Impact of E-marketing Capabilities and E-marketing Orientation on Sustainable Firm Performance of SME in KSA Through E-relationship Management
Bibliographic record
Abstract
This study aims to investigate the impact of e-marketing orientation and e-marketing capabilities on sustainable business performance through e-customer relationship management. Employing a positivistic and deductive approach with an experimental technique, this research utilizes a cross-sectional design, collecting 152 responses via a Google Docs questionnaire. Smart PLS3 analysis reveals that sustainable business performance significantly hinges on e-marketing capabilities and orientation, with e-customer relationship management acting as a mediator. Notably, this study underscores strong interrelationships among all variables and highlights noteworthy positive influence of social media marketing on SME performance in Kingdom of Saudi Arabia. While this research acknowledge need for future studies to broaden the variable scope, its implications offer valuable assistance to SME top management for achieving long-term performance objectives. The distinctive contribution of this study lies in its examination of sustainable SME performance in KSA through the lenses of e-marketing and e-relationship management, enriching the understanding of these factors in fostering enduring success.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".