Journal of Systems Thinking in Practice

Article 1, Volume 1, Issue 1, January 0, Pages 1-23   

DOI: 10.22067/jstinp.2022.76130.1005

References

Albert, R. and Barabási, A.L., 2000. Topology of evolving networks: local events and universality. Physical review letters, 85(24), pp. 5234-5237. https://doi.org/10.1103/PhysRevLett.85.5234.

Alkemade, F. and Castaldi, C., 2005. Strategies for the diffusion of innovations on social networks. Computational Economics, 25(1), pp.3-23. https://doi.org/10.1007/s10614-005-6245-1.

Amini, M., Wakolbinger, T., Racer, M. and Nejad, M.G., 2012. Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach. European journal of operational research, 216(2), pp.301-311. https://doi.org/10.1016/j.ejor.2011.07.040.

Barabási, A.L. and Albert, R., 1999. Emergence of scaling in random networks. science, 286(5439), pp.509-512. https://doi.org/10.1126/science.286.5439.509.

Bass, F.M., 1969. A new product growth for model consumer durables. Management science, 15(5), pp.215-227. https://doi.org/10.1287/mnsc.15.5.215.

Berger, T., 2001. Agent‐based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis. Agricultural economics, 25(2‐3), pp.245-260.  https://doi.org/10.1111/j.1574-0862.2001.tb00205.x.

Bohlmann, J.D., Calantone, R.J. and Zhao, M., 2010. The effects of market network heterogeneity on innovation diffusion: An agent‐based modeling approach. Journal of Product Innovation Management, 27(5), pp.741-760. https://doi.org/10.1111/j.1540-5885.2010.00748.x.

Chandrasekaran, D. and Tellis, G.J., 2007. A critical review of marketing research on diffusion of new products. Review of marketing research, 3, pp.39-80. https://doi.org/10.1108/S1548-6435(2007)0000003006.

Delre, S.A., Jager, W. and Janssen, M.A., 2007. Diffusion dynamics in small-world networks with heterogeneous consumers. Computational and Mathematical Organization Theory, 13(2), pp.185-202. https://doi.org/10.1007/s10588-006-9007-2.

Delre, S.A., Jager, W., Bijmolt, T.H. and Janssen, M.A., 2010. Will it spread or not? The effects of social influences and network topology on innovation diffusion. Journal of Product Innovation Management, 27(2), pp.267-282. https://doi.org/10.1111/j.1540-5885.2010.00714.x.

Fazeli, A. and Jadbabaie, A., 2012, December. Game theoretic analysis of a strategic model of competitive contagion and product adoption in social networks. In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC) (pp. 74-79). IEEE.

Fourt, L.A. and Woodlock, J.W., 1960. Early prediction of market success for new grocery products. Journal of marketing, 25(2), pp.31-38. https://doi.org/10.1177/00222429600250020.

Goldenberg, J. and Efroni, S., 2001. Using cellular automata modeling of the emergence of innovations. Technological Forecasting and Social Change, 68(3), pp.293-308. https://doi.org/10.1016/S0040-1625(00)00095-0.

Goldenberg, J., Libai, B., Solomon, S., Jan, N. and Stauffer, D., 2000. Marketing percolation. Physica A: statistical mechanics and its applications, 284(1-4), pp.335-347. https://doi.org/10.1016/S0378-4371(00)00260-0.

Günther, M. and Stummer, C., 2018. Simulating the diffusion of competing multi-generation technologies: An agent-based model and its application to the consumer computer market in Germany. In Operations research proceedings, 2016, Springer, Cham. pp. 569-574. https://doi.org/10.1007/978-3-319-55702-1_75.

Günther, M., Stummer, C., Wakolbinger, L. M., and Wildpaner, M., 2011. An agent-based simulation approach for the new product diffusion of a novel biomass fuel. Journal of the Operational Research Society, 62(1), pp. 12-20.‏ https://doi.org/10.1057/jors.2009.170.

Heppenstall, A., Evans, A. and Birkin, M., 2006. Using hybrid agent-based systems to model spatially-influenced retail markets. Journal of Artificial Societies and Social Simulation, 9(3). Available at: https://www.jasss.org/9/3/2.html.

Jones, J.M. and Ritz, C.J., 1991. Incorporating distribution into new product diffusion models. International Journal of Research in Marketing, 8(2), pp.91-112. https://doi.org/10.1016/0167-8116(91)90018-3.

Kaufmann, P., Stagl, S. and Franks, D.W., 2009. Simulating the diffusion of organic farming practices in two New EU Member States. Ecological Economics, 68(10), pp.2580-2593. https://doi.org/10.1016/j.ecolecon.2009.04.001.

Kiesling, E., Günther, M., Stummer, C. and Wakolbinger, L.M., 2012. Agent-based simulation of innovation diffusion: a review. Central European Journal of Operations Research, 20(2), pp.183-230. https://doi.org/10.1007/s10100-011-0210-y.

