Accounting for exogenous influences in a benevolent performance evaluation of teachers.

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 teaching differently, and, to be fair, (2) SETs should be determined solely by the teacher’s actual performance in the classroom, not by other influences (related to the teacher, the students or the course) which are not under his or her control. To account for these two issues, this paper constructs SETs using a specially tailored version of the popular non-parametric Data Envelopment Analysis (DEA) approach. In particular, in a so-called ‘Benefit of the doubt’ model we account for different values and interpretations that teachers attach to ‘good teaching’. Within this model, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics. To show the potentiality of the method, we examine teacher performance for the Hogeschool Universiteit Brussel (located in Belgium). Our findings suggest that heterogeneous background characteristics play an important role in teacher performance.Teacher performance; Data evelopment analysis; Conditional efficiency; Education;

Accounting for exogenous influences in a benevolent performance evaluation of teachers

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 teaching differently, and, to be fair, (2) SETs should be determined solely by the teacher’s actual performance in the classroom, not by other influences (related to the teacher, the students or the course) which are not under his or her control. To account for these two issues, this paper constructs SETs using a specially tailored version of the popular non-parametric Data Envelopment Analysis (DEA) approach. In particular, in a so-called ‘Benefit of the doubt’ model we account for different values and interpretations that teachers attach to ‘good teaching’. Within this model, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics. To show the potentiality of the method, we examine teacher performance for the Hogeschool Universiteit Brussel (located in Belgium). Our findings suggest that heterogeneous background characteristics play an important role in teacher performance.Teacher performance, Data envelopment analysis, Conditional efficiency, Education.

Constructing a knowledge economy composite indicator with imprecise data.

This paper focuses on the construction of a composite indicator for the knowledge based economy using imprecise data. Specifically, for some indicators we only have information on the bounds of the interval within which the true value is believed to lie. The proposed approach is based on a recent offspring in the Data Envelopment Analysis literature. Given the setting of evaluating countries, this paper discerns a ‘strong country in weak environment’ and ‘weak country in strong environment’ scenario resulting in respectively an upper and lower bound on countries’ performance. Accordingly, we derive a classification of ‘benchmark countries’, ‘potential benchmark countries’, and ‘countries open to improvement’.Knowledge economy indicators; Composite indicators; Multiple Imputation; Benefit of the doubt; Weight restrictions; Data Envelopment Analysis; Data impreciseness;

Creating Composite Indicators with DEA and Robustness Analysis: the case of the Technology Achievement Index

Composite indicators are regularly used for benchmarking countries’ performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of sub-indicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries’ composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration.factor is more important in explaining the observed progress.composite indicators, aggregation, weighting, Internal Market

Creating composite indicators with DEA and robustness analysis: The case of the technology achievement index.

Composite indicators are regularly used for benchmarking countries’ performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of sub-indicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries’ composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration.Indexes; Indicators; Robustness; Technology;

Circular economy inspired imaginaries for sustainable innovations

In this chapter, Narayan and Tidström draw on the concept of imaginaries to show how Circular Economy (CE) can facilitate values that enable sustainable innovation. Innovation is key for sustainability, however, understanding and implementing sustainable innovation is challenging, and identifying the kind of actions that could direct sustainable innovations is important. The findings of this study indicate that CE-inspired imaginaries enable collaboration and by relating such imaginaries to common and shared social and cultural values, intermediaries could motivate actors into taking actions that contribute to sustainable innovation.fi=vertaisarvioitu|en=peerReviewed

EU countries' progress towards 'Europe 2020 strategy targets'

© 2019 The Society for Policy Modeling This paper describes and analyzes EU Member States’ progress towards the national EU2020 targets. To do so, this paper constructs a geometric composite index with Benefit-of-the-Doubt weights as a measure of a Member State's overall performance on the EU2020 headline indicators. A tripartite decomposition of Member State performance change is presented to explain and analyze performance change of the EU-region and the individual EU Member States during the period 2008–2014. The results reveal that all Member States are in general making progress towards their national targets. Member States generally moved forward in the areas of R&D, environmental and educational policy and moved backwards in terms of employment and poverty and social inclusion. As to the realization of the national targets, the majority of the Member States are still mostly lagging on R&D and social inclusion and poverty reduction.status: publishe

Autism and Decision-Making Tendencies

Autism and Decision-Making Tendencie

Undesirable specialization in the construction of composite policy indicators: The Environmental Performance Index

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 most important advantage: DEA allows each evaluated country to look for its own optimal weights that maximize the composite indicator relative to the other countries. However, this flexibility also carries a potential disadvantage as it may allow countries to appear as a brilliant performer in a manner that is hard to justify: by ignoring or overemphasizing one or multiple of the judiciously selected performance indicators. To illustrate this issue of undesirable specialization in DEA-based evaluations, this paper compares the Environmental Performance Index (EPI) as computed by the optimistic and pessimistic version of the DEA-model as proposed by Zhou et al. (2007). Based on both computed composites, undesirable specialization in performance is identified. © 2012 Elsevier Ltd. All rights reserved.nrpages: 30status: publishe

A dynamic assessment of education policy: a Malmquist productivity index approach

Although considerable uncertainties remain about the specific economic impact of education, the recent literature provides clear evidence of its key importance in improving productivity and other economic outcomes. The general belief is that this role will become even more crucial in the knowledge-based economy. In almost every European country education is highly subsidized, accounting for a considerable percentage in public spending. This perspective warrants a rigorous monitoring of the efficiency of the education process. This paper uses the the Malmquist Productivity Index approach to assess the dynamic progress of the educational system of the OECD countries over time. The disaggregation of member states’ observed performance shifts over the last years into a catching-up and an environmental progress component allows to observe whether or not any improvements have been made by the European countries vis à vis the other OECD member states.status: publishe