Dynamics of agglomeration and competition in the hotel industry: A geographically weighted regression analysis based on an analytical hierarchy process and geographic information systems (GIS) data

• Authors: María D. Illescas-Manzano , Sergio Martínez-Puertas , Gema M. Marín-Carrillo , María B. Marín-Carrillo

Abstracts

EN

Research background: The effects of locating next to other establishments of equivalent activity is a decision with serious and far-reaching implications, not only from the point of view of location decisions but also with regard to competitive strategy, pricing, or promotion decisions. The literature provides evidence of the negative effects of being proximate to competitors (erosion of market share), but there are also benefits associated with the increased attraction of demand (attraction effect). This phenomenon is of particular interest in the case of hospitality, where hotel concentrations can be found around certain tourism resources, and is a crucial factor in hoteliers' decisions as they evaluate these contradictory effects. Purpose of the article: Drawing from the relevance that the confrontation between agglomeration and competition has in the hotel industry, our study aims to examine if this confrontation can be driven by geographical location and how both vertical and horizontal differentiation factors can unbalance it. Methods: Based on the use of geographical information systems and the estimation of a geographically weighted regression model with a wide dataset that includes 3,153 European hotels located in Spain, France and the United Kingdom. Findings & value added: We extend agglomeration and competition theoretical bodies related to location decisions by providing new findings about their simultaneous effect. Specifically, this study contributes to filling the gap regarding their combined effects on pricing and the conditions under which one prevails over the other. Results show that the role of geographical location and a hotel's online reputation are more decisive differentiation factors than hotel category when explaining the asymmetry of the effects of agglomeration and competition.

Keywords

EN

agglomeration; competition; geographical information systems; geographically weighted regression; differentiation

• Publisher: Instytut Badań Gospodarczych
• Journal: Oeconomia Copernicana
• Year: 2023
• Volume: 14
• Issue: 1
• Pages: 213-252

