From Mobile Data Towards Better Customer Knowledge: Proposals for an Information Framework

Shankar, 2010, Mobile marketing in the retailing environment: Current insights and future research avenues, Journal of interactive marketing, 24, 111, 10.1016/j.intmar.2010.02.006 Takeuchi, Y., Sugimoto, M. Cityvoyager: An outdoor recommendation system based on user location history. In: Ubiquitous intelligence and computing. Springer; 2006, p. 625-636. Standing, 2005, Consumer perspectives on mobile advertising and marketing. In:, Australian and New Zealand Marketing Academy Conference (ANZMAC), Perth, Australia, 135 Persaud, 2012, Innovative mobile marketing via smartphones: Are consumers ready?, Marketing Intelligence & Planning, 30, 418, 10.1108/02634501211231883 Shankar, 2009, Mobile marketing: A synthesis and prognosis, Journal of Interactive Marketing, 23, 118, 10.1016/j.intmar.2009.02.002 Chen, 2003, Understanding customer relationship management (CRM): People, process and technology, Business process management journal, 9, 672, 10.1108/14637150310496758 Chan, 2005, Toward a unified view of customer relationship management, Journal of American Academy of Business, 6, 32 Payne, 2005, A strategic framework for customer relationship management, Journal of marketing, 69, 167, 10.1509/jmkg.2005.69.4.167 Ghose, A., Han, S.P. Marketing in the new mobile economy. In: Coussement, K., De Bock, K.W., Neslin, S.A., editors. Advanced database marketing. Gower Publishing Limited. ISBN 9781409444619; 2013, p. 189-207. Mike, M. Agenda overview for mobile marketing, 2014 2013 URL: https://www.gartner.com/doc/2629228/agenda-overview-mobile-marketing%7D. Adomavicius, G., Tuzhilin, A. Context-aware recommender systems. In: Recommender systems handbook. Springer; 2011, p. 217-253. Su, 2010, Music recommendation using content and context information mining, Intelligent Systems, IEEE, 25, 16, 10.1109/MIS.2010.23 Luo, 2013, Mobile targeting, Management Science, 60, 1738, 10.1287/mnsc.2013.1836 Goh, 2004, Mobile data mining by location dependencies, In: Intelligent Data Engineering and Automated Learning–IDEAL 2004. Springer;, 225 de Montjoye, Y.A., Quoidbach, J., Robic, F., Pentland, A.S. Predicting personality using novel mobile phone-based metrics. In: Social Computing, Behavioral-Cultural Modeling and Prediction. Springer; 2013, p. 48-55. Pentland, A. Reality mining of mobile communications: Toward a new deal on data. The Global Information Technology Report 2008-2009 2009;:1981. Bart, B. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications. Wiley; 2014. Farrahi, 2011, A probabilistic approach to socio-geographic reality mining, ACM SIG Multimedia Records, 3, 6, 10.1145/2069203.2069206 Yuan, 2003, A recommendation mechanism for contextualized mobile advertising, Expert Systems with Applications, 24, 399, 10.1016/S0957-4174(02)00189-6 Jiang, S., Fiore, G.A., Yang, Y., Ferreira Jr, J., Frazzoli, E., González, M.C. A review of urban computing for mobile phone traces: current methods, challenges and opportunities. In: Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing. ACM; 2013, p. 2. Nathan, E., Alex, P. Reality Mining: Sensing Complex Social Systems. <JT>Personal and Ubiquitous Computing</JT> 2006;10:255-268. Kim, 2007, Value-based adoption of mobile internet: an empirical investigation, Decision Support Systems, 43, 111, 10.1016/j.dss.2005.05.009