Transfer of spatial knowledge from a virtual environment to reality: Impact of route complexity and subject’s strategy on the exploration mode

The use of virtual reality as tool in the area of spatial cognition raises the question of the quality of learning transfer from a virtual to a real environment. It is first necessary to determine with healthy subjects, the cognitive aids that improve the quality of transfer and the conditions required, especially since virtual reality can be used as effective tool in cognitive rehabilitation. The purpose of this study was to investigate the influence of the exploration mode of virtual environment (Passive vs. Active) according to Route complexity (Simple vs. Complex) on the quality of spatial knowledge transfer in three spatial tasks. Ninety subjects (45 men and 45 women) participated. Spatial learning was evaluated by Wayfinding, sketch-mapping and picture classification tasks in the context of the Bordeaux district. In the Wayfinding task, results indicated that active learning in a Virtual Environment (VE) increased the performances compared to the passive learning condition, irrespective of the route complexity factor. In the Sketch-mapping task, active learning in a VE helped the subjects to transfer their spatial knowledge from the VE to reality, but only when the route was complex. In the Picture classification task, active learning in a VE when the route was complex did not help the subjects to transfer their spatial knowledge. These results are explained in terms of knowledge levels and frame/strategy of reference [SW75, PL81, TH82].

Path Dependence in Decision-Making Processes: Exploring the Impact of Complexity under Increasing Returns

The development of path-dependent processes basically refers to positive feedback in terms of increasing returns as the main driving forces of such processes. Furthermore, path dependence can be affected by context factors, such as different degrees of complexity. Up to now, it has been unclear whether and how different settings of complexity impact path-dependent processes and the probability of lock-in. In this paper we investigate the relationship between environmental complexity and path dependence by means of an experimental study. By focusing on the mode of information load and decision quality in chronological sequences, the study explores the impact of complexity on decision-making processes. The results contribute to both the development of path-dependence theory and a better understanding of decision-making behavior under conditions of positive feedback. Since previous path research has mostly applied qualitative case-study research and (to a minor part) simulations, this paper makes a further contribution by establishing an experimental approach for research on path dependence.

Calculation of the average travel distance in a low-level picker-to-part system considering any distribution function within the aisles

The estimation of the average travel distance in a low-level picker-to-part order picking system can be done by analytical methods in most cases. Often a uniform distribution of the access frequency over all bin locations is assumed in the storage system. This only applies if the bin location assignment is done randomly. If the access frequency of the articles is considered in the bin location assignment to reduce the average total travel distance of the picker, the access frequency over the bin locations of one aisle can be approximated by an exponential density function or any similar density function. All known calculation methods assume that the average number of orderlines per order is greater than the number of aisles of the storage system. In case of small orders this assumption is often invalid. This paper shows a new approach for calculating the average total travel distance taking into account that the average number of orderlines per order is lower than the total number of aisles in the storage system and the access frequency over the bin locations of an aisle can be approximated by any density function.