Kim, S., Lee, K., Cho, J.K. and Kim, C.O., 2011. Agent-based diffusion model for an automobile market with fuzzy TOPSIS-based product adoption process. Expert Systems with Applications, 38(6), pp.7270-7276. https://doi.org/10.1016/j.eswa.2010.12.024.

Mahajan, V. and Muller, E., 1979. Innovation diffusion and new product growth models in marketing. Journal of marketing, 43(4), pp.55-68. https://doi.org/10.1016/j.ijresmar.2009.12.012.

Meade, N. and Islam, T., 2006. Modelling and forecasting the diffusion of innovation–A 25-year review. International Journal of forecasting, 22(3), pp.519-545. https://doi.org/10.1016/j.ijforecast.2006.01.005.

Milling, P.M., 1996. Modeling innovation processes for decision support and management simulation. System Dynamics Review: The Journal of the System Dynamics Society, 12(3), pp.211-234. https://doi.org/10.1002/(SICI)1099-1727(199623)12:3<211::AID-SDR105>3.0.CO;2-8.

Miremadi, A. and Faghanie, E., 2012. An empirical study of consumer buying behavior and its influence on consumer preference in Iranian FMCG market: A case study. International Business and Management, 5(1), pp.146-152. https://doi.org/10.3968/J.IBM.1923842820120501.1115.

Moldovan, S. and Goldenberg, J., 2004. Cellular automata modeling of resistance to innovations: Effects and solutions. Technological Forecasting and Social Change, 71(5), pp.425-442. https://doi.org/10.1016/S0040-1625(03)00026-X.

Rand, W. and Rust, R.T., 2011. Agent-based modeling in marketing: Guidelines for rigor. International Journal of research in Marketing, 28(3), pp.181-193. https://doi.org/10.1016/j.ijresmar.2011.04.002.

Rogers, E. M. 1962, Diffusion of Innovations, Free Press, New York.‏

Rosales, C.R., Whipple, J.M. and Blackhurst, J., 2018. The impact of distribution channel decisions and repeated stockouts on manufacturer and retailer performance. IEEE transactions on engineering management, 66(3), pp.312-324. https://doi.org/10.1109/TEM.2018.2835653.

Ryan, B. and Gross, N.C., 1943. The diffusion of hybrid seed corn in two Iowa communities. Rural sociology, 8(1), pp.15-24.

Sonderegger-Wakolbinger, L.M. and Stummer, C., 2015. An agent-based simulation of customer multi-channel choice behavior. Central European Journal of Operations Research, 23(2), pp.459-477. https://doi.org/10.1007/s10100-015-0388-5.

Strang, D. and Soule, S.A., 1998. Diffusion in organizations and social movements: From hybrid corn to poison pills. Annual review of sociology, 24(1), pp.265-290. https://doi.org/10.1146/annurev.soc.24.1.265.

Stummer, C., Kiesling, E., Günther, M. and Vetschera, R., 2015. Innovation diffusion of repeat purchase products in a competitive market: An agent-based simulation approach. European Journal of Operational Research, 245(1), pp.157-167.‏ https://doi.org/10.1016/j.ejor.2015.03.008.

Stummer, C., Lüpke, L. and Günther, M., 2021. Beaming market simulation to the future by combining agent-based modeling with scenario analysis. Journal of Business Economics, 91(9), pp.1469-1497. https://doi.org/10.1007/s11573-021-01046-9.

Sturley, C., Newing, A. and Heppenstall, A., 2018. Evaluating the potential of agent-based modelling to capture consumer grocery retail store choice behaviours. The International Review of Retail, Distribution and Consumer Research, 28(1), pp.27-46. https://doi.org/10.1080/09593969.2017.1397046.

Sultan, F., Farley, J.U. and Lehmann, D.R., 1990. A meta-analysis of applications of diffusion models. Journal of marketing research, 27(1), pp.70-77. https://doi.org/10.1177/002224379002700107.

Tseng, F. M., 2008. Quadratic interval innovation diffusion models for new product sales forecasting. Journal of the Operational Research Society, 59(8), pp.1120-1127.‏ https://doi.org/10.1057/palgrave.jors.2602457.

Valente, T.W. and Rogers, E.M., 1995. The origins and development of the diffusion of innovations paradigm as an example of scientific growth. Science communication, 16(3), pp.242-273.‏
https://doi.org/10.1177/1075547095016003002.

Xiao, Y. and Han, J., 2016. Forecasting new product diffusion with agent-based models. Technological Forecasting and Social Change, 105, pp.167-178. https://doi.org/10.1016/j.techfore.2016.01.019.

Zhang, T., Gensler, S. and Garcia, R., 2011. A study of the diffusion of alternative fuel vehicles: An agent‐based modeling approach. Journal of Product Innovation Management, 28(2), pp.152-168. https://doi.org/10.1111/j.1540-5885.2011.00789.x.