REDWOOD CITY, Calif., Jan. 8, 2015 (GLOBE NEWSWIRE) -- The Wharton School of the University of Pennsylvania's Wharton Customer Analytics Initiative (WCAI) has announced a Research Opportunity and webinar on a new dataset from Equilar, the leading executive data solutions provider. WCAI's Research Opportunity program leverages a modified crowd-sourced approach to connect companies with academic researchers already working on problems of importance to their business. Together with WCAI, Equilar has outlined key business challenges and will provide a comprehensive dataset to research teams that submit the "best-fit" proposals.
The dataset includes information on the executive leadership and board membership of over 9,000 companies and more than 125,000 individuals. It also includes 13 years of leadership and board changes, as well as biographies of key individuals. Additionally, there are dozens of variables concerning company characteristics and various board perquisites. Extensive lists of self-identified peer companies are also available. Finally, details on executive compensation and equity plans, including changes over time, are part of this comprehensive dataset.
Equilar is open to proposals in any area using this data, but potential research could explore:
- Board composition or compensation as they might impact company performance
- Composition of boards over time, including forecasting board changes
- Executive compensation and what impact various vehicles, incentives, and distribution might have on long-term shareholder value
- Histories or activities of individual board members and contribution to board composition
- Optimal board composition for different stages of company lifecycle
- Existence or evolution of networks of boards and board members
- Comparison of equity plans and relationship of plans to shareholder value
- Peer identification analysis
To learn more about the data and business context, interested researchers can attend the live webinar on January 16, 2015 at 12 pm EST/ 9 am PST. During the webinar, details of the data will be described and executives from the project sponsor will be available for questions. The webinar will also be archived for those who cannot attend live.
After the webinar, interested researchers can submit proposals by February 2nd to receive access to the data. Proposals will be evaluated based on their potential for academic contribution and the researcher's ability to address issues of strategic importance to the program sponsor.
Registration and additional information available at http://wcai.wharton.upenn.edu/event/equilar/
About the Wharton School
Founded in 1881 as the first collegiate business school, the Wharton School of the University of Pennsylvania is recognized globally for intellectual leadership and ongoing innovation across every major discipline of business education. With a broad global community and one of the most published business school faculties, Wharton creates ongoing economic and social value around the world. The School has 5,000 undergraduate, MBA, executive MBA, and doctoral students; more than 9,000 annual participants in executive education programs; and a powerful alumni network of more than 93,000 graduates.
| Contact: |
| Peter Winicov |
| Director, Media Relations |
| The Wharton School |
| 215-746-6471 |
| winicov@wharton.upenn.edu |
About Equilar (www.equilar.com)
Headquartered in Redwood City, Calif., Equilar is the leading provider of executive compensation data and governance tools for corporations, nonprofits, consulting firms, institutional investors, and the media. As the trusted data and executive solutions provider to 70% of the Fortune 500, Equilar helps companies accurately benchmark and track executive and board compensation, pay for performance results, and compensation practices. In addition, Equilar offers a leading business and event networking solution focused on serving executives and board members. Equilar's research is cited regularly by Bloomberg, The New York Times, The Wall Street Journal, and other leading media outlets.