the Art and Science Museums and Mindseums of the Future

Ted Kahn, co-founder, President, and CEO of DesignWorlds for Learning, Inc. speaks about his research and practice in developing uses for interactive learning technologies in museums, schools, and workplaces.

Nature, Art, and Science

Professor Emeritus David Lee of FIU speaks on the interaction of art and the sciences. Lecture held at the Green Library, Modesto Maidique Campus on January 15, 2014.

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. ^ In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. ^ The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area. ^

A comprehensive study of bankruptcy prediction: Accounting ratios, market variables, and microstructure

Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area.

Neuroscience and Hindu Aesthetics: A Critical Analysis of V.S. Ramachandran’s “Science of Art”

Neuroaesthetics is the study of the brain’s response to artistic stimuli. The neuroscientist V.S. Ramachandran contends that art is primarily “caricature” or “exaggeration.” Exaggerated forms hyperactivate neurons in viewers’ brains, which in turn produce specific, “universal” responses. Ramachandran identifies a precursor for his theory in the concept of rasa (literally “juice”) from classical Hindu aesthetics, which he associates with “exaggeration.” The canonical Sanskrit texts of Bharata Muni’s Natya Shastra and Abhinavagupta’s Abhinavabharati, however, do not support Ramachandran’s conclusions. They present audiences as dynamic co-creators, not passive recipients. I believe we could more accurately model the neurology of Hindu aesthetic experiences if we took indigenous rasa theory more seriously as qualitative data that could inform future research.