Online relationship quality: scale development and initial testing
Bibliographic record
Abstract
Purpose – The purpose of this paper is to propose a reliable and valid integrative scale for online relationship quality based on both the relationship marketing and electronic commerce literature. Design/methodology/approach – The scale was developed using the approach put forward by Churchill (1979). The scale development and validation process includes a qualitative exploratory phase, three pre-tests and a final study using an online questionnaire (476 members of a consumer panel). Findings – The findings support a third-order integrative model of online relationship quality composed of three dimensions (trust, commitment and satisfaction). The final scale is composed of 21 items. Research limitations/implications – The study shows a lack of discrimination between satisfaction and trust, which other studies have also found. As the scale is validated in only one sector, online banking, it should be tested and replicated in other contexts (e.g. insurance). Practical implications – An instrument for assessing the quality of online relationships between banks and consumers is important for marketing professionals who want to determine their relational positioning and focus on those dimensions that promote long-term online relationships. The scale developed here can be used to assess customers’ perceptions of the quality of the relationship with an online financial institution, to segment those customers more effectively, and to improve targeting of marketing strategies and activities. Originality/value – This study contributes to the enrichment of the body of theory and provides researchers with a tool for the further investigation of the quality of online relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".