Advertisement

Agent-based simulation of innovation diffusion: a review

  • Elmar Kiesling
  • Markus Günther
  • Christian Stummer
  • Lea M. Wakolbinger
Original Paper

Abstract

Mathematical modeling of innovation diffusion has attracted strong academic interest since the early 1960s. Traditional diffusion models have aimed at empirical generalizations and hence describe the spread of new products parsimoniously at the market level. More recently, agent-based modeling and simulation has increasingly been adopted since it operates on the individual level and, thus, can capture complex emergent phenomena highly relevant in diffusion research. Agent-based methods have been applied in this context both as intuition aids that facilitate theory-building and as tools to analyze real-world scenarios, support management decisions and obtain policy recommendations. This review addresses both streams of research. We critically examine the strengths and limitations of agent-based modeling in the context of innovation diffusion, discuss new insights agent-based models have provided, and outline promising opportunities for future research. The target audience of the paper includes both researchers in marketing interested in new findings from the agent-based modeling literature and researchers who intend to implement agent-based models for their own research endeavors. Accordingly, we also cover pivotal modeling aspects in depth (concerning, e.g., consumer adoption behavior and social influence) and outline existing models in sufficient detail to provide a proper entry point for researchers new to the field.

Keywords

Agent-based modeling Simulation Innovation diffusion Review 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abrahamson E, Rosenkopf L (1997) Social network effects on the extent of innovation diffusion: a computer simulation. Org Sci 8(3): 289–309CrossRefGoogle Scholar
  2. Ajzen I (1991) The theory of planned behavior. Org Behav Hum Decis Process 50(2): 179–211CrossRefGoogle Scholar
  3. Alkemade F, Castaldi C (2005) Strategies for the diffusion of innovations on social networks. Comput Econ 25(1–2): 3–23CrossRefGoogle Scholar
  4. Amaral LAN, Scala A, Barthélémy M, Stanley HE (2000) Classes of small-world networks. Proc Natl Acad Sci USA 97(21): 11,149–11,152CrossRefGoogle Scholar
  5. Arndt J (1967) Role of product-related conversations in the diffusion of a new product. J Mark Res 4(3): 291–295CrossRefGoogle Scholar
  6. Axelrod R (2007) Simulation in the social sciences. In: Reynard JP (eds) Handbook of research on nature inspired computing for economy and management. Idea Group, Hershey, pp 90–100Google Scholar
  7. Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439): 509–512CrossRefGoogle Scholar
  8. Barabási AL, Bonabeau E (2003) Scale-free networks. Sci Am 288(5): 60–69CrossRefGoogle Scholar
  9. Bass FM (1969) A new product growth for model consumer durables. Manag Sci 15(5): 215–227CrossRefGoogle Scholar
  10. Bass FM (1980) The relationship between diffusion rates, experience curves, and demand elasticities for consumer durable technological innovations. J Bus 53(3): S51–S67CrossRefGoogle Scholar
  11. Bass FM, Krishnan TV, Jain DC (1994) Why the Bass model fits without decision variables. Mark Sci 13(3): 203–223CrossRefGoogle Scholar
  12. Bass FM, Jain D, Krishnan T (2000) Modeling the marketing-mix influence in new-product diffusion. In: Mahajan V, Muller E, Wind Y (eds) New-product diffusion models. Springer, Berlin, pp 99–122Google Scholar
  13. Bemmaor AC (1994) Modeling the diffusion of new durable goods: word-of-mouth effect versus consumer heterogeneity. In: Laurent G, Lilien GL, Pras B (eds) Research traditions in marketing. Kluwer, Dordrecht, pp 201–229Google Scholar
