Abstract
It is well established that S-shaped curves describe the diffusion processes of many innovations quite well, but little insight on the mechanics of diffusion is achieved by simple curve fitting. We propose an evolutionary model of the diffusion process, focusing on the characteristics of economic agents and on the interactions among them, and relate those determinants with the observed shape of the diffusion curve. Using simulation techniques, we show that the proposed model is able to explain why an innovation may not diffuse globally across an economy/region, even when it faces no rival innovations. Moreover, we show how network size, informational spillovers, and the behavior of innovation prices shape the diffusion process. The results regarding network size and informational spillovers rationalize the importance of informational lock-outs, proving they can influence both the aggregate adoption rate and the speed of the diffusion process. With respect to innovation prices, simulation results show that faster price decline leads to higher aggregate adoption rates, and that the diffusion process is more sensitive to the pricing dynamics than to the network size or the behavior of spillovers.
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References
Abernathy W, Utterback J (1975) A dynamic model of process and product innovation. Omega 3: 639–656
Abrahamson E, Rosenkopf L (1997) Social network effects on the extent of innovation diffusion: a computer simulation. Organ Sci 8: 289–309
Arrow KJ (1962) The economic implications of learning by doing. Rev Econ Stud 29: 155–173
Arthur WB (1989) Competing technologies and lock-in by historical small events. Econ J 99: 116–131
Arthur WB (1994) Competing technologies, increasing returns and lock-in by historical small events. In: Increasing returns and path dependence in the economy. University of Michigan Press, Ann Arbor, MI, Chap. 2, pp 13–32
Balcer Y, Lippman SA (1984) Technological expectations and adoption of improved technology. J Econ Theory 34: 292–318
Bass FM (1969) A new product growth model for consumer durables. Manage Sci 15: 2155–2227
Bikhchandani S, Hirshleifer D, Welch I (1992) A theory of fads, fashion, custom, and cultural change as informational cascades. J Polit Econ 100: 992–1026
Burt RS (1987) Social contagion and innovation, cohesion versus structural equivalence. Am J Sociol 92: 1287–1335
Cainarca GC, Colombo MG, Mariotti S (1989) An evolutionary pattern of innovation diffusion. The case of flexible automation. Res Policy 18: 59–86
Cantono S, Silverberg G (2009) A percolation model of eco-innovation diffusion: the relationship between diffusion, learning economies and subsidies. Technol Forecast Soc Change 76: 487–496
Chiffoleau Y (2005) Learning about innovation through networks: the development of environment-friendly viticulture. Technovation 25: 1193–1204
Cusumano MA, Mylonadis Y, Rosenbloom RS (1992) Strategic maneuvering and mass-market dynamics: the triumph of VHS over Beta. Bus Hist Rev 66: 51–94
David P (1994) Why are institutions the carriers of history?. Struct Change Econ Dyn 5: 205–220
Davies S (1979) The diffusion of process innovations. Cambridge University Press, Cambridge
Deroïan F (2002) Formation of social networks and diffusion of innovations. Res Policy 31: 1–12
Dosi G (1982) Technological paradigms and technological trajectories. Res Policy 11: 147–162
Geroski PA (2000) Models of technology diffusion. Res Policy 29: 603–625
Gibbons M, Metcalfe JS (1986) Technological variety and the process of competition. In: Conference on innovation diffusion Venice, 17–21 March
Gold B (1981) Technological diffusion in industry: research needs and shortcomings. J Indus Econ 29: 247–268
Goldenberg J, Libai B, Muller E (2010) The chilling effect of network externalities. Int J Res Market 27: 4–15
Golder P, Tellis GJ (2004) Growing, growing, gone: cascades, diffusion, and turning points in the product life cycle. Market Sci 23: 207–218