Dates

published

2023

Contributors

author

María D. Illescas-Manzano

• Agrifood Campus of International Excellence (ceiA3), University of Almería

• https://orcid.org/0000000274585553

author

Sergio Martínez-Puertas

• Agrifood Campus of International Excellence (ceiA3), University of Almería

• https://orcid.org/0000000338224336

author

Gema M. Marín-Carrillo

• Agrifood Campus of International Excellence (ceiA3), University of Almería

• https://orcid.org/0000000239889578

author

María B. Marín-Carrillo

• Agrifood Campus of International Excellence (ceiA3), University of Almería

• https://orcid.org/0000000267840560

References

• Abrate, G., Capriello, A., & Fraquelli, G. (2011). When quality signals talk: Evi-dence from the Turin hotel industry. Tourism Management, 32(4), 912?921. doi: 10.1016/j .tourman.2010.08.006.
• Adam, I., & Mensah, E. A. (2014). Perceived spatial agglomeration effects and hotel location choice. Anatolia, 25(1), 49?60. doi: 10.1080/13032917.2013.822818.
• Ayuntamiento de Madrid (2018). Límites de los Barrios Administrativos de Madrid. Retrieved from https://datos.madrid.es/portal/site/egob/menuitem.c05c1f754a 33a9fbe4b2e4b284f1a5a0/?vgnextoid=46b55cde99be2410VgnVCM1000000b205a0aRCRD&
• Balaguer, J., & Pernías, J. C. (2013). Relationship between spatial agglomeration and hotel prices. Evidence from business and tourism consumers. Tourism Management, 36, 391?400. doi: 10.1016/j.tourman.2012.10.004.
• Barros, C. P. (2005). Evaluating the efficiency of a small hotel chain with a Malmquist productivity index. International Journal of Tourism Research, 7(3), 173?184. doi: org/10.1002/jtr.529.
• Baum, J. A., & Haveman, H. A. (1997). Love thy neighbour? Differentiation and agglomeration in the Manhattan hotel industry, 1898-1990. Administrative Sci-ence Quarterly, 42(2) 304?338. doi: 10.2307/2393922.
• Baum, J. A., & Mezias, S. J. (1992). Localized competition and organizational fail-ure in the Manhattan hotel industry, 1898-1990. Administrative Science Quarterly, 37(4), 580?604. doi: 10.2307/2393473.
• Becerra, M., Santaló, J., & Silva, R. (2013). Being better vs. being different: Differen-tiation, competition, and pricing strategies in the Spanish hotel industry. Tourism Management, 34, 71?79. doi: 10.1016/j.tourman.2012.03.014.
• Blomberg-Nygard, A., Anderson, C. K., & United Nations World Tourism Org, U. (2016). United Nations World Tourism Organization study on online guest re-views and hotel classification systems: An integrated approach. Service Science, 8(2), 139?151. doi: 10.1287/serv.2016.0139.
• Canina, L., Enz, C. A., & Harrison, J. S. (2005). Agglomeration effects and strategic orientations: Evidence from the US lodging industry. Academy of Management Journal, 48(4), 565?581. doi: 10.5465/amj.2005.17843938.
• Chisholm, D. C., McMillan, M. S., & Norman, G. (2010). Product differentiation and film-programming choice: Do first-run movie theatres show the same films? Journal of Cultural Economics, 34(2), 131?145. doi: org/10.1007/s10824-010-9118-y.
• Chung, W., & Kalnins, A. (2001). Agglomeration effects and performance: A test of the Texas lodging industry. Strategic Management Journal, 22(10), 969?988. doi: 10.1002/smj.178.
• Cró, S., & Martins, A. M. (2018). Hotel and hostel location in Lisbon: Looking for their determinants. Tourism Geographies, 20(3), 504?523.doi: 10.1080/14616688.20 17.1360386.
• Deephouse, D. L. (1999). To be different, or to be the same? It?s the question (and theory) of strategic balance. Strategic Management Journal, 20(2), 147?166. doi: 10.1002/(SICI)1097-0266(199902)20:2<147::AID-SMJ11>3.0.CO;2-Q.
• Dubé, L., & Renaghan, L. M. (2000). Creating visible customer value: How custom-ers view best-practice champions. Cornell Hotel and Restaurant Administration Quarterly, 41(1), 62?72. doi: 10.1177/001088040004100124.