  14. Bemmaor AC, Lee J (2002) The impact of heterogeneity and ill-conditioning on diffusion model parameter estimates. Mark Sci 21(2): 209–220CrossRefGoogle Scholar
  15. Berger T (2001) Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis. Agric Econ 25(2–3): 245–260CrossRefGoogle Scholar
  16. Bernhardt I, Mackenzie KD (1972) Some problems in using diffusion models for new products. Manag Sci 19(2): 187–200CrossRefGoogle Scholar
  17. Bohlmann JD, Calantone RJ, Zhao M (2010) The effects of market network heterogeneity on innovation diffusion: an agent-based modeling approach. J Product Innov Manag 27(5): 741–760CrossRefGoogle Scholar
  18. Bottomley PA, Fildes R (1998) The role of prices in models of innovation diffusion. J Forecast 17(7): 539–555CrossRefGoogle Scholar
  19. Broekhuizen TLJ, Delre SA, Torres A (2011) Simulating the cinema market: how cross-cultural differences in social influence explain box office distributions. J Product Innov Manag 28(2): 204–217CrossRefGoogle Scholar
  20. Brown JJ, Reingen PH (1987) Social ties and word-of-mouth referral behavior. J Consumer Res 14(3): 350–362CrossRefGoogle Scholar
  21. Buchta C, Meyer D, Pfister A, Mild A, Taudes A (2003) Technological efficiency and organizational inertia: a model of the emergence of disruption. Comput Math Organ Theory 9(2): 127–146CrossRefGoogle Scholar
  22. Buttle FA (1998) Word of mouth: understanding and managing referral marketing. J Strateg Mark 6(3): 241–254CrossRefGoogle Scholar
  23. 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(4): 487–496CrossRefGoogle Scholar
  24. Chatterjee R, Eliashberg J (1990) The innovation diffusion process in a heterogeneous population: a micromodeling approach. Manag Sci 36(9): 1057–1079CrossRefGoogle Scholar
  25. Chattoe E (2002) Building empirically plausible multi-agent systems: a case study of innovation diffusion. In: Dautenhahn K, Bond A, Edmonds B (eds) Socially intelligent agents: creating relationships with computers and robots. Springer, Berlin, pp 109–116Google Scholar
  26. Chen SH, Yang YH (2010) Agent-based social simulation: a bibliometric review. In: Proceedings of the 3rd world congress on social simulation (WCSS 2010)Google Scholar
  27. Choi H, Kim S, Lee J (2010) Role of network structure and network effects in diffusion of innovations. Ind Mark Manag 39(1): 170–177CrossRefGoogle Scholar
  28. David PA (1985) Clio and the economics of QWERTY. Am Econ Rev 75(2): 332–337Google Scholar
  29. Dawid H (2006) Agent-based models of innovation and technological change. In: Tesfatsion L, Judd K (eds) Handbook of computational economics. North-Holland, pp 1235–1272Google Scholar
  30. DeCanio SJ, Dibble C, Amir-Atefi K (2000) The importance of organizational structure for the adoption of innovations. Manag Sci 46(10): 1285–1299CrossRefGoogle Scholar
  31. Deffuant G, Huet S, Bousset JP, Henriot J, Amon G, Weisbuch G (2002) Agent based simulation of organic farming conversion in Allier departement. In: Janssen MA (eds) Complexity and ecosystem management: the theory and practice of multi-agent systems. Edward Elgard Publishing, Arnold, pp 158–189Google Scholar
  32. Deffuant G, Huet S, Amblard F (2005) An individual-based model of innovation diffusion mixing social value and individual benefit. Am J Sociol 110(4): 1041–1069CrossRefGoogle Scholar
  33. Delre SA (2007) Effects of social networks on innovation diffusion and market dynamics. PhD Dissertation, University GroningenGoogle Scholar
  34. Delre SA, Jager W, Bijmolt THA, Janssen MA (2007) Targeting and timing promotional activities: an agent-based model for the takeoff of new products. J Bus Res 60(8): 826–835CrossRefGoogle Scholar
  35. Delre SA, Jager W, Janssen MA (2007) Diffusion dynamics in small-world networks with heterogeneous consumers. Comput Math Organ Theory 13(2): 185–202CrossRefGoogle Scholar
