Reviewing the concept of CKM with social perspective by means of the ANN-GT approach (case study: environmental protection by the water market implementation)
Maedeh Rabbanimehr,
Ali Sanayei and
Ali Kazemi
International Journal of Procurement Management, 2020, vol. 13, issue 4, 462-481
Abstract:
The purpose of this research is to develop a customer knowledge management model adopting a social marketing approach for solving social problems by a case study for the facilitation of water market implementation. In this regard, mixed research and qualitative approaches consisting of thematic analysis and grounded theory, together with a quantitative approach (artificial neural network) have been used, and ultimately, a combination model has been proposed. The statistical population incorporates three groups of experts (academics, farmers and water industry experts) in the qualitative section of the research, and in the quantitative section, it includes farmers throughout the Zayandehrood Basin in Iran. One of the most important results of this research is the ranking of customer knowledge management indicators taking a neural network approach in predicting the social facilitation and planning, based on which it attracts popular participation in social issues.
Keywords: customer knowledge management; CKM; social marketing; social facilitation; water market; artificial neural network; ANN; GT. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=108614 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpman:v:13:y:2020:i:4:p:462-481
Access Statistics for this article
More articles in International Journal of Procurement Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().