We propose a non-parametric methodology to study the presence of economies of scope between teaching and research (i.e., the teaching-research nexus). In particular, the paper advocated a conditional version of the ‘benefit-of-the-doubt’ approach to estimate the relationship between the...

The non-parametric Data Envelopment Analysis approach is increasingly used to construct composite indicators for country performance monitoring, benchmarking, and policy evaluation in a large variety of fields. The flexibility in the definition of aggregation weights is praised as the method's...

Teaching and research are widely regarded as the two key activities of academics. We propose a tailored version of the popular Data Envelopment Analysis methodology to evaluate the overall performance of university faculty. The methodology enables accounting for the potential presence of...

Students evaluations of teacher performance (SETs) are increasingly used by universities and colleges for teaching improvement and decision making (e.g., promotion or tenure). However, SETs are highly controversial mainly due to two issues: (1) teachers value various aspects of excellent...

This paper proposes a non-parametric methodology to construct composite scores of citizen satisfaction with local police corpses. More precisely, the paper advocates a custom made version of the popular Data Envelopment Analysis approach, also referred to as the ‘Benefit-of-the-Doubt’-model....

Although benevolent (BoD) weighting has some appealing features for the construction of evaluation scores of teacher performance (i.e., SET-scores), it still suffers from an important drawback in its basic form: the sensitivity of its outcomes to the influence of potential outliers, extreme...

Hard data alone are not sufficient to evaluate local police effectiveness in the new age of community policing. Citizens can provide useful feedback regarding strengths and weaknesses of police operations. However, citizen satisfaction indicators typically fail to accurately convey the...