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Record W1538464371

Cultural Differences in Television Celebrity Use in the United States and Lebanon

2009· article· en· W1538464371 on OpenAlexaboutno aff
Morris Kalliny, Abdul-Rahman Beydoun, Anshu Saran, Lance Gentry

Bibliographic record

VenueJournal of international business research · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsAdvertisingEntertainmentContext (archaeology)NikeQuarter (Canadian coin)IndividualismPoliticsPolitical scienceBusinessLawHistory
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT Jagdish and Kamakura (1995) argued that celebrity endorsement has become a prevalent form of advertising in United States. Approximately 20% of all television commercials feature a famous person, and approximately 10% of dollars spent on television advertising are used in celebrity endorsement advertisements (Advertising Age 1987; Sherman 1985). The purpose of this study is to compare use of celebrity endorsement between United Sates and Lebanon in terms of two fundamental cultural dimensions: 1) low versus high context, and 2) individualism versus collectivism. This study investigates differences and similarities regarding celebrity characteristics in U.S. and Lebanon. INTRODUCTION Jagdish and Kamakura (1995) argued that celebrity endorsement has become a prevalent form of advertising in United States. Approximately 20% of all television commercials feature a famous person, and approximately 10% of dollars spent on television advertising are used in celebrity endorsement advertisements (Advertising Age 1987; Sherman 1985). Schickel (1985) stated that American society is fascinated with celebrities and individuals from various fields such as, politics, sports, entertainment, business, fashion, and others are often elevated to celebrity status. Shimp (2000) estimated that around one-quarter of all commercials screened in United States include celebrity endorsers. Celebrities have been able to generate millions of dollars in endorsement deals to appear in advertisements. Erdogan (1999) postulated that companies invest large sums of money to align their brands and themselves with endorsers. For example, Nike signed a $100 million, five-year contract with Tiger Woods for his endorsements (Choi et al. 2005). There are several reasons for extensive use of celebrities in advertising. Research findings show that celebrities make advertisements believable (Kamins et al., 1989), enhance message recall (Friedman and Friedman 1979), aid in recognition of brand names (Petty, Cacioppo, and Schumann 1983), create a positive attitude towards brand (Kamins et al. 1989), and create a distinct personality for endorsed brand (McCracken 1989). Because is believed that celebrity endorsements are likely to generate a greater likelihood of customers choosing endorsed brand (Heath, McCarthy, and Mothersbaugh 1994; Kahle and Homer 1985), business are willing to pay high prices to obtain it. Choi, Lee and Kim (2005) argued that celebrity phenomenon is not limited to United Sates and appears to be universal. In spite of universality of this phenomenon, Choi et al. (2005. p. 85) state, No research to date has empirically examined assumption that celebrity endorsement strategy is used in a similar fashion from country to country, or that consumers around world respond to in a similar way. Most of celebrity research that has been conducted has been about United States. We believe that in order to develop a general understanding of such a universal phenomenon, research efforts must be broadened to cover more parts of world. The Arab world is one of regions historically ignored in advertising research. Abernethy and Franke (1996) found 40 out of 59 content analysis studies dealt with United States media and concluded, Much less is known about advertising information in other countries. For example, no study has examined advertising information in any African nation, any part of Middle East other than Saudi Arabia, or any of 'economies in transition' associated with former USSR (p. 15). Elbashier & Nicholls (1983, p. 68) stated that, it is perhaps somewhat surprising that academics have not gone further and attempted to examine impact of cultural differences in Arab countries on Marketing, as there is a considerable field of literature suggesting that several aspects of the marketing mix are culturally sensitive. …

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.137
GPT teacher head0.372
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations21
Published2009
Admission routes1
Has abstractyes

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