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.

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.

The Impact of Information Technology on Service Quality,Satisfaction,and Customer Relationship Management(Case Study:IT Organization Individuals)

Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.

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.

顾企互动视角下顾客体验的前因组态研究———NCA与fsQCA混合方法

当前体验经济下顾客体验成为企业吸引顾客和塑造竞争优势的关键所在,学者们越来越关注顾企互动对价值共创的作用,然而过往研究大多关注单一要素对顾客体验的净效应,忽视了多因素间的联动效应。因此,本文基于顾企互动视角,使用NCA与fsQCA混合方法,对315份有效问卷数据进行分析,探索影响顾客体验的商业模式创新类型、资源整合、价值感知、关系倾向和顾客参与的不同组态效应。研究结果表明:引致积极顾客体验的路径有三种类型;提升顾客体验既不能简单追求商业模式创新,也不能简单追求高水平顾客参与;高水平资源整合和价值感知有助于构建积极顾客体验;低水平关系倾向会带来消极顾客体验,但高水平的关系倾向不一定产生积极顾客体验。基于组态理论从顾企互动视角计算积极与消极顾客体验的路径,为企业实践中营造好的顾客体验提供决策依据、增进对策建议的有效性。

基于AISAS模型的“微信营销”效果评价及营销路径——以W护肤品为例

本文以“企业微信”为视角,基于用户消费模型——AISAS模型和传统客户转化率理论,分别构建营销总过程和五个营销阶段的客户转化率模型,确立每个阶段的评价指标,并以W护肤品营销数据为样本,对实验组和对照组分别进行测试。研究表明,依据AISAS模型建立的营销路径采用针对性营销活动的实验组产生了较好的营销效果,并通过统计检验验证实验组营销策略的有效性,进而总结出基于AISAS模型的“企业微信”营销路径。

基于fsQCA的国产服装品牌忠诚提升路径研究

为探究中国服装企业维护和提升消费者品牌忠诚的方式,以京东平台上30个国产服装品牌为案例,在收集商品评论并对其进行文本分析的基础上,运用模糊集定性比较分析(fsQCA)方法,探究国产服装企业维护和提升品牌忠诚的多种因素组合路径。研究结果表明,国产服装企业品牌忠诚的提升是多因素组态作用的结果,产生高品牌忠诚的7条路径可以归纳为5种模式,分别为质量领先+影响力型、质量领先+情感驱动型、情感驱动+社会责任感型、质量领先+在线社群运营型、品牌形象+价值让渡型。在此结论的基础上提出服装企业应注重生产制造能力提升、积极履行社会责任以及要以满足消费者需求为中心等建议,为国产服装企业提供了理论和实践启示。

Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-Cat Boost

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 CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.

Research on Optimal Delivery Days and Customer Satisfaction Based on Quality Costs

Customer satisfaction is an important index to evaluate the competitiveness and efficiency of an enterprise. Every enterprise is confront with the subject of supplying with the customer satisfactory products at the lowest costs and the highest manufacturing speed. Regarding the delivery days of a coach company as a design variable, this paper builds up an optimization model of customer satisfaction, and suggests an effective method to reduce costs and increase customer satisfaction based on analysis and research.

Customer Churn Prediction Framework of Inclusive Finance Based on Blockchain Smart Contract

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 the time decay function are used to optimize the search and analysis of the characteristics of pre-lost customers,and the key index combination is screened to obtain the data of potential lost customers.The framework will change with time according to the customer’s interest,adding the time factor to the customer churn prediction,and improving the dimensionality reduction and prediction generalization ability in feature selection.Logistic regression,naive Bayes and decision tree are used to establish a prediction model in the experiment,and it is compared with the financial customer churn prediction framework under situational awareness.The prediction results of the framework are evaluated from four aspects:accuracy,accuracy,recall rate and F-measure.The experimental results show that the context-aware customer churn prediction framework can be effectively applied to predict customer churn trends,so as to obtain potential customer data with high churn probability,and then these data can be transmitted to the company’s customer service department in time,so as to improve customer churn rate and customer loyalty through accurate service.

Multi-Objective Cold Chain Path Optimization Based on Customer Satisfaction

To improve customer satisfaction of cold chain logistics of fresh agricultural goods enterprises and reduce the comprehensive distribution cost composed of fixed cost, transportation cost, cargo damage cost, refrigeration cost, and time penalty cost, a multi-objective path optimization model of fresh agricultural products distribution considering client satisfaction is constructed. The model is solved using an enhanced Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), and differential evolution is incorporated to the evolution operator. The algorithm produced by the revised algorithm produces a better Pareto optimum solution set, efficiently balances the relationship between customer pleasure and cost, and serves as a reference for the long-term growth of organizations. .

