Turizm Lojistiğinde Havalimanı-Otel Operasyonları: Maliyet-Kalite Ödünleşimi

Öz

Bu çalışma, turizm sektöründe en önemli hizmet unsurlarından biri olan havalimanı-otel lojistik operasyonlarının yönetimindeki temel zorlukları incelemektedir. Çalışma, dengeli hizmet sunarken operasyonel maliyetlerin optimizasyonu hedefini göz önünde bulundurarak, bu iki hedef arasındaki optimum dengenin nasıl sağlanacağına dair analizler sunmaktadır. Araştırma, biri maliyet odaklı, diğeri dengeli hizmet odaklı olmak üzere iki farklı operasyonel stratejinin karşılaştırmalı analizini içermektedir. Türkiye'nin önde gelen turizm destinasyonlarından birinde gerçekleştirilen bu ampirik çalışma, dengeli hizmet stratejisinin işletme maliyetlerini yüzde 2,2 oranında artırırken, hizmet seviyesini yüzde 28,5 oranında iyileştirdiğini göstermektedir. Bu ödünleşim analizi, turizm işletmelerinin operasyonel karar süreçlerinde maliyet ve hizmet kalitesi arasında optimum dengeyi nasıl kurabileceklerine dair önemli çıkarımlar sunmaktadır.

Anahtar Kelimeler

• Operasyonel Ödünleşim
• Turizm Lojistiği
• Dengeli Operasyon Tasarımı
• Maliyet-Kalite İlişkisi
• Araç Rotalama

Etik Beyan

Çalışmanın veri toplanmasında ve araştırma modelinin kurulmasında herhangi bir etik kurul iznine gerek yoktur.

Airport-Hotel Operations in Tourism Logistics: Cost-Quality Trade-Off

Öz

This study examines the fundamental challenges in managing airport-hotel logistics operations, one of the most critical service elements in the tourism sector. The study presents analyses on how to achieve the optimal balance between these two objectives, considering the goal of optimizing operational costs while providing balanced service. The research includes a comparative analysis of two different operational strategies: one focused on cost and the other on balanced service delivery. This empirical study, conducted in one of Turkey's leading tourism destinations, demonstrates that a balanced service strategy increases operational costs by 2.2 percent while improving service levels by 28.5 percent. This trade-off analysis provides significant insights into how tourism businesses can establish an optimal balance between costs and service quality in their operational decision-making processes.

Anahtar Kelimeler

• Operational Tradeoffs
• Tourism Logistics
• Balanced Operation Design
• Cost-Quality Relationship
• Vehicle Routing

Kaynakça

1. Aziz, H. A.; Ukkusuri, S. V. (2014), “Exploring the trade-off between greenhouse gas emissions and travel time in daily travel decisions: Route and departure time choices”, Transportation Research Part D: Transport and Environment, 32, 334-353.
2. Bhusiri, N., Qureshi, A. G., ve Taniguchi, E. (2014). The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem. Transportation Research Part E: Logistics and Transportation Review, 62, 1-22.
3. Casse, T., Razafintsalama, M. H., ve Milhøj, A. (2022). A trade-off between conservation, development, and tourism in the vicinity of the Andasibe-Mantadia National Park, Madagascar. SN Social Sciences, 2(2), 12.
4. Cen, X., Zhou, G., Ji, B., Yu, S. S., Zhang, Z., ve Fang, X. (2023). Modelling and heuristically solving three-dimensional loading constrained vehicle routing problem with cross-docking. Advanced Engineering Informatics, 57, 102029.
5. Coindreau, M. A., Gallay, O., ve Zufferey, N. (2021). Parcel delivery cost minimization with time window constraints using trucks and drones. Networks, 78(4), 400-420.
6. Cook, D., Saviolidis, N., Davíðsdóttir, B., Jóhannsdóttir, L., ve Ólafsson, S. (2019). Synergies and trade-offs in the sustainable development goals—the implications of the Icelandic tourism sector. Sustainability, 11(15), 4223.
7. Cordeau, J. F., Desaulniers, G., Desrosiers, J., Solomon, M. M., ve Soumis, F. (2007). VRP with time windows. In The vehicle routing problem (pp. 157-193). SIAM.
8. Darvish, M., Archetti, C., ve Coelho, L. C. (2019). Trade-offs between environmental and economic performance in production and inventory-routing problems. International Journal of Production Economics, 217, 269-280.

