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基于动态分类器集成的客户流失预测模型研究 总被引：1，自引：0，他引：1
目前大多数客户流失预测研究常采用单一预测模型.因此,本文将动态分类器组合与自组织数据挖掘理论(SODM)相结合,提出了基于SODM的动态分类器集成方法.以国内、国外电信公司客户流失预测数据为例,并与单一的预测模型以及已有的动态分类器组合方法进行了详细对比,发现该方法能在很大程度上提高客户流失预测的准确率、命中率以及提升系数,是进行客户流失预测的有效工具. 相似文献
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分析了通信企业客户流失现状,给出选择CART算法的原因,然后利用CART算法建立客户流失预测模型并以移动通信企业为例,对其客户流失情况进行预测,把预测结果反馈给相关部门,从而制定出有效的营销措施预防客户流失。 相似文献
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基于CART二叉决策树的电信业客户流失的模型构建与控制 总被引：1，自引：0，他引：1
分析了决策树在电信业客户流失分析中的重要应用,建立了基于CART算法的二叉决策树构造的电信业客户流失分析模型,研究如何使用二叉决策树的构造方法来克服客户流失分析中数据碎片的产生,使用spss clementin数据挖掘平台构造挖掘模型并且使用实时的数据出现概率来进行模型的优化控制。实验与仿真证明,该模型的准确率较高,效果显著。 相似文献
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In this paper, a Generalized Cluster Centroid based Classifier (GCCC) and its variants for text categorization are proposed by utilizing a clustering algorithm to integrate two well-known classifiers, i.e., the K-nearest-neighbor (KNN) classifier and the Rocchio classifier. KNN, a lazy learning method, suffers from inefficiency in online categorization while achieving remarkable effectiveness. Rocchio, which has efficient categorization performance, fails to obtain an expressive categorization model due to its inherent linear separability assumption. Our proposed method mainly focuses on two points: one point is that we use a clustering algorithm to strengthen the expressiveness of the Rocchio model; another one is that we employ the improved Rocchio model to speed up the categorization process of KNN. Extensive experiments conducted on both English and Chinese corpora show that GCCC and its variants have better categorization ability than some state-of-the-art classifiers, i.e., Rocchio, KNN and Support Vector Machine (SVM). 相似文献
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Michel Laroche Mohammad Reza Habibi Marie-Odile Richard 《International Journal of Information Management》2013
There is an ongoing debate over the activities of brands and companies in social media. Some researchers believe social media provide a unique opportunity for brands to foster their relationships with customers, while others believe the contrary. Taking the perspective of the brand community building plus the brand trust and loyalty literatures, our goal is to show how brand communities based on social media influence elements of the customer centric model (i.e., the relationships among focal customer and brand, product, company, and other customers) and brand loyalty. A survey-based empirical study with 441 respondents was conducted. The results of structural equation modeling show that brand communities established on social media have positive effects on customer/product, customer/brand, customer/company and customer/other customers relationships, which in turn have positive effects on brand trust, and trust has positive effects on brand loyalty. We find that brand trust has a fully mediating role in converting the effects of enhanced relationships in brand community to brand loyalty. The implications for marketing practice and future research are discussed. 相似文献
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《International Journal of Information Management》2016,36(5):686-699
Social commerce sites (SCSs), a new model of social media, provide fertile ground for customers to communicate their opinions and exchange product- or service- related information. Given the significant opportunities related to the use of social media data for customers’ insight, we explore the factors driving information sharing behavior on SCSs. In this paper, we propose and empirically test a comprehensive theoretical model for customer information sharing behavior through analysis of online survey data as well as network and behavioral usage data of over four months from 1177 customers in a SCS. The research model was empirically validated with the use of both subjective and objective data in a longitudinal setting. Our results show that customer information sharing is influenced by both individual (i.e., reputation and the enjoyment of helping others) and social capital (i.e., out-degrees’ post, in-degrees’ feedback, customer expertise and reciprocity) factors. This study contributes to the existing literature by highlighting the role of directed social network in customer information sharing behavior on SCSs. We believe that the results of our study offer important insights to the IS research and practice. 相似文献
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Numerous articles, books and essays have shown that ongoing efforts to meet customers’ needs characterize market leaders. For a firm to successfully develop customer-oriented attitudes throughout the entire organization, employees at all levels and sections need to be committed to providing a high level of service. It is therefore essential to understand what drives employees – especially those who do not interact daily with customers – to adopt a customer-oriented attitude. The aim of this study is to shed some light on one facet of this relationship, namely the mechanism of knowledge sharing that may impact employee customer orientation. The underlying notion is that technology, in its various advanced forms of CRM software, enhances and enables client “knowing.” In other words, it leads to a greater ability on the part of employees to share knowledge, which brings about real customer orientation.This paper provides empirical evidence, based on a sample of 345 Hi-Tech workers from a telecommunication company, of a link between sharing explicit knowledge and tacit knowledge to enhance customer orientation. The findings indicate that sharing tacit knowledge has a positive effect on increasing employee customer orientation and increases sharing of explicit knowledge, while also strengthening communication about customers in the organization. It is concluded that firms should encourage tacit knowledge sharing and its transformation by technology into explicit knowledge to augment employees’ customer-oriented attitudes. 相似文献
