Presentation of a combined data mining model using associative rules and clustering to identify the dominant patterns of customer behavior (Case study: Ansar Bank)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Gharib Iman; Toloie Abbas; HEIDARZADEH KAMBIZ

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Management Future Research Year:2019 | Volume:30 | Issue:118 Page(s): 189-202

Download Full-Text

Persian Verion

View:

555

Download:

Cites:

Information Journal Paper

Title

Presentation of a combined data mining model using associative rules and clustering to identify the dominant patterns of customer behavior (Case study: Ansar Bank)

Author(s)

Gharib Iman | Toloie Abbas | HEIDARZADEH KAMBIZ | Issue Writer Certificate

Keywords

segmentationQ1

Customer Dynamic BehaviorQ1

Association RulesQ1

Abstract

Background: A new matter that arises in term of the dynamic behavior of customers is considering the customer segmentation. Based on the banks competitions to increase market share as well as the psychological and environmental factors the dynamics of customers’ behavior should be considered over time. Transferring customers to different sectors over time and discovering the dominant models in their displacements between sectors are of important topics in this context. Objective: this article aims to identify the behavioral clusters, the dominant patterns of displacement, and the leading characteristics and patterns of customer displacements with a focus on the customer dynamics behavior of Ansar banks. Design/Methodology: A Hybrid method based on clustering and Association Rules has been proposed. Finding: four different behavioral group of customer are identified: " low-value customers with sustainable model", "low-value customer with unsustainable profitability model", "turned away customers with average profitability", "loyal customers with low profitability". Relations between of these groups are analyzed by Association Rules.

Cites

No record.

References

No record.

Cite

APA: Copy

Gharib, Iman, Toloie, Abbas, & HEIDARZADEH, KAMBIZ. (2019). Presentation of a combined data mining model using associative rules and clustering to identify the dominant patterns of customer behavior (Case study: Ansar Bank). JOURNAL OF MANAGEMENT FUTURES RESEARCH(JOURNAL OF MANAGEMENT RESEARCH), 30(118 ), 189-202. SID. https://sid.ir/paper/204332/en

Vancouver: Copy

Gharib Iman, Toloie Abbas, HEIDARZADEH KAMBIZ. Presentation of a combined data mining model using associative rules and clustering to identify the dominant patterns of customer behavior (Case study: Ansar Bank). JOURNAL OF MANAGEMENT FUTURES RESEARCH(JOURNAL OF MANAGEMENT RESEARCH)[Internet]. 2019;30(118 ):189-202. Available from: https://sid.ir/paper/204332/en

IEEE: Copy

Iman Gharib, Abbas Toloie, and KAMBIZ HEIDARZADEH, “Presentation of a combined data mining model using associative rules and clustering to identify the dominant patterns of customer behavior (Case study: Ansar Bank),” JOURNAL OF MANAGEMENT FUTURES RESEARCH(JOURNAL OF MANAGEMENT RESEARCH), vol. 30, no. 118 , pp. 189–202, 2019, [Online]. Available: https://sid.ir/paper/204332/en

Related Journal Papers