• Enz, C. A., Canina, L., & Liu, Z. (2008). Competitive dynamics and pricing behav-iour in US hotels: The role of co?location. Scandinavian Journal of Hospitality and Tourism, 8(3), 230?250. doi: 10.1080/15022250802305303.
• Fang, L., Li, H., & Li, M. (2019). Does the hotel location tell a true story? Evidence from geographically weighted regression analysis of hotels in Hong Kong. Tourism Management, 72, 78?91. doi: 10.1016/j.tourman.2018.11.010.
• Fang, L., Xie, Y., Yao, S., & Liu, T. (2021). Agglomeration and/or differentiation at a regional scale? Geographic spatial thinking of hotel distribution?a case study of Guangdong, China. Current Issues in Tourism, 24(10), 1358?1374. doi: 10.1080/ 13683500.2020.1792852.
• Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2003). Geographically weighted regression: The analysis of spatially varying relationships. New York: John Wiley & Sons.
• Freedman, M. L., & Kosová, R. (2012). Agglomeration, product heterogeneity and firm entry. Journal of Economic Geography, 12(3), 601?626. doi: 10.1093/jeg/lbr022.
• Gardiner, B., Martin, R., & Tyler, P. (2010). Does spatial agglomeration increase national growth? Some evidence from Europe. Journal of Economic Geography, 11(6), 979?1006. doi: 10.1093/jeg/lbq047
• Getis, A. (2007). Reflections on spatial autocorrelation. Regional Science and Urban Economics, 37(4), 491?496. doi: 10.1016/j.regsciurbeco.2007.04.005.
• Ghose, A., Ipeirotis, P. G., & Li, B. (2012). Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Science, 31(3), 493?520. doi: 10.1287/mksc.1110.0700.
• Gollini, I., Lu, B., Charlton, M., Brunsdon, C., & Harris, P. (2015). Gwmodel: An r package for exploring spatial heterogeneity using geographically weighted models. Journal of Statistical Software, 63, 17. doi: 10.18637/jss.v063.i17.
• Hollenbeck, B. (2018). Online reputation mechanisms and the decreasing value of chain affiliation. Journal of Marketing Research, 55(5), 636?654. doi: 10.1177/00222 43718802844.
• Horwath HTL (2022). Spain hotels & chains report 2022. Retrieved from https://horwathhtl.com/publication/spain-hotels-chains-report-2022/.
• Kalnins, A. (2016). Beyond Manhattan: Localized competition and organizational failure in urban hotel markets throughout the United States, 2000?2014. Strate-gic Management Journal, 37(11), 2235?2253. doi: 10.1002/smj.2578.
• Kalnins A, & Chung W. (2004). Resource-seeking agglomeration: a study of mar-ket entry in the lodging industry. Strategic Management Journal, 25(7), 689?699. doi: 10.1002/smj.403.
• Kennedy, P. (2008). A guide to econometrics. Chicester: John Wiley & Sons.
• Kim, W. G., Li, J., Han, J. S., & Kim, Y. (2017). The influence of recent hotel ameni-ties and green practices on guests? price premium and revisit intention. Tour-ism Economics, 23(3), 577?593. doi: 10.5367/te.2015.0531.
• Kim, M., Roehl, W., & Lee, S. K. (2020). Different from or similar to neighbours? An investigation of hotels' strategic distances. Tourism Management, 76, 103960. doi: 10.1016/j.tourman.2019.103960.
• Lee, S. K. (2015). Quality differentiation and conditional spatial price competition among hotels. Tourism Management, 46, 114?122. doi: 10.1016/j.tourman.2014.06. 019
• Lee, S. K., & Jang, S. (2013). Asymmetry of price competition in the lodging mar-ket. Journal of Travel Research, 52(1), 56?67. doi: 10.1177/0047287512457268.
• Lee, S. K., & Jang, S. (2015). Conditional agglomeration externalities in lodging markets. Journal of Hospitality & Tourism Research, 39(4), 540?559. doi: 10.1177/10 96348013491605.
• Lee, K. H., Kang, S., Terry, W. C., & Schuett, M. A. (2018). A spatial relationship between the distribution patterns of hotels and amenities in the United States. Cogent Social Sciences, 4(1), 1444918. doi: 10.1080/23311886.2018.1444918.
• Leung, Y., Mei, C. L., & Zhang, W. X. (2000). Statistical tests for spatial nonstation-arity based on the geographically weighted regression model. Environment and Planning A, 32(1), 9?32. doi: 10.1068/a3162.
