Identificación de clústeres en la Zona Metropolitana de Guadalajara: restaurantes
Publicado 2022-09-22
Palabras clave
- clusterización,
- Kulldorff,
- localización,
- análisis espacial,
- restaurantes.
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Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Métrica
Resumen
El objetivo de este artículo es identificar la metodología de clusterización más apropiada para aplicarse en el sector restaurantero de la Zona Metropolitana de Guadalajara (ZMG). Se llevó a cabo un recuento de las distintas técnicas de clusterización espacial, para después identificar que la más conveniente es la técnica de Kulldorff, la cual fue utilizada para mapear los clústeres de los restaurantes existentes en la metrópoli. Los resultados muestran diez clústeres de restaurantes en la ZMG, siete de ellos con alta concentración de unidades económicas. El presente estudio es innovador respecto a la detección de clústeres en la industria restaurantera de la ZMG.
Referencias
- Alcaide, J., Calero de la Paz, R. y Hernández, R. (2012). Geomarketing: cómo sacar partido al marketing territorial para vender y fidelizar más. Pozuelo de Alarcón: ESIC.
- Almeida, A., Duarte, A., Duczmal, L., Oliveira, F. y Takahashi, R. (2011). Data-driven inference for the spatial scan statistic. International Journal of Health Geographics, 10(47). https://link.springer.com/article/10.1186/1476-072X-10-47 DOI: https://doi.org/10.1186/1476-072X-10-47
- Anselin, L. (1999). The future of spatial analysis in the social sciences. Geographic Information Sciences, 5(2), 67-76. http://www.agrod.com/research/projects/p20070118_SpatialPoverty/References/Anselin.lecture.notes.Spring2001/futuresa.pdf DOI: https://doi.org/10.1080/10824009909480516
- Barnes, T. J. (2003). The place of locational analysis: A selective and interpretive history. Progress in Human Geography, 27(1), 69-95. https://journals.sagepub.com/doi/10.1191/0309132503ph419oa DOI: https://doi.org/10.1191/0309132503ph419oa
- Bersimis, S., Chalkias, C. y Anthopoulou, T. (2014). Detecting and interpreting clusters of economic activity in rural areas using scan statistic and LISA under a unified framework. Applied Stochastic Models in Business and Industry, 30(5), 573-587. https://onlinelibrary.wiley.com/doi/10.1002/asmb.2003 DOI: https://doi.org/10.1002/asmb.2003
- Brown, S. (1989). Retail location theory: The legacy of Harold Hotelling. Journal of Retailing, 65(4), 450-470. https://go.gale.com/ps/i.do?p=AONE&u=googlescholar&id=GALE|A8193466&v=2.1&it=r&sid=googleScholar&asid=0564b6ef
- Burdina, M. (2004). Impact of transportation on business location decisions in rural upper great plains. (Tesis de maestría, Dakota State University, Fargo, Dakota del Norte). https://www.ag.ndsu.edu/ansc/agribusiness-applied-economics/research-extension-centers/Burdina1-Thesis.pdf
- Canirac. (2014). Situación actual de la industria. En Monografía de la industria restaurantera (pp. 11-21). Ciudad de México: Cámara Nacional de la Industria de Restaurantes y Alimentos Condimentados.
- Canirac. (2016). Industria restaurantera. Todo sobre la mesa. Ciudad de México: Cámara Nacional de la Industria de Restaurantes y Alimentos Condimentados.
