Factors which contribute to ease of use of Decision Support Systems and the impact of ease of use on decision effectiveness

This research addresses the factors which contribute to the ease of use of decision support systems and the impact of ease of use on decision effectiveness. Using a stochastic, multi-product inventory environment, complexity, and interface modes were manipulated, and an array of individual differences were taken into account in the development of a predictive model of ease of use of Decision Support Systems. Ease of use was developed as a canonical variate comprised of elements of creativity, dependence, and user perception. Multi-variate analysis of covariance was employed to determine which combinations of individual user, problem, and system traits impacted on ease of use. Subsequently, regression analysis was employed to determine if easy to use systems yield more effective decisions. Previous computer coursework and typing speed were found to be positively related to ease of use, while age was a detriment to ease of use. Menu and choice systems were found to be easier to use than command based interfaces, and interaction was detected between cognitive congruence and problem complexity as they impact on ease of use. Regression analysis showed that systems which are easier to use also yielded more effective decisions. Various ease of use constructs were tested with strikingly similar results.