A Data Mining Based Approach to a Firm's Marketing Channel
| dc.contributor.author | Ozyirmidokuz, Esra Kahya | |
| dc.contributor.author | Uyar, Kumru | |
| dc.contributor.author | Ozyirmidokuz, Mustafa Hakan | |
| dc.date.accessioned | 2025-02-24T17:18:33Z | |
| dc.date.available | 2025-02-24T17:18:33Z | |
| dc.date.issued | 2015 | |
| dc.department | Nuh Naci Yazgan | |
| dc.description | 22nd International Economic Conference of Sibiu (IECS) -- MAY 15-16 -- 2015 -- Sibiu -- ROMANIA | |
| dc.description.abstract | Firms need to collect and analyze marketing data in order to have a competitive advantage in the sector. The aim of this research is to extract knowledge from an international firm's marketing channel to improve the efficiency of the marketing system. The Cross Industry Standard Process for Data Mining (CRISP-DM) is used to analyze the survey data. Data are clustered by applying a Kohonen Self Organizing Map (SOM) to reduce the attributes. Anomaly detection analysis is applied. We generate a C5.0 Decision Tree (DT) model used for predicting the marketing channel firms' complaints with very high accuracy. Decision rules are also extracted. (C) 2015 The Authors. Published by Elsevier B.V. | |
| dc.description.sponsorship | Lucian Blaga Univ Sibiu, Fac Econ Sci,Assoc Excellence Econ,Econ Sci Fac Assoc Romania,Management Acad Soc Romania | |
| dc.identifier.doi | 10.1016/S2212-5671(15)00975-2 | |
| dc.identifier.endpage | 84 | |
| dc.identifier.issn | 2212-5671 | |
| dc.identifier.startpage | 77 | |
| dc.identifier.uri | https://doi.org/10.1016/S2212-5671(15)00975-2 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14440/740 | |
| dc.identifier.volume | 27 | |
| dc.identifier.wos | WOS:000381115300011 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.language.iso | en | |
| dc.publisher | Elsevier Science Bv | |
| dc.relation.ispartof | 22nd International Economic Conference of Sibiu 2015, Iecs 2015 Economic Prospects in the Context of Growing Global and Regional Interdependencies | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.snmz | KA_WOS_20250201 | |
| dc.subject | Knowledge discovery in databases | |
| dc.subject | data mining | |
| dc.subject | DT, rule induction, marketing channel complaints | |
| dc.title | A Data Mining Based Approach to a Firm's Marketing Channel | |
| dc.type | Conference Object |