  36. Delre SA, Jager W, Bijmolt THA, Janssen MA (2010) Will it spread or not? The effects of social influences and network topology on innovation diffusion. J Product Innov Manag 27(2): 267–282CrossRefGoogle Scholar
  37. Deroïan F (2002) Formation of social networks and diffusion of innovations. Res Policy 31(5): 835–846CrossRefGoogle Scholar
  38. Dockner E, Jorgensen S (1988) Optimal advertising policies for diffusion models of new product innovation in monopolist situations. Manag Sci 34(1): 119–130CrossRefGoogle Scholar
  39. Dodson JA, Muller E (1978) Models of new product diffusion through advertising and word-of-mouth. Manag Sci 24(15): 1568–1578CrossRefGoogle Scholar
  40. Dugundji ER, Gulyás L (2008) Sociodynamic discrete choice on networks in space: impacts of agent heterogeneity on emergent outcomes. Environ Plan B Plan Des 35(6): 1028–1054CrossRefGoogle Scholar
  41. Edmonds B, Moss S (2006) From KISS to KIDS: an ‘anti-simplistic’ modelling approach. In: Davidsson P, Logan B, Takadama K (eds) Multi agent based simulation (LNAI 3415). Springer, Berlin, pp 130–144Google Scholar
  42. Eliashberg J, Chatterjee R, Mahajan V, Wind Y (1986) Stochastic issues in innovation diffusion models. In: Innovation diffusion models of new product acceptance. Ballinger Publishing, pp 151–199Google Scholar
  43. Emmanouilides CJ, Davies RB (2007) Modelling and estimation of social interaction effects in new product diffusion. Eur J Oper Res 177(2): 1253–1274CrossRefGoogle Scholar
  44. Erdős P, Rényi A (1960) On the evolution of random graphs. Publ Math Inst Hung Acad Sci 5(17): 17–61Google Scholar
  45. Evered RD (1976) A typology of explicative models. Technol Forecast Soc Change 9(3): 259–277CrossRefGoogle Scholar
  46. Faber A, Valente M, Janssen P (2010) Exploring domestic micro-cogeneration in the Netherlands: an agent-based demand model for technology diffusion. Energy Policy 38(6): 2763–2775CrossRefGoogle Scholar
  47. Feichtinger G (1982) Optimal pricing in a diffusion model with concave price-dependent market potential. Oper Res Lett 1(6): 236–240CrossRefGoogle Scholar
  48. Fourt LA, Woodlock JW (1960) Early prediction of market success for grocery products. J Mark 25(4): 31–38CrossRefGoogle Scholar
  49. Gallego B, Dunn AG (2010) Diffusion of competing innovations: the effects of network structure on the provision of healthcare. J Artif Soc Soc Simul 13(4): 8Google Scholar
  50. Garber T, Goldenberg J, Libai B, Muller E (2004) From density to destiny: using spatial dimension of sales data for early prediction of new product success. Mark Sci 23(3): 419–428CrossRefGoogle Scholar
  51. Garcia R (2005) Uses of agent-based modeling in innovation/new product development research. J Product Innov Manag 22(5): 380–398CrossRefGoogle Scholar
  52. Garcia R, Rummel P, Hauser J (2007) Validating agent-based marketing models through conjoint analysis. J Bus Res 60(8): 848–857CrossRefGoogle Scholar
  53. Gatignon H (2010) Commentary on Jacob Goldenberg, Barak Libai and Eitan Muller’s “The chilling effects of network externalities”. Int J Res Mark 27(1): 16–17CrossRefGoogle Scholar
  54. Gilbert EN (1959) Random graphs. Ann Math Stat 30(4): 1141–1144CrossRefGoogle Scholar
  55. Gilbert N (1997) A simulation of the structure of academic science. Sociol Res Online 2(2): 3Google Scholar
  56. Goldenberg J, Efroni S (2001) Using cellular automata modeling of the emergence of innovations. Technol Forecast Soc Change 68(3): 293–308CrossRefGoogle Scholar
  57. Goldenberg J, Libai B, Solomon S, Jan N, Stauffer D (2000) Marketing percolation. Phys A Stat Mech Appl 284(1–4): 335–347CrossRefGoogle Scholar
  58. Goldenberg J, Libai B, Muller E (2001) Talk of the network: a complex systems look at the underlying process of word-of-mouth. Mark Lett 12(3): 211–223CrossRefGoogle Scholar
