An exploration of indirect human costs associated with information systems adoption
One of the dilemmas that information systems (IS) decision-makers encounter is the identification of the often hidden costs associated with IS adoption, particularly since most of them are reported to be external to the traditional IS budget. The review of the IS literature has identified that much effort to date has focused on the identification and measurement of direct costs, and that much less attention has been paid to indirect costs. One of the main problems reported in the literature associated with looking at indirect costs is that they are intangible and difficult to quantify, and there is evidence suggesting that these indirect costs are rarely completely budgeted for, and thus deserve a much closer consideration by decision-makers. This research investigates this view, arguing that one element of indirect costs, that is, indirect human costs (lRCs), is underestimated and little understood. The author argues that it is not possible to estimate or evaluate IHCs without first identifying all their components, yet there is an absence of models that show how such costs are allocated for IS adoption. This underpins the necessity of the present research. Proposed here is a framework of nine sequential phases for accommodating indirect human costs. In addition to this, 1) three conjectures, 2) cost taxonomy and 3) an interrelationship-mapping cost driver model of IRCs, are proposed based on the literature analysis and underpinning the conceptual phases of the framework. To test the conjectures and validate the models proposed, a case research strategy using case settings were carried out in the private sector. Empirical findings validates the models proposed and reveal that indirect human costs are perceived as costs associated with IS adoption, nevertheless not included in the evaluation process or investment proposals. However, during the empirical research, new cost factors and drivers emerged, which resulted in modifications being made to the previously proposed conceptual models. In doing so, it provides investment decision-makers with novel frames of reference and an extensive list of IRCs that can be used during both the IS budget proposals and the evaluation process of the IS investment.