Herd behaviour and the emergence of clusters

REFERENCES

• Ajraldi, V., Pittavino, M., & Venturino, E. (2011). Modeling herd behavior in population systems. Nonlinear Analysis: Real World Applications, 12(4), 2319–2338. https://doi.org/10.1016/j.nonrwa.2011.02.002
   Google Scholar
• Alós-Ferrer, C., Hügelschäfer, S., & Li, J. (2016). Inertia and decision making. Frontiers in Psychology, 7. Article no. 169. https://doi.org/10.3389/fpsyg.2016.00169
   Google Scholar
• Armstrong, H., & Taylor, J. (2000). Regional Economics and policy: Vol. 3rd edition. Blackwell.
   Google Scholar
• Armstrong, M., & Huck, S. (2010). Behavioral economics as applied to firms: A primer. MPRA Paper, 20356. https://mpra.ub.uni-muenchen.de/20356/.
   Google Scholar
• Arthur, W. B. (2021). Foundations of complexity economics. Nature Reviews Physics, 3(2), 136–145. https://doi.org/10.1038/s42254-020-00273-3
   Google Scholar
• Arthur, W. B., Ermoliev, Y. M., & Kaniovski, Y. M. (1987). Path-dependent processes and the emergence of macro-structure. European Journal of Operational Research, 30(3), 294–303. https://doi.org/10.1016/0377-2217(87)90074-9
   Google Scholar
• Baddeley, M. (2010). Herding, social influence and economic decision-making: Socio-psychological and neuroscientific analyses. Philosophical Transactions of the Royal Society B, 365(1538), 281–290. https://doi.org/10.1098/rstb.2009.0169
   Google Scholar
• Balland, P.-A., Boschma, R., Crespo, J., & Rigby, D. L. (2019). Smart specialization policy in the European union: Relatedness, knowledge complexity and regional diversification. Regional Studies, 53(9), 1252–1268. https://doi.org/10.1080/00343404.2018.1437900
   Google Scholar
• Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817. https://doi.org/10.2307/2118364
   Google Scholar
• Beaudry, C., & Schiffauerova, A. (2009). Who’s right, Marshall or Jacobs? The Localization versus urbanization debate. Research Policy, 38(2), 318–337. https://doi.org/10.1016/j.respol.2008.11.010
   Google Scholar
• Berg, N. (2014). Success from satisficing and imitation: Entrepreneurs’ location choice and implications of heuristics for local economic development. Journal of Business Research, 67(8), 1700–1709. https://doi.org/10.1016/j.jbusres.2014.02.016
   Google Scholar
• Berg, N., & Gigerenzer, G. (2010). As-if behavioral economics: Neoclassical economics in disguise? History of Economic Ideas, 1, https://doi.org/10.1400/140334
   Google Scholar
• Bikhchandani, S., Hirshleifer, D., & Welch, I. (1998). Learning from the behavior of others: Conformity, fads, and informational cascades. Journal of Economic Perspectives, 12(3), 151–170. https://doi.org/10.1257/jep.12.3.151
   Google Scholar
• Boeing, G. (2018). The effects of inequality, density, and heterogeneous residential preferences on Urban displacement and metropolitan structure: An agent-based model. Urban Science, 2(3), 76. https://doi.org/10.3390/urbansci2030076
   Google Scholar
• Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99(Supplement 3), 7280–7287. https://doi.org/10.1073/pnas.082080899
   Google Scholar
• Boschma, R. A., & Frenken, K. (2006). Why is Economic Geography not an Evolutionary science? Towards an Evolutionary Economic Geography. Journal of Economic Geography, 6(3), 273–302. https://doi.org/10.1093/jeg/lbi022
   Google Scholar
• Braczyk, H.-J., Cooke, P., & Heidenreich, M. (2004). Regional innovation systems: The role of governances in a globalized world. Routledge.
   Google Scholar
• Brouwer, A. E., Mariotti, I., & Ommeren, J. N. v. (2004). The firm relocation decision: An empirical investigation. The Annals of Regional Science, 38(2), 335–347. https://doi.org/10.1007/s00168-004-0198-5
   Google Scholar
• Brunes, F. (2005). Overbuilding in office markets: Are behavioural aspects important? Building and real estate economics, Department of Infrastructure, Royal Institute of Technology.
