Discriminant Analysis of Factors Affecting Telecoms Customer Churn

Oghojafor, Ben E. Akpoyomare; Mesike, G. C.; Bakarea, Rasaki; Omoera, C. I; Adeleke, Ismaila

doi:10.5430/ijba.v3n2p59

Cited by 11 publications

(10 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Han et al [14] discussed the relationship between consumer sentiment, switching barriers, customer satisfaction, and customer retention and believed that customer satisfaction was positively correlated with customer retention. After analyzing the reasons for customer churn, Oghojafor et al [15] put forward strategies for reducing churn rate. Stauss and Friege [16] believed that effective customer win-back should trace the reason for customer churn.…”

Section: Literature Reviewmentioning

confidence: 99%

A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China

Zhao

Qing-jun

Chang

et al. 2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

Customer churn will cause the value flowing from customers to enterprises to decrease. If customer churn continues to occur, the enterprise will gradually lose its competitive advantage. When the growth of new customers cannot meet the needs of enterprise development, the enterprise will fall into a survival dilemma. Focusing on the customer churn prediction model, this paper takes the telecom industry in China as the research object, establishes a customer churn prediction model by using a logistic regression algorithm based on the big data of high-value customer operation in the telecom industry, effectively identifies the potential churned customers, and then puts forward targeted win-back strategies according to the empirical research results. This paper analyzes the trends and causes of customer churn through data mining algorithms and gives the answers to such questions as how the customer churn occurs, the influencing factors of customer churn, and how enterprises win back churned customers. The results of this paper can better serve the practice of customer relationship management in the telecom industry and provide a reference for the telecom industry to identify high-risk churned customers in advance, enhance customer loyalty and viscosity, maintain “high-value” customers, and continue to provide customers with “value” and reduce the cost of maintaining customers.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China

Zhao

Qing-jun

Chang

et al. 2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…Research on customer defection has been largely on two issues. The first is to understand its triggering forces for which hypothesized influence of antecedents on customer churning is investigated through customer data available from service providers or through self-report surveys (Ahn et al , 2006; Eshghi et al , 2006; Hejazinia and Kazemi, 2014; Kim and Yoon, 2004; Kisioglu and Topcu, 2011; Oghojafor et al , 2012; Portela and Menezes, 2010; Wong, 2011). The second approach is to develop prediction models of customer behaviors (Coussement and De Bock, 2013; Coussement et al , 2010; Glady et al , 2009; Gorgoglione and Panniello, 2011; Gürsoy 2010; Hadden et al , 2005; Hou and Tang, 2010; Huang et al , 2010; Huang et al , 2012; Jahromi et al , 2014; Jamal and Bucklin, 2006; Lariviere and Van den Poel, 2004; Lin et al , 2011; Migueis et al , 2012; Neslin et al , 2006; Owczarczuk, 2010; Qi et al , 2009; Richter et al , 2010; Tsai and Chen, 2010; Tsai and Lu, 2009; Verbeke et al , 2011; 2014; Wang et al , 2009; Xia and Jin, 2008; Xiao et al , 2014; Xie et al , 2009; Yu et al , 2011; Zhang et al , 2012).…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

“…In previous studies, various antecedents of consumer defections have been studied in the context of different service industries. The antecedents include such clients’ demographic factors as residential areas, income levels and ages (Ahn et al , 2006; Kim and Yoon, 2004; Kisioglu and Topcu, 2011; Oghojafor et al , 2012; Portela and Menezes, 2010; Wong, 2011). It has been frequently shown that higher levels of perceived service quality and satisfaction lead to lower chances of consumer churn (Ahn et al , 2006; Eshghi et al , 2006; Hejazinia and Kazemi, 2014).…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

“…Also, network service providers need to manage customer satisfaction based on broad service elements, including QoS, terminals and brand images (Kim and Yoon, 2004). Besides, through systematic analysis of client data, optimization may be necessary on service pricing, payment arrangement and the level of commercialization (Wong, 2011; Oghojafor et al , 2012). Despite that many studies have been conducted on customer retention and churn, there is scant research on customer behaviors in the context of IT convergence service such as IPTV and, to the best of our knowledge, few empirical works of this type have been undertaken based on real customer data – rather than perception-driven surveys – gathered by a large telecommunications service company.…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Understanding IPTV churning behaviors: focus on users in South Korea

Kim¹,

Kim

Park

2017

APJIE

View full text Add to dashboard Cite

Purpose-This study aims to investigate customers' churning out of Internet Protocol Television (IPTV) service, one of the most prevalent forms of IT convergence. Design/methodology/approach-Based on the review of current literature, a research model is introduced to depict the effects of select independent variables on customer churning behavior. First of all, the two groups are compared in terms of predictor variables, including switching barriers, voice of customer (VOC), membership period and degree of contents usage. Then, a curvilinear regression was applied to understand the association relationship between the level of IPTV contents usage and variables of switching barriers, VOC and membership period. Third, a logit regression was performed to predict customer churning through the variables of switching barriers, VOC, membership period and level of IPTV contents usage. Findings-Through the empirical analysis, this study analyzed the factors affecting customer churning behavior of IPTV service providers based on switching barriers, VOC and contents usage. Originality/value-Although several studies on IPTV have been undertaken globally, they have largely depended on self-reporting surveys to examine dynamics between antecedent variables and IPTV performance in terms of customer satisfaction, usage intension and customer retention. This empirical study is performed to understand influential factors of IPTV service defection through the weblog analysis of 3,906 service users, who represented both service defectors and non-defectors during a specific month.

show abstract

“…A set of discriminatory functions predicted the willingness of subscribers to drop their current service provider [2]. Discriminant analysis was employed to classify retail bank customers on the basis of users and non-users, and then they identified which variables contribute to the classification [3].…”

Section: Introductionmentioning

confidence: 99%

A Discriminant Function Analysis Approach to Country’s Economy Status

M.N¹,

D.C²

2017

JAS

View full text Add to dashboard Cite

Abstract. In this paper, discriminant function analysis was used to classify 68 randomly selected countries to their respective economy status (Weak or Strong) on World Bank website data. The following economic indicators were used as independent variables: Gross Domestic Product (GDP), Ln(Mortality_rate), Ln(Inflation_rate) and Access_to_electricicty. It showed that Ln(Mortality_rate) and Access_to_electricity contributed most to linearly discriminate within the group (economy status) for the two levels (weak or strong) while GDP contributed least with 93.6% sensitivity and 91.2% of cross-validated grouped cases correctly classified.

show abstract

Discriminant Analysis of Factors Affecting Telecoms Customer Churn

Cited by 11 publications

References 14 publications

A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China

A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China

Understanding IPTV churning behaviors: focus on users in South Korea

A Discriminant Function Analysis Approach to Country’s Economy Status

Contact Info

Product

Resources

About