In this thesis, we conduct an experimental simulation of 131 students from a university in Hong Kong and investigate the relationship between pay changes and the perceived values (i.e., utility). Applying traditional psychophysical methods, we measure the utility of pay changes (i.e., pay raises and pay cuts) of different sizes by individual responses (i.e., happiness/unhappiness). Drawing on utility theory and expectancy theory, we examine the function that best fits this relationship by considering common function forms including linear, quadratic, logarithmic, and power functions. Using regression techniques, we find that a quadratic function best fits the data, and the utility function is concave in the pay change. When we examine the best form of utility functions for pay raises and pay cuts separately, we find that the utility of pay raises and that of pay cuts are best described by a quadratic function and a linear function, respectively. We further show that a single model involving all pay changes better describes the utility than two separate models for pay raises and pay cuts. In addition, our best-fit utility model reveals that a sufficiently small amount of pay increase may generate a negative value of utility, and we calculate the percentage of smallest meaningful pay increase that results in non-negative utility. We also discuss the theoretical contributions of our findings to the literature and their implications to practitioners.
|Date of Award||2017|
- Department of Computing and Decision Sciences
|Supervisor||Li Ping LIANG (Supervisor) & Yifeng Nancy CHEN (Supervisor)|