Characteristics of New Firms: A Comparison by Gender

Based on data from the Kauffman Firm Survey, compares characteristics of the owner, type of business, industry, financing, size, and performance of new firms owned by women and by men. Considers the factors behind women-owned firms' underperformance

Sources of Economic Hope: Women's Entrepreneurship

This report suggests that accelerating female entrepreneurship could have the same positive effect on the U.S. economy that the large-scale entry of women into the labor force had during the 20th century. While women represent more than half of the educated U.S. population, they have far lower levels of participation in growth-oriented entrepreneurship than men do. Women-owned businesses account for only about 16 percent of the nation's employer firms and, among high-growth firms, they typically account for fewer than 10 percent of founders

Capital Structure in Small Manufacturing Firms: Evidence from the Data

This article examines theories of capital structure pertaining to small firms and looks at the capital structure of small to mid-sized manufacturing firms within the context of those theories. Results provide support for Leland and Pyle\u27s (1977) Signaling Theory, Myer\u27s (1984) Pecking Order Theory, Berger and Udell\u27s (1998) Life Cycle Theory. Contrary to the findings of prior research, these results revealed that industry sector was not a significant determinant of capital structure. Rather, these findings show that capital structure in small to mid-sized firms is determined by measures of firm size, firm age, organizational status, profitability, and asset structure

The Liability of Newness and Small Firm Access to Debt Capital: Is There a Link?

Literature pertaining to the “liability of newness†contends that newer firms face particular difficulties and a greater risk of failure. This article seeks to determine if “newness†is also a disadvantage in the acquisition of debt capital. Results indicate that newer firms were significantly less likely to have lines of credit and were also significantly more likely to have been turned down for their most recent loan. Even when we control for length of relationship with the primary financial services provider, personal guarantees, and collateral, younger firms were still more likely to be turned down for loans. Small firms are an essential part of the United States economy. According to the U.S. Small Business Administration (SBA), there were 22.9 million small firms, defined as firms having 500 or fewer employees, in the United States in 2002 (Small Business by the Numbers, 2002). In fact, small firms represent 99 percent of all firms in this country. They provide approximately half of Gross Domestic Product as well as the majority of new jobs. Small firms are also an important source of innovation in the development of new products, services, and technologies. Given the role played by small firms, it is in our interest to identify factors that contribute to their likely success. In keeping with that, studies of small firm survival and failure have repeatedly identified difficulties with financial management and an inability to secure adequate sources of capital as major contributors to dissolution (Gaskill et al., 1993), Lussier, 1996; Watson et al., 1998). Many small firms are launched with inadequate financial resources. To compound this problem, small firms, unlike larger, publicly-held firms, are unable to raise capital in the public debt and equity markets (Ang, 1991). Alternatively, they are restricted to sources of capital that include the owner’s savings, loans from family and friends, trade credit, and loans from banks and other financial service providers (Berger & Udell, 1998; Bitler et al., 2001). Even in the case of bank loans, however, small firms are more likely to be denied than larger, more established firms. As noted above, the inability to secure external sources of capital raises the risk of firm failure. On a slightly less dire note, inadequate capital may also restrict the firm’s ability to grow, to hire employees, or to introduce new products and services thus impairing profitability and growth in the long term

The Impact of Human Capital Measures on Firm Performance: A Comparison by Gender, Race and Ethnicity

Prior research suggests that firms owned by women and minorities are smaller, less profitable, and less growth-oriented than those owned by white men. Prior research also suggests that firm performance is influenced by the firm owner\u27s level of human capital in the form of education, employment experience, and life experiences that might help him to prepare for the challenges of small business ownership. This artical compares the performance of firms owned by white men to those owned by white women and by minority small business owners to determine if higher levels of human capital eliminate performance gaps between them. Results reveal that firms owned by white and black women and firms owned by black men were still significantly smaller, even controlling for industry sector and various measures of human capital. Contrary to prior research, however, firms owned by women and minorities were no less profitable nor less likely to grow. The sole exception to this finding was that firms owned by Asian men were significantly less likely to exhibit sales growth than firms owned by white men

Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering