Evaluating the Effects of Service Quality, Customer Satisfaction, and Service Value on Behavioral Intentions with Life Insurance Customers in India
Bibliographic record
Abstract
The present study aims to empirically test and evaluate the direct and indirect effects of service encounter constructs of service quality, customer satisfaction and service value on loyalty related behavioral intentions of customers in Indian Life services in India to determine the best fitting model. Most studies based on comprehensive models of service constructs relationships have not considered alternative competing models. The theoretical background and the empirical support for these issues derive mostly from prior studies in the developed markets of the U.S., UK and Canada. Further, the study aims to contribute to resolution of the variance in structure and dimensionality of service quality (dimensionality) in literature by developing and validating a second order model of service quality which integrates the two dominant perspectives ie the Nordic and the American approach. Design/methodology/approach: A second order scale of service quality was developed and validated by integrating the American and Nordic approach to Service Quality using exploratory factor analysis and confirmatory factor analysis. The constructs of Customer satisfaction, service value and Behavioural intentions were validated using confirmatory factor analysis. Two competing models of effects of the three service encounter constructs on Behavioral Intentions were tested using structural equation modeling. The results show that Service quality is a second order construct consisting of the dimensions of Core service, Service Delivery, Sales Agent Quality, Tangibles and Empathy. The process dimensions (sales Agent Quality and Service delivery) are most important in overall service quality perceptions. The effect of service quality on positive behavioural intentions is both direct and indirect with the moderating effect of service value and customer satisfaction being significant. The study contributes to research by developing and validating a hierarchical model of service quality and testing two competing models of direct and indirect effects of service quality on behavioral intentions so that there is better understanding of the simultaneous and composite interactions and effects of the three service encounter constructs. The results would provide practitioners with a valid measure of service quality in life insurance services and would enable them to devise marketing strategies which enhance customer loyalty related behavioral intentions. The study addresses the gap related to wide divergence in dimensionality and structure of service quality and contributes to the debate on whether the effect of service quality on behavioral intentions is only indirect or both direct and indirect.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".