Xin Zhang^1,2, Gege Jiang^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.3, pp. 1-5, 2023, DOI:10.32604/icces.2023.09222

Abstract With the booming development of the ride-sourcing (RS)industry, aggregation platforms that integrate RS companies have emerged in recent years, such as Gaode and Meituan. Aggregation platforms can consolidate resources and avoid fragmentation of the market. But the emergence of aggregation platforms has also changed the market structure and brought challenges. This paper explores the impact of aggregation platforms on the market with two models of companies: customer-to-customer (C2C) companies, and business-to-customer (B2C) companies. C2C companies adjust supply and demand to maximize revenue by determining travel fares and the cut taken from the travel fares, i.e., the commission. B2C companies will… More >

Yaling Xu, Congjun Rao^*, Xinping Xiao, Fuyan Hu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2715-2742, 2023, DOI:10.32604/cmes.2023.029023

Abstract As the banking industry gradually steps into the digital era of Bank 4.0, business competition is becoming increasingly fierce, and banks are also facing the problem of massive customer churn. To better maintain their customer resources, it is crucial for banks to accurately predict customers with a tendency to churn. Aiming at the typical binary classification problem like customer churn, this paper establishes an early-warning model for credit card customer churn. That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm (GSA) and an Improved Beetle Antennae Search (IBAS) is proposed to optimize the parameters of the… More > Graphic Abstract

Fang Yu¹, Wenbin Bi², Ning Cao^3,4,*, Hongjun Li¹, Russell Higgs⁵

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.018349

Abstract In view of the fact that the prediction effect of influential financial customer churn in the Internet of Things environment is difficult to achieve the expectation, at the smart contract level of the blockchain, a customer churn prediction framework based on situational awareness and integrating customer attributes, the impact of project hotspots on customer interests, and customer satisfaction with the project has been built. This framework introduces the background factors in the financial customer environment, and further discusses the relationship between customers, the background of customers and the characteristics of pre-lost customers. The improved Singular Value Decomposition (SVD) algorithm and… More >

Nagaraju Jajam, Nagendra Panini Challa^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 977-997, 2023, DOI:10.32604/cmc.2023.036098

Abstract In the insurance sector, a massive volume of data is being generated on a daily basis due to a vast client base. Decision makers and business analysts emphasized that attaining new customers is costlier than retaining existing ones. The success of retention initiatives is determined not only by the accuracy of forecasting churners but also by the timing of the forecast. Previous works on churn forecast presented models for anticipating churn quarterly or monthly with an emphasis on customers’ static behavior. This paper’s objective is to calculate daily churn based on dynamic variations in client behavior. Training excellent models to… More >

Osman M. Karatepe^1,*, Raheleh Hassannia¹, Tuna Karatepe¹, Constanţa Enea², Hamed Rezapouraghdam¹

International Journal of Mental Health Promotion, Vol.25, No.2, pp. 287-307, 2023, DOI:10.32604/ijmhp.2022.025706

Abstract There are a plethora of empirical pieces about employees’ pro-environmental behaviors. However, the extant literature has either ignored or not fully examined various factors (e.g., negative or positive non-green workplace factors) that might affect employees’ pro-environmental behaviors. Realizing these voids, the present paper proposes and tests a serial mediation model that examines the interrelationships of job insecurity, emotional exhaustion, met expectations, and proactive pro-environmental behavior. We used data gathered from hotel customer-contact employees with a time lag of one week and their direct supervisors in China. After presenting support for the psychometric properties of the measures via confirmatory analysis in… More >

Zizhen Qin, Yuxin Liu, Tianze Zhang^*

Journal on Artificial Intelligence, Vol.4, No.3, pp. 143-154, 2022, DOI:10.32604/jai.2022.031843

Abstract With the rapid development of interest rate market and big data, the banking industry has shown the obvious phenomenon of “two or eight law”, 20% of the high quality customers occupy most of the bank’s assets, how to prevent the loss of bank credit card customers has become a growing concern for banks. Therefore, it is particularly important to establish a customer churn early warning model. In this paper, we will use the random forest method to establish a customer churn early warning model, focusing on the churn of bank credit card customers and predicting the possibility of future churn… More >

Ayodeji O. J Ibitoye^1,*, Olufade F. W Onifade²

Journal on Big Data, Vol.4, No.2, pp. 87-95, 2022, DOI:10.32604/jbd.2022.024533

Abstract Community based churn prediction, or the assignment of recognising the influence of a customer’s community in churn prediction has become an important concern for firms in many different industries. While churn prediction until recent times have focused only on transactional dataset (targeted approach), the untargeted approach through product advisement, digital marketing and expressions in customer’s opinion on the social media like Twitter, have not been fully harnessed. Although this data source has become an important influencing factor with lasting impact on churn management. Since Social Network Analysis (SNA) has become a blended approach for churn prediction and management in modern… More >

Lin Lang¹, Shuang Zhou¹, Minjuan Zhong^1,*, Guang Sun¹, Bin Pan¹, Peng Guo^1,2

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3503-3513, 2023, DOI:10.32604/cmc.2023.023596

Abstract Using the RFM (Recency, Frequency, Monetary value) model can provide valuable insights about customer clusters which is the core of customer relationship management. Due to accurate customer segment coming from dynamic weighted applications, in-depth targeted marketing may also use type of dynamic weight of R, F and M as factors. In this paper, we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights. Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data… More >

A. S. Harish^*, C. Malathy

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 589-600, 2023, DOI:10.32604/iasc.2023.032030

Abstract Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers. It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities. The volume and volatility of the business makes it one of the prospective fields for analytical study and data modeling. This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting, customer targeting, customized offers, value proposition etc. The segmentation could be on various… More >

Vani Haridasan^*, Kavitha Muthukumaran, K. Hariharanath

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3531-3544, 2023, DOI:10.32604/iasc.2023.030628

Abstract Customer retention is one of the challenging issues in different business sectors, and various firms utilize customer churn prediction (CCP) process to retain existing customers. Because of the direct impact on the company revenues, particularly in the telecommunication sector, firms are needed to design effective CCP models. The recent advances in machine learning (ML) and deep learning (DL) models enable researchers to introduce accurate CCP models in the telecommunication sector. CCP can be considered as a classification problem, which aims to classify the customer into churners and non-churners. With this motivation, this article focuses on designing an arithmetic optimization algorithm… More >