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利用多案例分析和扎根理论探讨了平台型企业开放式服务创新风险的内在机理及作用机制。研究发现了风险因素的9个主范畴,3个风险核心范畴,以及2个风险发生后果,构成了平台型企业开放式服务创新的风险成因。实证研究表明,商业环境风险、平台战略风险、管理风险这三个风险对平台创新活动影响巨大,显著影响了平台型企业客户流失以及经营绩效。商业环境风险是平台创新面临的外部风险,与平台战略风险和管理风险呈显著正向关系,战略风险会增加管理风险发生的可能性。三大风险与客户流失呈正比,与平台经营绩效呈反比。本研究拓展了传统的管理要素模型,揭示了互联网平台企业创新过程中的风险互动机制。 相似文献
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Undoubtedly, the change in consumers’ choices and expectations, stemming from the emerging technology and also significant availability of different products and services, created a highly competitive landscape in various customer service sectors, including the financial industry. Accordingly, the Canadian banking industry has also become highly competitive due to the threats and disruptions caused by not only direct competitors, but also new entrants to the market.The primary objective of this paper is to construct a predictive churn model by utilizing big data, including the structured archival data, integrated with unstructured data from sources such as online web pages, the number of website visits and phone conversation logs, for the first time in the financial industry. It also examines the effect of different aspects of customers’ behavior on churning decisions. The Datameer big data analytics tool on the Hadoop platform and predictive techniques using the SAS business intelligence system were applied to study the client retirement journey path and to create a churn prediction model. By deploying the above systems, we were able to uncover a wealth of data and information associated with over 3 million customers’ records within the retiree segment of the target bank, from 2011 to 2015. 相似文献
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To develop highly competitive products, companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology, customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining, aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However, most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs, this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes, an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall. 相似文献
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《Information processing & management》2022,59(6):103085
Nowadays, Artificial Intelligence (AI) based modeling is the major consideration to build efficient, automated, and smart systems for our today's needs. Many companies are benefited from these modeling methods for their marketing efforts. Each firm has expected to increase its product development in an innovative way to improve its business growth. Successful firm marketing is to offer the right product to the right person at the right time. To market the product to the customer successfully, it is needed to segment the customer by finding their behavioral patterns. The customer behaviors and their purchasing patterns are used to generate profit for the company. Customer segmentation is the process of grouping customers based on commonalities. Developing an efficient AI-based customer segmentation to improve digital marketing growth is a challenging task. In this paper, an unsupervised deep learning model called a Self-organizing map with an Improved social spider optimization approach has been used for efficient customer segmentation. The customer data are analyzed by a feature engineering process using a swarm intelligence model called Modified social spider optimization to select the behavioral features of the customer. Then, the customers are clustered using Self Organizing neural network (SONN). Based on the clusters, the customers are classified using the Deep neural network (DNN) model. The experimental results prove the performance of the proposed model with high clustering and segmentation capability to improve the business profit in marketing. 相似文献
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Kangrok Oh Zhengguo Li Beom-Seok Oh Kar-Ann Toh 《Journal of The Franklin Institute》2018,355(4):1614-1637
In this paper, an optimization problem is formulated for stable binary classification. Essentially, the objective function seeks to optimize a full data transformation matrix along with the learning of a linear parametric model. The data transformation matrix and the weight parameter vector are alternatingly optimized based on the area above the receiver operating characteristic curve criterion. The proposed method improves the existing means via an optimal data transformation rather than that based on the diagonal, random and ad-hoc settings. This optimal transformation stretches beyond the fixed settings of known optimization methods. Extensive experiments using 34 binary classification data sets show that the proposed method can be more stable than competing classifiers. Specifically, the proposed method shows robustness to imbalanced and small training data sizes in terms of classification accuracy with statistical evidence. 相似文献
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决策列表是进行数据分析和数据挖掘的重要方法,一般用于形成公司决策和模型预测。文章介绍了决策列表、关联规则及其客户响应模型的构建,然后将决策列表算法应用于金融机构营销计划的实施中,通过对历史数据分析得到一些较为实用的预测性客户属性规则,提高销售效率。 相似文献
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客户重复购买意向决定因素的实证研究 总被引：19，自引：1，他引：19
根据社会交易理论和投资模型，识别出了客户重复购买意向的决定因素，并提出了重复购买意向理论模型。选择中国IT分销行业为背景，聘请专业调研公司以上门走访的方式收集了367个企业客户的样本数据，然后利用结构方程建模（SEM）软件EQS5.7b，对该模型作了检验。检验结果表明：客户认知价值、客户满意和转移成本是客户重要购买意向的三个决定因素，其中客户认知价值是核心决定因素，对客户重复购买意向有着最大的影响。讨论了实证结论对企业CRM实践的指导意义。 相似文献
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在弄清了美国GE公司Buell型分级机的分选机理基础上,对Buell型分级机的外形进行了重大改进,应用气固两相流动理论,通过计算机数值模拟,确定了模型分级机的几何参数和运行条件。在模型分级机的实验研究基础上,通过流体力学相似理论,放大到中间试验分级机,并与杭州高达机械有限公司合作,在中试机的大量实验基础上,再用流体力学相似理论开发成功了GFX型粉煤灰涡流离心式气流分级机系列产品。通过在全国100多家燃煤电厂的实际应用表明,GFX型离心式分级机的理论模型和开发途径是正确的,应用是成功的。 相似文献
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本文首先对目前中国电信企业信息化建设规划进行了阐述,重点分析了其中电信企业运营数据仓库(ODS)建设的思路,并结合江西电信分公司的实际情况,提出了较实用的建设方法。 相似文献
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本文首先结合商业模式画布详细剖析了高端装备制造企业陕鼓动力的商业模式九大构成要素。然后,鉴于画布方法的局限性,引入系统动力学方法,构建案例企业转型前后的存量流量模型,进一步剖析了九要素如何以不同的方式有机组合促成了装备制造企业商业模式创新路径的产生。最后借助Vensim-PLE软件,对模型进行仿真分析。结果显示：价值主张定位精准与否决定了商业模式创新路径选择的成败;商业模式创新路径始于客户需求,终于客户需求满足;客户需求导向型路径优于核心资源导向型路径;商业模式创新路径是一条系统集成创新之路。 相似文献