Leveraging Olympic Sponsorship to Engage Employees: Evaluating Employee Engagement Tactics within the Canadian Tire Corporation
Bibliographic record
Abstract
TITLE: Leveraging Olympic Sponsorship to Engage Employees: Evaluating Employee Engagement Tactics within the Canadian Tire Corporation ABSTRACT: Employee engagement (EE) is an internal marketing concept that aids in developing emotional commitment and shared values between the employee and the organization (Farrely, Greyser, & Rogan, 2012). Using sport sponsorship, organizations can use sponsorship assets and a sports-inspired identity to improve EE and internal business performance. Although researchers have identified benefits and tactics (e.g., ticket incentive programs, meet and greets, merchandise programs) for engaging employees (e.g., Kuo & Shao, 2008; Papadimitriou, Dimitra, Apostolopoulou, Artemisia, & Theofanis, 2008), there is limited research evaluating the return on investment for these programs (Farrely et al., 2012; Macey, Schneider, Barbera, & Young, 2011). As part of its sponsorship of the Canadian Olympic Committee, the Canadian Tire Corporation (CTC) uses various tactics to engage employees via its sponsorship assets, such as: athlete appearances, Olympic viewing parties, and employee hosting trips to the Olympics. The purpose of this study is to evaluate the effectiveness of current Olympic-focused EE tactics used by the CTC. To accomplish this, a mixed methods approach involving a document analysis of past EE campaigns during the Sochi 2014 and Rio 2016 Olympic Games at CTC, a review of academic literature on EE evaluation practices, and semi-structured interviews with employees at CTC will be employed. Approximately two employees from each of the Internal Communications, Human Resources, Internal Events, and Sport Partnerships departments who are involved in EE planning and execution at the CTC Corporate Head Office will be interviewed to determine areas of improvement for the current EE tactics. These combined learnings and evaluations will aid in developing recommendations for future Olympic-focused engagement programs orchestrated by the CTC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".