- Chain, C. P., Dos Santos, A., Gonzaga, L. y Do Prado, J. (2019). Bibliometric analysis of the quantitative methods applied to the measurement of industrial clusters. Journal of Economic Surveys, 33(1), 60-84. https://onlinelibrary.wiley.com/doi/abs/10.1111/joes.12267 DOI: https://doi.org/10.1111/joes.12267
- Chasco, C. (2003). Econometría espacial aplicada a la predicción-extrapolación de datos microterritoriales. (Tesis de doctorado, Universidad Autónoma de Madrid, Economía y Planificación). https://repositorio.uam.es/handle/10486/4077
- Chasco, C. (2006). Análisis estadístico de datos geográficos en geomarketing: el programa GeoDa. Distribución y Consumo, 16(86), 34-47. https://www.mapa.gob.es/ministerio/pags/biblioteca/revistas/pdf_DYC/DYC_2006_86_34_45.pdf
- Chasco, C., Le Gallo, J. y López, F. (2018). A scan test for spatial groupwise heteroscedasticity in cross-sectional models with an application on houses prices in Madrid. Regional Science and Urban Economics, 68, 226-238. https://www.sciencedirect.com/science/article/pii/S0166046216302927?casa_token=fXX5_fydxRgAAAAA:IlCX0WPUnItv4_dU-x7PIGqo3wuFLMQB-1z17vgDzxJzqlf-KeoyStF-yuKNq0kRn_57w4VAceWC DOI: https://doi.org/10.1016/j.regsciurbeco.2017.10.015
- Chen, J., Roth, R., Naito, A., Lengerich, E. y MacEachren, A. (2008). Geovisual analytics to enhance spatial scan statistic interpretation: An analysis of US cervical cancer mortality. International Journal of Health Geographics, 7(57), 1-18. https://link.springer.com/article/10.1186/1476-072X-7-57 DOI: https://doi.org/10.1186/1476-072X-7-57
- Christaller, W. (1935). Die Zentralen Orte in Süddeuntschland. Alemania: WBG Academic.
- Coase, R. (1995). The nature of the firm. Essential Readings in Economics, 6, 37-54. https://link.springer.com/chapter/10.1007/978-1-349-24002-9_3 DOI: https://doi.org/10.1007/978-1-349-24002-9_3
- Conapo. (2018). Delimitación de las zonas metropolitanas de México 2015. Ciudad de México: Secretaría de Desarrollo Social / Conapo / INEGI. https://www.gob.mx/conapo/documentos/delimitacion-de-las-zonas-metropolitanas-de-mexico-2015
- Cuadros, D., Awad, S. y Abu-Raddad, L. (2013). Mapping HIV clustering: A strategy for identifying populations at high risk of HIV infection in Sub-Saharan Africa. International Journal of Health Geographics, 12(28). https://link.springer.com/article/10.1186/1476-072X-12-28 DOI: https://doi.org/10.1186/1476-072X-12-28
- Czamanski, S. y de Q. Ablas, L. A. (1979). Identification of industrial clusters and complexes: A comparison of methods and findings. Urban Studies, 16(1), 61-80. https://www.jstor.org/stable/43081447 DOI: https://doi.org/10.1080/713702464
- Dahl, M. S. y Sorenson, O. (2009). The embedded entrepreneur. European Management Review, 6(3), 172-181. https://onlinelibrary.wiley.com/doi/abs/10.1057/emr.2009.14 DOI: https://doi.org/10.1057/emr.2009.14
- De Melo, S., Pereira, D., Andresen, M. y Matias, L. (2018). Spatial/temporal variations of crime: A routine activity theory perspective. International Journal of Offender Therapy and Comparative Criminology, 62(7), 1967-1991. https://journals.sagepub.com/doi/10.1177/0306624X17703654 DOI: https://doi.org/10.1177/0306624X17703654
- Figueiredo, O., Guimaraes, P. y Woodward, D. (2002). Home-field advantage: Location decisions of portuguese entrepreneurs. Journal of Urban Economics, 52(2), 341-361. https://www.sciencedirect.com/science/article/abs/pii/S0094119002000062 DOI: https://doi.org/10.1016/S0094-1190(02)00006-2
