Sport Sponsorship as a Tool of Marketing Communication – A Case Study of Two Real Estate Companies
Bibliographic record
Abstract
Sponsorship, in general, is an important component of promotional mix devised by many companies. Companies are known to use sponsorship as a means to associate with a particular event as part of their marketing efforts. Sponsoring of sporting events has been in use since long in various parts of the world and has also found ready acceptance in India. Many companies, whether their products /services have some association with a sport or not, are using sport sponsorship. The purpose of this paper is, therefore, to make an attempt to better understand the use of sport sponsorship as a tool of marketing communication. To achieve this purpose, a simple instrument was designed with questions related to the sponsorship objectives, process of selecting the event, and evaluation of effectiveness of sport sponsorship. Review of literature was carried out to develop a conceptual framework presenting a foundation for data collection. Real Estate companies are prominent sponsors of sports in the country. A qualitative, case study methodology has been used, based on documents and interviews of two Real Estate companies. The study shows that sport sponsorship has varied objectives. However, some of the most commonly used objectives of sport sponsorship are the corporate related objectives like corporate image, entertainment for clients, and employee relations. The study further shows that companies select a specific sport sponsorship property on the basis of different criteria such as the interest of the top management and the concerned sport’s potential to convey the marketing message. Further, the results of the study show that companies do not carry out formal evaluation of the effectiveness of sport sponsorship.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".