A review of quality frameworks in information systems

Quality is a multidimensional concept that has different meanings in different contexts and perspectives. In the domain of Information system, quality is often understood as the result of an IS development process and as the quality of an IS product. Many models and frameworks have been proposed for evaluating IS quality. However, as yet there is not a commonly accepted framework or standard of IS quality. Typically, researchers propose a set of characteristics, so-called quality factors contributing to the quality of IS. Different stakeholders' perspectives are resulting in multiple definitions of quality factors of IS. For instance, some approaches are based on the IS delivery process for the selection of quality factors; while some other approaches do not clearly explain the rationale of their selection. Moreover, often relations or impacts among selected quality factors are not taken into account. Quality aspects of information are frequently considered isolated from IS quality. The impact of IS quality on information quality seems to be neglected in most approaches. Our research aims to incorporate these levels, by which we propose an IS quality framework based on IS architecture. Considering user and IS developer's perspectives, different quality factors are identified for various abstraction levels. Besides, the presentation on impacts among different quality factors helps to retrieve the root cause of IS defects. Thus, our framework provides a systematic view on quality of information and IS

Quality and perceived usefulness of process models

Modeling is now an essential ingredient in business process management and information systems development. The general usefulness of models in these areas is therefore generally accepted. It is also undisputed that the quality of the models has a significant impact on their usefulness. In the literature we can find any number of quality metrics, but hardly any study that investigates their relation with (perceived) usefulness and none that considers their relative impact on usefulness. We take a look at some of the most frequent quality dimensions and their relative impact on the perceived usefulness of models