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Record W2154490377 · doi:10.5539/ibr.v3n3p154

How will market orientation and external environmnet influence the performance among SMEs in the agri-food sector in Malaysia?

2010· article· en· W2154490377 on OpenAlexvenueno aff
Norzalita Abd Aziz, Norjaya Mohd Yasin

Bibliographic record

VenueInternational Business Research · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsMarket orientationBusinessMarketingLinkage (software)Industrial organizationOrientation (vector space)Customer orientation

Abstract

fetched live from OpenAlex

Abstract Many researchers have explored the relationship between market orientation and firm performance in manufacturing and services industries but such studies in agri-food SMEs are scarce. Previous research conducted has conceptually and empirically supported the notion that market orientation independently or collectively have positive correlations with the business performance of organization (such as Narver and Slater, 1990; Jaworski and Kohli, 1993; Lee and Peterson, 2000). The aim of this paper is to examine the marketing practices and the marketing orientation-business performance relationship among SMEs in agri-food sector in Malaysia. This study also investigated the role of the external environment in the market orientation-performance linkage. From an analysis of a survey data of 102 agri- food organizations, three dimensions namely customer-competitor orientation, inter-functional coordination and information dissemination extracted from factor analysis result of market orientation. The study revealed that customer-competitor orientation and information dissemination were positively related to business performance. In terms of the role of external environment, two dimensions produced by factor analysis, market-technology turbulence and competitive intensity did not moderate the relationship between market orientation and business performance. Findings are discussed and implications are highlighted. Keywords: Market Orientation, External Environment, Business Performance

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.005
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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

Citations78
Published2010
Admission routes1
Has abstractyes

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