- Galindo, L., Escalante, R. y Asuad, N. (2004). El proceso de urbanización y el crecimiento económico en México. Estudios Demográficos y Urbanos, 19(2), 289-312. https://estudiosdemograficosyurbanos.colmex.mx/index.php/edu/article/view/1188/1181 DOI: https://doi.org/10.24201/edu.v19i2.1188
- Gómez, S. (coord.). (2014). Agendas de competitividad de los destinos turísticos de México. Vol.1. Zona Metropolitana de Guadalajara. México: Universidad de Guadalajara, Gobierno del Estado de Jalisco, Secretaría de Turismo. http://cucea.udg.mx/coordinacion-de-investigacion/publicaciones/libro/?id=48
- Gómez-Mejía, L., Haynes, K., Núñez-Nickel, M., Jacobson, K. y Moyano-Fuentes, J. (2007). Socioemotional wealth and business risks in family-controlled firms: Evidence from Spanish olive oil mills. Administrative Science Quarterly, 52(1), 106-137. https://www.jstor.org/stable/20109904 DOI: https://doi.org/10.2189/asqu.52.1.106
- González Rodríguez, S. (2012). Globalización, funcionalidad económica y estructura urbana en la zona conurbada de Guadalajara, 1980-2000. México: Universidad de Guadalajara, Centro Universitario de Ciencias Económico Administrativas. http://www.cucea.udg.mx/include/publicaciones/coorinv/pdf/Globalizacion,funcionalidadeconomica.pdf DOI: https://doi.org/10.32870/9786074505924
- Guttmann, A., Li, X., Gaudart, J., Gérard, Y., Demongeot, J., Boire, J. y Ouchchane, L. (2014). Spatial heterogeneity of type I error for local cluster detection tests. International Journal of Health Geographics, 13. https://link.springer.com/article/10.1186/1476-072X-13-15 DOI: https://doi.org/10.1186/1476-072X-13-15
- Guttmann, A., Ouchchane, L., Li, X., Perthus, I., Gaudart, J., Demongeot, J. y Boire, J. (2013). Performance map of a cluster detection test using extended power. International Journal of Health Geographics, 12. https://link.springer.com/article/10.1186/1476-072X-12-47 DOI: https://doi.org/10.1186/1476-072X-12-47
- Hamilton, B. (2000). Does entrepreneurship pay? An empirical analysis of the returns to self-employment. Journal of Political Economy, 108(3), 604-631. https://www.jstor.org/stable/10.1086/262131 DOI: https://doi.org/10.1086/262131
- Hormigo Ventura, J. P. (2006). La evolución de los factores de localización de actividades. (Tesis de doctorado, Universitat Politécnica de Catalunya, Barcelona) https://upcommons.upc.edu/handle/2099.1/3308
- Hotelling, H. (1929). Stability in competition. The Economic Journal, 39(153), 41-57. https://www.jstor.org/stable/2224214 DOI: https://doi.org/10.2307/2224214
- INEGI. (2016). La industria restaurantera en México. Ciudad de México: Instituto Nacional de Estadística y Geografía. INEGI. (2020a). Directorio Estadístico Nacional de Unidades Económicas DENUE. Ciudad de México: Instituto Nacional de Estadística y Geografía. https://www.inegi.org.mx/app/mapa/denue/
- INEGI. (2020b). Mapa digital de México para escritorio. https://www.inegi.org.mx/contenidos/temas/MapaDigital/Doc/aspectos_generales.pdf
- INEGI. (2020c). Sistema Automatizado de Información Censal (SAIC). https://www.inegi.org.mx/app/saic/default.html
- Jin, C., Xu, J. y Huang, Z. (2019). Spatiotemporal analysis of regional tourism development: A semiparametric geographically weighted regression model approach. Habitat International, 87, 1-10. https://www.sciencedirect.com/science/article/pii/S0197397518311354?casa_token=aop4EK23IQMAAAAA:0iZf--O65_cIVMiF6CaGj8BRL6RXcKci5d4hXUnCkQACMFGMJMAePk0a5pyof-XpKXkXMr5mrZZX
- Johnson, J. L. y Kuehn, R. (1987). The small business owner/manager’s search for external information. Journal of Small Business Management, 25(3), 53-60.