• Li, Y., & Du, T. (2018). Assessing the impact of location on hotel development: An analysis of Manhattan hotels, 1822?2012. Papers in Applied Geography, 4(1), 21?33. doi: 10.1080/23754931.2017.1366356.
• 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. doi: 10.1016/j.ijhm.2014.11.005.
• Liu, S., Gao, B., Gallivan, M., & Gong, Y. (2020). Free add-on services and perceived value in competitive environments: Evidence from online hotel reviews. International Journal of Hospitality Management, 90, 102611. doi: 10.1016/j.ijhm.202 0.102611.
• Liu, A. X., Steenkamp, J. B. E., & Zhang, J. (2018). Agglomeration as a driver of the volume of electronic word of mouth in the restaurant industry. Journal of Marketing Research, 55(4), 507?523. doi: 10.1509/jmr.16.0182.
• Lodging Econometrics (2022). Hotel conversions in Europe?s hotel construction pipeline reach all-time high. Retrieved from: https://lodgingeconometrics.com/ hotel-conversions-in-europes-hotel-construction-pipeline-reach-all-time-high/.
• London Stock Exchange Group (2017). London Stock Exchange Group 1000 compa-nies to inspire. Retrieved from https://www.lseg.com/resources/1000-compan ies-inspire.
• London Ward (2018). Retrieved form https://data.london.gov.uk/dataset/statistical-gis-boundary-files-london'>https://data.london.gov.uk/dataset/statistical-gis-bo undary-files-london.
• Lu, A. C. C., Gursoy, D., & Lu, C. Y. R. (2016). Antecedents and outcomes of con-sumers? confusion in the online tourism domain. Annals of Tourism Research, 57, 76?93. doi: 10.1016/j.annals.2015.11.020.
• 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. doi: 10.1016/j.ijhm.2016.09.007.
• Mankad, S., Han, H. S., Goh, J., & Gavirneni, S. (2016). Understanding online hotel reviews through automated text analysis. Service Science, 8(2), 124?138. doi: 10.1287/serv.2016.0126.
• Marco-Lajara, B., Claver-Cortés, E., & Úbeda-García, M. (2014). Business agglom-eration in tourist districts and hotel performance. International Journal of Contemporary Hospitality Management, 26(8), 1312?1340. doi: 10.1108/IJCHM-07-2013-0319.
• Marco-Lajara, B., Claver-Cortés, E., Úbeda-García, M., & del Carmen Zaragoza-Sáez, P. (2016). A dynamic analysis of the agglomeration and performance re-lationship. Journal of Business Research, 69(5), 1874?1879. doi: 10.1016/j.jbusres.201 5.10.072.
• Marco-Lajara, B., del Carmen Zaragoza-Sáez, P., Claver-Cortés, E., Úbeda-García, M., & García-Lillo, F. (2017). Tourist districts and internationalization of hotel firms. Tourism Management, 61, 451?464. doi: 10.1016/j.tourman.2017.03.015.
• Masiero, L., Yang, Y., & Qiu, R. T. (2019). Understanding hotel location preference of customers: Comparing random utility and random regret decision rules. Tourism Management, 73, 83?93. doi: 10.1016/j.tourman.2018.12.002.
• McCann, B. T., & Folta, T. B. (2008). Location matters: where we have been and where we might go in agglomeration research. Journal of Management, 34(3), 532?565. doi: 10.1177/0149206308316057.
• McCann, B. T., & Vroom, G. (2010). Pricing response to entry and agglomeration effects. Strategic Management Journal, 31(3), 284?305. doi: 10.1002/smj.805.
• Nicholls, S., & Kim, J. (2022). Spatial is special: The need to consider spatial effects in leisure research. Leisure Sciences, 44(4), 476?496. doi: 10.1080/01490400.2019.16 00441.
• Núñez-Serrano, J. A., Turrion, J., & Velázquez, F. J. (2014). Are stars a good indica-tor of hotel quality? Assymetric information and regulatory heterogeneity in Spain. Tourism Management, 42, 77?87. doi: 10.1016/j.tourman.2013.10.004.
• Open platform for French public data (2018). Arrondissements de Paris. Retrieved from https://www.data.gouv.fr/en/datasets/arrondissements-1/
• Park, C., Kim, Y. R., & Frye, W. D. (2022). Keeping the competition close: The im-pact of competitor distance in the lodging industry. International Journal of Tourism Research, 24(3), 400?412. doi: 10.1002/jtr.2510.
