Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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.

Airport Management—Value of Customer Display Systems

By providing real-time updates of essential information, airports not only display and disseminate information but also help control the flow of traffic. In order to maximize available space, particularly in high traffic areas, Airport Display Information Systems should be integrated into the overall design of the airport and their positioning should be carefully planned to deliver optimal results. Airport Display Information Systems can help airports maximize space, increase customer satisfaction, and generate new revenue opportunities. The technology is designed not only to comply with environmental regulations, but also to help airports keep budgets in check. This paper discusses airport display systems, their connections and interoperability with other systems and who the key airport users of these airport display systems are.

Chinese Telephone Number-Input Technology and Its Applications in a Customer Service Call Center

The Chinese intelligence input technology, its applications, and a customer service call center system are developed. This technology can be used both in standard English telephone number input keyboard and in Chinese telephone number input keyboard .And authors develop sophisticated technologies including "Pinyin" (the Chinese phonetic alphabet ) encoding technology of phonetic symbol code and formal symbol code of Chinese character structure, phrase encoding technology, input technology of whole sentence intelligence encoding and input technology of Chinese telephone number encoding.

Beyond Customer Churn: Generating Personalized Actions to Retain Customers in a Retail Bank by a Recommender System Approach

Customer churn may be a critical issue for banks. The extant literature on statistical and machine learning for customer churn focuses on the problem of correctly predicting that a customer is about to switch bank, while very rarely consid-ers the problem of generating personalized actions to improve the customer retention rate. However, these decisions are at least as critical as the correct identification of customers at risk. The decision of what actions to deliver to what customers is normally left to managers who can only rely upon their knowledge. By looking at the scientific literature on CRM and personalization, this research proposes a number of models which can be used to generate marketing ac-tions, and shows how to integrate them into a model embracing both the analytical prediction of customer churn and the generation of retention actions. The benefits and risks associated with each approach are discussed. The paper also describes a case of application of a predictive model of customer churn in a retail bank where the analysts have also generated a set of personalized actions to retain customers by using one of the approaches presented in the paper, namely by adapting a recommender system approach to the retention problem.

Prediction Models for Total Customer Satisfaction Based on the ISO/IEC9126 System Quality Model

The profitability of the system product is decided on the sales of the product. Furthermore, a customer satisfaction for products quality and a price have a big influence on the sales of the product. It spends limited financial resources effectively to raise the profitability of the system product, and it is necessary to realize the high quality product correspond to the customer needs as much as possible. There may be close relationship between cost of a product and an expense to implement the individual inherent attribute of system product. For the purpose of improvement of the customer satisfaction for quality of system product, the method of quantitative quality requirement and evaluation based on the ISO/IEC9126 quality model that includes six quality characteristics is widely recognized. However, independency among each quality characteristic has not been sure and the suitability of method for quality requirement of system product by using these six quality characteristics could not certified statistically. In the precedent study, introduced the requirements definition method for the quality of system product based on the system quality model defined in ISO/IEC9126 and proposed the effectiveness of it statistically. This study have measured the customer satisfaction for the system quality from the viewpoint of six quality characteristics quantitatively and confirmed the effectiveness of the technique to evaluate. In this study, we have confirmed the relationship between inherent attributes of the product and quantitative result of a measured value of total customer satisfaction from the view point of six quality characteristics statistically. This study performed the trial to clarify the relations with the inherent attributes that quantitative result of a measurement of the customer satisfaction based on six quality characteristics by the quality model of ISO/IEC9126. In addition, this study performed the development of the prediction model to estimate the total customer satisfaction for the system product from the view point of inherent attribute of the product. In this paper, we propose the effectiveness of application of the estimated prediction model and possibility of improvement of the total customer satisfaction of a system product.

Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

Investigating customer churn in banking:a machine learning approach and visualization app for data science and management

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is essential in today’s extremely competitive banking market.Additionally,having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele.These factors make reducing client attrition a crucial step that banks must pursue.In our research,we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers.We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics.In addition,we developed a Data Visualization RShiny app for data science and management regarding customer churn analysis.Analyzing this data will help the bank indicate the trend and then try to retain customers on the verge of attrition.

