Understanding “scaleup” location choices in European cities: an empirical analysis

Autores/as

DOI:

https://doi.org/10.17561/ree.n2.2025.9039

Palabras clave:

scaleups, high-growth firms, location, entrepreneurship, entrepreneurial ecosystem

Resumen

This study investigates the factors influencing scaleup location choices in European cities using a diverse dataset and statistical techniques such as PLS-SEM. According to the literature, a scaleup is a new entrepreneurial company, up to 10 years old, that has achieved a stable and consistent growth rate. The results highlight the significant relationships between scaleup location choices and factors like city climate, working environment, technological development, and educational level. A sequential model shows the direct and positive effect of education on scaleup location choices, while also revealing relationships between city climate, working environment and technology. The research offers valuable insights for policymakers and entrepreneurs seeking to enhance cities’ attractiveness for scaleup businesses. Fostering a supportive entrepreneurial ecosystem, promoting technological development, and improving the working environment emerge as key strategies for attracting and retaining scaleup companies in European cities. This study contributes to the literature on urban entrepreneurship and regional development by exploring the impact of novel variables and examining the role of the entrepreneurial ecosystem.

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Biografía del autor/a

  • Virginia Pérez-Benítez, Universidad de Málaga

    Virginia Perez-Benitez is a professor of Economics and Business Administration at the University of Malaga, Spain, in the Department of Economics and Business Administration. His research has focused on quantitative methods in business and economics research.

  • Pablo Gemar, Universidad de Málaga

    Pablo Gemar, PhD, is an accomplished professional with extensive expertise in business management and a distinguished background in Economics and Business. His research has advanced quantitative methods in these fields, leaving a lasting impact on academia and industry.

  • German Gemar, Universidad de Málaga

    German Gemar es Profesor de Economía y Administración de Empresas en la Universidad de Málaga, España, en el Departamento de Economía y Administración de Empresas. Es Doctor en Administración de Empresas por la Universidad de Málaga. Su investigación se ha centrado en gestión estratégica, negocios, supervivencia empresarial, turismo, hotelería, medio ambiente, responsabilidad social corporativa y distancia cultural. También ha dirigido hoteles durante 15 años y ha trabajado como director general de la Diputación Provincial de Málaga.

Referencias

thinknow. (2019). Innovation Cities™ Program. Retrieved 06 2025, from Innovation Cities™ Program: https://www.innovation-cities.com/europe-cities-ranking-2019-innovation-cities/18839/

Acs, Z., & Armington, C. (2004). The impact of geographic differences in human capital on service firm formation rates. Journal of Urban Economics, 56(2), 244-278. https://doi.org/10.1016/j.jue.2004.03.008

Acs, Z., & Audretsch, D. (2003). Innovation and technological change. In Handbook of entrepreneurship research: An interdisciplinary survey and introduction (pp. 55-79). Boston, MA: Springer US. In Handbook of entrepreneurship research: An interdisciplinary survey and introduction, 55-79.

Acs, Z., Sameeksha, D., & Hessels, J. (2008). Entrepreneurship, economic development and institutions. Small business economics, 31, 219-234. Retrieved from https://doi.org/10.1007/s11187-008-9135-9

Ahn, K., & Winters, J. (2022). Does education enhance entrepreneurship? Small Business Economics(61), 717-743. https://doi.org/10.1007/s11187-022-00701-x

Akın, B., & Seyfettinoğlu, Ü. (2022). Factors determining the location decision: Analysis of location choice preferences of the ICI-1000 companies with the nested logit model. Central Bank Review, 22(1), 57-75. https://doi.org/10.1016/j.cbrev.2022.03.001

Ali, F., Rasoolimanesh, S., Sarstedt, M., Ringle, C., & Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management., 30(1), 514-538. https://doi.org/10.1108/IJCHM-10-2016-0568

Alizadeh, H., & Sharifi, A. (2023). Societal smart city: Definition and principles for post-pandemic urban policy and practice. Cities, 134, 104207. https://doi.org/10.1016/j.cities.2023.104207

Arauzo-Carod, J., Liviano-Solis, D., & Manjón-Antolín, M. (2010). Empirical studies in industrial location: An assessment of their methods and results. Journal of Regional Science, 50(3), 685-711. https://doi.org/10.1111/j.1467-9787.2009.00625.x

Arauzo‐Carod, J.-M. (2013). Location determinants of new firms: does skill level of human capital really matter? Growth and Change, 44(1), 118-148. https://doi.org/10.1111/grow.12004

Audretsch, D. (1995). Innovation and industry evolution. MIT press.

