Skip to content
Surf Wiki
Save to docs
general/motivation

From Surf Wiki (app.surf) — the open knowledge base

Double demotivation


Double demotivation is a theory involving pay and motivation first postulated by S.C. Carr and MacLachlan. Double demotivation hypothesises that pay discrepancies decrease work motivation among both lower and higher paid individuals who essentially perform the same task. Compared with equitably paid workers, employees who felt they were being under- or overpaid reported lower job satisfaction and greater readiness to change jobs.

References

  • Carr S.C., McLoughlin D, .Hodgson M., MacLachlan M (1996) Effects of unreasonable pay discrepancies for under- and overpayment on double demotivation. Genetic and Social General Psychology Monographs. Nov;122(4):475-94.
  • McLoughlin, D. and S.C. Carr (1997), Equity Sensitivity and Double De-motivation, Journal of Social Psychology, 137, 668–70.
  • MacLachlan, M. and Carr, S.C. (2005) The Human Dynamics of Aid. Policy Insights, OECD Development Centre, 10, June. Online at: www.oecd.org/dataoecd/35/56/35041556.pdf, accessed on 10 August 2006.
  • Carr, S. C., Hodgson, M. R., and Vent, D. H. (2004) Pay Diversity Across Work Groups: A Doubly De-Motivating Influence? Journal of Management Psychology, Vol. 20, No. 5. (May 2005), 417–439.
  • http://www.scu.edu/ethics/publications/iie/v3n2/justworld.html
Info: Wikipedia Source

This article was imported from Wikipedia and is available under the Creative Commons Attribution-ShareAlike 4.0 License. Content has been adapted to SurfDoc format. Original contributors can be found on the article history page.

Want to explore this topic further?

Ask Mako anything about Double demotivation — get instant answers, deeper analysis, and related topics.

Research with Mako

Free with your Surf account

Content sourced from Wikipedia, available under CC BY-SA 4.0.

This content may have been generated or modified by AI. CloudSurf Software LLC is not responsible for the accuracy, completeness, or reliability of AI-generated content. Always verify important information from primary sources.

Report