Customer complaints monitoring with customer review data analytics: An integrated method of sentiment and statistical process control analyses

This study presents a data-driven method to monitor customer complaints for efficient service quality management. Recognising the value of customer reviews as a pool of 'voice of the customer', we propose an integrated method of sentiment and statistical process control analyses. The use of customer review data for statistical process control analysis extends the scope of research and application from the supplier perspective to customer-centric service quality management. The sentiment analysis enables systematic identification of a customer satisfaction score from customer review data while the statistical process control chart analysis allows early detection of significant customer complaints and prevents service failures. The integration of two analyses makes it possible to monitor customer complaints at acceptable time and cost. We applied and validated the proposed method using a mobile game service, offering a guideline for its implementation and customisation. The proposed method is expected to be used as an effective tool for customer complaints monitoring over time, which enables responsive and preventive quality management.     

Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA)

In this study, we consider customer to be a company's crucial asset. In order to have a fast, efficient decision-making process, it is vital that a customer relationship management (CRM) decision-maker condenses and abstracts the existing information. A questionnaire survey was conducted among respondents in order to obtain the required data. The questionnaire contains nine categories of satisfaction variables. To perform the analysis, we used principal component analysis (PCA) and data envelopment analysis (DEA). PDA has been utilised as an abbreviation for the integration of these two methods. To effectively analyse the procedure, PCA was utilised to assign a number to each category of questions related to each satisfaction variable. To achieve optimal precision, DEA was applied to the three categories of customers (‘most important’, ‘important’ and ‘ordinary’ customers) in order to determine the strengths and weaknesses of customer services from these customers’ perspectives. Customers were clustered and then DEA was used to determine their viewpoints. Using DEA, we have optimised our recognition of customers’ complaints and then provided recommendations and remedial actions to resolve the current issues in logistics and transport industry in general, and at Fremantle port in particular.SignificanceThe current study integrates soft computing and optimisation technique in order to build the CRM recommender system. It demonstrates the hybrid soft computing strengthens in area of CRM as the relevance solution. The significance of the proposed algorithm is three fold. First, it integrates soft computing and optimisation technique in order to build the CRM recommender system. Second, it utilises the most standard CRM variables in its decision making process. Third, it is an optimising algorithm because it integrates DEA with PCA technique.     

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.     

Modeling customer satisfaction for new product development using a PSO-based ANFIS approach

When developing new products, it is important to understand customer perception towards consumer products. It is because the success of new products is heavily dependent on the associated customer satisfaction level. If customers are satisfied with a new product, the chance of the product being successful in marketplaces would be higher. Various approaches have been attempted to model the relationship between customer satisfaction and design attributes of products. In this paper, a particle swarm optimization (PSO) based ANFIS approach to modeling customer satisfaction is proposed for improving the modeling accuracy. In the approach, PSO is employed to determine the parameters of an ANFIS from which better customer satisfaction models in terms of modeling accuracy can be generated. A notebook computer design is used as an example to illustrate the approach. To evaluate the effectiveness of the proposed approach, modeling results based on the proposed approach are compared with those based on the fuzzy regression (FR), ANFIS and genetic algorithm (GA)-based ANFIS approaches. The comparisons indicate that the proposed approach can effectively generate customer satisfaction models and that their modeling results outperform those based on the other three methods in terms of mean absolute errors and variance of errors.     

电力体制改革新时代下如何提升客户满意度

过去电网企业是垄断经营,随着电力体制改革和国有企业改革的纵深推进,客户有了更多选择。优质服务关乎电网企业新时代改革发展大局,只有优质服务才能使电网企业在改革发展中进入良性循环。然而,从第三方客户满意度调查报告中反映的情况可以看出,部分单位还存在垄断思维,“以客户为中心”的服务意识在实际工作中还未得到很好的落实,具体表现在停电次数多、电压不稳定、业扩流程长、抄表催费欠规范等客户用电体验较敏感的供电服务上。本文从客户体验管理角度,关注客户的用电体验和感受,把满足人民美好生活的电力需要作为电网企业工作的出发点和落脚点,围绕提升客户服务质量的关键点、电网企业存在的客户服务短板、提升客户满意度的有效措施等方面进行了有益地探讨。     

A fuzzy logic based approach for modeling quality and reliability related customer satisfaction in the automotive domain

This paper presents an approach to assess quality and reliability related customer satisfaction from field failure data at each individual customer level. The quality satisfaction has been modeled based on number of failures and severity of failures, while, reliability satisfaction has been modeled based on number of visits to dealer and time span between visits. The satisfaction modeled at an individual vehicle (customer) level is further aggregated to a vehicle model level to determine overall satisfaction of customers with that specific vehicle model. A fuzzy logic approach is used to construct the satisfaction model. A grid search technique is used to tune the model parameters such that the output of the model for specific vehicle models matches with survey based ratings assigned to the vehicle models.     