Granovetter M (1978) Threshold models of collective behavior. Am J Sociol 83: 1420–1443
Griliches Z (1957) Hybrid corn: an exploration in the economics of technological change. Econometrica 25: 501–522
Hall B (2005) Innovation and diffusion. In: Fagerberg J, Mowery DC, Nelson RR (eds) The Oxford handbook of innovation. Oxford University Press, Oxford, pp 459–482
Harkola J, Greve A (1995) Diffusion of technology: cohesion or structural equivalence? In: Academy of management meeting, Vancouver, pp 422–426
Huang H-C, Shih H-Y, Wu Y-C (2011) Contagion effects of national innovative capacity: comparing structural equivalence and cohesion models. Technol Forecast Soc Change 78: 244–255
Ireland NJ, Stoneman P (1986) Technological diffusion, expectations and welfare. Oxford Econ Pap 38: 283–304
Jackson MO (2008) Social and economic networks. Princeton University Press, Princeton
Kossinets G, Watts DJ (2006) Empirical analysis of an evolving social network. Science 311: 88–90
Leenders RThAJ (1995) Structure and influence: statistical models for the dynamics of actor attributes. Thela Thesis Publishers, Amsterdam
Lekvall P, Wahlbin C (1973) A study of some assumptions underlying innovation diffusion functions. Swedish J Econ 75: 362–377
Lim B, Choi M, Park M (2003) The late take-off phenomenon in the diffusion of telecommunication services: network effect and the critical mass. Inf Econ Policy 15: 537–557
Loch CH, Huberman BA (1999) A punctuated-equilibrium model of technology diffusion. Manage Sci 45: 160–177
Lundvall B-A (1992) National systems of innovation: towards a theory of innovation and interactive learning. Pinter Publications, London
Mansfield E (1961) Technical change and the rate of imitation. Econometrica 29: 741–766
Marchetti C (1991) Modeling innovation diffusion. In: Henry B (ed) Forecasting technological innovation, pp 55–77
Metcalfe JS (1981) Impulse and diffusion in the study of technical change. Futures 13: 347–359
Metcalfe JS (1988) The diffusion of innovations: an interpretative survey. In: Dosi G, Freeman C, Nelson RR, Silverberg G, Soete L (eds) Technical advance and economic theory. Frances Pinter, London, pp 560–589
Parker PM (1994) Aggregate diffusion forecasting models in marketing: a critical review. Int J Forecast 10: 353–380
Peres R, Muller E, Mahajan V (2010) Innovation diffusion and new product growth models: a critical review and research directions. Int J Res Market 27: 91–106
Reinganum J (1981) On the diffusion of new technology: a game theoretic approach. Rev Econ Stud 48: 395–405
Rogers EM (1985) Diffusion of innovations. Free Press, New York
Rohlfs J (2001) Bandwagon effects in high-technology industries. MIT Press, Cambridge
Rosenberg N (1976) Perspectives on technology. Cambridge University Press, Cambridge
Sarkar J (1998) Technological diffusion: alternative theories and historical evidence. J Econ Surv 12: 131–176
Shih H-Y (2008) Contagion effects of electronic commerce diffusion: perspective from network analysis of industrial structure. Technol Forecast Soc Change 75: 78–90
Silverberg G, Dosi G, Orsenigo O (1988) Innovation, diversity, and diffusion: a self-organization model. Econ J 98: 1032–1054
Simon HA, Egidi M (1992) Economics, bounded rationality and the cognitive revolution. Elgar, Aldershot
Spiwoks M, Bizer K, Hein O (2008) Informational cascades: a mirage?. J Econ Behav Organ 67: 193–199
Stoneman P, Battisti G (2010) The diffusion of new technology. In: Hall B, Rosenberg N (eds) Handbook of the economics of innovation. Elsevier, North Holland, Chap. 17, pp 734–760
Stoneman P, Ireland NJ (1983) The role of supply factors in the diffusion of new process technology. Econ J 93(suppl): 66–78
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Leite, R., Teixeira, A.A.C. Innovation diffusion with heterogeneous networked agents: a computational model. J Econ Interact Coord 7, 125–144 (2012). https://doi.org/10.1007/s11403-011-0086-x
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DOI: https://doi.org/10.1007/s11403-011-0086-x