   Google Scholar
• Caragliu, A., De Dominicis, L., & de Groot, H. L. F. (2016). Both Marshall and Jacobs were right!. Economic Geography, 92(1), 87–111. https://doi.org/10.1080/00130095.2015.1094371
   Google Scholar
• Cipriani, M., & Guarino, A. (2009). Herd Behavior in Financial Markets: An experiment with Financial Market professionals. Journal of the European Economic Association, 7(1), 206–233. https://doi.org/10.1162/JEEA.2009.7.1.206
   Google Scholar
• Cohen, A. R., Gadon, H., & Miaoulis, G. (1976). Decision making in firms: The impact of noneconomic factors. Journal of Economic Issues, 10(2), 242–258. https://doi.org/10.1080/00213624.1976.11503343
   Google Scholar
• Content, J., & Frenken, K. (2016). Related variety and economic development: A literature review. European Planning Studies, 24(12), 2097–2112. https://doi.org/10.1080/09654313.2016.1246517
   Google Scholar
• Cyert, R. M., & Hedrick, C. L. (1972). Theory of the firm: Past, present, and future; An interpretation. Journal of Economic Literature, 10(2), 398–412.
   Google Scholar
• de Bok, M., & van Oort, F. (2011). Agglomeration economies, accessibility, and the spatial choice behavior of relocating firms. Journal of Transport and Land Use, 4(1), 5–24. JSTOR. https://doi.org/10.5198/jtlu.v4i1.144
   Google Scholar
• Ding, M., Ross, W. T., & Rao, V. R. (2010). Price as an indicator of quality: Implications for utility and demand functions. Journal of Retailing, 86(1), 69–84. https://doi.org/10.1016/j.jretai.2010.01.002
   Google Scholar
• Diodato, D., Neffke, F., & O’Clery, N. (2018). Why do industries coagglomerate? How Marshallian externalities differ by industry and have evolved over time. Journal of Urban Economics, 106, 1–26. https://doi.org/10.1016/j.jue.2018.05.002
   Google Scholar
• Duranton, G., & Puga, D. (2001). Nursery cities: Urban diversity, process innovation, and the life cycle of products. American Economic Review, 91(5), 1454–1477. https://doi.org/10.1257/aer.91.5.1454
   Google Scholar
• Durlauf, S. N. (2004). Neighborhood effects. In J. V. Henderson, & J.-F. Thisse (Eds.), Handbook of Urban and Regional Economics: Cities and geography (pp. 2173–2242). Elsevier.
   Google Scholar
• Edmans, A. (2009). Blockholder trading, market efficiency, and Managerial myopia. The Journal of Finance, 64(6), 2481–2513. https://doi.org/10.1111/j.1540-6261.2009.01508.x
   Google Scholar
• Elgar, I., Farooq, B., & Miller, E. J. (2009). Modeling location decisions of office firms: Introducing anchor points and constructing choice sets in the model system. Transportation Research Record: Journal of the Transportation Research Board, 2133(1), 56–63. https://doi.org/10.3141/2133-06
   Google Scholar
• Ellison, G. D., & Glaeser, E. L. (1997). Geographic concentration in US manufacturing industries: A dartboard approach. Journal of Political Economy, 105(5), 889–927. https://doi.org/10.1086/262098
   Google Scholar
• Ellison, G. D., Glaeser, E. L., & Kerr, W. R. (2007). What causes industry agglomeration? Evidence from coagglomeration patterns. SSRN ELibrary, http://ssrn.com/paper=980966.
   Google Scholar
• Elsner, W. (2017). Complexity Economics as heterodoxy: Theory and policy. Journal of Economic Issues, 51(4), 939–978. https://doi.org/10.1080/00213624.2017.1391570
   Google Scholar
• Frenken, K., van Oort, F. G., & Verburg, T. (2007). Related Variety, unrelated Variety and Regional Economic growth. Regional Studies, 41(5), 685–697. https://doi.org/10.1080/00343400601120296
   Google Scholar
• Gao, J., Jun, B., Pentland, A., ‘Sandy,’ Zhou, T., & Hidalgo, C. A. (2021). Spillovers across industries and regions in China’s regional economic diversification. Regional Studies, https://www.tandfonline.com/doi/abs/10.1080/00343404.2021.1883191.
