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The study of properties of the word of mouth marketing using cellular automata

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This article presents the possibility of using cellular automata, to study the properties of word of mouth (w-o-m) marketing. Cellular automata allow to analyze the dynamics of changes in views and attitudes in social groups based on local interactions between people in small groups of friends, family members etc. The proposed paper shows the possibility of modelling the dynamics of word of mouth mechanism, if the basic assumptions of this process are: different size groups where this phenomenon occurs, and varied access to information. On the competing firms market, the dependence of the w-o-m mechanism dynamics on the model parameters is shown.
Rocznik
Strony
27--37
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Silesian University of Technology, Faculty of Organisation and Management
Bibliografia
  • [1] Sarkar P., A brief history of cellular automata, ACM Computing Surveys, 32 (1), 2000, 80-107.
  • [2] Wolfram S., A New Kind of Science, Wolfram Media, Inc., 2002.
  • [3] Kowalska - Styczeń A.: Simulation of complicated economic processes with the use of cellular automatons. Wydawnictwo Politechniki Śląskiej, Gliwice, 2007 (in Polish).
  • [4] Macy M.W., Willer R., From factors to actors: Computational sociology and agentbased modeling, Annual Review of Sociology 28, 2002, 143-166.
  • [5] Rand W., Rust R. T., Agent-based modeling in marketing: Guidelines for rigor, International Journal of Research in Marketing, Volume 28, Issue 3, 2011, 181-193.
  • [6] Peres R., Muller E., Mahajan V., Innovation diffusion and new product growth models: A critical review and research directions, International Journal of Research in Marketing 27, 2010, 91-106.
  • [7] Goldenberg J., Libai B., Muller E., Using Complex Systems Analysis to Advance Marketing Theory Development: Modeling Heterogeneity Effects on New Product Growth through Stochastic Cellular Automata, Academy of Marketing Science Review 9, 2001.
  • [8] Goldenberg, J., Efroni S., Using Cellular Automata Modeling of the Emergence of Innovations, Technological Forecasting and Social Change, 68 (3), 2001, 293-308.
  • [9] Moldovan S., Goldenberg J., Cellular automata modeling of resistance to innovations: Effects and solutions, Technological Forecasting and Social Change, 71, 2004, 425-442.
  • [10] Mahayan V., Muller E., Kerin R. A., Introduction strategy for new products with positive and negative word-of mouth, Management Science, 30, 12, 1984, 1389
  • [11] Brown J. J., Reingen P. H., Social Ties and Word-of-Mouth Referral Behavior, Journal of Consumer Research, 14, 1987, 350 - 362.
  • [12] Hennig-Thurau, T., Walsh, G., Electronic word-of-mouth: motives for and consequences of reading consumer articulations on the Internet, International Journal of Electronic Commerce, 8, 2, Winter, 2004, 51-74.
  • [13] Steffes E. M., Burgee L. E., Social ties and online word of mouth, Internet Research, 19, 1, 2009, 42-59.
  • [14] Goldsmith R.E., Horowitz D., Measuring motivations for online opinion seeking, Journal of Interactive Advertising, 6, 2, Spring, 2006, 1-16.
  • [15] Godes D., Mayzlin D., Firm-Created Word-of-Mouth Communication: Evidence from a Field Test, Marketing Science, 28, 4, 2009, 721-739.
  • [16] Goldenberg J., Libai B., Muller E., Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth, Marketing Letters, 12:3, 2001, 211 - 223.
  • [17] Moldovan S., Goldenberg J., Chattopadhyay A., The different roles of product originality and usefulness in generating word-of-mouth, International Journal of Research in Marketing, 28, 2011, 109-119.
  • [18] Goldenberg J., Libai B., Muller E., Riding the Saddie: How Cross-Market Communications Can Create a Major Slump in Sales, Journal of Marketing, 66, 2002, 1-16.
  • [19] Garber, T., Goldenberg, J., Libai, B., Muller E., From Density to Destiny: Using Spatial Dimension of Sales Data for Early Prediction of New Product Success, Marketing Science, 23, 3, 2004, 419-428.
  • [20] Goldenberg J., Libai B., Muller E., The chilling effects of network externalities, International Journal of Research in Marketing, 27, 2010, 4-15.
  • [21] Ma F., Chao G., Research on Communication Products Diffusion in China Using Cellular Automata, International Business Research, 4, 2, 2011, 147 - 152.
  • [22] Kowalska-Styczeń A., Sznajd-Weron K., Access to information in word of mouth marketing within a cellular automata model, Advances in Complex Systems, 15, 7, 2012, 1250080 (17 pages).
  • [23] Schelling, T., Dynamic models of segregation, Journal of Mathematical Sociology, 1, 1971, 43-186.
  • [24] Kowalska - Styczeń A., Model symulujący podejmowanie decyzji przez konsumentów, Badania Operacyjne i Systemowe: Decyzje, Gospodarka, Kapitał Ludzki i Jakość, seria Badania Systemowe, 64, Warszawa, 2008, 227-236 (in Polish).
  • [25] Alkemade F., Castaldi C., Strategies for the diffusion of innovations on social networks, Computational Economics, 25, 1, 2005, 3-23.
  • [26] Bohlmann J. D., Calantone R. J., Zhao M., The Effects of Market Network Heterogeneity on Innovation Diffusion: An Agent-Based Modeling Approach, Journal of Product Innovation Management, 27, 2010, 741-760.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8c3440c9-3212-4dba-8f8e-3ee51d8d9a17
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