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

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 for investigating the customer review.… More >

Olfat M. Mirza¹, G. Jose Moses², R. Rajender³, E. Laxmi Lydia⁴, Seifedine Kadry⁵, Cheadchai Me-Ead⁶, Orawit Thinnukool^7,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3757-3769, 2022, DOI:10.32604/cmc.2022.030428

Abstract 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… More >

K. Meenakshi^*, K. Sashi Rekha

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

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 problems including lack of data… More >

Chang-Yi Kao¹, Hao-En Chueh^2,*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 913-924, 2023, DOI:10.32604/iasc.2023.024734

Abstract

The use of voice to perform biometric authentication is an important technological development, because it is a non-invasive identification method and does not require special hardware, so it is less likely to arouse user disgust. This study tries to apply the voice recognition technology to the speech-driven interactive voice response questionnaire system aiming to upgrade the traditional speech system to an intelligent voice response questionnaire network so that the new device may offer enterprises more precise data for customer relationship management (CRM). The intelligence-type voice response gadget is becoming a new mobile channel at the current time, with functions of… More >

Soban Arshad¹, Khalid Iqbal^1,*, Sheneela Naz², Sadaf Yasmin¹, Zobia Rehman²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4283-4301, 2022, DOI:10.32604/cmc.2022.025442

Abstract Telecom industry relies on churn prediction models to retain their customers. These prediction models help in precise and right time recognition of future switching by a group of customers to other service providers. Retention not only contributes to the profit of an organization, but it is also important for upholding a position in the competitive market. In the past, numerous churn prediction models have been proposed, but the current models have a number of flaws that prevent them from being used in real-world large-scale telecom datasets. These schemes, fail to incorporate frequently changing requirements. Data sparsity, noisy data, and the… More >

Rashin Kaviti, Osman M. Karatepe^*

International Journal of Mental Health Promotion, Vol.24, No.3, pp. 331-345, 2022, DOI:10.32604/ijmhp.2022.018516

Abstract The current knowledge base lacks evidence about situational- and surface-level personality variables and their impacts on job embeddedness and proclivity to be absent from work. With this recognition, drawing from the hierarchical personality model and fit theory as well as job embeddedness theory, our paper explores the influences of job resourcefulness (JR) and customer orientation (CO) on job embeddedness and propensity to be absent from work. We tapped time-lagged data gathered from hotel customer-contact employees in the United Arab Emirates to assess the aforementioned linkages via structural equation modeling. CO is a complete mediator between JR and job embeddedness, while… More >

B. Srikanth^1,*, Swarajya Lakshmi V. Papineni², Gutta Sridevi³, D. N. V. S. L. S. Indira⁴, K. S. R. Radhika⁵, Khasim Syed⁶

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 21-34, 2022, DOI:10.32604/iasc.2022.022423

Abstract In India, the banks have a formidable edge in maintaining their customer retention ratio for past few decades. Downfall makes the private banks to reduce their operations and the nationalised banks merge with other banks. The researchers have used the traditional and ensemble algorithms with relevant feature engineering techniques to better classify the customers. The proposed algorithm uses a Meta classifier instead of an ensemble algorithm with an adaptive genetic algorithm for feature selection. Churn prediction is the number of customers who wants to terminate their services in the banking sector. The model considers twelve attributes like credit score, geography,… More >

R. Siva Subramanian^1,*, D. Prabha²

Computer Systems Science and Engineering, Vol.41, No.1, pp. 339-355, 2022, DOI:10.32604/csse.2022.020043

Abstract Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain and redundant attributes in the… More >

Xian Zhao, Pantea Keikhosrokiani^*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3855-3874, 2022, DOI:10.32604/cmc.2022.019750

Abstract The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down. The general public has responded to call of the government to stay at home. Offline retail stores have been severely affected. Therefore, in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience, this study aims to utilize historical sales data for exploring, building sales prediction and recommendation models. A novel data science life-cycle and process model with Recency, Frequency, and Monetary (RFM) analysis method with the combination of various analytics algorithms are utilized in this study for… More >

Iram Mushtaq¹, Muhammad Umer¹, Muhammad Imran², Inzamam Mashood Nasir³, Ghulam Muhammad^4,*, Mohammad Shorfuzzaman⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 59-72, 2022, DOI:10.32604/cmc.2022.019337

Abstract During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers. A questionnaire has been… More >