Creating Competitive Advantage by Using Data Mining Technique as an Innovative Method for Decision Making Process in Business

Orientarea organizatiilor spre marketingul relational a adus in prim plan trei concepte a caror importanta a crescut semnificativ in ultimul deceniu: atragerea, retentia si recastigarea clientilor pierduti. In mod firesc, se prefigureaza intrebarea privind gradul de prioritate al atragerii si respectiv al mentinerii clientilor. Raspunsul corect nu trebuie sa contrapuna cele doua laturi ale aceluiasi proces de dezvoltare a valorii fluxurilor viitoare de profit generate de portofoliul de clienti al organizatiei. In esenta, fiecare organizatie trebuie sa realizeze simultan demersuri pentru atragerea si retentia clientilor, investind insa un volum diferit de resurse in fiecare dintre cele doua arii, in functie de stadiul de evolutie al organizatiei, produsului/marcii si pietei. Optiunile managerilor si specialistilor de marketing se pot indrepta spre strategii ofensive, de atragere a unor noi clienti, sau spre strategii defensive, de mentinere a clientilor actuali.

[1]  Riyad Eid,et al.  Drivers and Barriers to Online Social Networks' Usage: The Case of Facebook , 2011, Int. J. Online Mark..

[2]  M. Porter Competitive Advantage: Creating and Sustaining Superior Performance , 1985 .

[3]  S. Carlsson Knowledge managing and knowledge management systems in inter-organizational networks , 2003 .

[4]  J. Barney Firm Resources and Sustained Competitive Advantage , 1991 .

[5]  Mehmed Kantardzic,et al.  Data Mining: Concepts, Models, Methods, and Algorithms , 2002 .

[6]  Olusegun Folorunso,et al.  Data mining as a technique for knowledge management in business process redesign , 2005, Inf. Manag. Comput. Security.

[7]  Chengqi Zhang,et al.  Association Rule Mining , 2002, Lecture Notes in Computer Science.

[8]  Robert Groth,et al.  Data Mining: Building Competitive Advantage , 1999 .

[9]  Parag C. Pendharkar Managing Data Mining Technologies in Organizations: Techniques and Applications , 2003 .

[10]  Chris Robertson Co-Constructing a Learning Community: A Tool for Developing International Understanding , 2011, Int. J. Technol. Educ. Mark..

[11]  Gregory Piatetsky-Shapiro,et al.  Advances in Knowledge Discovery and Data Mining , 2004, Lecture Notes in Computer Science.

[12]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[13]  Stephan Kudyba,et al.  Data Mining and Business Intelligence: A Guide to Productivity , 2001 .

[14]  Retha Snyman,et al.  The interdependency between strategic management and strategic knowledge management , 2004, J. Knowl. Manag..

[15]  R. Ayhan Yilmaz Marketing Online Education Programs: Frameworks for Promotion and Communication , 2011 .

[16]  Shichao Zhang,et al.  Association Rule Mining: Models and Algorithms , 2002 .

[17]  Vijay V. Raghavan,et al.  Dynamic Data Mining , 2000, IEA/AIE.

[18]  John Wang,et al.  Data Mining: Opportunities and Challenges , 2003 .

[19]  Hamid R. Nemati,et al.  Key factors for achieving organizational data-mining success , 2003, Ind. Manag. Data Syst..

[20]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[21]  Mindy Crain-Dorough,et al.  Financing Distance Education in a Time of Economic Challenge , 2011 .

[22]  Michael J. A. Berry,et al.  Data mining techniques - for marketing, sales, and customer support , 1997, Wiley computer publishing.

[23]  Ramaraj Palanisamy,et al.  Leveraging Cognition for Competitive Advantage: a Knowledge-Based Strategy Process , 2004, J. Inf. Knowl. Manag..

[24]  Sankar K. Pal,et al.  Pattern Recognition Algorithms for Data Mining: Scalability, Knowledge Discovery, and Soft Granular Computing , 2004 .