   Google Scholar
• Gordon, I. R., & McCann, P. (2005). Innovation. Agglomeration, and Regional Development. Journal of Economic Geography, 5(5), 523–543. https://doi.org/10.1093/jeg/lbh072
   Google Scholar
• Graf, H., & Broekel, T. (2020). A shot in the dark? Policy influence on cluster networks. Research Policy, 49(3), 103920. https://doi.org/10.1016/j.respol.2019.103920
   Google Scholar
• Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., Huse, G., Huth, A., Jepsen, J. U., Jørgensen, C., Mooij, W. M., Müller, B., Pe’er, G., Piou, C., Railsback, S. F., Robbins, A. M., … DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1), 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023
   Google Scholar
• Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., Deangelis, D. L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., Johnston, A. S. A., Milles, A., Nabe-Nielsen, J., Polhill, J. G., Radchuk, V., Rohwäder, M. S., Stillman, R. A., Thiele, J. C., & Ayllón, D. (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23(2), Article 2. http://eprints.bournemouth.ac.uk/33918/. https://doi.org/10.18564/jasss.4259
   Google Scholar
• Hervas-Oliver, J.-L., & Albors-Garrigos, J. (2014). Are technology gatekeepers renewing clusters? Understanding gatekeepers and their dynamics across cluster life cycles. Entrepreneurship & Regional Development, 26(5–6), 431–452. https://doi.org/10.1080/08985626.2014.933489
   Google Scholar
• Hotelling, H. (1929). Stability in economic competition. Economic Journal, 39(153), 41–57. https://doi.org/10.2307/2224214
   Google Scholar
• Iqbal, K., Islam, A., List, J. A., & Nguyen, V. (2021). Myopic Loss Aversion and Investment Decisions: From the Laboratory to the Field (Working Paper No. 28730; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w28730.
   Google Scholar
• Isaksen, A., Martin, R., & Trippl, M. (2018). New avenues for regional innovation systems—theoretical advances, empirical cases and policy lessons. Springer.
   Google Scholar
• Kaplan, S., & Henderson, R. (2005). Inertia and incentives: Bridging Organizational Economics and Organizational theory. Organization Science, 16(5), 509–521. https://doi.org/10.1287/orsc.1050.0154
   Google Scholar
• Keynes, J. M. (1936). The general theory of employment, interest, and money. Palgrave Macmillan.
   Google Scholar
• Klepper, S. (2007). Disagreements, spinoffs, and the evolution of Detroit as the capital of the US automobile industry. Management Science, 53(4), 616–631. https://doi.org/10.1287/mnsc.1060.0683
   Google Scholar
• Klepper, S. (2010). The origin and growth of industry clusters: The making of Silicon Valley and Detroit. Journal of Urban Economics, 67(1), 15–32. https://doi.org/10.1016/j.jue.2009.09.004
   Google Scholar
• Koetsier, I., & Bikker, J. A. (2017). Herding behaviour of Dutch pension funds in sovereign bond investments (SSRN scholarly Paper ID 3041258). Social Science Research Network, https://doi.org/10.2139/ssrn.3041258
   Google Scholar
• Koster, H. R. A., van Ommeren, J., & Rietveld, P. (2014). Is the sky the limit? High-rise buildings and office rents. Journal of Economic Geography, 14(1), 125–153. https://doi.org/10.1093/jeg/lbt008
   Google Scholar
• Larwood, L., & Whittaker, W. (1977). Managerial myopia: Self-serving biases in organizational planning. Journal of Applied Psychology, 62(2), 194–198. https://doi.org/10.1037/0021-9010.62.2.194
   Google Scholar
• Lejarraga, J., & Martinez-Ros, E. (2008). Comparing small vs large firms’ R&D productivity through a dual process perspective. Academy of Management Proceedings, 2008(1), 1–6. https://doi.org/10.5465/ambpp.2008.33631743
   Google Scholar
• Louw, E. (1996). Kantoorgebouw en vestigingsplaats. Een geografisch onderzoek naar de rol van huisvesting bij locatiebeslissingen van kantoorhoudende organisaties [TU Delft]. http://resolver.tudelft.nl/uuid:3f62884d-9375-44b5-b42a-ef8457b705bb.
