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Record W1897987819 · doi:10.1108/ejm-03-2013-0156

On ‘being there’

2015· article· en· W1897987819 on OpenAlexaff
François A. Carrillat, Alain d’Astous, François Bellavance, François Eid

Bibliographic record

VenueEuropean Journal of Marketing · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsArousalPsychologyRecallCongruence (geometry)Stimulus (psychology)AdvertisingAmateurIce hockeySocial psychologyEvent (particle physics)Applied psychologyCognitive psychologyBusinessPolitical science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to assess the effectiveness of field sponsorship through sponsor recall and recognition across two environments that differ on the degree of felt presence they trigger among viewers: on-site and television. A series of research hypotheses concerning the interaction effects of viewing environment, event – sponsor congruence and arousal intensity were developed. Design/methodology/approach – To test the effect of the viewing environment, a field experiment was conducted where 44 ice hockey fans attended a professional ice hockey game in the local team’s arena, whereas 44 others saw the same game, at the same time, on television. The participants were randomly assigned to one of the two game viewing conditions. Findings – A higher level of arousal was detrimental to sponsor identification in a manner consistent with the intensity of the processing principle according to which arousal polarizes attention resources on the arousing stimulus (the event) while diverting resources away from the peripheral stimuli (the sponsors). In addition, because the event congruent sponsors are more superficially processed in comparison with the incongruent ones, this negative impact was more pronounced in the former group. This was qualified by a three-way interaction with the type of environment; the on-site, direct, audience was less affected by the processing intensity principle and exhibited better recall and recognition than the television audience as arousal and congruency increased, whereas, at lower levels of arousal, higher event – sponsor congruence hampered on-site sponsor identification in comparison with television. Research limitations/implications – The findings were obtained in the context of a single sports event; additional studies need to be conducted using different sports. In addition, the comparison of on-site audience with other types of media audiences (e.g. on-line broadcasting) is warranted. Practical implications – Arousal intensity results from the game’s drama, which is a function of game importance and game outcome uncertainty. Hence, except for low-stakes games (e.g. pre-season matches, exhibitions), initiatives that promote a leveled playing field such as salary cap, financial fair play and open leagues are likely to jeopardize sponsor identification, particularly for congruent sponsors. With respect to the impact of the viewing environment, congruent sponsors should reap superior benefits from the television audience when the stakes are low. However, when the stakes are high, their benefits will accrue to a greater extent from on-site spectators. Originality/value – This is the first study to offer a rigorous comparison of sponsorship’s impact on direct (on-site) versus indirect (television) audiences through a field experiment. This is also the first research to provide a framework based on the processing intensity principle that encompasses predictions related to arousal and its interaction with event – sponsor congruence and the viewing environment. Within this perspective, the degree of sponsor integration in the viewing environment is instrumental in predicting sponsorship outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0050.006
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0340.011

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.

Opus teacher head0.044
GPT teacher head0.239
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2015
Admission routes1
Has abstractyes

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