The Mechanisms through Which Certain Variables Influence Customer Loyalty: The Mediating Roles of Perceived Value and Satisfaction

This study surveyed 123 bank users who experienced problems with their banks’ online banking services, with the aim of understanding the mechanisms through which certain variables influence customer loyalty. Principally, the possible mediating roles of value and satisfaction on the relationships between recovery and loyalty and between ISO 9001 and loyalty were scrutinized. The dimensionalities of the scales were assessed using exploratory and confirmatory factor analysis. Thereafter, structural equation modeling and multiregression analyses were used to test the proposed model. The overall results showed that service recovery can be used to enhance customers’ satisfaction and perception of value and, therefore, customer loyalty. This study also confirmed the partial mediating roles of customers’ satisfaction and perception of value in the relationship between service recovery and loyalty. In contrast, ISO 9001 has no influence on perceived value, satisfaction, and loyalty; the mediating roles of both perceived value and satisfaction were not supported in the relationship between ISO 9001 and loyalty. In practice, even though ISO 9001 appeared to offer few extras to satisfy and retain customers, its use is still advisable because of the other potential benefits that it provides.     

Customer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modeling

Businesses can maintain their effectiveness as long as they have satisfied and loyal customers. Customer relationship management provides significant advantages for companies especially in gaining competitiveness. In order to reach these objectives primarily companies need to identify and analyze their customers. In this respect, effective communication and commitment to customers and changing market conditions is of great importance to increase the level of satisfaction and loyalty. To evaluate this situation, level of customer satisfaction and loyalty should be measured correctly with a comprehensive approach. In this study, customers are investigated in 4 main groups according to their level of satisfaction and loyalty with a criteria and group based analysis with a new method. We use classification algorithms in WEKA programming software and Structural Equation Modeling (SEM) with LISREL tools together to analyze the effect of each satisfaction and loyalty criteria in a satisfaction–loyalty matrix and extend the customer satisfaction and loyalty post-analysis research bridging the gap in this field of research. To convert developed conceptual thought to experimental study, white goods industry is exemplified. 15 criteria are used for evaluation in 4 customer groups and a satisfaction–loyalty survey developed by experts is applied to 200 customers with face-to-face interviews. As a result of the study, a customer and criteria grouping method is created with high performance classification methods and good fit structural models. In addition, results are evaluated for developing a customer strategy improvement tool considering method outcomes.     

FCM-based customer expectation-driven service dispatch system

Maintaining long-term customer loyalty has been an important issue in the service industry. Although customer satisfaction can be enhanced with better service quality, delivering appropriate services to customers poses challenges to service providers, particularly in real-time and resource-limited dynamic service contexts. However, customer expectation management has been regarded as an effective way for helping service providers achieve high customer satisfaction in the real world that is nevertheless less real-time and dynamic. This study designs a FCM-based customer expectation-driven service dispatch system to empower providers with the capability to deal effectively with the problem of delivering right services to right customers in right contexts. Our evaluation results show that service providers can make appropriate decisions on service dispatch for customers by effectively managing customer expectations and arranging their contextual limited resources and time via the proposed service dispatch system. Meanwhile, customers can receive suitable service and obtain high satisfaction when appropriate services are provided. Accordingly, a high-performance ecosystem can be established by both service providers and customers who co-create value in the dynamic service contexts.     

Constructing online switching barriers: examining the effects of switching costs and alternative attractiveness on e-store loyalty in online pure-play retailers

Developing switching barriers to retain customers has become a critical marketing strategy for online retailers. However, research on the role of switching barriers in e-retailing is still limited. Recent trends show that when competitors are just one click away, it is questionable if customer loyalty can be achieved at all in online environments. This leads to the research question on whether switching barriers have any impact on e-loyalty in pure-play retailers. The paper examines the influence of switching barriers on customer retention (i.e., e-store loyalty) and further investigates the moderating effects of switching costs and alternative attractiveness. Data were gathered via a survey of 590 shoppers of online pure-play retailers in the UK. Findings show that customer satisfaction and the two dimensions of switching barriers (perceived switching costs and perceived attractiveness of alternatives) significantly influence customer loyalty. Contrary to findings in earlier studies, it was found that switching costs did not moderate the relationships between satisfaction and loyalty nor between perceived attractiveness of alternatives and loyalty. The paper makes imperative recommendations to develop switching barriers and to foster loyalty along with suggestions for future research.     

