Chilean wine producer market orientation: comparing MKTOR versus MARKOR
Bibliographic record
Abstract
Purpose The purpose of this paper is to assess the degree of market orientation of a sample of Chilean wine producers; to compare two different instruments for assessing market orientation in this context; and to comment on the possible cultural sensitivities of these two measurement instruments developed from a North American context but applied in culturally dissimilar contexts. Design/methodology/approach In total, 69 CEO and Marketing Managers, representing approximately one quarter of the total number of wineries in Chile, completed a face‐to‐face survey questionnaire that utilized both the Narver and Slater MKTOR and the Kohli and Jaworski MARKOR market orientation scales. SmartPLS was used to carry out the measurement and structural analysis. Findings Results reveal that more than half of surveyed Chilean wine producers are market oriented, with 65 per cent congruence between the two scales. Cluster analysis also reveals three distinct segments and sets of characteristics that distinguish market oriented from non‐market oriented wineries. MKTOR and MARKOR scales show similar level of predictive power when using subjective or perceptual measures of performance as dependent variables. However, the MARKOR scale is found to be better in explaining changes in the dependent variable when the latter is measured by actual sales and gross margins (objective performance). National cultural dimensions (power distance and uncertainty avoidance) have an impact within organizations in the implementation of a market‐oriented strategy in a consistent and coordinated manner. Research limitations/implications The MARKOR scale appears to have superior predictive validity and to be more practical for measuring market orientation since it explains the change in dependent variables to greater degree when performance is measured with objective as opposed to the perceptual measures. Practical implications Chilean winery managers should devote significant attention to market sensing activities and competitive intelligence gathering. The competitive and national cultural environment plays an important role in moderating the relationship between market orientation and a firm's business performance. They may also wish to consider becoming involved in various trade organisations, as well as collaborative partnerships with academic institutions, to enhance their competitive intelligence and technological competences. Originality/value This paper is the first to illustrate the market orientation of Chilean wine producers, and one of only a few to discuss the impact of national cultural values on market orientation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".