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Network of Contradictions Analysis in Marketing Information Quality Management

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Book cover Systematic Complex Problem Solving in the Age of Digitalization and Open Innovation (TFC 2020)

Abstract

The aim of this paper is to develop the method for network of contradiction analysis and improve the marketing information quality management. The issue of information is discussed. The information is considered as an abstract system and the marketing information is the variant form of this system. The reference to the basis of Classical Theory of Inventive Problem Solving (TRIZ) and General Theory of Powerful Thinking (OTSM) is made. The method of representing and selecting appropriate subset of contradictions among a complete set of contradictions within technical systems is presented. The principles and operations of Qualitology, Grey System Theory and Statistics are applied to adjust the method to guide the problem solver in choosing the most important contradictions within the abstract system of marketing information. The developed method for network of contradiction analysis in marketing information quality management was applied in the sales department of a manufacturing company. It is noticed that the selected subset of contradiction is to be further faced with ARIZ85-C. The analysis of the possibilities of the concept of the ARIZ85-C algorithms application to provide the best approach to be followed in solving the inventive problems in abstract system of information is the objective for the future studies.

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Correspondence to Joanna Majchrzak .

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Majchrzak, J., Miądowicz, M. (2020). Network of Contradictions Analysis in Marketing Information Quality Management. In: Cavallucci, D., Brad, S., Livotov, P. (eds) Systematic Complex Problem Solving in the Age of Digitalization and Open Innovation. TFC 2020. IFIP Advances in Information and Communication Technology, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-030-61295-5_25

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  • DOI: https://doi.org/10.1007/978-3-030-61295-5_25

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-61295-5

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