A new procedure to estimate waiting time in GI/G/2 system by server observation

Most GI/G/2 queueing formulae need the variance of inter-arrival time, which is in many cases more difficult to estimate than the other values used in the formulae such as the mean of inter-arrival time, mean of service time and variance of service time. This paper presents a new GI/G/2 queueing formula which uses a slightly different set of data easier to obtain than the variance of inter-arrival time. The key variables are the numbers of system busy periods and system idle periods. Also, it is shown, by simulation, that the waiting time estimation error from the new formula is far less than other popular queueing formulae which use the first two moments of service time and inter-arrival time over a wide range of coefficient of variation.Scope and purposeWaiting is very common in our daily life, and the estimation is sometimes very important for the design of service and manufacturing systems. If the number of barbers at a barber's shop is too small, customers frequently wait for the service too long. If the number of machines in a manufacturing shop is too small, the production lead time from order entry to product delivery can be very long.The waiting time is closely related not only to the average service requirement but also to the variability of it. If customers require service at the same time, the average waiting time of the customers will be longer than the average waiting time with even requests. Traditionally, the variance of inter-arrival time has been used to represent the variability; however, estimation of the variance needs observation of customer arrivals, which often needs much effort. This paper presents another procedure to estimate the waiting time. This procedure does not need the observation of customers. The estimation of waiting time for bank teller machines can be a good application example of this new procedure because the machines do not have the arrival data of the customers. The procedure presented here is for a two parallel server case.     

Prediction of members’ repurchase rates with time weight function

Customer relationship management (CRM) leverages historical users’ behaviors to dawn effort of enhancing customer satisfaction and loyalty. Thus, constructing a successful customer profile plays a critical role in CRM. In this study, we are expected to predict the repurchase rates for the registered members at the specific category of e-shop. However, customers’ preferences change over time. To capture the preference drifts of the members, we propose a novel and simple time function to increase/decrease the weight of the old data in evaluating various members’ past behaviors. Then, we construct a repurchase index with time factor (RIT) model to effectively predict repurchase rates. The marketers of e-shop can thus target the members with high repurchase rates. Experimental results with a real dataset have demonstrated that this RIT model can be practically implemented and provide satisfactory results.     

A methodology to map customer complaints and measure customer satisfaction and loyalty

In this study, an analysis was conducted for the relationships between the main components of customer relationship management (CRM) and customer complaints in the domain of logistics and transport. Today, complaints and the handling of complaints play a pivotal role in customer relationships. Moreover, companies are reluctant to admit that they have difficulties with customers’ complaints, but as yet there appears to be no complete solution to this issue. To remedy this situation, customer complaints must be comprehensively collected and analysed. Issues must be classified, and timely solutions must be developed. In this paper, a conceptual framework is proposed including mathematical models, hypothesised relationships, perceived value and interactivity between customer, business and the system, as well as customer satisfaction analytics. The framework will address the relationship between customer satisfaction issues, loyalty and customer acquisition and estimate customer satisfaction and loyalty. For the purpose of analysis, this study uses both qualitative and quantitative approaches. For data collection, a survey questionnaire was distributed to 60 Fremantle Port logistics and transport customers. For the quantitative approach, linear and nonlinear modelling is adopted. Using the model, we are able to address the shortcomings of CRM technology, and tackle the issues of loyalty improvement and customer acquisition. Finally, based on nonlinear modelling and using a fuzzy inference system, namely the Takagi–Sugeno-type approach, we defined fuzzy rules, by means of which we ascertain the relationship between customer satisfaction and the main relevant variables.     