   Google Scholar
• Luo, B., & Lin, Z. (2013). A decision tree model for herd behavior and empirical evidence from the online P2P lending market. Information Systems and E-Business Management, 11(1), 141–160. https://doi.org/10.1007/s10257-011-0182-4
   Google Scholar
• Lux, T. (1995). Herd behaviour, bubbles and crashes. The Economic Journal, 105(431), 881. https://doi.org/10.2307/2235156
   Google Scholar
• Malmberg, A., & Maskell, P. (2002). The elusive concept of Localization economies: Towards a knowledge-based theory of spatial clustering. Environment and Planning A: Economy and Space, 34(3), 429–449. https://doi.org/10.1068/a3457
   Google Scholar
• Marini, M., Chokani, N., & Abhari, R. S. (2019). Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne. Computers, Environment and Urban Systems, 78, 101400. https://doi.org/10.1016/j.compenvurbsys.2019.101400
   Google Scholar
• Marshall, A. (1890). Principles of economics: An introductory volume. Macmillan.
   Google Scholar
• Martellato, D. (1998). Innovation, agglomeration and complexity in Urban systems. In C. S. Bertuglia, G. Bianchi, & A. Mela (Eds.), The city and Its sciences (pp. 439–452). Physica-Verlag HD.
   Google Scholar
• Maskell, P., & Malmberg, A. (2007). Myopia, knowledge development and cluster evolution. Journal of Economic Geography, 7(5), 603–618. https://doi.org/10.1093/jeg/lbm020
   Google Scholar
• Milidonis, A., & Stathopoulos, K. (2014). Managerial incentives, risk aversion, and debt. Journal of Financial and Quantitative Analysis, 49(2), 453–481. https://doi.org/10.1017/S0022109014000301
   Google Scholar
• Miller, J. H., & Page, S. E. (2007). Complex adaptive systems: An Introduction to computational models of social life (STU-student edition). Princeton University Press. http://www.jstor.org/stable/j.ctt7s3kx.
   Google Scholar
• Minniti, M. (2005). Entrepreneurship and network externalities. Journal of Economic Behavior & Organization, 57(1), 1–27. https://doi.org/10.1016/j.jebo.2004.10.002
   Google Scholar
• Nguyen, C. Y., Sano, K., Tran, T. V., & Doan, T. T. (2013). Firm relocation patterns incorporating spatial interactions. The Annals of Regional Science, 50(3), 685–703. https://doi.org/10.1007/s00168-012-0523-3
   Google Scholar
• Olsson, G., & Gale, S. (1968). Spatial theory and human behavior. Papers of the Regional Science Association, 21(1), 229–242. https://doi.org/10.1007/BF01952731
   Google Scholar
• Pellenbarg, P., van Steen, P., & van Wissen, L. (Eds.). (2005). Ruimtelijke aspecten van de bedrijvendynamiek in Nederland. Assen: Van Gorcum.
   Google Scholar
• Posen, H. E., Lee, J., & Yi, S. (2013). The power of imperfect imitation: The power of imperfect imitation. Strategic Management Journal, 34(2), 149–164. https://doi.org/10.1002/smj.2007
   Google Scholar
• Privault, N. (2013). Understanding Markov chains: Examples and applications. Heidelberg/New York: Springer.
   Google Scholar
• Rosenthal, S. S., & Strange, W. C. (2004). Evidence on the nature and sources of agglomeration economies. In V. Henderson, & J.-F. Thisse (Eds.), Handbook of Regional and Urban economics (pp. 2119–2171). Elsevier.
