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.

Decision strategies for policy decisions under uncertainties: The case of mitigation measures addressing methane emissions from ruminants

Decision strategies aim at enabling reasonable decisions in cases of uncertain policy decision problems which do not meet the conditions for applying standard decision theory. This paper focuses on decision strategies that account for uncertainties by deciding whether a proposed list of policy options should be accepted or revised (scope strategies) and whether to decide now or later (timing strategies). They can be used in participatory approaches to structure the decision process. As a basis, we propose to classify the broad range of uncertainties affecting policy decision problems along two dimensions, source of uncertainty (incomplete information, inherent indeterminacy and unreliable information) and location of uncertainty (information about policy options, outcomes and values). Decision strategies encompass multiple and vague criteria to be deliberated in application. As an example, we discuss which decision strategies may account for the uncertainties related to nutritive technologies that aim at reducing methane (CH4) emissions from ruminants as a means of mitigating climate change, limiting our discussion to published scientific information. These considerations not only speak in favour of revising rather than accepting the discussed list of options, but also in favour of active postponement or semi-closure of decision-making rather than closure or passive postponement.

Rethinking ERP-Outsourcing Decisions for Leveraging Technological and Preserving Business Knowledge

During the selection, implementation and stabilization phases, as well as the operations and optimization phase of an ERP system (ERP-lifecycle), numerous companies consider to utilize the support of an external service provider. This paper analyses how different categories of knowledge influence the sourcing decision of crucial tasks within the ERP lifecycle. Based on a review of the IS outsourcing literature, essential knowledge-related determinants for the IS outsourcing decision are presented and aggregated in a structural model. It will be hypothesized that internal deficits in technological knowledge in comparison to external vendors as well as the specificity of the synthesis of special technological and specific business knowledge have a profound impact on the outsourcing decision. Then, a classification framework will be developed which facilitates the assignment of various tasks within the ERP lifecycle to their respective knowledge categories and knowledge carriers which might be internal or external stakeholders. The configuaration task will be used as an example to illustrate how the structural model and the classification framework may be applied to evaluate the outsourcing of tasks within the ERP lifecycle.