nach oben

Information Systems and e-Business Management

Erschienen in:

01.09.2013 | Original Article

A credit assessment mechanism for wireless telecommunication debt collection: an empirical study

verfasst von: Hsiu-Yu Wang, Chechen Liao, Cheng-Hsiung Kao

Erschienen in: Information Systems and e-Business Management | Ausgabe 3/2013

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The wireless telecommunication market in Taiwan is now saturated. As the competition between wireless service carriers intensifies, retaining customers becomes more difficult. To prevent companies from increasing bad debt and experiencing customer churn, this study aims to apply data mining method to build a credit assessment mechanism that can effectively evaluate customer credit risks and help wireless service carriers to enhance the quality of debt collection processes by customizing collection strategies for various customer groups. The application of the proposed mechanism to related problems in a wireless telecommunication company in Taiwan has shown satisfactory effectiveness, accounting for a savings of $2 million of a total $500 million annual revenue. A mere 0.4 % savings is significant, given that wireless service carriers in Taiwan typically allocate 2–4 % of their revenue to uncollectible debts.

Vorheriger Artikel The need for systems development capability in design science research: enabling researcher-systems developer collaboration

Nächster Artikel A mapping model for assessing project effort from requirements

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Ahmed SR (2004) Applications of data mining in retail business. In: International conference on information technology: coding and computing, vol 2, no 2, pp 455–459

Bolton RN, Kannan P, Bramlett MD (2000) Implications of loyalty program membership and service experiences for customer retention and value. J Acad Mark Sci 28(1):95–108CrossRef

Bose R (2002) Customer relationship management: key components for IT success. Indus Manage Data Syst 102(2):89–97CrossRef

Bose I, Mahapatra RK (2001) Business data mining—a machine learning perspective. Inform Manage 39(3):211–225CrossRef

Burez J, Van den Poel D (2007) CRM at a pay-TV company: using analytical models to reduce customer attrition by targeted marketing for subscription services. Expert Syst Appl 32(2):277–288CrossRef

Caruana R, Niculescu-Mizil A (2004) Data mining in metric space: an empirical analysis of supervised learning performance criteria. In: Proceedings of the tenth international conference on knowledge discovery and data mining (KDD’ 04), pp 69–78

Chen SY, Liu X (2004) The contribution of data mining to information science. J Inform Sci 30(6):550–558CrossRef

Chuang CL, Lin RH (2009) Constructing a reassigning credit scoring model. Expert Syst Appl 36(2):1685–1694CrossRef

Crook JN, Edelman DB, Thomas LC (2007) Recent developments in consumer credit risk assessment. Eur J Oper Res 183(3):1447–1465CrossRef

Director NSA, Ojha S (2004) Measuring service performance in mobile communications. Serv Ind J 24(6):109–128CrossRef

Efrim Boritz J, Kennedy DB (1995) Effectiveness of neural network types for prediction of business failure. Expert Syst Appl 9(4):503–512CrossRef

Fayyad U, Piatetsky-Shapiro G, Smyth P (1996) The KDD process for extracting useful knowledge from volumes of data. Commun ACM 39(11):27–34CrossRef

Feelders A, Daniels H, Holsheimer M (2000) Methodological and practical aspects of data mining. Inform Manage 37(5):271–281CrossRef

Fletcher D, Goss E (1993) Forecasting with neural networks: an application using bankruptcy data. Inform Manage 24(3):159–167CrossRef

Frydman H, Schuermann T (2008) Credit rating dynamics and Markov mixture models. J Bank Finance 32(6):1062–1075CrossRef

Hsieh NC (2004) An integrated data mining and behavioral scoring model for analyzing bank customers. Expert Syst Appl 27(4):623–633CrossRef

Hui SC, Jha G (2000) Data mining for customer service support. Inform Manage 38(1):1–13CrossRef

Hung SY, Yen DC, Wang HY (2006) Applying data mining to telecom churn management. Expert Syst Appl 31(3):515–524CrossRef

Kim MK, Park MC, Jeong DH (2004) The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services. Telecommun Policy 28(2):145–160CrossRef

King SF, Burgess TF (2008) Understanding success and failure in customer relationship management. Ind Mark Manage 37(4):421–431CrossRef

Kolter P (1997) Marketing management: analysis, planning, implementation, and control. A Simon & Schuster Company, New Jersey

Lacher R, Coats PK, Sharma SC, Fant LF (1995) A neural network for classifying the financial health of a firm. Eur J Oper Res 85(1):53–65CrossRef

Larose DT (2005) Discovering knowledge in data. In: An introduction to data mining. Wiley Publishers, Hoboken

Lee TS, Chen IF (2005) A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines. Expert Syst Appl 28(4):743–752CrossRef

Lee TS, Chiu CC, Lu CJ, Chen IF (2002) Credit scoring using the hybrid neural discriminant technique. Expert Syst Appl 23(3):245–254CrossRef

Lee JY, Kim H, Kim PJ (2010) Domain analysis with text mining: analysis of digital library research trends using profiling methods. J Inform Sci 36(2):144–161CrossRef

Lin FR, Po RW, Orellan CVC (2011) Mining purchasing decision rules from service encounter data of retail chain stores. IseB 9(2):193–221CrossRef

Malhotra R, Malhotra D (2003) Evaluating consumer loans using neural networks. Omega 31(2):83–96CrossRef

Mithas S, Krishnan MS, Fornell C (2005) Why do customer relationship management applications affect customer satisfaction? J Market 69(4):201–209

Noh HJ, Roh TH, Han I (2005) Prognostic personal credit risk model considering censored information. Expert Syst Appl 28(4):753–762CrossRef

Rust RT, Moorman C, Dickson PR (2002) Getting return on quality: revenue expansion, cost reduction, or both? J Market 66(4):7–24

Sörensen K, Janssens GK (2003) Data mining with genetic algorithms on binary trees. Eur J Oper Res 151(2):253–264CrossRef

Thomas LC (2000) A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers. Int J Forecast 16(2):149–172CrossRef

Thomas L, Oliver R, Hand D (2005) A survey of the issues in consumer credit modelling research. J Oper Res Soc 56(9):1006–1015CrossRef

Wang HF, Hong WK (2006) Managing customer profitability in a competitive market by continuous data mining. Ind Mark Manage 35(6):715–723CrossRef

Woo KS, Fock HKY (1999) Customer satisfaction in the Hong Kong mobile phone industry. Serv Indus J 19(3):162–174CrossRef

Yang Y (2007) Adaptive credit scoring with kernel learning methods. Eur J Oper Res 183(3):1521–1536CrossRef

Zhang D, Zhou L (2004) Discovering golden nuggets: data mining in financial application. Syst Man Cybernet Part C Appl Rev IEEE Trans 34(4):513–522CrossRef

Titel: A credit assessment mechanism for wireless telecommunication debt collection: an empirical study
verfasst von: Hsiu-Yu Wang
Chechen Liao
Cheng-Hsiung Kao
Publikationsdatum: 01.09.2013
Verlag: Springer Berlin Heidelberg
Erschienen in: Information Systems and e-Business Management / Ausgabe 3/2013
Print ISSN: 1617-9846
Elektronische ISSN: 1617-9854
DOI: https://doi.org/10.1007/s10257-012-0192-x

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 3/2013

A method to support a reflective derivation of business components from conceptual models

An empirical study of cost-sensitive learning in cultural modeling

The need for systems development capability in design science research: enabling researcher-systems developer collaboration

A mapping model for assessing project effort from requirements

Performance of e-invoicing in Spanish firms

Design and design research as contextual practice