The influence of marital status on customer-centric measures in the context of a ski resort using the importance-performance map analysis (IPMA) framework
Bibliographic record
Abstract
Purpose This study assesses the impact of marital status towards customer-centric measures in a Canadian ski resort using the importance-performance map analysis (IPMA) as the analytical framework. For the purpose of this paper, the three groups that were assessed included singles, partnership without children and partnership with children as marital status indicators. From the theoretical and especially managerial point of view, knowing the importance and the performance of the relevant ski resort-related customer-centric perceptions is of key importance. Design/methodology/approach A survey was completed to assess customer-centric measures including customer satisfaction, repurchase intent, value for money, willingness to recommend, overall performance in terms of meeting expectations, relationship quality and skiing service quality. An IPMA was conducted with partial least square-structural equation modelling (PLS-SEM) to assess the importance-performance perceptions of the three marital status groups. Findings The results indicated that for five of the seven customer-centric measures, there were significant differences between the marital status groups. Overall, singles appeared to have the lowest values in customer-centric measures, whereas respondents living in partnership with children had the highest. This was also the case with the value for money perceptions, although the cost for the ski resort visit was likely to be the highest for the respondents living in partnership with children. There were also differences between the marital status groups in terms of the importance-performance evaluations. Originality/value Results of this research have implications for ski resort management as the three marital status groups appear to perceive the customer-centric measures quite differently in the IPMA framework.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".