THE ROLE OF CUSTOMER SATISFACTION MEDIATES THE INFLUENCE OF SERVICE INNOVATION AND PRODUCT QUALITY ON CUSTOMER LOYALTY IN AGRICULTURAL PRODUCTS: A STUDY ON CUSTOMERS AT PT. TANIHUB BALI
Bibliographic record
Abstract
E-Commerce is the use of the internet or technology to purchase goods, sell goods, send goods, or even exchange data online.Agricultural E-Commerce around the world is growing very rapidly.Developed countries such as the United States, Japan, Canada are currently also increasingly developing agricultural E-Commerce which is quite serious in the world.Customer loyalty is certainly important for E-Commerce like Tanihub to gain profits by expanding their business as well as supporting companies to obtain further funding.The purpose of this study was to test and explain the effect of customer satisfaction in mediating service innovation and product quality on customer loyalty in Tanihub Bali.This research is a quantitative associative research conducted in Badung Regency and Denpasar City.The data used consisted of 130 samples, collected by distributing questionnaires containing questions that had been tested for validity and reliability.The analysis technique uses the Structural Equation Model (SEM) with the Smart PLS3.3.3 analysis tool.According to the findings, service innovation and product quality had a favorable and considerable impact on consumer happiness and loyalty.Furthermore, in Tanihub Bali, customer satisfaction has a favorable and strong influence on customer loyalty, as well as the ability to partially mediate the relationship between service innovation and customer loyalty and partially mediate the relationship between product quality and customer loyalty.This study is expected to provide empirical data for future research and to contribute to the advancement of marketing management science, particularly in the areas of service innovation, product quality, customer satisfaction, and customer loyalty.Management benefits can be utilized as a marketing approach to build customer loyalty to Tanihub Bali.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".