Understanding online customers’ ties to merchants: the moderating influence of trust on the relationship between switching costs and e-loyalty

Fostering customer loyalty is a key objective for online businesses. Initial transactions with new customers are less profitable than transactions with existing customers, making loyalty an important strategy. Drawing on research examining online customer loyalty (termed e-loyalty), switching costs, and trust, this study provides an empirical test of the relative influence of trust vs switching costs on e-loyalty for e-service providers. We further examine whether trust moderates the relationship between switching costs and e-loyalty. We propose that in the presence of high customer trust, e-service providers should have less need to rely on switching costs as a driver of e-loyalty. We test the hypothesized relationships using data collected from 299 repeat users of online travel services. Our results confirm that trust is a more important predictor of e-loyalty than switching costs. In addition, we find that the impact of switching costs on e-loyalty depends on the level of trust felt by customers. This study extends our understanding of customer loyalty, switching costs, and trust in e-commerce environments and provides practical, theory-driven guidelines to e-businesses seeking to develop customer loyalty programmes.     

Consumer perception of interface quality, security, and loyalty in electronic commerce

Customer interface quality, perceived security, and customer loyalty are critical factors for success of an e-commerce website; however, the relationships among them are not fully understood. We proposed a model for testing the relationships among them and the important outcomes of the site: switching costs and customer loyalty. Data was collected to test the model using a web-based survey, and empirical analyses were performed using SEM. The analytical results demonstrated that customer interface quality and perceived security positively affected customer satisfaction and switching costs, and thus customer loyalty to an e-commerce website. Specifically, our study showed that switching costs positively moderated the effect of customer satisfaction on customer loyalty; this moderating effect is discussed.     

One multiserver mixed queueing system with the limited waiting time

In this paper, a M/G/n/c multiserver queueing system with basic and standby servers is studied. Customers servicing is disturbed by failures of servers that make up a simplest flow. After the failure, the server needs a random time for renewal. It is also assumed that customers have limited, exponentially distributed waiting time in the system. The system is studied in both stationary and nonstationary modes.     

The impact of customer interface quality, satisfaction and switching costs on e-loyalty: Internet experience as a moderator

Customer interface quality has been confirmed to critically influence the success of electronic commerce, and there has been extensive discussion about the effects of customer interface quality on consumer behavior. However, few studies have examined how customer interface quality affects e-loyalty. Furthermore, although satisfaction and switching costs are expected to be antecedents to customer loyalty, few studies have systematically examined how these elements are related to customer interface quality. This study proposes an integrating theoretical framework for testing the relationships among customer interface quality, satisfaction, switching costs, and e-loyalty. Moreover, this study argues that the relationships among these constructs are moderated by Internet experience. Empirical analyses are performed using structural equations modeling analysis. The findings confirm that customer interface quality, including customization, interaction, convenience and character, contributes to generating e-loyalty. Particularly, the results show that convenience directly enhances e-loyalty. Additionally, this study finds that customer interface quality positively influences switching costs for customers with higher Internet experience, a phenomenon that has not previously been explored.     

The Effects of Customer Value on Loyalty and Profits in a Dynamic Competitive Market

Providing high value products and services to customers normally leads to customer loyalty and profits. In practice, the relationship of customer value, loyalty, and profits can be observed in the market. However, the dynamic interactive relationships which lead to customer loyalty and profits still remain ambiguous. In this paper, the Agent-Based Computational Economics (ACE) model is introduced to explore the formation of customer loyalty in the Taiwanese imported lumber market. Using agents with reinforced learning algorithms in trading simulations, the effects of customer value on loyalty and profit are incorporated and examined in this interactive dynamic model. As results, the positive correlations among variables of customer value, loyalty, and profits are observed. A controlled experiment shows that changing customer value leads to changes in customer loyalty and profits, but price is not the determinant factor for improving customer loyalty. The R ² values of customer loyalty and profits elucidate that they are increasing as the time lapsed elongate. Providing high value of products and services is a better strategy for suppliers to attract potential loyal customers.      