Research on the Value Positioning of University Library Based on Customer Delivered Value

With the rise of various new reading media and the rapid development of the digitization of paper resources,the traditional function positioning of university libraries based on information query is facing unprecedented challenges.How to deal with the change of social information?The library should be demand-oriented,re-examine its own value and find a new starting point.With the help of the concept of customer delivered value and based on 4P theory,this paper constructs the value chain of university library from the dimensions of product,image,personnel and service,and forms a multi-dimensional development positioning system.

Customer Requirements Mapping Method Based on Association Rule Mining for Mass Customization

Customer requirements analysis is the key step for product variety design of mass customiza-tion(MC). Quality function deployment (QFD) is a widely used management technique for understanding the voice of the customer (VOC), however, QFD depends heavily on human subject judgment during extracting customer requirements and determination of the importance weights of customer requirements. QFD pro-cess and related problems are so complicated that it is not easily used. In this paper, based on a general data structure of product family, generic bill of material (GBOM), association rules analysis was introduced to construct the classification mechanism between customer requirements and product architecture. The new method can map customer requirements to the items of product family architecture respectively, accomplish the mapping process from customer domain to physical domain directly, and decrease mutual process between customer and designer, improve the product design quality, and thus furthest satisfy customer needs. Finally, an example of customer requirements mapping of the elevator cabin was used to illustrate the proposed method.

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

Background:As the market demands change,SMEs(small and medium-sized enterprises)have long faced many design issues,including high costs,lengthy cycles,and insufficient innovation.These issues are especially noticeable in the domain of cosmetic packaging design.Objective:To explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization.Methods:To accomplish this objective,the basic-element theory has been introduced and applied to the design and development system of the product family.Results:By examining the mapping relationships between the demand domain,functional domain,technology domain,and structure domain,four interrelated models have been developed,including the demand model,functional model,technology model,and structure model.Together,these models form the mechanism and methodology of product family modeling,specifically for cosmetic packaging design.Through an analysis of a case study on men’s cosmetic packaging design,the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design,and the design efficiency has been enhanced.Conclusion:The product family modeling technology employs a formalized element as a module configuration design language,permeating throughout the entire development cycle of cosmetic packaging design,thus facilitating a structured and modularized configuration design process for the product family system.The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design,while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

Innovative Product Design Based on Customer Requirement Weight Calculation Model

In the processes of product innovation and design, it is important for the designers to find and capture customer＇s focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.

基于QFD的可伸缩式登船栈桥设计方法

针对可伸缩式登船栈桥设计流程,以客户需求为导向,构建了基于质量功能展开法的设计思路和方法。运用实景体验和场景打分的方法,深度挖掘5个维度的客户需求、关键质量特性和关键物料特性,通过AHP等方法进行权重分析,构建可伸缩栈桥分析的一阶质量屋和二阶质量屋,开展关键物料的重要度-成本分析,有效满足了客户需求和规范要求,形成可伸缩栈桥设计开发新模式。

Corneal collagen cross-linking in patients with keratoconus from the Dresden protocol to customized solutions:theoretical basis

Keratoconus is an ectatic condition characterized by gradual corneal thinning,corneal protrusion,progressive irregular astigmatism,corneal fibrosis,and visual impairment.The therapeutic options regarding improvement of visual function include glasses or soft contact lenses correction for initial stages,gas-permeable rigid contact lenses,scleral lenses,implantation of intrastromal corneal ring or corneal transplants for most advanced stages.In keratoconus cases showing disease progression corneal collagen crosslinking(CXL)has been proven to be an effective,minimally invasive and safe procedure.CXL consists of a photochemical reaction of corneal collagen by riboflavin stimulation with ultraviolet A radiation,resulting in stromal crosslinks formation.The aim of this review is to carry out an examination of CXL methods based on theoretical basis and mathematical models,from the original Dresden protocol to the most recent developments in the technique,reporting the changes proposed in the last 15y and examining the advantages and disadvantages of the various treatment protocols.Finally,the limits of non-standardized methods and the perspectives offered by a customization of the treatment are highlighted.

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.

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 Effect of Service Quality on Behavioral Loyalty Through Customer Satisfaction and Attitudinal Loyalty in the 4-Star Hotel in East Java, Indonesia

This research was conducted to test and analyze the influence of service quality on behavioral loyalty through customer satisfaction and attitudinal loyalty to 4-Star Hotel in East Java.This research is a survey research.The sampling technique used is non probability sampling.Sample sizes are 200 respondents.The analysis tool used is Structural Equation Model(SEM)Analysis.The result of the research shows that hypothesis proposed in this research is accepted.Academic suggestion submitted is for research that will come dating need to be explored influence of other variables that influence behavioral loyalty.While practical suggestions submitted to business actors is for business actors to pay attention and keep the variables that effect behavioral loyalty.Especially studied in this study they are:service quality,customer satisfaction,and attitudinal loyalty.