The influence of moral intensity on decision-making in the context of an artificial intelligence-based online personalised pricing model

This research sought to describe the influence that moral intensity has on managers’ decision-making in the context of artificial intelligence (AI)-based online personalised pricing models. Moral intensity is a construct from the issue-contingent model, a decision-making framework stating that the more morally intense an issue, the more moral the judgement applied in decision-making. Jones (1991) described moral intensity as the proportionality of moral responsibility. Of the six factors of moral intensity in the issue-contingent model, three were used in this research: social consensus, magnitude of consequences and likelihood of effect. A hypothetical scenario was described about an online AI-based personalised pricing model for groceries. Experimental vignette methodology was used, in which eight vignettes were described with varying levels of moral intensity and questions on moral judgement were posed on each vignette. Personal characteristics of the decision-maker were also captured to account for variation they may cause in decision-making. Univariate analyses of variance and covariance were conducted. Findings were that personal characteristics have no influence on decision-making in this context, but each of the factors of moral judgement do. Implications are that moral decision-making in the use of AI-based online personalised pricing models can be improved by increasing the awareness of probable consequences and of the social opinion on whether these types of models are considered fair.Mini Dissertation (MBA)--University of Pretoria, 2021.zl22Gordon Institute of Business Science (GIBS)MBAUnrestricte