Audretsch, D., & Belitski, M. (2017). Entrepreneurial ecosystems in cities: establishing the framework conditions. The Journal of Technology Transfer, 42, 1030-1051. https://doi.org/10.1007/s10961-016-9473-8

Audretsch, D., & Feldman, M. (1996). R&D spillovers and the geography of innovation and production. The American economic review, 86(3), 630-640. Retrieved from http://www.jstor.org/stable/2118216

Audretsch, D., & Fritsch, M. (2002). Growth regimes over time and space. Regional studies, 36(2), 113-124. https://doi.org/10.1080/00343400220121909

Audretsch, D., & Keilbach, M. (2004). Entrepreneurship capital and economic performance. Regional studies, 38(8), 949-959.

Autio, E. (2016). Entrepreneurship support in Europe: Trends and challenges for EU policy. Brussels: Policy Reports. Brussels: European Commission. https://doi.org/10.13140/RG.2.1.1857.1762

Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94. https://doi.org/10.1007/BF02723327

Berkowitz, D., & DeJong, D. (2005). Entrepreneurship and post‐socialist growth. Oxford bulletin of economics and statistics, 67(1), 25-46. https://doi.org/10.1111/j.1468-0084.2005.00108.x

Beynon, M., Jones, P., & Pickernell, D. (2019). The role of entrepreneurship, innovation, and urbanity-diversity on growth, unemployment, and income: US state-level evidence and an fsQCA elucidation,. Journal of Business Research, 675-687. https://doi.org/10.1016/j.jbusres.2019.01.074

Block, J., Hoogerheide, L., & Thurik, R. (2013). Education and entrepreneurial choice: An instrumental variables analysis. International Small Business Journal, 31(1), 23-33. https://doi.org/10.1177/0266242611400470

Cai, X., Lu, Y., & Wang, J. (2018). The impact of temperature on manufacturing worker productivity: Evidence from personnel data. Journal of Comparative Economics, 46(4), 889-905. https://doi.org/10.1016/j.jce.2018.06.003

Chang, X., & Li, J. (2019). Business performance prediction in location-based social commerce. Expert Systems with Applications, 126, 112-123. https://doi.org/10.1016/j.eswa.2019.01.086

Chen, M., Huang, X., Cheng, J., Tang, Z., & Huang, G. (2023). Urbanization and vulnerable employment: Empirical evidence from 163 countries in 1991–2019. Cities, 135, 104208. https://doi.org/10.1016/j.cities.2023.104208

Cheng, S., Stough, R., & Jackson, R. (2009). Measuring and building high-quality entrepreneurship: a research prospectus. Innovation: The European Journal of Social Science Research, 22(3), 329–340. https://doi.org/10.1080/13511610903399088

Chin, W., Cheah, J.-H., Liu, Y., Ting, H., & Lim, X.-J. (2020). Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research. Industrial Management & Data Systems, 120(12), 2161 - 2209. https://doi.org/10.1108/IMDS-10-2019-0529

Clark, L., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. https://doi.org/10.1037/14805-012

Craig, C., & Feng, S. (2018). A temporal and spatial analysis of climate change, weather events, and tourism businesses. Tourism Management, 67, 351-361. https://doi.org/10.1016/j.tourman.2018.02.013

Craig, C., Ma, S., Karabas, I., & Feng, S. (2021). Camping, weather, and disasters: Extending the Construal Level Theory. Journal of Hospitality and Tourism Management, 49, 353-363. https://doi.org/10.1016/j.jhtm.2021.10.005

Darwish, M. (2023). Optimal workday length considering worker fatigue and employer profit. Computers & Industrial Engineering, 109162. https://doi.org/10.1016/j.cie.2023.109162

Day, J., Chin, N., Sydnor, S., & Cherkauer, K. (2013). Weather, climate, and tourism performance: A quantitative analysis. Tourism Management Perspectives, 5, 51-56. https://doi.org/10.1016/j.tmp.2012.11.001

Diamantopoulos, A. (1999). Viewpoint – Export performance measurement: reflective versus formative indicators. International Marketing Review, 16(6), 444-457. https://doi.org/10.1108/02651339910300422

Eurostat, O.E.C.D. (2007). Eurostat-OECD Manual on Business Demography Statistics. Luxembourg: Office for Official Publications of the European Communities.

Falk, R., & Miller, N. (1992). A primer for soft modeling. University of Akron Press.

Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American statistical Association, 70(350), 320-328. https://doi.org/10.1080/01621459.1975.10479865

Glaeser, E., Kerr, W., & Ponzetto, G. (2010). Clusters of entrepreneurship. Journal of Urban Economics, 67(1), 150-168. https://doi.org/10.1016/j.jue.2009.09.008

Gordon, R., & Sarada. (2018). How should taxes be designed to encourage entrepreneurship? Journal of Public Economics, 166, 1-11. https://doi.org/10.1016/j.jpubeco.2018.08.003

Guo, Z., Wilson, N., & Rahbee, A. (2007). Impact of weather on transit ridership in Chicago, Illinois. Transportation Research Record, 2034(1), 3-10. https://doi.org/10.3141/2034-01

Hair , J., Hult, G., Ringle, C., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: Sage.

Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027

Hair, J., Hollingsworth, C., Randolph, A., & Loong Chong, A. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130

Hair, J., Hult, G., Ringle, C., & Sarstedt, M. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the academy of marketing science, 45(5), 616-632. https://doi.org/10.1007/s11747-017-0517-x

Hair, J., Ringle, C., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202

Hair, J., Risher, J., Sarstedt, M., & Ringle, C. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203

Hanafiah, M. (2020). Formative Vs. Reflective Measurement Model: Guidelines for Structural Equation Modeling Research. International Journal of Analysis and Applications, 18, 876-889. https://doi.org/10.28924/2291-8639-18-2020-876

Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8

Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. London: Sage publications.

Hosseini, S., Peluffo, D., Okoye, K., & Nganji, J. (2021). The Impact of Technological Advancements on Educational Innovation (VSI-tei). Computers & Electrical Engineering, 93, 107333. https://doi.org/10.1016/j.compeleceng.2021.107333

Isenberg, D., & Onyemah, V. (2016). Fostering scale up ecosystems for regional economic growth. In Global Entrepreneurship Congress. 71-97. https://doi.org/10.1162/inov_a_00248

Jafari‐Sadegh, V., Kimiagari, S., & Biancone, P. (2019). Level of education and knowledge, foresight competency and international entrepreneurship. European Business Review(32), 46-68. https://doi.org/10.1108/ebr-05-2018-0098

Jiang, S., & Cai, C. (2023). The impacts of weather conditions on metro ridership: An empirical study from three mega cities in China. Travel Behaviour and Society, 31, 166-177. https://doi.org/10.1016/j.tbs.2022.12.003

Jiménez, A., Palmero-Cámara, C., González-Santos, M., Gonzáez-Bernal, J., & Jiménez-Eguizábal, J. (2015). The impact of educational levels on formal and informal entrepreneurship. BRQ Business Research Quarterly, 18(3), 204-212.

Jo, Y., & Lee, C.-Y. (2014). Technological capability, agglomeration economies and firm location choice. Regional Studies, 48(8), 1337-1352. https://doi.org/10.1080/00343404.2012.711946

Jöreskog, K. (1970). A general method for estimating a linear structural equation system. ETS Research Bulletin Series, 2, i-41. https://doi.org/10.1002/j.2333-8504.1970.tb00783.x

Kerr, W., & Nanda, R. (2009). Democratizing entry: Banking deregulations, financing constraints, and entrepreneurship. Journal of Financial Economics, 94(1), 124-149. https://doi.org/10.1016/j.jfineco.2008.12.003

Kline, R. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.

Lafuente, E., Vaillant, Y., & Serarols, C. (2010). Location decisions of knowledge-based entrepreneurs: why some Catalan KISAs choose to be rural? Technovation, 30(11-12), 590-600. https://doi.org/10.1016/j.technovation.2010.07.004

Lee, N., & Clarke, S. (2019). Do low-skilled workers gain from high-tech employment growth? High-technology multipliers, employment and wages in Britain. Research Policy, 48(9), 103803. https://doi.org/10.1016/j.respol.2019.05.012

Lee, N., & Rodríguez-Pose, A. (2016). Is there trickle-down from tech? Poverty, employment, and the high-technology multiplier in US cities. Annals of the American Association of Geographers, 106(5), 1114-1134. https://doi.org/10.1080/24694452.2016.1184081

Leendertse, J., Schrijvers, M., & Stam, E. (2022). Measure Twice, Cut Once: Entrepreneurial Ecosystem Metrics. Research Policy, 51(9), 104336. https://doi.org/10.1016/j.respol.2021.104336

Li, M., Goetz, S., Partridge, M., & Fleming, D. (2016). Location determinants of high-growth firms. Entrepreneurship & Regional Development, 28(1-2), 97-125. https://doi.org/10.1080/08985626.2015.1109003

Luo, Q., Hu, H., Feng, D., & He, X. (2022). How does broadband infrastructure promote entrepreneurship in China: Evidence from a quasi-natural experiment. Telecommunications Policy, 46(10), 102440. https://doi.org/10.1016/j.telpol.2022.102440