The User Analysis of Amazon Using Artificial Intelligence at Customer Churn

Customer churns remains a key focus in this research, using artificial intelligence-based technique of machine learning. Research is based on the feature-based analysis four main features were used that are selected on the basis of our customer churn to deduct the meaning full analysis of the data set. Data-set is taken from the Kaggle that is about the fine food review having more than half a million records in it. This research remains on feature based analysis that is further concluded using confusion matrix. In this research we are using confusion matrix to conclude the customer churn results. Such specific analysis helps e-commerce business for real time growth in their specific products focusing more sales and to analyze which product is getting outage. Moreover, after applying the techniques, Support Vector Machine and K-Nearest Neighbour perform better than the random forest in this particular scenario. Using confusion matrix for obtaining the results three things are obtained that are precision, recall and accuracy. The result explains feature-based analysis on fine food reviews, Amazon at customer churn Support Vector Machine performed better as in overall comparison.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

Assessing the impact of artificial intelligence on customer performance: a quantitative study using partial least squares methodology

The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically the partial least squares method,to test the hypotheses and explore the relationships between various variables.The findings indicate that effective business practices and successful AI assimilation have a positive impact on customer performance.Additionally,the results of this study provide valuable insights for both academic and practical communities.This study highlights the importance of specific variables,such as organizational and customer agility,customer experience,customer relationship quality,and customer performance in AI assimilation.By exploring these variables,it contributes significantly to the academic,managerial,and social aspects of AI and its impact on customer performance.

Dynamic Analysis of Customer Demand Based on Intuitionistic Fuzzy Number in Product Planning

To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.

Modeling customer satisfaction for bus rapid transit in Changzhou, China

This paper aims to develop a customer satisfaction model for bus rapid transit （BRT）. Both the socio-economic and travel characteristics of passengers were considered to be independent variables. Changzhou BRT was taken as an example and on which on-board surveys were conducted to collect data. Ordinal logistic regression （OLR） was used as the modeling approach. The general OLR-based procedure for modeling customer satisfaction is proposed and based on which the customer satisfaction model of Changzhou BRT is developed. Some important findings are concluded： Waiting sub-journey affects customer satisfaction the most, riding sub- journey comes second and arriving station sub-journey has relatively fewer effects. The availability of shelter and benches at stations imposes heavy influence on customer satisfaction. Passengers＇ socio-economic characteristics have heavy impact on customer satisfaction.

A model of targeted advertising with customer recognition

A two-period duopoly model is developed to examine the competitive effects of targeted advertising with customer recognition （TACR）. In the model, two competing firms sell goods to end consumers in the first period, during which customer recognition is obtained. In the second period, advertising can be targeted toward different consumer types. Advertising is assumed to be persuasive in the way that consumer valuation is increased. Equilibrium decisions and profits in each period are derived, showing that the firm who loses the current competition will win in the future. As a result, forward-looking firms price less aggressively so that their long-term profits can be enhanced with the help of TACR. Particularly, TACR improves profits through three important effects： valuation increasing, customer poaching, and anti-competition. Finally, this paper investigates the welfare issues, showing that firms enhance profits at the expense of consumer surplus. It is, therefore, suggested that public sectors take a step to protect consumers with the rapid development of targeting technology.

Customer Perception of Bus Services Based on the SERVQUAL Dimensions——A report of Wessex Red Bus service in UK

With the development of society, customers are having an increasing expectation on bus service. Problems such as bus being late all the time seem to become common. It usually annoys the customers and have a bad influence on bus companies.It's crucial to improve the bus service. This report adapts and applies a modified SERVQUAL approach to estimate the service quality in public transport. Wessex Red servcie, bus service in England UK, operated in partnership with the University of the West of England and the University of Bristol, is evaluated in the report being representative for bus service. In this study, the author has applied the SERVQUAL questionnaire among the three groups of customers in Bristol UK based on these five dimensions of SERVQUAL:"Tangibles, Responsiveness, Assurance, Reliability and Empathy"(Parasuraman, 1988). The results illustrates a high degree of importance placed on reliability, in which bus being late is an issue most concerned. The author analyzes the problem and finally provides suggestions and recommendation for the issue. This study is to provide a quality evaluation tool readily usable by transport operators willing to certify the service offered and it also offers a tool for practioners characterized by flexibility so as to fit individual needs. In addition, this study is beneficial to students who are learning Marketing. The study provides students a methodology in their marketing research. It also gives students a tool to evaluate services so as to set up their marketing plan and could give a better horizon to understand marketing.

Applying CBR to Machine Tool Product Configuration Design Oriented to Customer Requirements

Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer＇s experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the based on grey correlation analysis is proposed to evaluate similar cases best overall performance, an evaluation method of similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.

