Labour Econ. 2009, 16, 679–688. 37. Corgnet, B.; Hernán-González, R.; Schniter, E. Why real leisure really matters: Incentive effects on real effort in the laboratory. Exp. Econ. 2014, 18, 1–18. 38. Malachowski, D.; Simonini, J. Wasted time at work costing companies billions. San Francisco Chronicle, 11 July 2005. Available online: http://www.salary.com/wasted-time-at-work-stillcosting-companies-billions-in-2006/ (accessed on 2 November 2015). 39. World’s Shortest Work Weeks 2013. Available online: http://www.money.cnn.com (accessed on 2 November 2015). 40. Wagner, D.T.; Barnes, C.M.; Lim, V.K.G.; Ferris, D.L. Lost sleep and cyberloafing: Evidence from the laboratory and a daylight saving time quasi-experiment. J. Appl. Psychol. 2012, 97, 1068–1076. 41. Charness, N.; Campbell, J.I. Acquiring skill at mental calculation in adulthood: A task decomposition. J. Exp. Psychol. Gen. 1988, 117, 115–129. 42. Van Dijk, F.; Sonnemans, J.; van Winden, F. Incentive systems in a real effort experiment. Eur. Econ. Rev. 2001, 45, 187–214. 43. Barker, J.R. Tightening the iron cage: Concertive control in self-managing teams. Adm. Sci. Q. 1993, 38, 408–437. 44. Schachter, H. Eight questions that cause leaders to lose sleep. The Globe and Mail, 5 January 2014. Available online: http://www.theglobeandmail.com/report-on-business/careers/management/eightquestions-that-cause-leaders-to-lose-sleep/article16186886/ (accessed on 2 November 2015). 45. Muller, J. Cyberloafing becoming all too common at office. Deseret News, 22 November 1998. Available online: http://www.deseretnews.com/article/664207/Cyberloafing-becoming-all-toocommon-at-office.html?pg=all (accessed on 2 November 2015). © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).