Role of Electronic Customer Relationship Management in Demand Chain Management: A Predictive Analytic Approach
In 21st century, collaborative business supply chain environments are required to be proactive rather than reactive so that they can better deal with the uncertainty, growing competition, shorter cycle times, more demanding customers and pressure to cut costs. Demand chain management as a new business model requires investing in consumer insights and closer relationships in the supply chain to conduct predictive analysis of retail intelligent solutions. In this regard new kinds of methodologies are required to be discussed. However, at the execution level the limitations in terms of scalability, data integration and knowledge based decision support to providers or suppliers in terms of strategy building and in providing deductive inference capabilities are to be addressed. Therefore, it is required to describe how predictive analytics helps in constructing the knowledge base to conduct verification and validation in terms of semantic predictive analytic for the domain of demand chain management.
Year of publication: |
2017
|
---|---|
Authors: | Vasista, T. G. K. ; AlAbdullatif, A. M. |
Published in: |
International Journal of Information Systems and Supply Chain Management (IJISSCM). - IGI Global, ISSN 1935-5734, ZDB-ID 2400984-2. - Vol. 10.2017, 1 (01.01.), p. 53-67
|
Publisher: |
IGI Global |
Subject: | Business Intelligence | CRASP Methodology | Demand Chain Management | ECRM | Predictive Analytics | Semantic Predictive Analytics | TAMPA Methodology |
Saved in:
Online Resource
Saved in favorites
Similar items by subject
-
Vasista, T. G. K., (2017)
-
Huikku, Jari, (2017)
-
Transforming Logistics Pricing: How Improved Business Intelligence Can Inform Logistics
Peck Jr, Jeffrey Drue, (2017)
- More ...
Similar items by person