Assessing e-justice smartness: A new framework for e-justice evaluation through public values

Abstract

As it is happening in the smart city literature, the topic of measuring the performance of smart e-justice systems is coming to the fore. However, the studies that deal with e-justice performance focus only on efficiency-oriented variables. That approach may be appropriate for Information Systems (IS) evaluation, but it is too simplistic for smart e-justice. E-justice system deployment also has a considerable effect on the broad spectrum of values guiding the administration of justice. Indeed, justice systems as also smart cities in democratic societies provide a set of services, but, above all, support a set of public values. In the case of justice, values belong to the general concept of the rule of law and comprise judges’ independence and impartiality, equality of access, fair trial, and procedural transparency. Since e-justice systems are also supposed to pursue these values, they have to be taken into account in any assessment exercise. In this paper, we present a new evaluative framework that integrates the efficiency-oriented variables derived from the IS literature with variables that measure the capacity of an e-justice system to support justice system public values. To design an integrated e-justice system assessment framework, we focused on the adaptation to e-justice of one of the most widely used frameworks for the evaluation of IS: the DeLone and McLean model. Moreover, through the analysis of the justice systems evaluation literature, we integrated the DeLone and McLean model with variables that focus on justice system values. The framework has been operationalized through a mixed methodology: quantitative analysis (users’ survey and secondary source data) and qualitative (in particular through semi-structured interviews). The framework has been tested by analyzing a real case, the Italian e-filing system Trial Online (TOL; in Italian Processo Civile Telematico—PCT). Through the analysis of the data gathered, we tested the parsimony and the applicability of the framework, and we provided a (non-statistically significant) evaluation of the system.