Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.


Search Results

Zhang, L. Zhang, J. and Tan, J. (2017). "Network Structure, Partner Features and Performance: Evidence from Venture Capital Syndicates, forthcoming in Best Paper Proceeding", Academy of Management Annual Meeting.

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Abstract Although many research has been done to understand the consequence of network structure on performance at the firm level, we have limited knowledge regarding how network structures influence alliance performance and how they interplay with partner attributes in this process. Focusing on the venture capital (VC) syndicate networks, we argue and show evidence for the positive influences of internal network density and external network structural hole on the performance of the investee startups. Moreover, we investigate how the features of lead and non-lead VC firms interact with the two network structural variables. The findings suggest that a big syndicate team augments the benefits of cooperation and coordination from a dense internal network, but a lead VC firm with high network status strengthens the information benefits from a high level of external network structural holes. Our cross-level research offers important implications on partner selection in strategic alliance research and the roles of lead and non- lead VC firms in VC studies.

Narayanan, M., and M. Lévesque (2014). "Venture Capital Deals: Belief and Ownership", IEEE Transactions on Engineering Management, 61(4), 570-582.

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Abstract We use a principal-agent model to examine how venture capitalists can determine the ownership division when fund-seeking entrepreneurs possess private information on their disutility of effort. This situation is especially applicable to early-stage first-time entrepreneurs seeking funding, since no history exists on their potential performance. The venture capitalist must thus consider this private information by forming a belief on the entrepreneur's effort level toward the proposed investment opportunity. Formal modeling enables us to describe how the deal process unfolds and to build a simulation. We then identify a unique investor's belief and resulting ownership sharing that maximizes the return to the entrepreneur, one that maximizes the return to the venture capitalist, as well as one that maximizes the deal welfare. We also conjecture an ordering relationship between these critical beliefs and between their resulting ownership allocations. Furthermore, we identify conditions under which the venture capitalist should choose to revise the investment offer if rejected by the entrepreneur. This paper thus moves us closer to a comprehensive theory of venture investment decisions.

Cumming, D., Henriques, I. and Sadorsky, P. (2013). "‘Cleantech’ Venture Capital Around the World", International Review of Financial Analysis, 44, 86-97.

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Abstract Cleantech venture capital investment differs from the typical venture capital investment in that it tends to be very capital intensive and faces greater technology risks associated with the functioning of the technology, scalability and exit requirements than the typical venture capital investment. Moreover, unlike the typical venture capital investment, the benefits arising from cleantech cannot be totally captured by the venture capitalist as many of its benefits accrue to society via reduced environmental degradation and better health and quality of life outcomes. The public goods literature posits that such externalities reduce investment in cleantech below the socially optimal level. We seek to determine whether there are countervailing factors which may incite greater cleantech investment. We argue that oil prices, increased stakeholder attention, as well as the impact of various formal and informal institutions are such factors. This paper provides a cross-country analysis of the determinants of cleantech venture capital investment with a unique worldwide dataset of 31 countries spanning 1996–2010. The data show consistent evidence of a pronounced role for oil prices in driving cleantech venture capital deals, which is more important than other economic, legal or institutional variables. Cleantech media coverage is likewise a statistically significant determinant of cleantech venture capital investment and as economically significant as other country level legal, governance, and cultural variables. Uncertainty avoidance has a negative impact on cleantech venture capital investment, as well as a moderating effect on other variables.