An empirical study on Web-based services and customer loyalty

E-business success is tied to the ability to foster customer loyalty. Businesses that deliver superior value derived from excellent services and quality products are likely to win customer loyalty. This paper examines Web-based services and the effects of three sets of factors: pre-purchase, transaction-related, and post-purchase services on customer loyalty (measured as repeat purchase intention from a given Web-based store) in a business-to-consumer environment. Based on the study's results, pre-purchase services that support search and evaluation of products replete in e-commerce systems have limited effect on customer loyalty. Among transaction-related services, transparency of the billing mechanism positively impacts customer loyalty. Customers shun any hidden costs associated with product acquisition. Post-purchase services consisting of support of order tracking, on-time delivery, and customer support positively influence customer loyalty. These findings imply that Web-based stores need to pay more attention to post-purchase services in their strategy to retain customers. This is what will keep customers satisfied and willing to continue the relationship with a company over the long term.     

How does customer self-construal moderate CRM value creation chain?

Most of the existing literature on CRM value chain creation has focused on the effect of customer satisfaction and customer loyalty on customer profitability. In contrast, little has been studied about the CRM value creation chain at individual customer level and the role of self-construal (i.e., independent self-construal and interdependent self-construal) in such a chain. This research aims to construct the chain from customer value to organization value (i.e., customer satisfaction → customer loyalty → patronage behavior) and investigate the moderating effect of self-construal. To test the hypotheses suggested by our conceptual framework, we collected 846 data points from China in the context of mobile data services. The results show that customer’s self-construal can moderate the relationship chain from customer satisfaction to customer loyalty to relationship maintenance and development. This implies firms should tailor their customer strategies based on different self-construal features.     

Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.     

Effects of outcome, process and shopping enjoyment on online consumer behaviour

Customer value is one of the most powerful forces in today’s marketplace and emerging as the strategic imperative for the 1990s. In this study, we proposed a three-component customer value model for e-commerce. Drawing upon the literature in marketing and information systems, our research model decomposed customer value into process value, outcome value, and shopping enjoyment. The results from this study showed that outcome value and process value contributed significantly to customer satisfaction and loyalty. Also, evidences confirmed that customer satisfaction affect customer loyalty. Enjoyment, however, had no significant positive impact on customer satisfaction.     

Expectation-based coopetition approach to service experience design

Service experience design is a key issue in the service industry. Satisfactory service experiences provide customers with good memories and increase customer satisfaction, thus increasing customer loyalty and service provider profitability. However, providing customers with quality service experiences requires considering numerous factors, and thus is a complex and difficult issue both in academia and in real service contexts. Customer satisfaction results from the difference between customer perceptions and customer expectations. Hence, customer expectation management is important in delivering quality service experiences. Additionally, a competitive relationship exists among different service providers as well as between service providers and customers. The service experience delivery process can be regarded as a value co-creation process for service providers and customers who can implement either a competitive or cooperative strategy based on their goals and needs. This study accordingly presents an expectation based coopetition approach by using a real exhibition data of AutoTronics 2009 for simulations. The evaluation results show that this expectation-based coopetition approach can help service providers design and deliver quality service experiences and co-create value with customers, yielding a high performance ecosystem.     

考虑客户分类的随机时间车辆路径优化模型与算法

针对一类考虑客户分类、随机旅行时间、随机服务时间及时间窗约束的车辆路径问题构建了机会约束规划模型,该模型考虑两类客户（普通客户与优质客户）并通过添加机会约束条件确保优质客户获得准时服务的概率。同时,设计了变邻域迭代局部搜索算法,并给出了一种基于最小等待时间的初始解生成启发式规则。基于Solomon算例进行了多组仿真实验。仿真实验结果表明,所设计生成初始解的启发式规则是有效的;所给算法能够在短时间内找到确定问题和随机问题的近似最优解;客户比与车辆使用数目呈正相关关系。研究结果对解决资源有限条件下克服随机不确定性因素带来的不利影响、保证客户服务水平等问题有一定的参考意义。     

决策树技术在医院住院客户划分中的应用

本文以省妇幼保健院历史的住院业务数据为样本,通过数据挖掘的决策树建模方法建立其住院客户的划分模型,得到分类规则,在此基础上将住院客户划分为不同的群体。通过对客户的划分及其特征分析,医院可清楚的了解重点客户并给予重点客户群体以按需要定制的个性化服务,这将极大提升这部分客户的忠诚度和满意度,从而确保医院主流利润和收入来源的长期性和稳定性。