Small Hotel Location Selection Problem: The Case of Cappadocia

Abstract

Identifying an appropriate location is one of the most significant factors in determining the success of a facility. This paper focuses on the selection of the most appropriate small hotel location in inner Cappadocia, based on seven destination-specific criteria. The Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) and Additive Ratio Assessment (ARAS) methodology is utilized to obtain the relative criteria weights and the final ranking of six alternative small hotel locations. The results indicate that the most important factors in small hotel location selection in Cappadocia are revenue per available room (REVPAR) potential, investment amount and view of hot air balloon flights. Goreme and Uchisar are identified as the most appropriate locations for small hotel investment in the region.

Keywords

• Small hotel location selection
• Cappadocia
• PIPRECIA
• ARAS

References

1. Adam, I., & Amuquandoh, F. E. (2014). Hotel characteristics and location decisions in Kumasi Metropolis, Ghana. Tourism Geographies, 16(4), 653-668.
2. Baker, S., Bradley, P., & Huyton, J. (2000). Principles of Hotel Front Office Operations. London: Cengage Learning EMEA.
3. Bakir, M., Akan, Ş., Kiraci, K., Karabasevic, D., Stanujkic, D., & Popovic, G. (2020). Multiple-criteria approach of the operational performance evaluation in the airline industry: Evidence from the emerging markets. Rom. J. Econ. Forecast, 23, 149.
4. Baum, J. A., & Haveman, H. A. (1997). Love thy neighbor? Differentiation and agglomeration in the Manhattan hotel industry, 1898-1990. Administrative Science Quarterly, 304-338.
5. Biswas, S. (2020). Measuring performance of healthcare supply chains in India: A comparative analysis of multi-criteria decision making methods. Decision Making: Applications in Management and Engineering, 3(2), 162-189.
6. Botti, L., & Peypoch, N., (2013). Multi-criteria ELECTRE method and destination competitiveness. Tourism Management Perspectives, 6, 108–113.
7. Briedenhann, J. (2009) Socio-cultural criteria for the evaluation of rural tourism projects – a Delphi consultation. Current Issues in Tourism, 12(4), 379-396.
8. Bull, A. O. (1998). The effects of location and other attributes on the price of products which are place-sensitive in demand. Unpublished doctoral dissertation, Griffith University, Australia.