  59. Goldenberg J, Libai B, Moldovan S, Muller E (2007) The NPV of bad news. Int J Res Mark 24(3): 186–200CrossRefGoogle Scholar
  60. Goldenberg J, Lowengart O, Shapira D (2009) Zooming in: self-emergence of movements in new product growth. Mark Sci 28(2): 274–292CrossRefGoogle Scholar
  61. Goldenberg J, Libai B, Muller E (2010) The chilling effects of network externalities. Int J Res Mark 27(1): 4–15CrossRefGoogle Scholar
  62. Goldenberg J, Libai B, Muller E (2010) The chilling effects of network externalities: perspectives and conclusions. Int J Res Mark 27(1): 22–24CrossRefGoogle Scholar
  63. Granovetter MS (1973) The strength of weak ties. Am J Sociol 78(6): 1360–1380CrossRefGoogle Scholar
  64. Griliches Z (1957) Hybrid corn: an exploration in the economics of technological change. Econometrica 25(4): 501–522CrossRefGoogle Scholar
  65. Günther M, Stummer C, Wakolbinger LM, Wildpaner M (2011) An agent-based simulation approach for the new product diffusion of a novel biomass fuel. J Oper Res Soc 62(1): 12–20CrossRefGoogle Scholar
  66. Hägerstrand T (1967) Innovation diffusion as a spatial process. University of Chicago Press, ChicagoGoogle Scholar
  67. Hauser JR, Tellis GJ, Griffin A (2006) Research on innovation: a review and agenda for marketing science. Mark Sci 25(6): 678–717CrossRefGoogle Scholar
  68. Heeler RM, Hustad TP (1980) Problems in predicting new product growth for consumer durables. Manag Sci 26(10): 1007–1020CrossRefGoogle Scholar
  69. Hegselmann R, Krause U (2002) Opinion dynamics and bounded confidence models, analysis, and simulation. J Artif Soc Soc Simul 5(3): 2Google Scholar
  70. Herr PM, Kardes FR, Kim J (1991) Effects of word-of-mouth and product-attribute information on persuasion: an accessibility-diagnosticity perspective. J Consumer Res 17(4): 454–462CrossRefGoogle Scholar
  71. Hohnisch M, Pittnauer S, Stauffer D (2008) A percolation-based model explaining delayed takeoff in new-product diffusion. Ind Corp Change 17(5): 1001–1017CrossRefGoogle Scholar
  72. Hopp WJ (2004) Ten most influential papers of management science’s first fifty years. Manag Sci 50(Suppl 12): 1763CrossRefGoogle Scholar
  73. Horsky D, Simon LS (1983) Advertising and the diffusion of new products. Mark Sci 2(1): 1–17CrossRefGoogle Scholar
  74. Jager W, Janssen MA, Vries HJMD, Greef JD, Vlek CAJ (2000) Behaviour in commons dilemmas: Homo economicus and Homo psychologicus in an ecological-economic model. Ecol Econ 35(3): 357–379CrossRefGoogle Scholar
  75. Jain D, Mahajan V, Muller E (1991) Innovation diffusion in the presence of supply restrictions. Mark Sci 10(1): 83–90CrossRefGoogle Scholar
  76. Jain DC, Rao RC (1990) Effect of price on the demand for durables: modeling, estimation, and findings. J Bus Econ Stat 8(2): 163–170CrossRefGoogle Scholar
  77. Janssen MA, Jager W (2001) Fashions, habits and changing preferences: simulation of psychological factors affecting market dynamics. J Econ Psychol 22(6): 745–772CrossRefGoogle Scholar
  78. Janssen MA, Jager W (2002) Stimulating diffusion of green products. J Evolut Econ 12(3): 283–306CrossRefGoogle Scholar
  79. Janssen MA, Jager W (2003) Simulating market dynamics: interactions between consumer psychology and social networks. Artif Life 9(4): 343–356CrossRefGoogle Scholar
  80. Jones JM, Ritz CJ (1991) Incorporating distribution into new product diffusion models. Int J Res Mark 8(2): 91–112CrossRefGoogle Scholar
  81. Katz E (1961) The social itinerary of technical change: two studies on the diffusion of innovation. Hum Organ 20(2): 70–82Google Scholar
  82. Katz ML, Shapiro C (1986) Technology adoption in the presence of network externalities. J Polit Econ 94(4): 822–841CrossRefGoogle Scholar
  83. Katz ML, Shapiro C (1992) Product introduction with network externalities. J Ind Econ 40(1): 55–83CrossRefGoogle Scholar
