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Record W2047276148 · doi:10.1108/02651330610678994

Employing information communication technologies to enhance qualitative international marketing enquiry

2006· article· en· W2047276148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Marketing Review · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMarketingOriginalityInformation and Communications TechnologyRespondentSample (material)Qualitative researchQualitative propertyBusinessPublic relationsSociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Purpose Extant international marketing enquiry has been widely criticised for lacking scope and ambition. Typically, empirical investigations have involved single market studies employing quantitative methods and survey techniques. Consequently, researchers have been challenged to embrace greater methodological pluralism and broaden their geographical perspectives. This contribution posits that new information communication technologies (ICT), particularly the internet, can significantly improve the robustness of qualitative and mixed‐method international marketing research. Design/methodology/approach The paper describes and evaluates the application of ICT in a recent cross‐national enquiry into rapidly internationalising small firms. Online sources were used to gather information on 218 internationalising small firms, in Australia, Canada, Ireland and New Zealand. An e‐mail instrument was then administered to verify this data and address information gaps, resulting in 143 usable responses, evenly distributed across locations. Key emerging themes were identified and a representative sub‐sample of 53 firms was selected for further in‐depth investigation via face‐to‐face interviews with CEOs. Findings The authors contend that such technologies can help to refine sample identification and selection procedures, improve response rates and encourage greater respondent “buy‐in” to depth interviews. They also lead to much more targeted lines of enquiry during depth interviews by identifying key research themes and issues, thus enhancing the depth and richness of the insights obtained. Originality/value The paper concludes that novel ICT‐enabled research approaches as described herein are particularly effective because, compared to conventional survey methods, they are more user friendly and better received by subjects.

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.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.017
GPT teacher head0.323
Teacher spread0.306 · 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