To stay competitive, the mobile telecommunication companies spend millions of Ghana cedi each year on building long-term relationships with their customers. Marketing managers are constantly challenged with the proble...To stay competitive, the mobile telecommunication companies spend millions of Ghana cedi each year on building long-term relationships with their customers. Marketing managers are constantly challenged with the problem of where to channel the limited resources in order to retain existing customers. This study approaches the customer retention problem in the mobile phone sector from a behavioural perspective, applying the Behavioural Perspective Model as the main analytical framework and further exploits some other factors that influence customer retention. The model includes a set of pre-behaviour and post-behaviour factors to study consumer choice, and explains its relevant drivers in a viable and comprehensive way, grounded in radical behaviourism. Data for the analysis were collected from tertiary students from Accra and Takoradi. Data collected were analysed using the multinomial regression technique. Analysis of the data revealed that the Behaviour setting factor is the only significant element in Behaviour Perspective Model. Further exploitation of behaviour situation revealed that the number of networks a customer uses, previous experience of a customer and customer’s intention are significant factors in determining customer retention in Ghana’s mobile telecommunication industry.展开更多
Presently,customer retention is essential for reducing customer churn in telecommunication industry.Customer churn prediction(CCP)is important to predict the possibility of customer retention in the quality of service...Presently,customer retention is essential for reducing customer churn in telecommunication industry.Customer churn prediction(CCP)is important to predict the possibility of customer retention in the quality of services.Since risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer behavior.Besides,deep learning(DL)models help in prediction of the customer behavior based characteristic data.Since the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business people.In this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application sector.In addition,the O-DCCAEP method purposes for determining the churning nature of the customers.The O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter optimization.Additionally,the DCCAE model is employed to classify the churners or non-churner.Furthermore,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.展开更多
Recent technological advances enable firms to engage more effectively with customers who reveal their intent to churn.When consumers disclose such intentions,firms can offer targeted discounts,a form of personalized p...Recent technological advances enable firms to engage more effectively with customers who reveal their intent to churn.When consumers disclose such intentions,firms can offer targeted discounts,a form of personalized pricing,to encourage retention.Prior literature,however,shows that broad use of personalized pricing for all returning customers can intensify competition and erode profits in competitive markets.We show that these adverse effects are substantially mitigated when personalized prices are offered selectively,i.e.,only after firms identify consumers who are likely to churn.Analyzing a retention-focused personalized pricing strategy,we find three main results.First,personalized pricing increases firm profits only when the proportion of disclosers is relatively low;although it raises margins on retained customers,it also intensifies first-period competition.Second,consumer surplus and social welfare improve when the share of disclosers is high,because higher disclosure induces stronger price reductions and greater retention.Third,firms often have incentives to invest in personalized pricing capabilities,but mutual investment can generate a Prisoner’s Dilemma:Even with low investment costs,simultaneous adoption may strengthen competition and reduce industry profits.These results emphasize the importance of selective targeting and timing when deploying personalized pricing for retention and offer guidance for firms and policymakers considering such investments.展开更多
文摘To stay competitive, the mobile telecommunication companies spend millions of Ghana cedi each year on building long-term relationships with their customers. Marketing managers are constantly challenged with the problem of where to channel the limited resources in order to retain existing customers. This study approaches the customer retention problem in the mobile phone sector from a behavioural perspective, applying the Behavioural Perspective Model as the main analytical framework and further exploits some other factors that influence customer retention. The model includes a set of pre-behaviour and post-behaviour factors to study consumer choice, and explains its relevant drivers in a viable and comprehensive way, grounded in radical behaviourism. Data for the analysis were collected from tertiary students from Accra and Takoradi. Data collected were analysed using the multinomial regression technique. Analysis of the data revealed that the Behaviour setting factor is the only significant element in Behaviour Perspective Model. Further exploitation of behaviour situation revealed that the number of networks a customer uses, previous experience of a customer and customer’s intention are significant factors in determining customer retention in Ghana’s mobile telecommunication industry.
文摘Presently,customer retention is essential for reducing customer churn in telecommunication industry.Customer churn prediction(CCP)is important to predict the possibility of customer retention in the quality of services.Since risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer behavior.Besides,deep learning(DL)models help in prediction of the customer behavior based characteristic data.Since the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business people.In this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application sector.In addition,the O-DCCAEP method purposes for determining the churning nature of the customers.The O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter optimization.Additionally,the DCCAE model is employed to classify the churners or non-churner.Furthermore,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.
基金supported in part by the National Natural Science Foundation of China(NSFC),under Grant No.72131004.
文摘Recent technological advances enable firms to engage more effectively with customers who reveal their intent to churn.When consumers disclose such intentions,firms can offer targeted discounts,a form of personalized pricing,to encourage retention.Prior literature,however,shows that broad use of personalized pricing for all returning customers can intensify competition and erode profits in competitive markets.We show that these adverse effects are substantially mitigated when personalized prices are offered selectively,i.e.,only after firms identify consumers who are likely to churn.Analyzing a retention-focused personalized pricing strategy,we find three main results.First,personalized pricing increases firm profits only when the proportion of disclosers is relatively low;although it raises margins on retained customers,it also intensifies first-period competition.Second,consumer surplus and social welfare improve when the share of disclosers is high,because higher disclosure induces stronger price reductions and greater retention.Third,firms often have incentives to invest in personalized pricing capabilities,but mutual investment can generate a Prisoner’s Dilemma:Even with low investment costs,simultaneous adoption may strengthen competition and reduce industry profits.These results emphasize the importance of selective targeting and timing when deploying personalized pricing for retention and offer guidance for firms and policymakers considering such investments.