9. Chou, T. Y., Hsu, C. L., & Chen, M. C. (2008). A fuzzy multi-criteria decision model for international tourist hotels location selection. International Journal of Hospitality Management, 27(2), 293-301.
10. Chu, R. K., & Choi, T. (2000). An importance-performance analysis of hotel selection factors in the Hong Kong hotel industry: a comparison of business and leisure travellers. Tourism management, 21(4), 363-377.
11. Combes, P. P., & Gobillon, L. (2015). The Empirics of Agglomeration Economies. Handbook of Regional and Urban Economics, 5, 247-348.
12. Dahooie, J. H., Zavadskas, E. K., Abolhasani, M., Vanaki, A., & Turskis, Z. (2018). A novel approach for evaluation of projects using an interval–valued fuzzy additive ratio assessment (ARAS) method: a case study of oil and gas well drilling projects. Symmetry, 10(2), 45.
13. Ðalic, I., Ateljevic, J., Stevic, Z., & Terzic, S. (2020a). An Integrated SWOT–Fuzzy PIPRECIA model for analysis of competitiveness in order to improve logistics performances. Facta Universitatis, Series: Mechanical Engineering, 18(3), 439-451.
14. Ðalic, I., Stevic, Z., Karamasa, C., & Puska, A. (2020b). A novel integrated fuzzy PIPRECIA–interval rough SAW model: green supplier selection. Decision Making: Applications in Management and Engineering, 3(1), 126-145.
15. Dobrosavljević, A., Urošević, S., Vuković, M., Talijan, M., & Marinković, D. (2020). Evaluation of process orientation dimensions in the apparel industry. Sustainability, 12(10), 4145.
16. Egan, D. J., & Nield, K. (2000). Towards a theory of intraurban hotel location. Urban Studies, 37(3), 611-621.
17. Fang, L., Li, H., & Li, M. (2019). Does hotel location tell a true story? Evidence from geographically weighted regression analysis of hotels in Hong Kong. Tourism Management, 72, 78-91.
18. Farahani, R. Z., Asgari, N., Heidari, N., Hosseininia, M., & Goh, M. (2012). Covering problems in facility location: A review. Computers & Industrial Engineering, 62(1), 368-407.
19. Ghenai, C., Albawab, M., & Bettayeb, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580-597.
20. Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66–83.
21. Huang, J. H., & Peng, K. H. (2012). Fuzzy Rasch model in TOPSIS: a new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries. Tourism Management, 33(2), 456–465.
22. Ilgin, M.A., Gupta, S. M., & Battaïa, O. (2015). Use of MCDM techniques in environmentally conscious manufacturing and product recovery: state of the art. Journal of Manufacturing Systems, 37, 746–758.
23. Jaukovic Jocic K., Jocic, G., Karabasevic, D., Popovic, G., Stanujkic, D., Zavadskas, E. K., & Thanh Nguyen, P. (2020). A novel integrated PIPRECIA–interval-valued triangular fuzzy ARAS model: Elearning course selection. Symmetry, 12(6), 928.
24. Jeong, J.S., García-Moruno, L., Hernández-Blanco, J., & Jaraíz-Cabanillas, F.J. (2014). An operational method to supporting siting decisions for sustainable rural second home planning in ecotourism sites. Land Use Policy, 41, 550–560.
25. Kalnins, A., & Chung, W., (2004). Resource-seeking agglomeration: a study of market entry in the lodging industry. Strategic Management Journal, 25(7), 689–699.
26. Karabašević, D., Stanujkić, D., & Urošević, S. (2015). The MCDM Model for Personnel Selection Based on SWARA and ARAS Methods. Management, 20(77), 1820-0222.
27. Karabasevic, D., Zavadskas, E. K., Turskis, Z., & Stanujkic, D. (2016). The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. Informatica, 27(1), 49-65.
28. Karabašević, D. M., Maksimović, M. V., Stanujkić, D. M., Jocić, G. B., & Rajčević, D. P. (2018). Selection of software testing method by using ARAS method. Tehnika, 73(5), 724-729.
29. Kaya, A.O., Kaya, T., & Kahraman, C. (2013). A fuzzy approach to urban ecotourism site selection based on integrated Promethee III methodology. Journal of Multiple-Valued Logic and Soft Computing, 21(1/2), 89–111.
30. Keršulienė, V., & Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and economic development of economy, 17(4), 645-666.
31. Krylovas, A., Zavadskas, E. K., Kosareva, N., & Dadelo, S. (2014). New KEMIRA method for determining criteria priority and weights in solving MCDM problem. International Journal of Information Technology Decision Making, 13(06), 1119–1133.
