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Record W4394886368 · doi:10.5267/j.uscm.2024.3.009

The role of collaborative competitiveness marketing tourism towards sustainable competitive advantage in creative industries in the VUCA era

2024· article· en· W4394886368 on OpenAlexvenueno aff
Siti Aliyati Al bushairi, Raden Andi Sularso, Diana Sulianti K. Tobing, Bambang Irawan

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingCompetitive advantageBusinessTourismStratified samplingCraftFlexibility (engineering)Descriptive statisticsEconomicsManagement

Abstract

fetched live from OpenAlex

This study examines the influence of strategic flexibility, innovation culture, agility, ambidexterity, and open innovation on sustainable competitive advantage, with corporate innovation and collaborative marketing tourism competitiveness as mediating variables. Data was collected directly through structured interviews guided by questionnaires. The research population was 534 registered "craft" creative industry companies including pearls, "Sasak" ikat weaving, and pottery in West Nusa Tenggara Province, Indonesia with the analysis unit being managers or assistant managers. The sampling method used stratified proportional random sampling with a sample size of 240 respondents. Data analysis in this study used descriptive statistics and Covariance-based SEM (Amos software). The findings prove that the eleven hypotheses which stated that there was a direct influence of the variables studied were all confirmed. Strategic flexibility and a culture of innovation play a role in increasing company innovation. Strategic flexibility plays a role in increasing the collaborative competitiveness of marketing tourism. Agility, ambidexterity, and open innovation play a role in increasing sustainable competitive advantage. Corporate innovation and collaborative competitiveness marketing tourism play a role in increasing sustainable competitive advantage. These results are very important to fill the research gap regarding the factors supporting innovation and collaborative competitiveness marketing tourism, and sustainable competitive advantage in Indonesia.

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)0.008
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.272
Teacher spread0.265 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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