Looking for Assistance in the Dark: Pay Secrecy, Expertise Perceptions, and Efficacious Help Seeking Among Members of Newly Formed Virtual Work Groups
Adopting an information processing perspective, we argue that in pay-for-performance contexts, pay secrecy may adversely affect the ability of members of newly formed, virtual work groups to source assistance from those most able to provide it, referred to here as efficacious help-seeking.
We conducted a repeated-measures laboratory study in which one hundred forty-six participants interacted with three confederates, each with a varying level of skill. Participants’ help-seeking behaviors were recorded and efficacious help-seeking was examined as a function of the four pay transparency conditions.
Our findings reveal that accurate perception of task expertise of the highest paid work group member mediates the impact of pay transparency on members’ efficacious help-seeking. The findings also show that the positive relationship between pay transparency and efficacious help-seeking is amplified for average and high performers and that for these same individuals a shift from secrecy to transparency is accompanied by a significant increase in efficacious help-seeking.
This study extends pay secrecy research by shifting the focus away from fairness, instrumentality, and sorting and toward information processing. More specifically, the study highlights how pay and pay comparisons can influence inter-relating behaviors in organizations in general and expertise identification and help seeking behaviors in particular.
We believe this is the first study to directly examine how the availability of pay comparison information determines inter-relating behaviors in organizations. The study offers insight for pay policy in organizations that rely upon employee help-seeking, showing that efficacious help-seeking can be enhanced through transparent pay practices. This is particularly evident in the virtual teams examined in the present study.
KeywordsPay secrecy Help-seeking Virtual team
- Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.Google Scholar
- Bamberger, P. (2009). Employee help-seeking: Antecedents, consequences and new insights for future research. Research in Personnel and Human Resources Management, 28, 49–98.Google Scholar
- Blau, P. M. (1964). Exchange and power in social life. Transaction Publishers.Google Scholar
- Bunderson, J. S., & Barton, M. A. (2011). Status cues and expertise assessment in groups: How group members size one another up … and why it matters. In J. L. Pearce (Ed.), Status in management and organizations (pp. 215–237). New York: Cambridge University Press.Google Scholar
- Cohen, K. (2006) The pulse of the profession: 2006–07, Salary Budget Survey. Workspan (September), 23–26.Google Scholar
- Colquitt, J. A. (2008). From the editors publishing laboratory research in AMJ: A question of when, not if. Academy of Management Journal, 51, 616–620.Google Scholar
- Cornally, N., & McCarthy, G. (2011). Help-seeking behaviour for the treatment of chronic pain. British Journal of Community Nursing, 16, 90. Retrieved from http://www.bjcn.co.uk/.
- Cross, R., & Borgatti, S. P. (2004). The ties that share: Relational characteristics that facilitate information seeking. Social Capital and Information Technology, 137–161. Retrieved from http://web.worldbank.org.
- Furnham, A., & Argyle, M. (1998). The psychology of money. London: Routledge.Google Scholar
- Griffith, T. L., & Neale, M. A. (2001). Information processing in traditional, hybrid, and virtual teams: From nascent knowledge to transactive memory. In B. M. Staw & R. L. Sutton (Eds.), Research in organizational behavior (Vol. 23, pp. 379–421). Greenwich, CT: JAI.Google Scholar
- Hackman, J. R. (2002). Leading teams: Setting the stage for great performances. Boston, MA: Harvard Business Press.Google Scholar
- Hollenbeck, J. R., Beersma, B., & Schouten, M. E. (2012). Beyond team types and taxonomies: A dimensional scaling conceptualization for team description. Academy of Management Review, 37, 82–106.Google Scholar
- Institute for Women’s Policy Research (IWPR)/Rockefeller Survey of Economic Security. (2011). Pay secrecy and wage discrimination. Fact Sheet #C382.Washington, DC: Institute for Women’s Policy Research.Google Scholar
- Jokisaari, M., & Nurmi, J. E. (2012). Getting the right connections? The consequences and antecedents of social networks in newcomer socialization. In C. Wanberg (Ed.), The oxford handbook of organizational socialization (pp. 78–96). New York: Oxford University Press.Google Scholar
- Kahneman, D. (2011). Thinking fast and slow. New York, NY: Farrar Strauss & Giroux.Google Scholar
- Kahneman, D., & Frederick, S. (2004). Attribute substitution in intuitive judgment. In M. Augier & J. G. March (Eds.), Models of a man: Essays in memory of Herbert A. Simon (pp. 411–432). Cambridge, MA: MIT Press.Google Scholar
- Kahneman, D., & Frederick, S. (2005). A model of heuristic judgment. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 267–294). New York: Cambridge University Press.Google Scholar
- Kline, P. (1998). The new psychometrics: Science, psychology and measurement. Florence, KY: Taylor & Frances/Routledge.Google Scholar
- Kozlowski, S. W. J., & Bell, B. S. (2003). Work groups and teams in organizations. In W. C. Borman, D. R. Ilgen, & R. J. Klimoski (Eds.), Handbook of psychology: Industrial and organizational psychology (Vol. 12, pp. 333–375). New York: Wiley.Google Scholar
- Lind, E. A. (2001). Fairness heuristic theory: Justice judgments as pivotal cognitions in organizational relations. In J. Greenberg & R. Cropanzano (Eds.), Advances in organizational justice (pp. 56–88). Stanford, CA: Stanford University Press.Google Scholar
- Locke, E. A. (Ed.). (1986). Generalizing from laboratory to field settings. Lexington, MA: Lexington Books.Google Scholar
- Moreland, R. L., Argote, L., & Krishnan, R. (1996). Socially shared cognition at work: Transactive memory and group performance. Thousand Oaks, CA: Sage.Google Scholar
- Muthén, L. K., & Muthén, B. O. (1998–2012). Statistical analysis with latent variables. In Mplus user’s guide (4th–7th ed.). Los Angeles, CA: Muthen & Muthen. Retrieved from http://www.statmodel.com.
- Satorra, A., & Bentler, P. M. (1988). Scaling corrections for Chi square statistics in covariance structure analysis. In Proceedings of the business and economic statistics section of the American Statistical Association (pp. 308–313). Alexandria, VA.Google Scholar
- Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variable analysis: Applications to developmental research (pp. 399–419). Thousand Oaks, CA: Sage.Google Scholar
- Van den Bos, K., & Lind, E. A. (2002). Uncertainty management by means of fairness judgments. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 34, pp. 1–60). San Diego, CA: Academic Press.Google Scholar
- Wills, T. A., & DePaulo, B. M. (1991). Interpersonal analysis of the help-seeking process. In C. R. Snyder & D. R. Forsyth (Eds.), Handbook of social and clinical psychology (pp. 350–375). Elmsford, NY: Pergamon.Google Scholar
- Yoon, K., & Hollingshead, A. B. (2010). Cultural stereotyping, convergent expectations, and performance in cross-cultural collaborations. Social Psychology and Personality Science, 1, 160–167.Google Scholar