The carbon disclosure project, an evolution in international environmental corporate governance : motivations and determinants of market response to voluntary disclosures

This paper examines the factors associated with Canadian firms voluntarily disclosing climate change information through the Carbon Disclosure Project. Five hypotheses are presented to explain the factors influencing management's decision to disclose this information. These hypotheses include a response to shareholder activism, domestic institutional investor shareholder activism, signalling, litigation risk, and low cost publicity. Both binary logistic regressions as well as a cross-sectional analysis of the equity market's response to the environmental disclosures being made were used to test these hypotheses. Support was found for shareholder activism, low cost publicity, and litigation risk. However, the equity market's response was not found to be statistically significant.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Major Sport Event Operational Planning Issues and Strategies: A Multi-Case Delphi Study

This study examined the operational planning, implementation and execution issues of major sport events, as well as the mitigation and management strategies used to address these issues, with the aim of determining best practices in sport event operational planning. The three Research Questions were: 1) What can previous major sport events provide to guide the operational management of future events? 2) What are the operational issues that arise in the planning and execution of a major sport event, how are they mitigated and what are the strategies used to deal with these issues? 3) What are the best practices for sport event operational planning and how can these practices aid future events? Data collection involved a modified Delphi technique that consisted of one round of in-depth interviews followed by two rounds of questionnaires. Both data collection and analysis were guided by an adaptation of the work of Parent, Rouillard & Leopkey (2011) with a focus on previously established issue and strategy categories. The results provided a list of Top 26 Prominent Issues and Top 17 Prominent Strategies with additional issue-strategy links that can be used to aid event managers producing future major sport events. The following issue categories emerged as having had the highest impact on previous major sport events that participants had managed: timing, funding and knowledge management. In addition, participants used strategies from the following categories most frequently: other, formalized agreements and communication.