Evaluation of the Customer Satisfaction Index for Wellhead Blowout Preventers of China’s Petroleum Industry——A new method based on PLS

This paper establishes an evaluation model of the customer satisfaction index for the wellhead blowout preventers of China＇s petroleum industry based on evaluation models of the customer satisfaction index at home and aboard, and by considering the consuming situation in China and the features of the China＇s petroleum industry. For the existence of： （1） multiple correlations among the factors in the model; （2） the variables need to be explained, but that are hard to observe; （3） the customer satisfaction degree of observation variables appears the shape of skewness or two or three peaks, the correlations between the satisfaction index and its factors cannot be described by common multiple regression. This paper uses a partial least squares （PLS） method based on principal components and typical correlative analysis to solve the problem. When PLS is used in the model of the customer satisfaction index of the wellhead blowout preventers, the latent variables and the explanation degree coefficient of the manifest variable to the corresponding latent variables are estimated by PLS path analysis, and the influencing coefficient among the latent variables in the model is estimated by PLS regression analysis. PLS is also be used to calculate and analyze the model and disclose the correlations among the structural variables as well as the correlation between structural variables and its corresponding observation variables, evaluating results of which provide useful information for petroleum industry to improve the product quality and to the enhancement of the customer satisfaction to the product.

Hybrid customer requirements rating method for customer-oriented product design using QFD

Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This pa- per aims to propose a novel method to deal with the relative importance ratings （RIRs） of CRs problem considering customers＇ diversified requirements and unknown information on customers＇ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer＇s assessment structure is proposed according to the basic idea of grey relational analysis （GRA）, and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers＇ personalized and diversified requirements. Furthermore, an im- mune particle swarm optimization （IPSO） algorithm is designed to solve the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method＇s potential application in deter- mining the RIRs of CRs.

Transforming Multidisciplinary Customer Requirements to Product Design Specifications

With the increasing of complexity of complex mechatronic products, it is necessary to involve multidis- ciplinary design teams, thus, the traditional customer requirements modeling for a single discipline team becomes difficult to be applied in a multidisciplinary team and project since team members with various disciplinary backgrounds may have different interpretations of the customers＇ requirements. A new synthesized multidisci- plinary customer requirements modeling method is pro- vided for obtaining and describing the common understanding of customer requirements （CRs） and more importantly transferring them into a detailed and accurate product design specifications （PDS） to interact with dif- ferent team members effectively. A case study of designing a high speed train verifies the rationality and feasibility of the proposed multidisciplinary requirement modeling method for complex mechatronic product development. This proposed research offersthe instruction to realize the customer-driven personalized customization of complex mechatronic product.

A dynamic optimization model of an integrated coal supply chain system and its application

Various nodes,logistics,capital flows,and information flows are required to make systematic decisions concerning the operation of an integrated coal supply system. We describe a quantitative analysis of such a system. A dynamic optimization model of the supply chain is developed. It has achieved optimal system profit under conditions guaranteeing a certain level of customer satisfaction. Applying this model to coal production of the Xuzhou coal mines allows recommendations for a more systematic use of washing and processing,transportation and sale resources for commercial coal production to be made. The results show that this model,which is scientific and effective,has an important value for making reasonable decisions related to complex coal enterprises.

Effect of restoration technique on resistance to fracture of endodontically treated anterior teeth with flared root canals

This study was designed to compare the impact of post and core systems on resistance to fracture of endodontically treated anterior teeth with flared root canals and to assess their fracture pattern. Sixty central incisors were cut horizontally 2 mm coronal to the cementoenamel junction(CEJ). After root canal therapy, teeth were assigned into 6 groups(n = 10 each) based on a post system and used as follows: Group C, non-flared root received size #1 glass fiber posts(Control); Group AP, flared root restored with anatomical post; Group RC, flared root restored with size #1 fiber post and cemented with thick layer of resin cement; Group CR, flared root restored with size #1 and reinforced with composite resin; Group CM, cast post-core; Group CP, CAD/CAM polymer-infiltrated ceramic post and core.Following post cementation, core build-up and crown insertion, the specimens were thermo-cycled up to 10,000 cycles(5 C/55 C; 30 seconds dwell time, 6 seconds transition time) and then statically loaded at 1 mm/minute crosshead speed using a universal testing machine. One-way ANOVA and Tukey HSD post hoc test(α= 0.05) were used for data analysis. Group C recorded significantly higher resistance to fracture values [(826.9±39.1) N] followed by group CP [(793.8±55.6) N] while group RC yielded the lowest fracture resistance values [(586.7±51.4) N]. The resistance to fracture of wide root canals can be enhanced by using one-piece CAM/CAM post and core as an alternative to the use of either glass fiber post, relined with composite resin increasing the thickness of luting cement or the use of cast post and core system. However, this was an in vitro investigation and further in vivo studies are necessary.