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Service quality, customer satisfaction and customer value have become the priority of both manufacturers and service provider in the increasingly intensified competition for customers in today's customer-centered era. However, findings regarding service quality, customer satisfaction and customer value are rather divergent and related studies are fragmented, especially for the complicated interrelationships among them. Thus, less is known about the relative impacts of quality-related factors on customer value and customer satisfaction up to now and the moderating role of customer value in the relationship between service quality and customer satisfaction has been neglected. Further, it is very difficult to find related studies, supported by evidence, that focus on service quality, customer satisfaction and customer value, and their influences on customer behavior intentions in the telecommunication industry. In this paper, much attention is paid to the measurement model of service quality in China's mobile communication market based on the well-known SERVQUAL model, but with reasonable modification on the basis of focus group discussions and expert opinions to reflect the specific industry attributes and the special culture of China. By taking a disaggregated approach, the key drivers of service quality, customer value and customer satisfaction are first identified and the impact of customer perceived sacrifice on customer value is emphasized. Then attention is given to the systematic study of the dynamic relationships among them, especially the moderating effect of customer value on the relationship between service quality and customer satisfaction, which is followed by the examination of their influences on behavior intentions of customers. Results are based on the development of structural equation models using Partial Least Square technique.  相似文献
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In recent years, firms have focused on how to enter markets and meet customer requirements by improving product attributes and processes to boost their market share and profits. Consequently, market-driven product design and development has become a popular topic in the literature. However, past research neither covers all of the major influencing factors that together drive customers to make purchase decisions, nor connects these various influencing factors to customer purchasing behavior. Past studies further fail to take the time value of money and customer value into consideration. This study proposes a decision support system to (a) predict customer purchasing behavior given certain product, customer, and marketing influencing factors, and (b) estimate the net customer lifetime value from customer purchasing behavior toward a specific product. This will not only enable decision-makers to compare alternatives and select competitive products to launch on the market, but will also improve the understanding of customer behavior toward particular products for the formulation of effective marketing strategies that increase customer loyalty and generate greater profits in the long term. Decision-makers can also make use of the system to build up confidence in new product development in terms of idea generation and product improvement. The application of the proposed system is illustrated and confirmed to be sensible and convincing through a case study.  相似文献
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The more the telecom services marketing paradigm evolves, the more important it becomes to retain high value customers. Traditional customer segmentation methods based on experience or ARPU (Average Revenue per User) consider neither customers’ future revenue nor the cost of servicing customers of different types. Therefore, it is very difficult to effectively identify high-value customers. In this paper, we propose a novel customer segmentation method based on customer lifecycle, which includes five decision models, i.e. current value, historic value, prediction of long-term value, credit and loyalty. Due to the difficulty of quantitative computation of long-term value, credit and loyalty, a decision tree method is used to extract important parameters related to long-term value, credit and loyalty. Then a judgments matrix formulated on the basis of characteristics of data and the experience of business experts is presented. Finally a simple and practical customer value evaluation system is built. This model is applied to telecom operators in a province in China and good accuracy is achieved.  相似文献
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随着移动通信的不断发展,移动客户数量也在不断增加,而通信行业中的竞争也日益显著。因此,过去以生产为中心、以销售产品为目的的市场战略逐渐被以客户为中心、以服务为目的的市场战略所取代。该文就移动CRM客户价值细分做出了一些探讨。  相似文献
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The purposes of this study are to construct an instrument to evaluate service quality of mobile value-added services and have a further discussion of the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention. Structural equation modeling and multiple regression analysis were used to analyze the data collected from college and graduate students of 15 major universities in Taiwan. The main findings are as follows: (1) service quality positively influences both perceived value and customer satisfaction; (2) perceived value positively influences on both customer satisfaction and post-purchase intention; (3) customer satisfaction positively influences post-purchase intention; (4) service quality has an indirect positive influence on post-purchase intention through customer satisfaction or perceived value; (5) among the dimensions of service quality, “customer service and system reliability” is most influential on perceived value and customer satisfaction, and the influence of “content quality” ranks second; (6) the proposed model is proven with the effectiveness in explaining the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile added-value services.  相似文献
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终端客户推荐系统是大型制造商终端营销的一种有效工具.如何在互联网+环境下通过采集全域市场数据,设计一个寻找最佳目标客户的推荐方法成为了一项挑战.为解决这一问题,本文提出一种基于全域市场数据感知的终端客户推荐方法(GMF).即采用全域分析的思想对全国范围内的客户数据进行预处理,建立全方位,多角度的评估指标,得到目标客户价值.然后通过域子空间分解的方法,在域子空间中对数据进行分解分析,得到某一区域内的客户评价标准,将二者分析结果进行有效融合,通过计算耦合对象相似度,并筛选出最相似的TopN个数据作为最佳目标客户结果集.在大型制造商营销活动所生成的数据集上的实验结果表明:本文提出的推荐算法其性能明显优于当前主流的协同过滤算法.  相似文献
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