Malecki, E. (1985). Industrial location and corporate organization in high technology industries. Economic Geography. Economic Geography, 61(4), 345-369. https://doi.org/10.2307/144054

Malecki, E. (2018). Entrepreneurship and entrepreneurial ecosystems. Geography Compass, 12(3), e12359. https://doi.org/10.1111/gec3.12359

Marchesani, F., Masciarelli, F., & Doan, H. (2022). Innovation in cities a driving force for knowledge flows: Exploring the relationship between high-tech firms, student mobility, and the role of youth entrepreneurship. Cities, 130, 103852. https://doi.org/10.1016/j.cities.2022.103852

Mason, C., & Brown, R. (2014). Entrepreneurial ecosystems and growth oriented entrepreneurship. Final report to OECD, 30(1), 77-102.

Mind the Bridge. (2018). StartupCity Hubs in Europe. Brussels. Retrieved from https://mindthebridge.com/startupcity-hubs-in-europe/

Moore, G. (1991). Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream. New York: NY: Harper Business Essentials.

Morgado, S. (2021). Urban rehabilitation, social innovation, and new working spaces in Lisbon. Sustainability, 13(21), 11925.

Napier, G., & Hansen, C. (2011). Ecosystems for young scalable firms. FORA Group, 190-208.

Neidell, M., Zivin, J., Sheahan, M., & Willwerth, J. (2021). Temperature and work: Time allocated to work under varying climate and labor market conditions. PLoS ONE, 16(8). https://doi.org/10.1371/journal.pone.0254224

Nickell, S., Nicolitsas, D., & Dryden, N. (1997). What makes firms perform well? European economic review, 41(3-5), 783-796.

Nightingale, P., & Coad, A. (2014). Muppets and gazelles: political and methodological biases in entrepreneurship research. Industrial and corporate change, 23(1), 113-143.

Nunnally, J., & Bernstein, I. (1994). Psychometric Theory (3 ed.). New York, USA: McGraw Hill.

Nyström, K. (2008). The institutions of economic freedom and entrepreneurship: evidence from panel data. Public choice, 136, 269-282.

OECD. (2018). Rethinking Urban Sprawl: Moving Towards Sustainable Cities. Paris: OECD Publishing. Retrieved from https://doi.org/10.1787/9789264189881-en.

Onetti, A. (2014, 07 29). Scaleups. When does a Startup turn into a Scaleup. Startup Europe Partnership. Retrieved from http://startupeuropepartnership.eu/scaleups-when-does-a-startup-turn-into-a-scaleup/#

Parteka, A., Wolszczak-Derlacz, J., & Nikulin, D. (2024). How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe. Technological Forecasting and Social Change, 198, 122998. https://doi.org/10.1016/j.techfore.2023.122998

Piacentino, D., Bono, F., Cracolici, M., & Giuliani, D. (2017). A spatial analysis of new business formation: Replicative vs innovative behaviour. Spatial Statistics, 21, 390-405. https://doi.org/10.1016/j.spasta.2017.02.004

Qian, H., Acs, Z., & Stough, R. (2013). Regional systems of entrepreneurship: the nexus of human capital, knowledge and new firm formation. Journal of economic geography, 13(4), 559-587. https://doi.org/10.1093/jeg/lbs009

QS Quacquarelli Symonds Limited 1994 - 2022. (n.d.). QS Top universities. Retrieved from QS Top universities: https://www.topuniversities.com/

Ribeiro-Soriano, D., & Huarng, K.-H. (2013). Innovation and entrepreneurship in knowledge industries. Journal of Business Research, 66(10), 1964-1969. https://doi.org/10.1016/j.jbusres.2013.02.019

Ringle, C., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH, 584. Retrieved from https://www.smartpls.com

Rosol, M., & Blue, G. (2022). From the smart city to urban justice in a digital age. City, 26(4), 684-705. https://doi.org/10.1080/13604813.2022.2079881

Sarstedt, M., Ringle, C., & Hair, J. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-57413-4_15

Shane, S. (2009). Why encouraging more people to become entrepreneurs is bad public policy. Small Business Economics, 33(2), 141-149. https://doi.org/10.1007/s11187-009-9215-5

Simón-Moya, V., Revuelto-Taboada, L., & Guerrero, R. (2014). Institutional and economic drivers of entrepreneurship: An international perspective. Journal of Business Research, 67(5), 715-721. https://doi.org/10.1016/j.jbusres.2013.11.033

Skans, O. (2004). The impact of working-time reductions on actual hours and wages: evidence from Swedish register-data. Labour Economics, 11(5), 647-665. https://doi.org/10.1016/j.labeco.2003.06.002