- Joseph, L. y Kuby, M. (2016). The location types of US retailers. International Journal of Applied Geospatial Research (IJAGR), 7(4), 1-22. https://dl.acm.org/doi/10.4018/IJAGR.2016100101 DOI: https://doi.org/10.4018/IJAGR.2016100101
- Jung, S. S. y Jang, S. S. (2019). To cluster or not to cluster?: Understanding geographic clustering by restaurant segment. International Journal of Hospitality Management, 77, 448-457. https://www.cabdirect.org/cabdirect/abstract/20193079111 DOI: https://doi.org/10.1016/j.ijhm.2018.08.008
- Ketels, C., Lindqvist, G. y Sölvell, Ö. (2006). Cluster initiatives in developing and transition economies. Estocolmo: Center for Strategy and Competitiveness. http://www.mea.szczecin.pl/klaster/CIsDevelopingTransitionMay06.pdf
- Kim, H. y Serfes, K. (2006). A location model with preference for variety. The Journal of Industrial Economics, 54(4), 569-595. https://www.jstor.org/stable/4622369 DOI: https://doi.org/10.1111/j.1467-6451.2006.00300.x
- Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483-499. https://www.jstor.org/stable/2937739 DOI: https://doi.org/10.1086/261763
- Kulchina, E. (2015). Personal preferences, entrepreneurs’ location choices, and firm performance. Management Science, 62(6), 1814-1829. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2665255 DOI: https://doi.org/10.1287/mnsc.2015.2199
- Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics - Theory and Methods, 26(6), 1481-1496. https://www.researchgate.net/publication/261671964_A_Spatial_Scan_Statistic DOI: https://doi.org/10.1080/03610929708831995
- Kulldorff, M., Huang, L. y Konty, K. (2009). A scan statistic for continuous data based on the normal probability model. International Journal of Health Geographics, 8(1), 58. https://link.springer.com/article/10.1186/1476-072X-8-58 DOI: https://doi.org/10.1186/1476-072X-8-58
- Kulldorff, M. y Nagarwalla, N. (1995). Spatial disease clusters: Detection and inference. Statistics in Medicine, 14(8), 799-810. https://www.satscan.org/papers/k-sm1995.pdf DOI: https://doi.org/10.1002/sim.4780140809
- Lambertini, L. y Orsini, R. (2013). On hotelling’s stability in competition with network externalities and switching costs. Papers in Regional Science, 92(4), 873-883. https://rsaiconnect.onlinelibrary.wiley.com/doi/full/10.1111/j.1435-5957.2012.00469.x DOI: https://doi.org/10.1111/j.1435-5957.2012.00469.x
- Lee, C. (2018). Geographical clustering and firm growth: Differential growth performance among clustered firms. Research Policy, 47(6), 1173-1184. https://www.sciencedirect.com/science/article/pii/S0048733318300830?casa_token=xpDvEfN1dAwAAAAA:DJUiw_0TJlLFFBUTnhlHYZS14U6bb0fPCQwNRG27HkVQDX9lbKGgQbNZMhXPLFrtQpDLLOvom9Lv DOI: https://doi.org/10.1016/j.respol.2018.04.002
- Liu, M., Li, Q., Zhang, Y., Ma, Y., Liu, Y., Feng, W., Hou, C., Amsala, E., Li, X., Wang, W., Li, W. y Guo, X. (2018). Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015. Infectious Diseases of Poverty, 7(106). https://link.springer.com/article/10.1186/s40249-018-0490-8 DOI: https://doi.org/10.1186/s40249-018-0490-8
- López, F. A., Chasco, C. y Gallo, J. L. (2015). Exploring scan methods to test spatial structure with an application to housing prices in Madrid. Papers in Regional Science, 94(2), 317-346. https://rsaiconnect.onlinelibrary.wiley.com/doi/full/10.1111/pirs.12063 DOI: https://doi.org/10.1111/pirs.12063
- López López, Á., López Pardo, G., Andrade Romo, E., Chávez Dagostino, R. M. y Espinoza Sánchez, R. (coords.). (2012). Lo glocal y el turismo. Nuevos paradigmas de interpretación. México: Academia Mexicana de Investigación Turística / Universidad de Guadalajara. http://www.cuc.udg.mx/es/lo-glocal-y-el-turismo-nuevos-paradigmas-de-interpretacion
- Losch, A. (1954). The economics of location. New Haven: Yale University Press.
- Lozano Uvario, K. M. y Méndez Guardado, P. (2018). Dinámica económica e impulso a la aglomeración: análisis del polígono “Chapultepec” en Guadalajara, Jalisco. En J. Gasca Zamora (coord.), Agenda pública para el desarrollo regional. La metropolización y la sostenibilidad. Volumen III (pp. 230-249). Ciudad de México: Universidad Nacional Autónoma de México / Asociación Mexicana de Ciencias para el Desarrollo Regional, A.C. http://ru.iiec.unam.mx/4308/
- Luquín-García, M., Macedo Ruiz, E., Rojas-Altamirano, O. y López-Hernández, C. (2018). Determination of the representative socioeconomic level by BSA in the Mexican Republic. Perspectiva Empresarial, 5(2), 83-100. https://revistas.ceipa.edu.co/index.php/perspectiva-empresarial/article/view/171 DOI: https://doi.org/10.16967/rpe.v5n2a6
- Marshall, A. (1920). Principles of economics. Londres: MacMillan.
