Compare methods

	360-Degree Feedback	Polynomial Regression with Response Surface Analysis
Field	Organizational Behavior	Organizational Behavior
Family	Process / pipeline	Regression model
Year of origin	1995	1993
Originator	Manuel London & James Smither; Richard Lepsinger & Anntoinette Lucia	Jeffrey R. Edwards & Mark E. Parry
Type	Multisource performance-feedback measurement and development process	Congruence-testing regression and surface-analysis method
Seminal source	Lepsinger, R., & Lucia, A. D. (1997). The Art and Science of 360 Degree Feedback. Pfeiffer. ISBN: 9780787909581	Edwards, J. R., & Parry, M. E. (1993). On the use of polynomial regression equations as an alternative to difference scores in organizational research. Academy of Management Journal, 36(6), 1577-1613.
Aliases	Multisource Feedback, MSF, Multi-Rater Feedback, 360 Feedback	Response Surface Methodology, RSA, Polynomial Regression for Congruence, Edwards Polynomial Regression
Related	3	3
Summary	360-degree feedback, also called multisource feedback, gathers ratings of a focal person's work behavior from the full circle of people around them, self, supervisor, peers, and direct reports, and sometimes customers, rather than from a single boss. The aim is to give a more complete, less biased picture of performance and, especially, to prompt self-awareness and development by revealing how different observers see the same person. Manuel London and James Smither's 1995 article gave the practice a theoretical foundation, explaining when and why multisource feedback might change self-evaluations, goals, and behavior. Richard Lepsinger and Anntoinette Lucia's 1997 practitioner book laid out how to design and implement sound 360 systems. Conway and Huffcutt's 1997 meta-analysis documented the psychometric reality that different sources agree only modestly, which is precisely what makes multiple perspectives informative. 360-degree feedback became one of the most widely adopted leadership-development tools in organizations.	Polynomial regression with response surface analysis is the methodological gold standard for testing congruence, fit, and agreement hypotheses in organizational behavior, introduced by Jeffrey Edwards and Mark Parry in 1993. It replaces the once-common practice of subtracting two scores and regressing the outcome on that difference, a practice that conflates several distinct effects and discards information. Instead, the two component variables are entered together with their squares and cross-product, and the resulting equation is interpreted as a three-dimensional surface relating the two predictors to the outcome. Edwards and Parry showed that difference scores impose untestable and usually false constraints, and that the polynomial approach recovers the constrained model as a special case while exposing far richer patterns. Shanock and colleagues' 2010 tutorial made the method accessible by providing surface coefficients, tests, and plotting tools. The technique is now standard wherever person-environment fit and rater agreement are studied.