Dynamics of effectuation and causation in technology-based new ventures (INTERACTIVE PAPER)

The creation of new ventures is a process characterized by the need to decide and take action in the face of uncertainty, and this is particularly so in the case of technology-based ventures. Effectuation theory (Sarasvathy, 2001) has advanced two possible approaches for making decisions while facing uncertainty in the entrepreneurial process. Causation logic is based on prediction and aims at lowering uncertainty, whereas effectuation logic is based on non-predictive action and aims at working with uncertainty. This study aims to generate more fine-grained insight in the dynamics of effectuation and causation over time. We address the following questions: (1) What patterns can be found in effectual and causal behaviour of technology-based new ventures over time? And (2) How may patterns in the dynamics of effectuation and causation be explained?

Coarse-to-fine skeleton extraction for high resolution 3D meshes

This paper presents a novel algorithm for medial surfaces extraction that is based on the density-corrected Hamiltonian analysis of Torsello and Hancock [1]. In order to cope with the exponential growth of the number of voxels, we compute a first coarse discretization of the mesh which is iteratively refined until a desired resolution is achieved. The refinement criterion relies on the analysis of the momentum field, where only the voxels with a suitable value of the divergence are exploded to a lower level of the hierarchy. In order to compensate for the discretization errors incurred at the coarser levels, a dilation procedure is added at the end of each iteration. Finally we design a simple alignment procedure to correct the displacement of the extracted skeleton with respect to the true underlying medial surface. We evaluate the proposed approach with an extensive series of qualitative and quantitative experiments. © 2013 Elsevier Inc. All rights reserved.