32. Lee, S. K., & Jang, S. (2011). Room rates of U.S. Airport hotels: Examining the dual effects of proximities. Journal of Travel Research, 50(2), 186–197.
33. Lewis, R. C., & Chambers, R. E. (1989). Marketing Leadership in Hospitality. New York: Van Nostrand Reinhold.
34. Li, M., Fang, L., Huang, X., & Goh, C. (2015). A spatial–temporal analysis of hotels in urban tourism destination. International Journal of Hospitality Management, 45, 34-43.
35. Liu, C. H., Tzeng, G. H., & Lee, M.H. (2012). Improving tourism policy implementation – the use of hybrid MCDM models. Tourism Management, 33(2), 413–426.
36. Luo, H., & Yang, Y. (2016). Intra-metropolitan location choice of star-rated and non-rated budget hotels: The role of agglomeration economies. International Journal of Hospitality Management, 59, 72–83.
37. Marco-Lajara, B., Claver-Cortés, E., Úbeda-García, M., & Zaragoza-Sáez, P. D. C. (2016). Hotel performance and agglomeration of tourist districts. Regional Studies, 50(6), 1016-1035.
38. Marco-Lajara, B., del Carmen Zaragoza-Saez, P., Claver-Cortés, E., Úbeda-García, M., & García-Lillo, F. (2017). Tourist districts and internationalization of hotel firms. Tourism Management, 61, 451-464.
39. Mardani, A., Jusoh MD, A., Nor, K., Khalifah, Z., Zakwan, N., & Valipour, A., (2015). Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research, 28(1), 516–571.
40. Marković, V., Stajić, L., Stević, Ž., Mitrović, G., Novarlić, B., & Radojičić, Z. (2020). A novel integrated subjective-objective mcdm model for alternative ranking in order to achieve business excellence and sustainability. Symmetry, 12(1), 164.
41. Memis, S., Demir, E., Karamaşa, Ç., & Korucuk, S. (2020). Prioritization of road transportation risks: An application in Giresun province. Operational Research in Engineering Sciences: Theory and Applications, 3 (2), 111-126.
42. Molina-Azorin, J. F., Pereira-Moliner, J., & Claver-Cortés, E. (2010). The importance of the firm and destination effects to explain firm performance. Tourism Management, 31(1), 22-28.
43. Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021). Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA–Fuzzy MABAC model. Plos one, 16(2), e0246857.
44. Nevsehir Provincial Directorate of Culture and Tourism. (2019). Cappadocia accommodation reports, 2019, Nevsehir.
45. Nweze, S., & Achebo, J. (2021). Comparative enhancement of mild steel weld mechanical properties for better performance using COPRAS–ARAS Method. European Journal of Engineering and Technology Research, 6(2), 70-74.
46. Pan, C. M. (2002). Market concentration ratio analysis of the international tourist hotel industry in Taipei area. Tourism Management Research, 2(2), 57-66.
47. Panahi, H., Mamipour, S., & Nazari, K. (2015) Tourism and economic growth: a timevarying parameter approach. Anatolia, 26(2), 173-185.
48. Peiró-Signes, A., Segarra-Oña, M. D. V., Miret-Pastor, L., & Verma, R. (2014). The effect of tourism clusters on US hotel performance. Cornell Hospitality Quarterly, 56(2), 155-167.
49. Popovic, G., & Mihajlovic, D., (2018). An MCDM approach to tourism projects evaluation: The Upper Danube Basin case. 3rd International Thematic Monograph - Thematic Proceedings: Modern Management Tools and Economy of Tourism Sector in Present Era, 129-141.
50. Popovic, G., Stanujkic, D., Brzakovic, M., & Karabasevic, D. (2019). A multiple-criteria decision-making model for the selection of a hotel location. Land use policy, 84, 49-58.
51. Puciato, D. (2016). Attractiveness of municipalities in South-Western Poland as determinants for hotel chain investments. Tourism Management, 57, 245-255.
52. Pulido-Fernández, J. I., Cárdenas-García, P. J., & Sánchez-Rivero, M. (2014) Tourism as a tool for economic development in poor countries. Turizam: međunarodni znanstvenostručni časopis, 62(3), 309-322.
53. Rigall-I-Torrent, R., Fluvià, M., Ballester, R., Saló, A., Ariza, E., & Espinet, J. M. (2011). The effects of beach characteristics and location with respect to hotel prices. Tourism Management, 32(5), 1150-1158.
