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

Sengupta, Ushnish and Henry M. Kim (2021). "Meeting Changing Customer Requirements in Food and Agriculture Through the Application of Blockchain Technology", Frontiers in Blockchain.

Open Access Download

Keywords
Abstract This research summarizes the implementation of blockchain technology in the food and agriculture industry in Canada. Our research indicates that blockchain solutions are an existing and proven set of technologies. We also describe how blockchain based supply chain traceability information has many more benefits than its current use for food safety and product recalls. We recommend that costs for development of blockchain based solutions should also be distributed across stakeholders, and apportioned by the relevant industry associations. Our research indicates that adoption of blockchain technology in agriculture will achieve critical mass earlier when the industry applies a consortium approach, in a regulatory environment that is supported by government. This report also makes recommendations relevant to the integration of blockchain for end consumers of food.

Noseworthy, T. and Taylor, N. (2021). "Your Fries are Less Fattening than Mine: How Food Sharing Biases Fattening Judgments Without Biasing Caloric Estimates", Journal of Consumer Psychology.

Open Access Download

Keywords
Abstract Food sharing has become quite popular over the last decade, with companies offering food options specifically designed to be shared. As the popularity has grown, so too has concerns over the potential negative impact on consumer health. Despite companies’ explicit claims to the contrary, critics maintain that food sharing may be encouraging excessive caloric intake. The current article provides the first systematic exploration of why this may be happening. Three main and two supplementary studies suggest that food sharing reduces perceived ownership, which, in turn, leads people to mentally decouple calories from their consequence. Thus, sharing can reduce the perceived fattening potential of a consumption episode without biasing caloric estimates. This phenomenon persists even when explicit caloric information is provided, and it applies to both healthy and unhealthy foods. Importantly, we establish a relevant downstream consequence by illustrating that people tend to subsequently select calorie‐dense foods after underestimating the fattening potential of a shared consumption episode. A roadmap for future research and practical implications are discussed.