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Record W3138224606 · doi:10.1108/ijebr-12-2020-0871

The impact of the interaction between an entrepreneurial marketing orientation and coopetition on business performance

2021· article· en· W3138224606 on OpenAlexaff
James M. Crick, Masoud Karami, Dave Crick

Bibliographic record

VenueInternational Journal of Entrepreneurial Behaviour & Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoopetitionMarketingCompetitor analysisBusinessMarket orientationStructural equation modelingEntrepreneurial orientationMarket intelligenceEntrepreneurshipEconomicsMicroeconomicsGame theory

Abstract

fetched live from OpenAlex

Purpose Certain small businesses do not possess the assets needed to implement a performance-enhancing entrepreneurial marketing orientation (opportunity-driven behaviours focussed on creating value for customers). Although some entrepreneurs cooperate with their competitors (coopetition) to achieve their day-to-day and long-term goals, it is unclear whether these partnerships are advantageous in this capacity. Thus, grounded in the resource-based view, the purpose of this investigation is to examine whether coopetition positively moderates the relationship between an entrepreneurial marketing orientation and financial performance. Design/methodology/approach Survey responses were obtained from 184 small tourism and hospitality organisations in New Zealand. Following a series of robustness checks, covariance-based structural equation modelling was used to test the elements of the conceptual model. Findings Unique insights illustrate an entrepreneurial marketing orientation yielding a negative and significant link with financial performance. Nevertheless, this result was potentially related to the entrepreneurial marketing-oriented opportunities that owner-managers pursued within the context of their sector; in particular, situations when employing an individualistic business model constrained certain decision-makers' ability to pursue “growth-oriented” objectives. However, coopetition produced a positive and significant moderating effect, enabling owner-managers to pursue opportunities via collaborative business models facilitating mutually beneficial performance outcomes. Practical implications Owner-managers of under-resourced small firms should be careful when implementing entrepreneurial marketing strategies utilising an individualistic business model. For example, they might pursue opportunities that are not viable and/or become over-loaded with market intelligence that they cannot handle. By collaborating with competitors, owner-managers can learn improved ways to operate within their industries, alongside being equipped with new resources and capabilities. In doing so, coopetition can help overcome some of the potential performance-limiting issues owner-managers face by being under-resourced, namely, via employing a collaborative business model. Originality/value This current study contributes to the extant literature by evaluating the complexities of entrepreneurial marketing practices. That is, although earlier research has focussed on the performance-driving outcomes of an entrepreneurial marketing orientation, prior studies typically overlook certain moderating factors that could influence this association. By examining the interaction between an entrepreneurial marketing orientation and coopetition on financial performance, new evidence has emerged on how owner-managers of small firms can utilise interfirm collaboration to succeed within their markets, as opposed to struggling to cope with the challenges of an individualistic business model. Specifically, an entrepreneurial marketing orientation is likely to enhance financial performance when under-resourced companies effectively collaborate with their competitors.

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)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.364
Teacher spread0.309 · 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 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

Citations74
Published2021
Admission routes1
Has abstractyes

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