Soler, I., Gémar, G., & Correia, M. (2020). The climate index-length of stay nexus. Journal of Sustainable Tourism, 28(9), 1272-1289. https://doi.org/10.1080/09669582.2020.1734603

Sosik, J., Kahai, S., & Piovoso, M. (2009). Silver bullet or voodoo statistics? A primer for using the partial least squares data analytic technique in group and organization research. Group & Organization Management, 34(1), 5-36. https://doi.org/10.1177/1059601108329198

Soumitra Dutta, B. L., & Wunsch-Vincent, S. (2020). The Global Innovation Index. World Intellectual Property Organization, Cornell SC Johnson College of Business, INSEAD.

Spencer, N., & Urquhart, M.-A. (2021). The impact of extreme weather on temporary work absence. Geneva: ILO Working Paper 30.

Stam, E. (2015). Entrepreneurial ecosystems and regional policy: A sympathetic critique. European Planning Studies, 23, 1759-1769. https://doi.org/10.1080/09654313.2015.1061484

Stel, A., Carre, M., & Thurik, R. (2005). The Effect of Entrepreneurial Activity on National Economic Growth. Small Business Economics, 24(3), 311-321. https://doi.org/10.1007/s11187-005-1996-6

Stephens, H. M., Mack, E. A., & Mann, J. (2022). Broadband and entrepreneurship: An empirical assessment of the connection between broadband availability and new business activity across the United States. Telematics and Informatics, 74, 101873. https://doi.org/10.1016/j.tele.2022.101873

Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the royal statistical society: Series B (Methodological), 36(2), 111-133. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x

Theofilatos, A., & Yannis, G. (2014). A review of the effect of traffic and weather characteristics on road safety. Accident Analysis & Prevention, 72, 244-256. https://doi.org/10.1016/j.aap.2014.06.017

Tomaz, E., & Henriques, C. (2023). The evolution and spatial dynamics of coworking spaces in Lisbon: a qualitative analysis. Cidades(46), 18-30.

Valliere, D., & Peterson, R. (2009). Entrepreneurship and economic growth: Evidence from emerging and developed countries. Entrepreneurship & Regional Development, 21(5-6), 459-480. https://doi.org/10.1080/08985620802332723

Vargas-Montoya, L., Gimenez, G., & Fernández-Gutiérrez, M. (2023). ICT use for learning and students’ outcomes: Does the country’s development level matter? Socio-Economic Planning Sciences, 87, 101550. https://doi.org/10.1016/j.seps.2023.101550

Vázquez-Cano, E., Parra-González, M., & López-Meneses, E. (2022). The Negative Effects of Technology on Education: A Bibliometric and Topic Modeling Mapping Analysis (2008-2019). International Journal of Instruction, 15(2), 37–60, 15(2), 37-60. https://doi.org/10.29333/iji.2022.1523a

Vital, T., Dall’erba, S., Ridley, W., & Wang, X. (2022). What do the 235 estimates from the literature tell us about the impact of weather on agricultural and food trade flows? Global Food Security, 35, 100654. https://doi.org/10.1016/j.gfs.2022.100654

Weber, A. (1929). Theory of the Location of Industries. Chicago: University of Chicago Press.

Wold, H. (1982). Soft modelling: the basic design and some extensions. Systems under indirect observation, 2, 36-37. Retrieved from https://cir.nii.ac.jp/crid/1571980074376633216.bib?lang=ja

World Bank. (2020). Doing Business. Washington, DC. https://doi.org/10.1596/978-1-4648-1440-2

World Tourism Organization. (2019). International Tourism Highlights: 2019 Edition. Madrid: World Tourism Organization (UNWTO).

World Wide Web Foundation. (2014). WebIndex Report 2014-15. Washington DC.

Xavier, S., Kelley, D., Kew, J., Herrington, M., & Vorderwülbecke, A. (2012). Global Entrepreneurship Monitor 2012 Global Report. London: Global Entrepreneurship Research Association. Retrieved from https://www.gemconsortium.org/report/48545

Zhao, Y., Liang, D., Li, J.-Y., Kehan, Y., & Zhang, N. (2023). High temperatures and urban entrepreneurship levels: Evidence from China. Science of The Total Environment, 166636-166636. https://doi.org/10.1016/j.scitotenv.2023.166636

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2025-10-23

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Pérez-Benítez, V., Gemar, P., & Gemar, G. (2025). Understanding “scaleup” location choices in European cities: an empirical analysis. Revista De Estudios Empresariales. Segunda Época, 2. https://doi.org/10.17561/ree.n2.2025.9039