"Fair" Allocations of Pay and Workload: Tests of a Subtractive Model with Nonlinear Judgment Function

Abstract

An allocation is commonly regarded as "fair" if the ratio of outcome of two persons equals the ratio of their respective inputs. In allocation of pay, however, a subtractive model with sigmoidal-shaped judgment function has recently been reported. The present research further tested the plausibility of the subtractive model in allocations of pay and workload. Subjects decided either pay (N = 17) or workload (N = 17) for Person A using three pieces of information - the pay of B and the input of A and B or the workload of B and the pay of A and B. As hypothesized, factorial plots of the input (or pay) of Persons A and B across the low, moderate, and high levels of pay (or workload) of Person B yielded the diverging, slanted barrel, and converging patterns, respectively. Monotonic transformations of the data rescaled nonparallelism to perfect parallelism. The judgment function had a sigmoidal shape characterized by "floor" and "ceiling" effects. These results support the subtractive model but question the ratio model of "fair" allocations.