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

Hossein Arshadi, Henry M. Kim (2025). "When Incentives Feel Different: A Prospect-Theoretic Approach to Ethereum’s Incentive Mechanism", Electronics, 14(24), 4916.

Open Access Download

Keywords
Abstract This study asks whether Ethereum’s proof-of-stake (PoS) incentives not only make economic sense on paper but also feel attractive to real validators who may be loss-averse and sensitive to risk. We take a canonical Eth2 slot-level model of rewards, penalties, costs, and proposer-conditional maximal extractable value (MEV) and overlay a prospect-theoretic valuation that captures reference dependence, loss aversion, diminishing sensitivity, and probability weighting. This Prospect-Theoretic Incentive Mechanism (PT-IM) separates the “money edge” (expected accounting return) from the “felt edge” (behavioral value) by mapping monetary outcomes through a prospect value function and comparing the two across parameter ranges. The mechanism is parametric and modular, allowing different MEV, cost, and penalty profiles to plug in without altering the base PoS model. Using stylized numerical examples, we identify regions where cooperation that pays in expectation can remain unattractive under plausible loss-averse preferences, especially when penalties are salient or MEV is volatile. We discuss how these distortions may affect validator participation, economic security, and the tuning of rewards and penalties in Ethereum’s PoS. Integrating behavioral valuation into crypto-economic design thus provides a practical diagnostic for adjusting protocol parameters when economics and perception diverge.

Kim, Henry M. and Marek Laskowski (2018). "Towards an Ontology-Driven Blockchain Design for Supply Chain Provenance", Intelligent Systems in Accounting, Finance, and Management, 25(1), 18-27.

Open Access Download

Keywords
Abstract An interesting research problem in our age of Big Data is that of determining provenance. Granular evaluation of provenance of physical goods--e.g. tracking ingredients of a pharmaceutical or demonstrating authenticity of luxury goods--has often not been possible with today's items that are produced and transported in complex, inter-organizational, often internationally-spanning supply chains. Recent adoption of Internet of Things and Blockchain technologies give promise at better supply chain provenance. We are particularly interested in the blockchain as many favoured use cases of blockchain are for provenance tracking. We are also interested in applying ontologies as there has been some work done on knowledge provenance, traceability, and food provenance using ontologies. In this paper, we make a case for why ontologies can contribute to blockchain design. To support this case, we analyze a traceability ontology and translate some of its representations to smart contracts that execute a provenance trace and enforce traceability constraints on the Ethereum blockchain platform.