- Michelacci, C. y Silva, O. (2007). Why so many local entrepreneurs? The Review of Economics and Statistics, 89(4), 615-633. https://econpapers.repec.org/article/tprrestat/v_3a89_3ay_3a2007_3ai_3a4_3ap_3a615-633.htm DOI: https://doi.org/10.1162/rest.89.4.615
- Ng, R. T. y Han, J. (2002). CLARANS: A method for clustering objects for spatial data mining. IEEE Transactions on Knowledge and Data Engineering, 14(5), 1003-1016. https://ieeexplore.ieee.org/document/1033770 DOI: https://doi.org/10.1109/TKDE.2002.1033770
- Nicotra, M., Romano, M. y Del Giudice, M. (2014). The evolution dynamic of a cluster knowledge network: The role of firms’ absorptive capacity. Journal of the Knowledge Economy, 5(1), 70-93. https://link.springer.com/article/10.1007/s13132-012-0140-5 DOI: https://doi.org/10.1007/s13132-012-0140-5
- O’Brien, A., Sherrard-Smith, E., Sile, B., Watts, C. y Simms, I. (2018). Spatial clusters of gonorrhoea in England with particular reference to the outcome of partner notification: 2012 and 2013. PLoS ONE, 13(4). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0195178 DOI: https://doi.org/10.1371/journal.pone.0195178
- Pérez-Suárez, A., Martínez-Trinidad, J. F. y Carrasco-Ochoa, J. A. (2019). A review of conceptual clustering algorithms. Artificial Intelligence Review, 52(2), 1267-1296. https://dl.acm.org/doi/10.1007/s10462-018-9627-1 DOI: https://doi.org/10.1007/s10462-018-9627-1
- Pfitzner, D., Leibbrandt, R. y Powers, D. (2009). Characterization and evaluation of similarity measures for pairs of clusterings. Knowledge and Information Systems, 19(3), 361. https://link.springer.com/article/10.1007/s10115-008-0150-6 DOI: https://doi.org/10.1007/s10115-008-0150-6
- Pineda, R. C., Lerner, L. D., Miller, M. C. y Phillips, S. J. (1998). An investigation of factors affecting the information-search activities of small business managers. Journal of Small Business Management, 36(1), 60. https://www.questia.com/library/journal/1G1-20454870/an-investigation-of-factors-affecting-the-information-search
- Porter, M. E. (1991). La ventaja competitiva de las naciones. Facetas, 91, 5-12. http://fcaenlinea1.unam.mx/anexos/1254/1254_u12_act1.pdf
- Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review Boston. 76(6), 77-90. https://www.hbs.edu/faculty/Pages/item.aspx?num=46852
- Rogerson, P. A. (2001). Data reduction: Factor analysis and cluster analysis. En P. A. Rogerson, Statistical Methods for Geography (pp. 193-209). Londres: Sage. DOI: https://doi.org/10.4135/9781849209953.n10
- Sandoval, J., Castañón-Puga, M., Gaxiola-Pacheco, C. y Suarez, E. D. (2017). Identifying clusters of complex urban-rural issues as part of policy making process using a network analysis approach: A case study in Bahía de Los Ángeles, Mexico. Sustainability, 9(6), 1059. https://www.mdpi.com/2071-1050/9/6/1059 DOI: https://doi.org/10.3390/su9061059
- Schneider, E. (1934). Johann Heinrich von Thünen. Econometrica: Journal of the Econometric Society, 2(1), 1-12. https://www.jstor.org/stable/1907947 DOI: https://doi.org/10.2307/1907947
- Setiadi, T., Pranolo, A., Aziz, M., Mardiyanto, S. y Hendrajaya, B. (2017). A model of geographic information system using graph clustering methods. 3rd International Conference on Science in Information Technology (ICSITech) (pp. 727-731). Bandung, Indonesia. https://ieeexplore.ieee.org/abstract/document/8257208 DOI: https://doi.org/10.1109/ICSITech.2017.8257208
- Sjøholt, P. (2001). Christaller revisited: Reconsidering Christaller’s analysis of services and central places. Service Industries Journal, 21(4), 198-200.
