1. bookVolume 49 (2016): Issue 2 (May 2016)
Journal Details
License
Format
Journal
First Published
17 Oct 2008
Publication timeframe
4 times per year
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English
access type Open Access

Analysis of Interactions of Key Stakeholders on B2C e-Markets - Agent Based Modelling and Simulation Approach

Published Online: 10 Jun 2016
Page range: 138 - 149
Received: 19 Mar 2015
Accepted: 29 Apr 2016
Journal Details
License
Format
Journal
First Published
17 Oct 2008
Publication timeframe
4 times per year
Languages
English

Background/purpose: This paper discusses the application of ABMS - agent-based modelling and simulation in the analysis of customer behaviour on B2C e-commerce websites as well as in the analysis of various business decisions upon the effects of on-line sales. The continuous development and dynamics in the field of e-commerce requires application of advanced decision-making tools. These tools must be able to process, in a short time period, a large amount of data generated by the e-commerce systems and enable the use of acquired data for making quality business decisions.

Keywords

Aggarwal, R., Gopal, R., Gupta, A., & Singh, H. (2012). Putting Money Where the Mouths Are: The Relation Between Venture Financing and Electronic Word-of- Mouth, Journal Information Systems Research, 23, 976-992.Search in Google Scholar

Bagozzi, R., Gurhan-Canli, Z., & Priester, J. (2002). The Social Psychology of Consumer Behaviour, Buckingham: Open University Press.Search in Google Scholar

Bailey, P. (1998). Electronic Commerce: Prices and Consumer Issues for Three Products: Books, OECD Digital Economy Papers, Retrieved January 5, 2016 from http://www.oecd.org/sti/35497325.pdfSearch in Google Scholar

Currie, C. S., & Rowley, I. T. (2010). Consumer behaviour and sales forecast accuracy: What’s going on and how should revenue managers respond?, Journal of Revenue & Pricing Management, 9(4), 374-376, http://dx.doi.org/10.1057/rpm.2010.22Search in Google Scholar

Dellarocas, C. (2003). The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms, Management Science, 49, 1407-1424, http://dx.doi.org/10.1287/mnsc.49.10.1407.17308Search in Google Scholar

Dyner, I., & Franco, C. J. (2004). Consumers’ bounded rationality: The case of competitive energy markets, Systems Research and Behavioral Science, 21(4), 373-389, http://dx.doi.org/10.1002/sres.644Search in Google Scholar

Engel, J., Blackwell R., & Miniard P. (1994). Consumer Behavior, The Dryden Press (8th ed.).Search in Google Scholar

Furaiji F., Łatuszyńska, M., & Wawrzyniak, A. (2012). An empirical study of the factors influencing consumer behaviour in the electric appliances market, Contemporary Economics, 6(3), 76-86.Search in Google Scholar

Godes, D., & Mayzlin, D. (2004). Using Online Conversations to Study Word of Mouth Communication, Marketing Science, 23(4), 545-560, http://dx.doi.org/10.1287/mksc.1040.0071Search in Google Scholar

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., & DeAngelis D. L. (2008). A standard protocol for describing individual-based and agent-based models, Ecological modelling, 198(1-2), 115-126, http://dx.doi.org/10.1016/j.ecolmodel.2006.04.023Search in Google Scholar

Harrison-Walker. L. J. (2001).The measurement of wordof- mouth communication and investigation of service quality and customer commitment as potential antecedents, Journal of Service Research, 4(1), 60-75, http://dx.doi.org/10.1177/109467050141006Search in Google Scholar

Hummel, A., Kern, H., Kuhne, S., & Dohler, A. (2012). An Agent-Based Simulation of Viral Marketing Effects in Social Networks, 26th European Simulation and Modelling Conference.Search in Google Scholar

Hyung, A. (2010). Evaluating customer aid functions of online stores with agent-based models of customer behavior and evolution strategy, Information Sciences, 180(9), 1555-1570, http://dx.doi.org/10.1016/j.ins.2009.12.029Search in Google Scholar

Jager, W. (2008). Simulating consumer behaviour: a perspective, paper prepared for the Netherlands Environmental Assessment Agency project “Environmental policy and modelling in evolutionary economics”. Retrieved January 5, 2016 from http://www.pbl.nl/sites/default/files/cms/publicaties/eem_paper_wj_revised.pdfSearch in Google Scholar

Kim, B., Blattberg, R. & Rossi, P. (1995). Modelling the distribution of price sensitivity and implications for optimal retail pricing, Journal of Business & Economic Statistics, 13(3), 291-303, http://dx.doi.org/10.2307/1392189Search in Google Scholar

Kim, D., Ferrin, D. & Raghav, R. H. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents, Decision Support Systems, 44(2), 544-564, http://dx.doi.org/10.1016/j.dss.2007.07.001Search in Google Scholar

Klever, A. (2009). Behavioural Targeting: An Online Analysis for Efficient Media Planning?, Hamburg: Diplomica Verlag.Search in Google Scholar