• Qin, J., Qin, Y., & Liu, C. (2021). Location and regionalization patterns of hotel chains: evidence from China. Tourism Geographies. Advance online publication. doi: 10.1080/14616688.2021.1966646.
• Rezvani, E., & Rojas, C. (2020). Spatial price competition in the Manhattan hotel market: The role of location, quality, and online reputation. Managerial and Decision Economics, 41(1), 49?63. doi: 10.1002/mde.3092.
• Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34?55. doi: 10.1086/260169
• Saaty, T. L., & Tran, L. T. (2007). On the invalidity of fuzzifying numerical judg-ments in the Analytic Hierarchy Process. Mathematical and Computer Modelling, 46(7-8), 962?975. doi: 10.1016/j.mcm.2007.03.022.
• Sánchez-Pérez, M., Illescas-Manzano, M. D., & Martínez-Puertas, S. (2020). You?re the only one, or simply the best. Hotels differentiation, competition, agglom-eration, and pricing. International Journal of Hospitality Management, 85, 102362. doi: 10.1016/j.ijhm.2019.102362.
• Shaked, A., & Sutton, J. (1982). Relaxing price competition through product differ-entiation. Review of Economic Studies, 49(1), 3?13. doi: 10.2307/2297136.
• Silva, R. (2015). Multimarket contact, differentiation, and prices of chain hotels. Tourism Management, 48, 305?315. doi: 10.1016/j.tourman.2014.11.006.
• Silva, R. (2016). Competition and demand effects of geographic distance to rivals. Service Industries Journal, 36(1-2), 37?57. doi: 10.1080/02642069.2016.1138470.
• Tierno, N. R., Puig, A. B., Vera, J. M. B., & Pérez, C. E. (2018). Assessing food retail competitors with a multi-criteria GIS-based method. Economía Agraria Y Recursos Naturales, 18(1), 5?22. doi: 10.7201/earn.2018.01.01.
• Tsang, E. W., & Yip, P. S. (2009). Competition, agglomeration, and performance of Beijing hotels. Service Industries Journal, 29(2), 155?171. doi: 10.1080/0264206080 2294896.
• UNWTO (United Nations World Tourism Organization) (2018). World Tourism Barometer and Statistical Annex. Retrieved from https://www.e-unwto.org/ toc/wtobarometereng/16/5 (3.01.2022).
• Urtasun, A., & Gutiérrez, I. (2006). Hotel location in tourism cities: Madrid 1936?1998. Annals of Tourism Research, 33(2), 382?402. doi: 10.1016/j.annals.2005.12.008.
• Urtasun, A., & Gutiérrez, I. (2017). Clustering benefits for upscale urban hotels. International Journal of Contemporary Hospitality Management, 29(5), 1426?1446. doi: 10.1108/IJCHM-10-2015-0583.
• Wheeler, D., & Tiefelsdorf, M. (2005). Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems, 7(2), 161?187. doi: 10.1007/s10109-005-0155-6.
• Woo, L., & Mun, S. G. (2020). Types of agglomeration effects and location choices of international hotels in an emerging market. Tourism Management, 77, 104034. doi: 10.1016/j.tourman.2019.104034.
• Yang, Y., Luo, H., & Law, R. (2014). Theoretical, empirical, and operational models in hotel location research. International Journal of Hospitality Management, 36, 209?220. doi: 10.1016/j.ijhm.2013.09.004.
• Ye, F., Xia, Q., Zhang, M., Zhan, Y., & Li, Y. (2022). Harvesting online reviews to identify the competitor set in a service business: Evidence from the hotel in-dustry. Journal of Service Research, 25(2), 301?327. doi: 10.1177/1094670520975143.
• Zhang, Z., Ye, Q., & Law, R. (2011a). Determinants of hotel room price: An explo-ration of travellers? hierarchy of accommodation needs. International Journal of Contemporary Hospitality Management, 23(7), 972?981. doi: 10.1108/09596111111 167551.
• Zhang, H., Zhang, J., Lu, S., Cheng, S., & Zhang, J. (2011b). Modelling hotel room price with geographically weighted regression. International Journal of Hospitali-ty Management, 30(4), 1036?1043. doi: 10.1016/j.ijhm.2011.03.010.
• Zhao, X. R., Wang, L., Guo, X., & Law, R. (2015). The influence of online reviews to online hotel booking intentions. International Journal of Contemporary Hospitality Management, 27(6), 1343?1364. doi: 10.1108/IJCHM-12-2013-0542.

Identifiers

DOI

10.24136/oc.2023.006

Biblioteka Nauki

19322753