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Vroom's VIE (expectancy) theory
Short answer
Vroom's expectancy theory states motivation = valence × instrumentality × expectancy. Employees are motivated when they believe effort leads to performance (expectancy), performance leads to rewards (instrumentality), and rewards are valued (valence). Rewards must be valued, performance-linked, fair, timely, and varied to strengthen motivation.
Explain Vroom's expectancy (VIE) theory of motivation and the importance of reward in it.
Victor Vroom (1964) proposed the expectancy theory (VIE theory). It states that a person is motivated to put effort when he believes that effort will lead to good performance, performance will lead to rewards, and the rewards are valued.
Motivation (Force) = Valence × Instrumentality × Expectancy
- Expectancy (E): Belief that effort leads to performance. "If I try hard I can finish this software on time." Value between 0 and 1.
- Instrumentality (I): Belief that performance will lead to a reward. "If I finish on time I will get a bonus or promotion."
- Valence (V): The value or attractiveness of the reward to the person. A bonus has a high valence for someone who needs money.
Effort --E--> Performance --I--> Reward --V--> Satisfaction
If any one factor is zero, motivation is zero. For example, if employees think promotion in a public enterprise depends on political connections (low instrumentality), they will not work harder, even if the promotion is attractive.
Importance of reward in the theory
- Valence depends on reward: Only rewards the employee values create force.
- Link of performance and reward must be visible: Fair, transparent appraisal builds instrumentality.
- Variety: Different employees value different rewards (pay, recognition, growth), so choose appropriately.
- Fairness: Unfair rewards reduce belief and motivation.
- Timeliness: Rewards should follow performance soon.
Managerial implications: clarify goals, give training so employees believe they can succeed, link pay to performance, and know what employees value.
Criticism: complex, assumes rational calculation, hard to measure the variables.
✓ Answer checked by Claude Opus 5.5 (high effort)
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