  84. Kaufmann P, Stagl S, Franks DW (2009) Simulating the diffusion of organic farming practices in two new EU member states. Ecol Econ 68(10): 2580–2593CrossRefGoogle Scholar
  85. Keeney RL, Raiffa H (1993) Decisions with multiple objectives: preferences and value tradeoffs. Cambridge University Press, CambridgeGoogle Scholar
  86. Kim S, Lee K, Cho JK, Kim CO (2011) Agent-based diffusion model for an automobile market with fuzzy TOPSIS-based product adoption process. Expert Syst Appl 38(6): 7270–7276CrossRefGoogle Scholar
  87. Kocsis G, Kun F (2008) The effect of network topologies on the spreading of technological developments. J Stat Mech Theory Exp 2008(10):P10,014Google Scholar
  88. Kohli R, Lehmann DR, Pae J (1999) Extent and impact of incubation time in new product diffusion. J Product Innov Manag 16(2): 134–144CrossRefGoogle Scholar
  89. Kuandykov L, Sokolov M (2010) Impact of social neighborhood on diffusion of innovation S-curve. Decis Support Syst 48(4): 531–535CrossRefGoogle Scholar
  90. Little JDC (1970) Models and managers: the concept of a decision calculus. Manag Sci 16(8): 466–485CrossRefGoogle Scholar
  91. Macy MW, Willer R (2002) From factors to actors: computational sociology and agent- based modeling. Annu Rev Sociol 28(1): 143–166CrossRefGoogle Scholar
  92. Mahajan V, Muller E (1979) Innovation diffusion and new product growth models in marketing. J Mark 43(4): 55–68CrossRefGoogle Scholar
  93. Mahajan V, Muller E, Bass FM (1990) New product diffusion models in marketing: a review and directions for further research. J Mark 54(1): 1–26CrossRefGoogle Scholar
  94. Mahajan V, Muller E, Bass FM (1995) Diffusion of new products: empirical generalizations and managerial uses. Mark Sci 14(3): 79–88CrossRefGoogle Scholar
  95. Mahajan V, Muller E, Wind Y (2000) New-product diffusion models. Springer, BerlinGoogle Scholar
  96. Maienhofer D, Finholt T (2002) Finding optimal targets for change agents: a computer simulation of innovation diffusion. Comput Math Organ Theory 8(4): 259–280CrossRefGoogle Scholar
  97. Maier FH (1998) New product diffusion models in innovation management: a system dynamics perspective. Syst Dyn Rev 14(4): 285–308CrossRefGoogle Scholar
  98. Mansfield E (1961) Technical change and the rate of imitation. Econometrica 29(4): 741–766CrossRefGoogle Scholar
  99. Martins ACR, Pereira CdB, Vicente R (2009) An opinion dynamics model for the diffusion of innovations. Phys A Stat Mech Appl 388(15–16): 3225–3232CrossRefGoogle Scholar
  100. Meade N, Islam T (2006) Modelling and forecasting the diffusion of innovation: a 25-year review. Int J Forecast 22(3): 519–545CrossRefGoogle Scholar
  101. Midgley D, Marks R, Kunchamwar D (2007) Building and assurance of agent-based models: an example and challenge to the field. J Bus Res 60(8): 884–893CrossRefGoogle Scholar
  102. Milling PM (1996) Modeling innovation processes for decision support and management simulation. Syst Dyn Rev 12(3): 211–234CrossRefGoogle Scholar
  103. Milling PM (2002) Understanding and managing innovation processes. Syst Dyn Rev 18(1): 73–86CrossRefGoogle Scholar
  104. Moldovan S, Goldenberg J (2004) Cellular automata modeling of resistance to innovations: effects and solutions. Technol Forecast Soc Change 71(5): 425–442CrossRefGoogle Scholar
  105. Ormerod P, Rosewell B (2009) Validation and verification of agent-based models in the social sciences. In: Squazzoni F (eds) Epistomological aspects of computer simulation in the social sciences (LNAI 5466). Springer, Berlin, pp 130–140CrossRefGoogle Scholar
  106. Parker PM (1994) Aggregate diffusion forecasting models in marketing: a critical review. Int J Forecast 10(2): 353–380CrossRefGoogle Scholar