- Sobrino, J. (2016). Localización industrial y concentración geográfica en México. Estudios Demográficos y Urbanos, 31(1), 9-56. https://estudiosdemograficosyurbanos.colmex.mx/index.php/edu/article/view/1502/1495 DOI: https://doi.org/10.24201/edu.v31i1.1502
- Song, C. y Kulldorff, M. (2003). Power evaluation of disease clustering tests. International Journal of Health Geographics, 2. https://link.springer.com/article/10.1186/1476-072X-2-9 DOI: https://doi.org/10.1186/1476-072X-2-9
- Sorenson, O. y Audia, P. G. (2000). The social structure of entrepreneurial activity: Geographic concentration of footwear production in the United States, 1940-1989. American Journal of Sociology, 106(2), 424-462. https://www.jstor.org/stable/10.1086/316962 DOI: https://doi.org/10.1086/316962
- Speldekamp, D., Knoben, J. y Saka-Helmhout, A. (2020). Clusters and firm-level innovation: A configurational analysis of agglomeration, network and institutional advantages in European aerospace. Research Policy, 49(3). https://www.sciencedirect.com/science/article/pii/S0048733320300019?casa_token=-fqyB87samsAAAAA:ITceS0zHVYpQyRpjhFN7fe-tfs5p1UB-ehlGiB1Izm1YEkqn2ned9oydiadS6CCOxfy7W4tTbGUc
- Sullivan, P., Sung, J., Halbrendt, C. C. y Buescher, M. (2000). Firm size and use of information sources in location decisions. Journal of Small Business and Entrepreneurship, 15(4), 52-66. https://www.tandfonline.com/doi/abs/10.1080/08276331.2000.10593293 DOI: https://doi.org/10.1080/08276331.2000.10593293
- Tanser, F., Bärnighausen, T., Cooke, G. S. y Newell, M.-L. (2009). Localized spatial clustering of HIV infections in a widely disseminated rural South African epidemic. International Journal of Epidemiology, 38(4), 1008-1016. https://spiral.imperial.ac.uk/bitstream/10044/1/20038/2/International%20Journal%20of%20Epidemiology_38_4_2009.pdf DOI: https://doi.org/10.1093/ije/dyp148
- Telizhenko, O., Pavlenko, O., Martynets, V. y Rybalchenko, S. (2019). Modeling the influence of cluster components on the economic development of a territory. TEM Journal, 8(3), 900. https://www.temjournal.com/content/83/TEMJournalAugust2019_900_907.pdf DOI: https://doi.org/10.18421/TEM83-30
- Velázquez-Castro, J. A., Vargas-Martínez, E. E., Cruz-Coria, E. y Briones-Juárez, A. (2019). Implicaciones de la innovación para la calidad en el sector pyme de restauración. Un estudio empírico de la Ciudad de México. Revista de Estudios Andaluces, 37, 50-70. https://idus.us.es/handle/11441/85818 DOI: https://doi.org/10.12795/rea.2019.i37.03
- Verduzco-Garza, T. y Gonzáles Aleu, F. (2017). Increasing competitiveness through a logistics and transportation cluster: A literature review. En Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 384-395). Bogotá, Colombia. http://ieomsociety.org/bogota2017/papers/74.pdf
- Vlachou, C. y Iakovidou, O. (2015). The evolution of studies on business location factors. Journal of Developmental Entrepreneurship, 20(4). https://www.worldscientific.com/doi/abs/10.1142/S1084946715500235 DOI: https://doi.org/10.1142/S1084946715500235
- Weber, A. (1982). On the location of industries. Progress in Geography, 6(1), 120-128. https://journals.sagepub.com/doi/abs/10.1177/030913258200600109 DOI: https://doi.org/10.1177/030913258200600109
- Wheeler, D. C. (2007). A comparison of spatial clustering and cluster detection techniques for childhood leukemia incidence in Ohio, 1996-2003. International Journal of Health Geographics, 6. https://link.springer.com/article/10.1186/1476-072X-6-13 DOI: https://doi.org/10.1186/1476-072X-6-13
- Yao, Z., Tang, J. y Zhan, F. B. (2011). Detection of arbitrarily-shaped clusters using a neighbor-expanding approach: A case study on murine typhus in South Texas. International Journal of Health Geographics, 10. https://link.springer.com/article/10.1186/1476-072X-10-23 DOI: https://doi.org/10.1186/1476-072X-10-23
- Zhang, Z. J. (1995). Price-matching policy and the principle of minimum differentiation. The Journal of Industrial Economics, 43(3), 287-299. https://www.jstor.org/stable/2950581 DOI: https://doi.org/10.2307/2950581