Is output performance all about the resources? A fuzzy-set Qualitative Comparative Analysis of street-level bureaucrats in Switzerland

This article refines Lipsky’s (1980) assertion that lacking resources negatively affect output performance. It uses fuzzy-set Qualitative Comparative Analysis to analyse the nuanced interplay of contextual and individual determinants of the output performance of veterinary inspectors as street-level bureaucrats in Switzerland. Moving ‘beyond Lipsky’, the study builds on recent theoretical contributions and a systematic comparison across organizational contexts. Against a widespread assumption, output performance is not all about the resources. The impact of perceived available resources hinges on caseloads, which prove to be more decisive. These contextual factors interact with individual attitudes emerging from diverse public accountabilities. The results contextualize the often-emphasized importance of worker-client interaction. In a setting where clients cannot escape the interaction, street-level bureaucrats are not primarily held accountable by them. Studies of output performance should thus sensibly consider gaps between what is being demanded of and offered to street-level bureaucrats, and the latter’s multiple embeddedness.

Street-level bureaucrats and new modes of governance - How conflicting roles affect the implementation of the Swiss Ordinance on Verterinary Drugs

Lipsky’s seminal concept of street-level bureaucrats (SLBs) focuses on their role as public servants. However, in the course of new modes of governance, private actors have gained an additional role as implementation agents. We explore the logic of private SLBs during the implementation of the Swiss Ordinance on Veterinary Medicinal Products (OVMP) where veterinarians are simultaneously implementing agents, policy addressees, and professionals with economic interests. We argue that, because of contradictory reference systems, it is problematic for the output performance if an actor is simultaneously the target group of a policy and its implementing agent.

Adapting a driving simulator to study pedestrians' street-crossing decisions: A feasibility study

The decision when to cross a street safely is a challenging task that poses high demands on perception and cognition. Both can be affected by normal aging, neurodegenerative disorder, and brain injury, and there is an increasing interest in studying street-crossing decisions. In this article, we describe how driving simulators can be modified to study pedestrians' street-crossing decisions. The driving simulator's projection system and the virtual driving environment were used to present street-crossing scenarios to the participants. New sensors were added to measure when the test person starts to cross the street. Outcome measures were feasibility, usability, task performance, and visual exploration behavior, and were measured in 15 younger persons, 15 older persons, and 5 post-stroke patients. The experiments showed that the test is feasible and usable, and the selected difficulty level was appropriate. Significant differences in the number of crashes between young participants and patients (p = .001) as well as between healthy older participants and patients (p = .003) were found. When the approaching vehicle's speed is high, significant differences between younger and older participants were found as well (p = .038). Overall, the new test setup was well accepted, and we demonstrated that driving simulators can be used to study pedestrians' street-crossing decisions.