Pricing strategy and marketing distribution channels on customer satisfaction and purchasing decision for green products
Bibliographic record
Abstract
This paper aims to investigate the impact of pricing strategy and distribution channels on the decision-making process of customers when purchasing green products. The focus is on the satisfaction of customers who purchase these products. The study is conducted on the population of all customers who purchase green products from small and medium-sized enterprises (SMEs). The sample size is determined using a formula that considers the number of variables or indicators. The study uses Partial Least Squares Structural Equation Modelling (PLS-SEM), which is a method used to test variants-based structural equation models with the support of SmartPLS software. The results show that all seven hypotheses are supported, indicating that pricing strategy and distribution channels play a critical role in customer satisfaction and decision-making processes when purchasing green products. The results have implications for SMEs that sell green products as they need to focus on their pricing strategies and distribution channels to increase customer satisfaction and decision-making. This study provides essential insights into the impact of pricing strategy and distribution channels on customer satisfaction and decision-making when purchasing green products. The findings can guide SMEs in developing effective marketing strategies to persuade more customers to purchase green products and contribute to environmental sustainability.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".