Firm Foundations in the Knowledge Intensive Business Service Sector. Results from a Comparative Empirical Study in Three German Regions

A key feature of the knowledge-based economy is a remarkable increase in the number of knowledge intensive business service firms (KIBS). KIBS are based upon highly specialised knowledge and they acquire knowledge in the course of the interaction process that takes place whilst they provide their services. As knowledge and its organisation are tied to personal capabilities and information, spatial “proximity” to providers and users of knowledge appears to be crucial for the foundation and early development of KIBS. The quality of regional environments (e.g. configurations of incubator and intermediate organisations or a regional “entrepreneurial climate”) and the foundation and development of KIBS are obviously interrelated. Based upon a standardised survey, the present paper analyses regional differences in the foundation process and early development of KIBS in three German regions in a comparative way. The results of our descriptive analysis show strong regional ties of founders and KIBS firms during the founding process as a result of spatial proximity. With only slight differences, those ties could be observed in all three regions. They are primarily related to the former activities of the founder, the transfer of results and experiences into the new firm, and spatial proximity to the most important customers or other partners within the exchange of knowledge. Major differences can be derived with regard to the development of the firms (e.g. Munich KIBS firms show a much better development in employment), obstacles in accessing the regional market, and the general assessment of the regional framework conditions from the point-of-view of the KIBS founders.KIBS; firm foundations; interaction; spatial proximity; Germany

Statistical Study of Supply Chain Developmental Training on Original Equipment Manufacturer’s Defect Rates

Learning is an amalgam of a student’s desire to understand, the willingness of an instructor to educate, the subject taught, its quality, and the delivery environment. Most importantly, a learning goal, both actionable and investment worthy, must exist for effective learning to take place. The ability to learn and then implement new concepts and ideas is the significant difference separating our species from other life on this planet. It has led to diverse discoveries such as disease vaccines, nuclear energy, the automobile, electronics, and rocket planes to name just a few.Science advances in small steps and big leaps. Inventions increase daily to improve the quality of life for this planet’s population. At the center of all these ideas are researchers looking to tease out the next piece of information for our world’s knowledge base. This body of knowledge (BOK) grows at an ever-expanding rate, doubling every few years. This doubling period is shrinking rapidly as more knowledge is accumulated.In the manufacturing world of products, this BOK is brought to bear on products that, hopefully, stand above their competition. If a product is excellent, consumers and producers are satisfied. The consumer gets the best quality for the price while the producer gets the best price for the quality offered. If product quality and price are right, there is someone willing to buy it.However, what happens when the opposite is experienced and the product, at its asking price, is of poor quality? Buyers are less willing to spend and quick to mention the lack of quality or defects found. Defects can impact the maker’s selling price and translate into extensive efforts to make the customer whole through warranty. The producer also risks the loss of their customer (brand loyalty) if the product is deficient in quality.Within this dissertation, training methods, useful practices, experiences, and the body of training knowledge will be presented in defense of developmental training and will conclude with a case study exploration into the connections between supply chain developmental training and defect reductions at an Original Equipment Manufacturer (OEM) using multiple statistical techniques

Classification of clinical outcomes using high-throughput and clinical informatics.

It is widely recognized that many cancer therapies are effective only for a subset of patients. However clinical studies are most often powered to detect an overall treatment effect. To address this issue, classification methods are increasingly being used to predict a subset of patients which respond differently to treatment. This study begins with a brief history of classification methods with an emphasis on applications involving melanoma. Nonparametric methods suitable for predicting subsets of patients responding differently to treatment are then reviewed. Each method has different ways of incorporating continuous, categorical, clinical and high-throughput covariates. For nonparametric and parametric methods, distance measures specific to the method are used to make classification decisions. Approaches are outlined which employ these distances to measure treatment interactions and predict patients more sensitive to treatment. Simulations are also carried out to examine empirical power of some of these classification methods in an adaptive signature design. Results were compared with logistic regression models. It was found that parametric and nonparametric methods performed reasonably well. Relative performance of the methods depends on the simulation scenario. Finally a method was developed to evaluate power and sample size needed for an adaptive signature design in order to predict the subset of patients sensitive to treatment. It is hoped that this study will stimulate more development of nonparametric and parametric methods to predict subsets of patients responding differently to treatment