  107. Peres R, Muller E, Mahajan V (2010) Innovation diffusion and new product growth models: a critical review and research directions. Int J Res Mark 27(2): 91–106CrossRefGoogle Scholar
  108. Radax W, Rengs B (2010) Timing matters: lessons from the CA literature on updating. In: Proceedings of the 3rd world congress on social simulation (WCSS 2010)Google Scholar
  109. Rahmandad H, Sterman J (2008) Heterogeneity and network structure in the dynamics of diffusion: comparing agent-based and differential equation models. Manag Sci 54(5): 998–1014CrossRefGoogle Scholar
  110. Reingen PH, Kernan JB (1986) Analysis of referral networks in marketing: methods and illustration. J Mark Res 23(4): 370–378CrossRefGoogle Scholar
  111. Richins ML (1983) Negative word-of-mouth by dissatisfied consumers: a pilot study. J Mark 47(1): 68–78CrossRefGoogle Scholar
  112. Robinson B, Lakhani C (1975) Dynamic price models for new-product planning. Manag Sci 21(10): 1113–1122CrossRefGoogle Scholar
  113. Rogers EM (1962) Diffusion of innovations. Free Press, New YorkGoogle Scholar
  114. Rogers EM (1976) New product adoption and diffusion. J Consumer Res 2(4): 290–301CrossRefGoogle Scholar
  115. Rogers EM (2003) Diffusion of innovations. 5. Free Press, New YorkGoogle Scholar
  116. Ruiz-Conde E, Leeflang PS, Wieringa JE (2006) Marketing variables in macro-level diffusion models. J für Betriebswirtschaft 56(3): 155–183CrossRefGoogle Scholar
  117. Rust RT (2010) Network externalities—not cool? A comment on “The chilling effects of network externalities”. Int J Res Mark 27(1): 18–19CrossRefGoogle Scholar
  118. Ryan B, Gross N (1943) The diffusion of hybrid seed corn in two Iowa communities. Rural Sociol 8(1): 15–24Google Scholar
  119. Schelling TC (1971) Dynamic models of segregation. J Math Sociol 1(1): 143–186CrossRefGoogle Scholar
  120. Schmittlein DC, Mahajan V (1982) Maximum likelihood estimation for an innovation diffusion model of new product acceptance. Mark Sci 1(1): 57–78CrossRefGoogle Scholar
  121. Schramm ME, Trainor KJ, Shanker M, Hu MY (2010) An agent-based diffusion model with consumer and brand agents. Decis Support Syst 50(1): 234–242CrossRefGoogle Scholar
  122. Schumpeter J (1928) The instability of capitalism. Econ J 38(151): 361–386CrossRefGoogle Scholar
  123. Schwarz N, Ernst A (2009) Agent-based modeling of the diffusion of environmental innovations: an empirical approach. Technol Forecast Soc Change 76(4): 497–511CrossRefGoogle Scholar
  124. Schwoon M (2006) Simulating the adoption of fuel cell vehicles. J Evol Econ 16(4): 435–472CrossRefGoogle Scholar
  125. Shaikh NI, Rangaswamy A, Balakrishnan A (2006) Modeling the diffusion of innovations using small-world networks. Technical report, Penn State UniversityGoogle Scholar
  126. Simon H, Sebastian K (1987) Diffusion and advertising: the German telephone campaign. Manag Sci 33(4): 451–466CrossRefGoogle Scholar
  127. Squazzoni F (2010) The impact of agent-based models in the social sciences after 15 years of incursions. Hist Econ Ideas 18(2): 197–233Google Scholar
  128. Srinivasan V, Mason CH (1986) Nonlinear least squares estimation of new product diffusion models. Mark Sci 5(2): 169–178CrossRefGoogle Scholar
  129. Strang D, Macy MW (2001) In search of excellence: fads, success stories, and adaptive emulation. Am J Sociol 107(1): 147–182CrossRefGoogle Scholar
  130. Strang D, Soule SA (1998) Diffusion in organizations and social movements: from hybrid corn to poison pills. Annu Rev Sociol 24(1): 265–290CrossRefGoogle Scholar
  131. Stremersch S, Tellis GJ, Franses PH, Binken JL (2007) Indirect network effects in new product growth. J Mark 71(3): 52–74CrossRefGoogle Scholar
  132. Stremersch S, Lehmann DR, Dekimpe M (2010) Preface to “The chilling effects of network externalities”. Int J Res Mark 27: 1–3CrossRefGoogle Scholar
