Leveraging international R&D teams of portfolio entrepreneurs and management controllers to innovate: Implications of algorithmic decision-making

We focus on how international research and development (R&D) teams of portfolio entrepreneurs and their management controllers can help to innovate and sustain entrepreneurial activities. An algorithmic decision-making model is implemented that indicates how such portfolio entrepreneurs build complex business structures and create a context for management accounting controllers' information that is suggestive of R&D internationalization challenges. A case study is utilized to compare one large and one medium-sized business conglomerate. Open interviews were conducted with portfolio entrepreneurs and their management controllers. We found that the international R&D teams of portfolio entrepreneurs and their management controllers have different mindsets when assessing sustainable innovative approaches for the existing business and for future expansion through acquisitions. Our findings assert the importance of context when understanding the challenges of management controllers dealing with the internationalization of such R&D efforts

Decorrelation of Neutral Vector Variables: Theory and Applications

In this paper, we propose novel strategies for neutral vector variable decorrelation. Two fundamental invertible transformations, namely serial nonlinear transformation and parallel nonlinear transformation, are proposed to carry out the decorrelation. For a neutral vector variable, which is not multivariate Gaussian distributed, the conventional principal component analysis (PCA) cannot yield mutually independent scalar variables. With the two proposed transformations, a highly negatively correlated neutral vector can be transformed to a set of mutually independent scalar variables with the same degrees of freedom. We also evaluate the decorrelation performances for the vectors generated from a single Dirichlet distribution and a mixture of Dirichlet distributions. The mutual independence is verified with the distance correlation measurement. The advantages of the proposed decorrelation strategies are intensively studied and demonstrated with synthesized data and practical application evaluations

Leveraging international R&D teams of portfolio entrepreneurs and management controllers to innovate: Implications of algorithmic decision-making

We focus on how international research and development (R&D) teams of portfolio entrepreneurs and theirmanagement controllers can help to innovate and sustain entrepreneurial activities. An algorithmic decision-making model is implemented that indicates how such portfolio entrepreneurs build complex business structures and create a context for management accounting controllers’ information that is suggestive of R&Dinternationalization challenges. A case study is utilized to compare one large and one medium-sized businessconglomerate. Open interviews were conducted with portfolio entrepreneurs and their management controllers. We found that the international R&D teams of portfolio entrepreneurs and their management controllers have different mindsets when assessing sustainable innovative approaches for the existing business and for future expansion through acquisitions. Our findings assert the importance of context when understanding the challenges of management controllers dealing with the internationalization of such R&D efforts.</p

Analysis of the mechanical impedance of bone-anchored hearing aids

Some patients who need hearing aids are unable to use an apparatus which transmits the sound via the external ear canal and have to use a bone conduction hearing aid. The bone vibration transducer of this aid is applied to the skin over the mastoid process and the sound is transmitted via the soft tissue and bone to the cochlea. The pressure needed to apply the transducer often gives the patient discomfort and the damping effect of the soft tissue gives poor quality of the sound transmitted. Advances in the ability to permanently implant foreign material in the body and perform permanent skin penetration has made it possible to develop a bone-anchored hearing aid. Fourteen patients have been equipped with such hearing aids. To be able to give these patients the best hearing aid, a new transducer has to be constructed to match the new situation. The impedance of the bone-anchored titaniumscrew/skull has been studied and the resistance and reactance of the mechanical impedance have been measured. The influence of a damping soft tissue layer over the bone has been analyzed. The difference between the impedance of the skull and the impedance of the soft tissue + skull was in the order of 10 to 25 dB depending on the frequency

Bayesian learning of Gaussian mixtures: Variational "over-pruning" revisited

This study reconsiders two simple toy data examples proposed by MacKay (2001) to illustrate what he called “symmetry-breaking” and inappropriate “over-pruning” by the variational inference (VI) approximation in Bayesian learning of probabilistic mixture models. The exact Bayesian solution is derived formally, including the effects of parameter values in the prior distribution of mixture weights. The exact solution is then compared to the results of VI approximation. In both toy examples both the exact solution and the VI approxi- mation normally assigned each data cluster entirely to its own mixture component. In both methods the number of active mixture components is normally the same as the number of data clusters. In this sense, the VI approach causes no “over-pruning”. In one extreme example with two clusters with only 1 and 3 samples, and very small parameter values in the prior Dirichlet distribution of mixture weights, the exact Bayesian solution assigned all samples to the same component, i.e., with “over-pruning”, whereas the VI approximation still converged to a solution using both mixture components, i.e., with no “over-pruning”. Thus, if inappropriate over-pruning occurs, it is probably caused by inappropriate selection of prior model parameters, and not by the VI approach. The VI approximation shows “symmetry-breaking” because it converges to one of the arbitrary and equivalent permutations of the indices of mixture components. The “symmetric” exact solution formally in- cludes all these permutations, but this is precisely what makes the exact Bayesian solution computationally impractical. Thus, in these toy examples, we must conclude that “symmetry-breaking” is not the same thing as “over-pruning”. The VI approximation shows “symmetry-breaking” but no “over-pruning”.QC 20130816</p