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., 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 - 03 August 2023

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… 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 - 26 May 2023

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… More >

Nagaraju Jajam, Nagendra Panini Challa^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 977-997, 2023, DOI:10.32604/cmc.2023.036098 - 06 February 2023

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… 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 - 02 February 2023

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 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 - 31 October 2022

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… More >

A. S. Harish^*, C. Malathy

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 589-600, 2023, DOI:10.32604/iasc.2023.032030 - 29 September 2022

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… 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 - 17 August 2022

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… More >

K. Selvasheela^1,*, A. M. Abirami², Abdul Khader Askarunisa³

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2537-2552, 2023, DOI:10.32604/csse.2023.029148 - 01 August 2022

Abstract Nowadays, commercial transactions and customer reviews are part of human life and various business applications. The technologies create a great impact on online user reviews and activities, affecting the business process. Customer reviews and ratings are more helpful to the new customer to purchase the product, but the fake reviews completely affect the business. The traditional systems consume maximum time and create complexity while analyzing a large volume of customer information. Therefore, in this work optimized recommendation system is developed for analyzing customer reviews with minimum complexity. Here, Amazon Product Kaggle dataset information is utilized More >

K. Meenakshi^*, K. Sashi Rekha

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 111-128, 2023, DOI:10.32604/iasc.2023.025032 - 06 June 2022

Abstract Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a network. Both transactions in the system are carried out by consensus processes and to preserve confidentiality all the files contained cannot be changed. Blockchain technology is the fundamental software behind digital currencies like Bitcoin, which is common in the marketplace. Cloud computing is a method of using a network of external machines to store, monitor, and process information, rather than using the local computer or a local personal computer. The software is currently facing multiple… More >