Mediating Effect of Product Innovation on Market Orientation and Marketing Performance of SME’S During the COVID-19 Pandemic in Indonesia
Bibliographic record
Abstract
The role of MSMEs is very large for Indonesia's economic growth, where the contribution of MSMEs to the gross domestic product (GDP) reaches 60.5% and to employment of 96.9% of the total national employment absorption. However, during the Covid-19 pandemic, the government imposed a semi-lockdown by limiting business operating hours, by limiting 50% of the capacity of arriving consumers and reducing operating hours to only 20.00 at night. This policy resulted in a decrease in product demand by 84.8%. However, the MSMEs coffee shop only had an impact of 16%. Based on this condition, researchers are interested in conducting research on MSMEs, especially coffee shops during a pandemic. The purpose of this study to analyze the Market Orientation effect of Product Innovation on Marketing Performance and to analyze the role of Product Innovation in mediating the influence of Market Orientation on Coffee Shop Marketing Performance in Medan City. The survey was conducted on 143 coffee shop entrepreneurs who still survived from the COVID-19 pandemic in the city of Medan. Data collection was carried out using a questionnaire with direct interview with the coffee shop owner. Data Analysis using the Partial Least Squares (PLS) analysis technique. The results indicate that market orientation has a positive and significant effect on product innovation at Coffee Shop in Medan. Market orientation has not significant effect on marketing performance at Coffee Shop in Medan City. Product innovation has a positive and significant effect on the marketing performance of the Coffee Shop in Medan City, and there is a role between product innovation in mediating the effect of market orientation on marketing performance at the Coffee Shop in Medan City. Coffee shop should establish mechanisms to obtain information about customer needs and expectations and to disseminate and effectively use this information among business functions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 source (direct Gemma or distilled Codex), 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".