Management And Accounting Web

Snead, K. C. 1991. An application of expectancy theory to examine managers' motivation to utilize a decision support system. Abstract. Journal of Management Accounting Research (3): 213-222.

Summary by Anita Reed
Ph.D. Program in Accounting
University of South Florida, Spring 2002

Behavioral Issues Main Page | Decision Theory Main Page | Expectancy Theory Main Page

Purpose/Motivation

The author is motivated by lack of consistent and generalizable findings from two research streams utilized to examine user acceptance of management information systems (MIS): implementation factor research and implementation process research. Neither research stream addresses the motivational and behavioral factors related to users. As a result, the author proposes to use the theoretical framework provided by expectancy theory to examine user acceptance of MIS through analysis of motivational and behavioral factors within a management control system setting. Managers support of MIS is a necessary element of successful implementation of the management control systems as measured by user acceptance.

Research Question

The research question addressed in the study is:

Can the principles of expectancy theory explain the motivation of a manager to make maximum use of a newly-developed decision support system (DSS)?

Theory

Vroom’s expectancy theory is utilized. The two models developed by Vroom are the valence model and the force model.

The valence model posits that the valence or attractiveness of a first level outcome for an individual is represented by the summation of the product of all corresponding second level outcome valences with their respective instrumentalities. In other words, the attractiveness to a manager of using a newly developed DSS is equal to the attractiveness of all related second level outcomes times the manager’s belief that the first level outcome will lead to the second level outcomes. If the manager believes that using the system to its maximum will lead to outcomes that are attractive to the manager, then the manager will find using the system attractive.

The force model posits that the motivational force acting upon a person to perform a particular act is equal to the summation of the product of the perceived attractiveness of first level outcomes related to the act and the expectancy that the act will be followed by these outcomes. In other words, the amount of effort a manager will exert to use a DSS to maximum will depend on the extent to which the manager finds the maximum use of the DSS to be attractive (as developed in the valence model) and the extent to which the manager believes the level of effort will result in successfully using the DSS in performance of his/her job.

Hypotheses

The following hypotheses are proposed:

H1: The valence model will explain a manager’s perception of the attractiveness of using a new DSS to the maximum extent.

H2: The force model will explain a manager’s motivation to use a new DSS to the maximum extent.

Methodology

A within-subject experimental procedure using 32 judgment modeling-based decision making cases to measure the two dependent variables (DV’s): valence associated with maximum use of the DSS and the level of motivational force associated with making maximum use. Five independent variables representing second-level outcomes were manipulated at two levels relative to the first DV, and one independent variable representing the likelihood (expectancy) of successfully using the DSS was manipulated at the same two levels relative to the second DV. The author refers to this as a one-half fractional factorial design. The experiment was administered in one session.

Sample

Participants were 91 students in the University of South Carolina Professional MBA Program, 71 males and 20 females. 90 initially usable responses were obtained.

Analysis

Analysis of valence was conducted using multiple regression techniques by estimating a multiple regression valence model for each participant. Average R2 of the 87 statistically significant models was .78, providing support for H1.

Analysis of force was also conducted using multiple regression techniques by estimating a multiple regression force model for each participant, using the additive model as indicated by hierarchical regression analysis. The additive model is more parsimonious than the multiplicative model and the average incremental value of the interaction term was only .07. 86 usable responses were analyzed individually and all were found to be statistically significant with average R2 of 82. H2 is supported.

Results

H1 is supported, indicating that managers’ reactions toward outcomes associated with DSS implementation (second level outcomes) are important in their overall assessment of the attractiveness of DSS implementation (first level outcome). The broad range across participants in the attractiveness of the second level outcomes indicates that additional research is needed to identify individual characteristics that contribute to the varying reactions.

H2 is supported, indicating that managers’ overall assessment of the attractiveness of DSS implementation and their expectation that effort to implement DSS will be successful are both important factors related to their motivation to implement and utilize a DSS. Of the two model components, the managers’ assessment of the overall attractiveness of the DSS is more influential than the expectation of success in determining the level of effort the manger is willing to exert in the implementation, providing additional support for the importance of the valence assessment and the contention that system impacts upon the user must be considered in understanding user behavior.

Conclusion

The decision by managers to implement MIS is complicated. These results indicate the usefulness of expectancy theory framework in understanding the decision process.

Anticipation of manager reaction to perceived outcomes of a DSS offers an indication of the level of user acceptance for the DSS. Incorporation of attractive user outcomes when possible can contribute to higher levels of use.

Future research using expectancy theory to examine the impacts of user participation, user training and individual differences on the elements of the valence and force models may offer additional insight into the decision process and the ever elusive user acceptance.

Full Title of Dissertation

"An Application of Vroom’s Expectancy Theory and McClelland’s Trichotomy of Needs Theory to Examine Managers’ Motivation to Implement a Decision Support System"

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