Gamification is a promising way to enhance performance and motivation at work. Flow experiences play a significant role in gamification design, while also being a possible gamification outcome and a predictor of performance. In a study with 89 participants, we compared gamified and non-gamified assembly tasks, examining flow and performance. While performance did not differ between groups, it improved over time. The gamified group reported more frequent flow experiences. Flow intensity increased over five assembly runs, but did not differ between groups. A positive repeated measures correlation was found between flow intensity and performance. The results suggest that gamified work can enhance flow, which in turn can be associated with improved performance. However, flow also occurs in non-gamified settings, indicating that other mechanisms may contribute. Possible explanations include playful work design and training effects in learning the assembly routine. Future research should consider personalization and adaptive tailoring of gamification.

A procedure for the parameterization of surface meshes of objects with spherical topology is presented. The generation of such a parameterisation has been formulated and solved as a large constrained optimization problem by C. Brechbuhler (1995), but the convergence of this algorithm becomes unstable for object meshes consisting of several thousand vertices. We propose a new more stable algorithm to overcome this problem using multi-resolution meshes. A triangular mesh is mapped to a sphere by harmonic mapping. Next, a mesh hierarchy is constructed. The coarsest level is then optimized using a modification of the original procedure to map object surfaces to the unit sphere. The result is used as a starting point for the mapping of the next finer mesh, a process which is repeated until the final result is obtained. The new approach is compared to the original one and some parameterized object surfaces are presented.