   Google Scholar
• Seiler, M. J., Lane, M. A., & Harrison, D. M. (2014). Mimetic herding Behavior and the decision to strategically default. The Journal of Real Estate Finance and Economics, 49(4), 621–653. https://doi.org/10.1007/s11146-012-9386-8
   Google Scholar
• Simon, H. A. (1955). A Behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99. https://doi.org/10.2307/1884852
   Google Scholar
• Simon, H. A. (2013). Administrative behavior (4th ed.). Simon and Schuster.
   Google Scholar
• Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2004). Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24(2), 311–322. https://doi.org/10.1111/j.0272-4332.2004.00433.x
   Google Scholar
• Smit, M. J. (2010). Agglomeration and innovation: Evidence from Dutch Microdata [Vrije Universiteit]. http://dare.ubvu.vu.nl/handle/1871/16065.
   Google Scholar
• Spencer, G. M. (2012). Creative economies of scale: An agent-based model of creativity and agglomeration. Journal of Economic Geography, 12(1), 247–271. https://doi.org/10.1093/jeg/lbr002
   Google Scholar
• Stein, J. C. (1988). Takeover threats and Managerial myopia. Journal of Political Economy, 96(1), 61–80. https://doi.org/10.1086/261524
   Google Scholar
• Suire, R., & Vicente, J. (2008). Why do some places succeed when others decline? A social interaction model of cluster viability. Journal of Economic Geography, 9(3), 381–404. https://doi.org/10.1093/jeg/lbn053
   Google Scholar
• Townroe, P. (1973). The supply of mobile industry: A cross-sectional analysis. Regional and Urban Economics, 2(4), 371–385. https://doi.org/10.1016/0034-3331(73)90003-1
   Google Scholar
• Townroe, P. (1991). Rationality in industrial location decisions. Urban Studies, 28(3), 383–392. https://doi.org/10.1080/00420989120080411
   Google Scholar
• van Dijk, J., & Pellenbarg, P. H. (2000). Firm relocation decisions in The Netherlands: An ordered logit approach. Papers in Regional Science, 79(2), 191–219. https://doi.org/10.1007/s101100050043
   Google Scholar
• van Witteloostuijn, A. (1998). Bridging Behavioral and Economic theories of decline: Organizational inertia, Strategic competition, and chronic failure. Management Science, 44(4), 501–519. https://doi.org/10.1287/mnsc.44.4.501
   Google Scholar
• Vicente, J., Dalla Pria, Y., & Suire, R. (2007). The ambivalent role of mimetic behavior in proximity dynamics: Evidence from the French ‘Silicon Sentier’. In J. Suriñach, R. Moreno, & E. Vay (Eds.), Knowledge externalities, innovation clusters and Regional development (pp. 61–91). Edward Elgar.
   Google Scholar
• Vicente, J., & Suire, R. (2007). Informational cascades versus network externalities in locational choice: Evidence of ‘ICT clusters’ formation and stability. Regional Studies, 41(2), 173–184. https://doi.org/10.1080/00343400601108424
   Google Scholar
• Weber, A. (1909). Über den Standort der industrien: Reine theorie des Standorts. Mohr.
   Google Scholar
• Weizsäcker, G. (2010). Do We follow others when We should? A simple test of rational expectations. American Economic Review, 100(5), 2340–2360. https://doi.org/10.1257/aer.100.5.2340
   Google Scholar
• Wernberg, J. (2017). The Inherent Complexity of Agglomeration: Essays on the self-organization of urban economies [Lund University]. https://portal.research.lu.se/portal/en/publications/the-inherent-complexity-of-agglomeration(0031ae28-1bbd-40b7-995d-fe4943ff4208).html.
   Google Scholar
• Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social, and engineered complex systems with NetLogo. The MIT Press.
   Google Scholar
• Willigers, J., & van Wee, B. (2011). High-speed rail and office location choices. A stated choice experiment for the Netherlands. Journal of Transport Geography, 19(4), 745–754. https://doi.org/10.1016/j.jtrangeo.2010.09.002
   Google Scholar
• Zhao, L., Yang, G., Wang, W., Chen, Y., Huang, J. P., Ohashi, H., & Stanley, H. E. (2011). Herd behavior in a complex adaptive system. Proceedings of the National Academy of Sciences, 108(37), 15058–15063. https://doi.org/10.1073/pnas.1105239108
   Google Scholar