{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T12:25:34Z","timestamp":1785241534486,"version":"3.55.0"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T00:00:00Z","timestamp":1645142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Improving decision-making has become of paramount importance for gaining a competitive edge across organizations. Segmentation\/clustering is a key enabler for enhancing decision-making. The RFM (Recency, Frequency and Monetary) is a scoring model, which consists of three parameters that is widely used for the same purpose, especially for customer-centric organizations. However, the current RFM still has some drawbacks that diminish the effectiveness of decision-making and thus, research is still needed in this area. In an attempt to fill this gap, a novel data-driven weighted model is proposed. It introduces a new parameter; \u2018Adoption\u2019, to be added to the existing RFM parameters. The research contribution is extended to hybrid the proposed model with a clustering technique to segment data into distinct and meaningful groups or clusters. The hybrid model was applied on real bank data as a case study to enhance the usage of its digital channels. The results showed that bank customers were grouped into four distinct clusters. The bank stakeholders were able to identify the characteristics of customers and develop their relevant strategies accordingly. The developed model was evaluated by measuring its stability and robustness from both scientific and business perspectives.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac009","type":"journal-article","created":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T20:12:25Z","timestamp":1643400745000},"page":"1228-1240","source":"Crossref","is-referenced-by-count":9,"title":["A Novel Hybrid Segmentation Approach for Decision Support: A Case Study in Banking"],"prefix":"10.1093","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4361-5131","authenticated-orcid":false,"given":"Mona","family":"Mosa","sequence":"first","affiliation":[{"name":"Information Systems , College of Computing and Information Technology, Arab Academy for Science, Technology and Maritime Transport, 9 Abou Qear, Abu Qir Al Gharbeyah, Montaza 2, Alexandria Governorate, Postal Code 1029, Alexandria , Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7229-2597","authenticated-orcid":false,"given":"Nedaa","family":"Agami","sequence":"additional","affiliation":[{"name":"Operations Research and Decision Support , Cairo University, 1 Gamaa Street, Giza, Egypt, Postal Code 12613, Giza"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6201-629X","authenticated-orcid":false,"given":"Ghada","family":"Elkhayat","sequence":"additional","affiliation":[{"name":"Information Systems and Computers Department , Faculty of Commerce, Alexandria University, 22 El-Gaish Rd, Al Azaritah WA Ash Shatebi, Bab Sharqi, Alexandria Governorate, Postal Code 21544, Alexandria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0043-6205","authenticated-orcid":false,"given":"Mohamed","family":"Kholief","sequence":"additional","affiliation":[{"name":"Computer Science and Information Systems , College of Computing and Information Technology, Arab Academy for Science, Technology and Maritime Transport, 9 Abou Qear, Abu Qir Al Gharbeyah, Montaza 2, Alexandria Governorate, Postal Code 1029, Alexandria , Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,2,18]]},"reference":[{"key":"2023052000433942800_ref1","first-page":"0474","volume-title":"6th One Day International Conference on Commerce, Management and Social Sciences","year":"2020"},{"key":"2023052000433942800_ref2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1108\/JSM-10-2016-0352","article-title":"Customer engagement in a big data world","volume":"31","author":"Kunz","year":"2017","journal-title":"J. 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