Does Gender Matter? Women Business Angels and the Supply of Entrepreneurial Finance

There is a substantial literature on the relationship between gender and access to finance. However, most studies have been concerned with access to debt finance. More recently, the focus of this research has broadened to examine women and venture capital. This article extends the focus further by examining the role of women in the business angel market, which is more important than the formal venture capital market in terms of both the number of ventures supported and total capital flows. Based on a detailed analysis of business angels in the U.K., the study concludes that women investors who are active in the market differ from their male counterparts in only limited respects. Future research into women business angels, and the possible existence of gender differences, needs to be based on more fully elaborated standpoint epistemologies that focus on the experience of the woman angel investor per se, and center on the examination of the role of homophily, social capital, networking, and competition in investment behavior.

A method to bridge the gap between breadth and depth in IS narrative analysis

A method extending narrative analysis with grounded theory analysis is proposed to bridge the gap between breadth and depth in IS narrative research. The purpose of the method is not to develop a theory but to make narrative analysis more accessible, transparent and accountable; and the resultant narrative more contextually grounded. The method is aimed particularly at inexperienced narrative researchers who currently lack guidance through the complexity of narrative analysis, but may also benefit experienced narrative researchers who may not be familiar with the applicability of grounded theory tools and techniques in this area.

Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random-Effects Models

This paper reports the findings from a discrete-choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness-to-pay values for every individual in the sample. This departs from customary approaches in which the willingness-to-pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random-effects models for panel data are subsequently used to identify the determinants of the individual-specific willingness-to-pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete-choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.