Integrating theories of motivation

Progress toward understanding human behavior has been hindered by discipline-bound theories, dividing our efforts. Fortunately, these separate endeavors are con-verging and can be effectively integrated. Focusing on the fundamental features of picoeconomics, expectancy theory, cumulative prospect theory, and need theory, we construct a temporal motivational theory (TMT). TMT appears consistent with the major findings from many other investigations, including psychobiology and behav-iorism. The potential implications of TMT are numerous, affecting our understanding on a wide range of topics, including group behavior, job design, stock market behav-ior, and goal setting. The fields of economics, decision making, so-ciology, and psychology share a common desire to understand our human nature—that is, our essential character, disposition, or tempera-ment. This extensive, multidisciplinary interest in establishing who we are reflects the enor-mous ramifications of the endeavor. As Pinker (2002) catalogs, theories of human nature have been used to direct relationships, lifestyles, and governments—with disastrous effects when based on faulty models. On a smaller applied scale, treatments, training, compensation, and selection all depend on our theories of human behavior. Even job design, which is an overtly physical enterprise, requires positing human el-ements such as “growth need strength ” (Hack-man & Oldham, 1976). To ensure the efficacy of our interventions, we need to determine what describes, drives, or decides our actions. Ironically, our understanding of behavior has been hindered by the very extent of our efforts. There is a superabundance of motivational the-ories. Not only does each field have its particu-lar interpretation, but there are ample subdivi-sions within each discipline. Psychology, for example, has the traditions of self-regulation, motivation, and personality, each with its own nomenclature, structure, and etiology. These subdivisions necessarily divide our efforts, lim-iting the extent to which insights can be shared. This problem has recently been recognized and lamented by many prominent researchers (e.g.