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Record W2886887435 · doi:10.1108/imr-04-2016-0085

Deal proneness and national culture: evidence from the USA, Thailand and Kenya

2018· article· en· W2886887435 on OpenAlexaff
Dheeraj Sharma, Satyendra Singh

Bibliographic record

VenueInternational Marketing Review · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsHofstede's cultural dimensions theoryUncertainty avoidanceIndividualismModerationFemininityCollectivismMasculinityIndex (typography)Social psychologyMarketingSociologyPsychologyBusinessEconomicsComputer scienceGender studies

Abstract

fetched live from OpenAlex

Purpose Culture is one of the critical variables in explaining consumer behavior and consumer response to external stimuli. The purpose of this paper is to delineate the relationship between deal proneness and culture. Specifically, this paper examines the relationship between Hofstede’s cultural dimensions, namely, power distance, individualism/collectivism, masculinity/femininity and uncertainty avoidance, and deal proneness. Additionally, the role of store image as a moderator between culture and deal proneness is explored. Finally, the paper offers prescriptive and descriptive insights for marketers to consider cultural perspectives when promoting products internationally. A clear understanding of cultural influences on deal proneness will allow marketers to target specific customer segments more accurately. Design/methodology/approach The authors collected data from consumers in shopping malls in USA, Thailand, and Kenya. The authors analyzed the data using structural equation modeling. Findings The authors found that societies with a high femininity index are more likely to respond to deals than masculine societies. An inverse relationship between the Power Distance Index (PDI) and deal proneness may exist, suggesting that societies with a high PDI may be less deal prone. The authors found that individualism index is positively related to deal proneness, and thus societies with a low individualism index should be more deal prone. Finally, individuals in high uncertainty avoidance countries are expected to exhibit low deal prone tendencies. Research limitations/implications The study utilized a sample from cities. Consequently, future studies may attempt to validate the relationship posited in this study by utilizing non-urban data. Additionally, the authors look at stores in a mall. Thus, there is a possibility of interaction between mall image and store image. It may be useful to validate the findings of this study by using data from stand alone stores and also examine the interaction effect of mall image and store image on the deal proneness in a given culture. Practical implications This study suggests that appropriate store selection for offering deals can possibly augment the effectiveness of deal-based promotions. Specifically, choice of store can alter the context, and thus the perception of the value proposition could increase, which in turn is likely to increase the acceptance of deal-based promotion. Originality/value Although several researchers have also examined differences in consumer behavior across cultures yet it appears that there is no direct study that examines the effects of cultural differences on deal proneness using data from three countries (USA, Thailand, and Kenya) which are diverse on all dimensions of national culture. This paper examines the influence of national culture on individual’s propensity to exhibit deal proneness. Furthermore, the paper examines the role of store image on the relationship between national culture and deal proneness.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.312
Teacher spread0.257 · 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.

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

Citations11
Published2018
Admission routes1
Has abstractyes

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