9. Gružauskas, V., Baskutis, S., ve Navickas, V. (2018). Minimizing the trade-off between sustainability and cost effective performance by using autonomous vehicles. Journal of Cleaner Production, 184, 709-717.
10. Hedgren, A., Genberg, D., ve Karakitsiou, A. (2024). Strategic evaluation of environmental trade-off solution in logistics: A multi criteria decision making approach. In Disruptive technologies and optimization towards industry 4.0 logistics (pp. 201-226). Springer International Publishing.
11. Huang, S. H., Huang, Y. H., Blazquez, C. A., ve Chen, C. Y. (2022). Solving the vehicle routing problem with drone for delivery services using an ant colony optimization algorithm. Advanced Engineering Informatics, 51, 101536.
12. Koo, B., Yu, J., ve Han, H. (2020). The role of loyalty programs in boosting hotel guest loyalty: Impact of switching barriers. International Journal of Hospitality Management, 84, 102328.
13. Küp, E. T., Cebeci, S., Bayram, B., Aydın, G., Bozkaya, B., ve Akhavan-Tabatabaei, R. (2024). An integrated framework for dynamic vehicle routing problems with pick-up and delivery time windows and shared fleet capacity planning. Symmetry, 16(4), 505.
14. Kyriakakis, N. A., Stamadianos, T., Marinaki, M., ve Marinakis, Y. (2022). The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries. Cleaner Logistics and Supply Chain, 4, 100041.
15. Li, Y., Chen, H., ve Prins, C. (2016). Adaptive large neighborhood search for the pickup and delivery problem with time windows, profits, and reserved requests. European Journal of Operational Research, 252(1), 27-38.
16. Lo Storto, C. (2016). The trade-off between cost efficiency and public service quality: A non-parametric frontier analysis of Italian major municipalities. Cities, 51, 52-63.
17. Martín, J. C., Román, C., ve Gonzaga, C. (2019). How different n-point Likert scales affect the measurement of satisfaction in academic conferences. International Journal for Quality Research, 13(2), 361-372.
18. Miranda, D. M., Branke, J., ve Conceição, S. V. (2018). Algorithms for the multi-objective vehicle routing problem with hard time windows and stochastic travel time and service time. Applied Soft Computing, 70, 66-79.
19. Nguyen, M. A., Dang, G. T. H., Hà, M. H., ve Pham, M. T. (2022). The min-cost parallel drone scheduling vehicle routing problem. European Journal of Operational Research, 299(3), 910-930.
20. Pitakaso, R., Srichok, T., Khonjun, S., Gonwirat, S., Nanthasamroeng, N., ve Boonmee, C. (2024). Multi-objective sustainability tourist trip design: An innovative approach for balancing tourists' preferences with key sustainability considerations. Journal of Cleaner Production, 449, 141486.
21. Ranabhat, C. L., ve Jakovljevic, M. (2023). Sustainable health care provision worldwide: is there a necessary trade-off between cost and quality? Sustainability, 15(2), 1372.
22. Shen, Z. J. M., ve Daskin, M. S. (2005). Trade-offs between customer service and cost in integrated supply chain design. Manufacturing and Service Operations Management, 7(3), 188-207.
23. Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2), 254-265.
24. Tarhini, A., Danach, K., ve Harfouche, A. (2022). Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers. Annals of Operations Research, 1-22.
25. Toth, P., ve Vigo, D. (2014). Vehicle routing: Problems, methods, and applications. Society for Industrial and Applied Mathematics.
26. UNWTO. (2023). International tourism highlights, 2022 edition. World Tourism Organization.
27. Wang, X., Golden, B., Wasil, E., ve Zhang, R. (2016). The min-max split delivery multi-depot vehicle routing problem with minimum service time requirement. Computers and Operations Research, 71, 110-126.
28. Wang, X., Li, X., ve Liu, Y. (2018). A multi-objective optimization model for electric vehicle routing problem with time windows. Transportation Research Part E: Logistics and Transportation Review, 119, 132-148.
29. Wu, D., Li, J., Cui, J., ve Hu, D. (2023). Research on the time-dependent vehicle routing problem for fresh agricultural products based on customer value. Agriculture, 13(3), 681.
30. Wu, D., ve Wu, C. (2022). Research on the time-dependent split delivery green vehicle routing problem for fresh agricultural products with multiple time windows. Agriculture, 12(6), 793.
31. Wu, J., ve Ming, X. (2009). Time-quality-cost tradeoff in logistics service management based on rough sets theory. International Conference on Transportation Engineering 2009, 327-332.
32. Wygonik, E., ve Goodchild, A. (2011). Evaluating CO2 emissions, cost, and service quality trade-offs in an urban delivery system case study. IATSS Research, 35(1), 7-15.
33. Zhang, J., Lam, W. H., ve Chen, B. Y. (2013). A stochastic vehicle routing problem with travel time uncertainty: Trade-off between cost and customer service. Networks and Spatial Economics, 13, 471-496.
34. Zhang, J., ve Zhang, Y. (2019). Trade‐offs between sustainable tourism development goals: An analysis of Tibet (China). Sustainable Development, 27(1), 109-117.
35. Zhu, S. (2022). Multi-objective route planning problem for cycle-tourists. Transportation Letters, 14(3), 298-306.