The impact of customer engagement and service leadership on the local food value chain of hotels
Bibliographic record
Abstract
Purpose This study was undertaken to investigate whether a service-oriented approach to the local food supply chain contributes to strengthened linkages between accommodation and agricultural sectors, thereby creating value for users. Design/methodology/approach The qualitative study examined levels of customer/consumer engagement (CE) within theoretical constructs of the service-oriented framework and value co-creation, intangible resources and valued relationship within the value chain and food service. Also, two explanatory case studies were conducted on two accommodation properties. Findings Empirical findings indicated that the hospitality business which emphasized a consumer-centric service approach throughout the value chain – both forward (toward the consumer) and backward (toward the supplier) – had greater success in engaging customers. It also highlighted the importance of service leadership. Practical implications The research study provides practical guidance to members of the local food supply chains in the hospitality sector and strategies that can be used to optimize all opportunities to ensure consumers’ needs are met and exceeded as a precursor for repeat business. Social implications The intricacies of services when well understood and applied in hospitality businesses are likely to generate favorable outcomes such as poverty alleviation. Developing destinations invest significantly in tourism as a channel for economic development. Unfortunately, gains are forfeited since limited attention is given to strategically advancing consumer-centric service at the micro level in tourism businesses to the extent that these benefit other stakeholders. Fostering CE and developing a culture of service leadership appear to be critical success factors. Originality/value This study is unique and extremely relevant to island destinations as it provides insights using a service management framework in the Caribbean context on how destinations may enhance hospitality business through improved service in island states.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".