Liu, X., Tang, Z., Yu, J., & Lu, N. (2013). An Agent Based Model for Simulation of Price War in B2C Online Retailers, Advances in Information Sciences and Service Sciences, 5(5), 1193-1202, http://dx.doi.org/10.4156/AISSSearch in Google Scholar

Michael, S., & Sinha, I. (2000). The Impact of Price and Extra Product Promotions on Store reference, International Journal of Retail & Distribution Management, 28(2), 83-9253, http://dx.doi.org/10.1108/09590550010315269Search in Google Scholar

Moe, W. (2003). Buying, searching, or browsing: Differentiating between online shoppers using in-store navigational clickstream, Journal of Consumer Psychology, 13, 29-39, http://dx.doi.org/10.1207/S15327663JCP13-1&2_03Search in Google Scholar

Moe W. Fader S. (2002), Fast-Track: Article Using Advance Purchase Orders to Forecast New Product Sales, Marketing Science, 21, 347-364, http://dx.doi.org/10.1287/mksc.21.3.347.138Search in Google Scholar

North, M., Macal, C., Aubin, J., Thimmapuram, P., Bragen, M., Hahn, J., Karr, J., Brigham, N., Lacy, M., & Hampton D. (2010). Multiscale agent-based consumer market modelling, Complexity, 15(5), 37-47, http://dx.doi.org/10.1002/cplx.20304Search in Google Scholar

Okada, I., & Yamamoto, H. (2009). Effect of online wordof- mouth communication on buying behavior in agentbased simulation, Proc. of the 6th Conference of the European Social Simulation Association, http:// www.isslab.org/study_work/essa2009proc.pdfSearch in Google Scholar

Poh, H., Yao, J., & Jasic, T. (1994). Neural Networks for the Analysis and Forecasting of Advertising and Promotion Impact, International Journal of Intelligent Systems in Accounting, Finance and Management, 7, 253-268, http://dx.doi.org/10.1002/(SICI)1099-1174(199812)7:4%3C253::AID-ISAF150%3E3.0.CO;2-XSearch in Google Scholar

Railsback, S., & Grimm, V. (2012). Agent-Based and Individual- Based Modeling, Princeton University Press, Princeton and Oxford.Search in Google Scholar

Roozmand, O., Ghasem-Aghaee, N., Hofstede, G. J., Nematbakhsh, M., Baraani, A., & Verwaart, T. (2011). Agent-based modeling of consumer decision making process based on power distance and personality. Knowledge-Based Systems, 24 (7), 1075-1095, http://dx.doi.org/10.1016/j.knosys.2011.05.001Search in Google Scholar

Russell, S., & Norvig, P. (2003). Artificial Intelligence: A Modern Approach, Prentice Hall.Search in Google Scholar

Said, L., Bouron, T. & Drogoul, A. (2002). Agent-based interaction analysis of consumer behaviour. In: Proceedings of the first international joint conference on Autonomous agents and multi-agent systems, IFAAMAS, p. 184-190.Search in Google Scholar

Schiffman, L., & Kanuk, L. (2009). Consumer Behavior, New Jersey: Prentice Hall (10th ed).Search in Google Scholar

Schramm, M., Trainor, J., Shanker, M., & Hu, Y. (2010). An agent-based diffusion model with consumer and brand agents, Decision Support Systems, 50(1), 234-242, http://dx.doi.org/10.1016/j.dss.2010.08.004Search in Google Scholar

Solomon, M., Bamossy, G., & Askegaard, S. (2009). Consumer Behaviour: A European Perspective, Prentice HallSearch in Google Scholar

Wang, Z., Wang, W., & Dong, L. (2010). Research on Influencing Factors of Perceived Risk in Online Shopping by Consumers, E-Business and E-Government (ICEE), 2010 International Conference on, Guangzhou, 2010, pp. 342-345, http://dx.doi.org/10.1109/ICEE.2010.94Search in Google Scholar

Zhang, T., & Zhang, D. (2007). Agent-based simulation of consumer purchase decision-making and the decoy effect, Journal of Business Research, 60(8), 912-922, http://dx.doi.org/10.1016/j.jbusres.2007.02.006Search in Google Scholar

Zhu, D. S., Lee, Z., O’Neal, G., & Chen, Y. (2009). The Effect of Trust and Perceived Risk on Consumers’ Online Purchase Intention, International Conference on Computational Science and Engineering, ISBN: 978-1-4244-5334-4, pp. 771-776.Search in Google Scholar

Zutshi, A., Grilo, A., Jardim-Gonçalves, R. (2014). A Dynamic Agent-Based Modeling Framework for Digital Business Models: Applications to Facebook and a Popular Portuguese Online Classifieds Website, Digital Enterprise Design & Management, Volume 261 of the series Advances in Intelligent Systems and Computing, pp. 105-117, http://dx.doi.org/10.1007/978-3-319-04313-5_10Search in Google Scholar

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