Women own nearly half of the small- and medium-sized enterprises (SMEs) in Canada but continue to be under-represented in senior positions in the private sector.

As International Women’s Day, celebrated on March 8, draws near, one of uOttawa’s leading researchers on women entrepreneurs says there is some cause for celebration when it comes to women in the business world. However, she feels that Canada still has some ways to go before achieving gender equality.

Catherine Elliott, assistant professor at the Telfer School of Management, says the proportion of women who own SMEs has remained constant at around 47% for the past decade. Between 2001 and 2011, the number of women who became self-employed grew by 23%, compared to a 14% increase among men. Elliot says that these statistics point to both good and bad news for women: the numbers indicate that plenty of women are able to start up new ventures, but that there are limitations on how big such businesses can grow.

Elliott and her colleague Professor Barbara Orser, vice-dean of the Telfer School of Management, are writing a book to be published by Stanford University Press in 2015 that looks at entrepreneurial feminists – women who start businesses partly to empower other women. Orser spearheaded the Taskforce for Women’s Enterprise Growth, a non-partisan consortium formed in 2009 to develop a blueprint for promoting women-owned businesses. One recommendation that emerged was to expand the network of women-focused enterprise centres across Canada in order to provide specialized training and support for entrepreneurs.

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Professor Jonathan Li of the Telfer School of Management explores how rich datasets available today can be leveraged to improve business decision-making. Li aims to develop new decision tools that incorporate a holistic view of risk, made possible by the ongoing revolution in data. His research draws on interdisciplinary knowledge from the fields of business analytics (operations research) and financial engineering, and relies heavily on the use of algorithmic tools such as optimization and simulation. Progress in these areas is expected to benefit a wide range of data-intensive business activities that typically have to contend with high degrees of uncertainty, such as financial investment and derivative pricing, supply chain management and revenue management.

Traditional decision models tend to take a narrow view of risk, and often understate the impact of uncertainty on our decisions. The 2008 financial crisis provides only the most famous recent example of how decisions based on naïve risk models can go awry, Li says. Successful implementation of risk management in decision models requires two ingredients: first, access to real-world data, and second, models that can convert the data into risk-relevant information and drive risk-aware decisions. Advances in IT have led to improved data sets, both in terms of quantity and quality, providing new opportunities to better calibrate risk models, Li says. The principal unmet challenge now lies in the design of the risk and decision models that can fully exploit risk-relevant information.

Examples of traditional risk models failing to account for the actual complexity of risk are easy to find. Many models measure risk by calculating simple statistics from the data such as standard deviation. However, lower standard deviation does not necessarily point to less risk. In these models, real-life uncertainties are often poorly approximated by the “well-shaped” normal distribution (or “bell curve”), Li explains. The root problem is the mistaken assumption that uncertainties are “well-structured” when in reality they are not. Li’s research focuses on developing methods that take a broader perspective in modeling uncertainties and hence are better able to project risk more accurately. “Instead of using a single model, one of our strategies is to consider calibrating multiple models simultaneously using large datasets,” Li says. “That will be far more effective in capturing uncertainty in risk measurement.”

Professor Li became assistant professor at the Telfer School after completing his Ph.D. in Operations Research from the Department of Mechanical and Industrial Engineering at the University of Toronto (2012) followed by postdoctoral work at HEC Montreal (2013). He will be teaching and working with colleagues and students at the Telfer School in the area of Business Analytics and Information Systems and master’s students from interdisciplinary master’s programs such as the M.Sc. in Systems Science.

Li continues the work he began during his Ph.D. program, which looked at how data collected directly from users can be used to calibrate the uncertainty of risk measures. This research recognizes that decision makers from different sectors or industries can have different perspectives of risk, depending on the nature of the work undertaken. That represents an exciting development because over the long term, Li’s risk measure could potentially be customized to suit these various risk perspectives. The work will certainly help to bridge the gap between the theory and practice in risk measurement, Li says.

“By relying on models that provide only a very incomplete picture of uncertainty, managers get a false sense of security about their projections, particularly when they don’t recognize the limitations of their models,” he explains. This is a pressing problem for decision making in today’s complex, fast-changing environments. Risk management “is about finding better ways to manage and foresee your worse-case scenarios. Risk measures that are sufficiently robust, that can address multi-faced uncertainty, can put you on the correct path from the outset.”

Congratulations to the following professors and students honoured in a ceremony on February 13, 2014. These awards recognize faculty members who have received external research funding, distinctions and awards and authored high visibility publications over the past year, as well as graduate students who have obtained major scholarships, and internship grants.

Professors:

• Doug Angus
• Joanne Leck & Catherine Elliott
• Pavel Andreev
• Morad Benyoucef & Student Amir Afriasibi Rad
• Wojtek Michalowski
• Greg Richards
• Craig Kuziemsky
• Bijan Raahemi
• Umar Ruhi & Student Sabbir Ahmed
• Jonathan Patrick
• Kaouthar Lajili & Daniel Zéghal
• David Doloreux
• Gurprit Kindra
• Shujun Ding
• Lamia Chourou
• Dan Lane
• Walid Ben Amar
• Samia Chreim
• Magda Donia

M.Sc. Students:

• Ioana Arbone
• Xiaoxi Chang
• Maria El Chababi
• Daniel Ironmonger
• Michael Lever
• Emily Rowland
• Shannon Tracey

A new study by the CGA-Canada Accounting and Governance Research Centre (CGA-AGRC) at the Telfer School of Management reveals that individual characteristics of corporate boards are more effective than commonly used governance indices in explaining the costs of financing of Canadian firms. The results suggest that governance indices are less reliable due to their low ability to reflect the quality of a board of directors.

Use of corporate governance indices has increased in recent years, denoting a shift away from evaluating individual governance mechanisms, such as specific characteristics of a company’s board of directors, says Professor Daniel Zéghal, FCGA, co-author of the study.

“Our analysis adds to the growing body of research that questions the superiority of governance indices in providing a reliable picture of corporate governance quality,” Zéghal says. “If investors had to choose between a governance index and one governance dimension to predict a firm’s performance based on the quality of its governance, our results show they may be better off analyzing the quality and effectiveness of the board of directors through an evaluation of its characteristics.”

The research findings reinforce the notion that an efficient board of directors helps reduce firm’s financing costs by limiting its exposure to market risk. This stems from better control of managerial opportunism, and improved transparency and reliability of financial statements.

The study examined the ability of two governance indices, the GM Index developed by the Globe & Mail and the Board Shareholder Confidence (BSC) Index developed by academics, and 11 individual board traits (such as size, representation, tenure, independence) to explain differences in firms’ financing costs. The analysis is based on a sample of 192 Canadian firms listed on the Toronto Stock Exchange and S&P/TSX composite market index.

The study, “A Comparative Analysis of the Effect of Board Characteristics and Governance Indices on Companies’ Cost of Financing: The Canadian Evidence” is authored by Raef Gouiaa, Université du Québec en Outaouais and Daniel Zéghal, University of Ottawa. It was recently published in Corporate Ownership & Control, Volume 11, Issue 1, 2013, pp. 136-150.

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