  133. Sultan F, Farley JU, Lehmann DR (1990) A meta-analysis of applications of diffusion models. J Mark Res 27(1): 70–77CrossRefGoogle Scholar
  134. Tanny SM, Derzko NA (1988) Innovators and imitators in innovation diffusion modelling. J Forecast 7(4): 225–234CrossRefGoogle Scholar
  135. Tarde G (1903) The laws of imitation. Henry, Holt and Co., New YorkGoogle Scholar
  136. Tellis GJ (2007) A critical review of marketing research on diffusion of new products. In: Malhotra NK (eds) Review of marketing research. Emerald, Bradford, pp 39–80CrossRefGoogle Scholar
  137. Thiriot S, Kant JD (2008) Using associative networks to represent adopters’ beliefs in a multiagent model of innovation diffusion. Adv Complex Syst 11(2): 261–272CrossRefGoogle Scholar
  138. Travers J, Milgram S (1969) An experimental study of the small world problem. Sociometry 32(4): 425–443CrossRefGoogle Scholar
  139. Urban GL, Hauser JR, Roberts JH (1990) Prelaunch forecasting of new automobiles. Manag Sci 36(4): 401–421CrossRefGoogle Scholar
  140. Vag A (2007) Simulating changing consumer preferences: a dynamic conjoint model. J Bus Res 60(4): 904–911CrossRefGoogle Scholar
  141. Valente TW, Davis RL (1999) Accelerating the diffusion of innovations using opinion leaders. Ann Am Acad Polit Soc Sci 566(1): 55–67CrossRefGoogle Scholar
  142. Valente TW, Rogers EM (1995) The origins and development of the diffusion of innovations paradigm as an example of scientific growth. Sci Commun 16(3): 242–273CrossRefGoogle Scholar
  143. Van den Bulte C, Lilien GL (1997) Bias and systematic change in the parameter estimates of macro-level diffusion models. Mark Sci 16(4): 338–353CrossRefGoogle Scholar
  144. Van den Bulte C, Stremersch S (2004) Social contagion and income heterogeneity in new product diffusion: a meta-analytic test. Mark Sci 23(4): 530–544CrossRefGoogle Scholar
  145. van Eck PS, Jager W, Leeflang PSH (2011) Opinion leaders’ role in innovation diffusion: a simulation study. J Product Innov Manag 28(2): 187–203CrossRefGoogle Scholar
  146. van Vliet O, de Vries B, Faaij A, Turkenburg W, Jager W (2010) Multi-agent simulation of adoption of alternative fuels. Transp Res Part D Transp Environ 15(6): 326–342CrossRefGoogle Scholar
  147. Veblen T (1899) The theory of the leisure class. Macmillan, New YorkGoogle Scholar
  148. Venkatesan R, Krishnan TV, Kumar V (2004) Evolutionary estimation of macro-level diffusion models using genetic algorithms: an alternative to nonlinear least squares. Mark Sci 23(3): 451–464CrossRefGoogle Scholar
  149. Walker JL (1969) The diffusion of innovations among the American states. Am Polit Sci Rev 63(3): 880–899CrossRefGoogle Scholar
  150. Watts DJ, Strogatz SH (1998) Collective dynamics of “small-world” networks. Nature 393(6684): 440–442CrossRefGoogle Scholar
  151. Windrum P, Fagiolo G, Moneta A (2007) Empirical validation of agent-based models: alternatives and prospects. J Artif Soc Soc Simul 10(2): 8Google Scholar
  152. Wissler C (1915) The diffusion of horse culture among the North American indians. Proc Natl Acad Sci USA 1(4): 254–256CrossRefGoogle Scholar
  153. Zhang T, Nuttall WJ (2011) Evaluating government’s policies on promoting smart metering diffusion in retail electricity markets via agent-based simulation. J Product Innov Manag 28(2): 169–186CrossRefGoogle Scholar
  154. Zhang T, Gensler S, Garcia R (2011) A study of the diffusion of alternative fuel vehicles: an agent-based modeling approach. J Product Innov Manag 28(2): 152–168CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Elmar Kiesling
    • 1
  • Markus Günther
    • 2
  • Christian Stummer
    • 2
  • Lea M. Wakolbinger
    • 1
  1. 1.Department of Business AdministrationUniversity of ViennaViennaAustria
  2. 2.Department of Business Administration and EconomicsBielefeld UniversityBielefeldGermany

Personalised recommendations