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

Simon J. Blanchard, Theodore J. Noseworthy, Ethan Pancer, and Maxwell Poole (2023). "Extraction of Visual Information to Predict Crowdfunding Success", Production and Operations Management, 32(12), 4172-4189.

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Keywords
Abstract Researchers have increasingly turned to crowdfunding platforms to gain insights into entrepreneurial activity and dynamics. While previous studies have explored various factors influencing crowdfunding success, such as technology, communication, and marketing strategies, the role of visual elements that can be automatically extracted from images has received less attention. This is surprising, considering that crowdfunding platforms emphasize the importance of attention‐grabbing and high‐resolution images, and previous research has shown that image characteristics can significantly impact product evaluations. Indeed, a comprehensive review of empirical articles (n = 202) utilized Kickstarter data, focusing on the incorporation of visual information in their analyses. Our findings reveal that only 29.70% controlled for the number of images, and less than 12% considered any image details. In this manuscript, we contribute to the existing literature by emphasizing the significance of visual characteristics as essential variables in empirical investigations of crowdfunding success. We review the literature on image processing and its relevance to the business domain, highlighting two types of visual variables: visual counts (number of pictures and number of videos) and image details. Building upon previous work that discussed the role of color, composition, and figure–ground relationships, we introduce visual scene elements that have not yet been explored in crowdfunding, including the number of faces, the number of concepts depicted, and the ease of identifying those concepts. To demonstrate the predictive value of visual counts and image details, we analyze Kickstarter data using flexible machine learning models (Lasso, Ridge, Bayesian additive regression trees, and eXtreme Gradient Boosting). Our results highlight that visual count features are two of the top three predictors of success and highlight the ease at which researchers can incorporate some information about visual information. Our results also show that simple image detail features such as color matter a lot, and our proposed measures of visual scene elements can also be useful. By supplementing our article with R and Python codes that help authors extract image details (https://osf.io/ujnzp/), we hope to stimulate scholars in various disciplines to consider visual information data in their empirical research and enhance the impact of visual cues on crowdfunding success.

Keyhani, M., Deutsch, Y., Madhok, A. and M. Lévesque (2022). "Exploration-Exploitation and Acquisition Likelihood in New Ventures", Small Business Economics, 58(3), 1475-1496.

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Keywords
Abstract The market for acquisitions has been a blind spot in exploration-exploitation research in the new venture context. The introduction of the acquisition exit outcome as a performance dimension for new ventures, especially among high-tech ventures, shifts the traditional temporal logic of exploration-exploitation theory by introducing previously unacknowledged short-term benefits of exploration. We bring the acquisition outcome into the picture and investigate the relationship between the exploration-exploitation continuum and profitability, survival, and acquisition likelihood simultaneously. Using the Kauffman Firm Survey data, we provide evidence for a link between exploration and the likelihood of acquisition (defined as the business being sold to or merged with another business), although industry technology level poses a boundary condition such that the association is not observed in low- and medium-technology firms. An inverse U-shaped relationship that is monotone negative for most of the data range was found between exploration and the profitability of low- and medium-tech firms, and a negatively linear relationship was found for exploration and the profitability of high-tech firms. Our findings lend some support to the viability of “born to flip” strategies involving comparatively higher exploration levels in high-tech start-ups and sacrifice of short-term profitability.