54. Rivers, M. J., Toh, R. S., & Alaoui, M. (1991). Frequent-stayer programs: the demographic, behavioural, and attitudinal characteristics of hotel steady sleepers. Journal of Travel Research, 30 (2), 41–45.
55. Sa, M. L. L., Choon-Yin, S., Chai, Y. K., & Joo, J. H. A. (2020). Knowledge creation process, customer orientation and firm performance: Evidence from small hotels in Malaysia. Asia Pacific Management Review, 25(2), 65-74.
56. Shirouyehzad, H., Lotfi, F. H., Arabzad, S. M., & Dabestani, R., (2013). An AHP/DEA ranking method based on service quality approach: a case study in hotel industry. International Journal of Production Quality Management, 11(4), 434–445.
57. Shoval, N., & Cohen-Hattab, K. (2001). Urban hotel development patterns in the face of political shifts. Annals of Tourism Research, 28(4), 908-925.
58. Shoval, N., McKercher, B., Ng, E., & Birenboim, A. (2011). Hotel location and tourist activity in cities. Annals of Tourism Research, 38(4), 1594-1612.
59. Sim, J., Mak, B., & Jones, D. (2006). A model of customer satisfaction and retention for hotels. Journal of Quality Assurance in Hospitality & Tourism, 7(3), 1–23.
60. Stanujkic, D., Kazimieras Zavadskas, E., Karabasevic, D., Smarandache, F., & Turskis, Z., (2017). The use of the pivot pairwise relative criteria importance assessment method for determining the weights of criteria. Romanian Journal of Economic, 20(4), 116-133.
61. Stanujkic, D., & Karabasevic, D. (2018).An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Operational Research in Engineering Sciences: Theory and Applications, 1(1), 29-39.
62. Stanujkic, D., Karabasevic, D., Zavadskas, E. K., Smarandache, F., & Cavallaro, F. (2019). An approach to determining customer satisfaction in traditional Serbian restaurants. Entrepreneurship and Sustainability Issues, 6(3), 1127-1138.
63. Stevic, Z., Stjepanovic, Z., Bozickovic, Z., Das, D. K., & Stanujkic, D. (2018). Assessment of conditions for implementing information technology in a warehouse system: a novel fuzzy PIPRECIA method. Symmetry, 10 (11), 586.
64. Stević, Ž., Karamaşa, Ç., Demir, E., & Korucuk, S. (2021). Assessing sustainable production under circular economy context using a novel rough-fuzzy MCDM model: a case of the forestry industry in the Eastern Black Sea region. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-10-2020-0419
65. Tomasevic, M., Lapuh, L., Stevic, Z., Stanujkic, D., & Karabasevic, D. (2020). Evaluation of criteria for the implementation of high-performance computing (HPC) in Danube Region countries using fuzzy PIPRECIA method. Sustainability, 12 (7), 3017.
66. Urtasun, A., & Gutiérrez, I. (2006). Hotel location in tourism cities: Madrid 1936–1998. Annals of Tourism Research, 33(2), 382–402.
67. Vesković, S., Stević, Ž., Stojić, G., Vasiljević, M., & Milinković, S. (2018). Evaluation of the railway management model by using a new integrated model DELPHISWARA- MABAC. Decision Making: Applications in Management and Engineering, 1(2), 34-50,
68. Veskovic, S., Milinkovic, S., Abramovic, B., & Ljubaj, I. (2020). Determining criteria significance in selecting reach stackers by applying the fuzzy PIPRECIA method. Operational Research in Engineering Sciences: Theory and Applications, 3(1), 72-88.
69. Wu, C. S., Lin, C. T., & Lee, C., (2010). Optimal marketing strategy: a decision-making with ANP and TOPSIS. International Journal of Production Economics, 127(1), 190–196.
70. Yang, Y., Luo, H., & Law, R. (2014). Theoretical, empirical, and operational models in hotel location research. International Journal of Hospitality Management, 36, 209–220.
71. Yang, Y., Wong, K. K., & Wang, T. (2012). How do hotels choose their location? Evidence from hotels in Beijing. International journal of hospitality management, 31(3), 675-685.
72. Yazdani, M., Chatterjee, P., Pamucar, D., & Abad, M.D. (2019). A risk-based integrated decision-making model for green supplier selection. Kybernetes, 49(4), 1229-1252.
73. Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision‐making. Technological and Economic Development of Economy, 16(2), 159-172.
74. Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179.