Class Notes (1,100,000)
CA (640,000)
York (40,000)
Lecture 5

# ADMS 2400 Lecture Notes - Lecture 5: Goal Setting, Bayesian Probability, Job Performance

Department
Course Code
Professor
Sabrina Deutsch Salamon
Lecture
5

This preview shows half of the first page. to view the full 3 pages of the document.
Motivation - is defined as a set of energetic forces that originates both within and outside an employee,
initiates work-related effort, and determines its direction, intensity, and persistence.
-motivation is a critical consideration because job performance is largely a function of two factors:
motivation and ability
Expectancy Theory
Expectancy - is a subjective probability, ranging from 0 to 1 that a specific amount of effort will result in a
specific level of performance abbreviated E → P.
Instrumentality - is a set of subjective probabilities, each ranging from 0 to 1 that successful
performance will bring a set of outcomes abbreviated P → O.
Valence - reflects the anticipated value of the outcomes associated with performance (abbreviated V).
^Can be positive, negative, or zero
Expectancy Theory, Cont’d
-Total motivational force to perform a given action can be described using the following formula:
Motivational Force = E P x Σ[P O) x V]
-Motivational force equals zero if any one of the three beliefs is zero.
Goal Setting Theory - views (self-set) goals as the primary drivers of motivation.
-Research shows that assigning employees specific & difficult goals leads to higher self-set goals, which,
in turn will result in higher levels of performance
-Why do specific and difficult goals have such positive effects?
-Goals determine the intensity of effort directed at goal-relevant activities, and they affect the
persistence of effort over time.
-Goals trigger the creation of task strategies, defined as learning plans and problem-solving approaches
used to achieve successful performance.
find more resources at oneclass.com
find more resources at oneclass.com