An Integrated Model for Customer Relationship Management: An Analysis and Empirical Study

Ensuring customer satisfaction and maintaining long‐term relationships with customers have become essential for survival among competitive service industries. The present study addresses this need by proposing a conceptually integrated four‐phase model that incorporates elements of customer relationship management (CRM) and customer satisfaction (represented by the extended American Customer Satisfaction Index model). Then, this study formulates structural equation modeling to test various research hypotheses related to the effect of the CRM initiative. An empirical study of 143 leading Taiwanese service firms distributed among seven service industries was conducted. The implementation levels of various constructs, input (customer knowledge), service provision (customer interactions), output quality, perceived quality, perceived value, perception of customer satisfaction, customer loyalty, purchasing intention, and profits of CRM are assessed in a range of service industries by means of a questionnaire survey and in‐depth interviews. The results of the empirical study reveal statistically significant influences among various constructs of the CRM integrated model. These results also represent a useful reference for managers of service organizations that could be used to improve the profitability and implementation level of CRM. The present study represents an important investigation in the development of an integrated CRM implementation system for service industries. © 2012 Wiley Periodicals, Inc.     

Optimal determination of warranty region for 2D policy: A customers' perspective

Warranty is treated by the manufacturer as a marketing strategy that creates better customer satisfaction, which finally helps to get hold of a bigger market share. The cost incurred towards this service is termed as warranty cost, which is a function of warranty policy and region, product quality and reliability, and the customers' usage pattern. Under the 2D warranty policy, there exists numerous iso-cost regions for any specified value of warranty cost. In this article, we propose a methodology to determine the optimal region when customers' utility is measured by the length of warranty coverage time. It is believed that the results will help the manufacturer to provide improved customer service.     

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.     

Becoming agile together: Customer influence on agile adoption within commissioned software teams

Despite the ongoing expansion of agile practices beyond software firms, agile adoption remains risky, challenging, and poorly understood. Although agile practices emphasize self-organization and customer collaboration, we know little about how customers influence agile adoption within self-organizing teams. Here, we analyze how a commissioned software team engaged in customer collaboration during agile adoption at a Danish IT service provider. Our case study shows that the software team's transition to self-organized teamwork practices, agile planning routines, and active customer engagement was mutually dependent on the customer's trust in the software team and flexible collaborative routines. As a result, we advance a theoretical perspective of customer influence on agile adoption within commissioned software teams, implying that both software teams and customers need to navigate a contradictory tension between self-organization and collaboration to become agile together.     

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。     

Rough set and PSO-based ANFIS approaches to modeling customer satisfaction for affective product design

Facing fierce competition in marketplaces, companies try to determine the optimal settings of design attribute of new products from which the best customer satisfaction can be obtained. To determine the settings, customer satisfaction models relating affective responses of customers to design attributes have to be first developed. Adaptive neuro-fuzzy inference systems (ANFIS) was attempted in previous research and shown to be an effective approach to address the fuzziness of survey data and nonlinearity in modeling customer satisfaction for affective design. However, ANFIS is incapable of modeling the relationships that involve a number of inputs which may cause the failure of the training process of ANFIS and lead to the ‘out of memory’ error. To overcome the limitation, in this paper, rough set (RS) and particle swarm optimization (PSO) based-ANFIS approaches are proposed to model customer satisfaction for affective design and further improve the modeling accuracy. In the approaches, the RS theory is adopted to extract significant design attributes as the inputs of ANFIS and PSO is employed to determine the parameter settings of an ANFIS from which explicit customer satisfaction models with better modeling accuracy can be generated. A case study of affective design of mobile phones is used to illustrate the proposed approaches. The modeling results based on the proposed approaches are compared with those based on ANFIS, fuzzy least-squares regression (FLSR), fuzzy regression (FR), and genetic programming-based fuzzy regression (GP-FR). Results of the training and validation tests show that the proposed approaches perform better than the others in terms of training and validation errors.     

Soccer shoe recommendation system based on multitechnology integration for digital transformation

Designing a soccer shoe that fits specific customer’s requirements can improve satisfaction. However, there is no sufficient information to bridge the semantic needs and design characteristics of soccer shoes. Hence, this study is aimed at integrating multiple technologies with semantic customer requirements, shoe-form categories, and appearance designs, and developing a practical Kansei soccer shoe recommendation system. The psychological responses of a customer and perceptions of soccer shoe products are evaluated using Kansei engineering method. Based on a factor analysis, customers’ requirements are classified as aesthetic, functional, and comfortable. A total of 203 soccer shoe images were used to evaluate and categorise the external shoe form into nine design elements using the Kawakida Jirou method, and the weight assigned to each shoe-form category under Kansei semantic adjectives was determined using grey system theory. The quantification theory Type 1 method was used to determine the priority of the design elements. The results indicate that 10 pairs of semantic adjectives used by customers are related to soccer shoe forms. Furthermore, the design priority of each design element of the form category under the three types is reported. A soccer shoe recommendation system that can generate suggested soccer shoe samples for customers is developed by integrating the above-mentioned technologies. A validation experiment was conducted to verify the feasibility of the proposed system. The overall satisfaction of the recommended samples generated via the system is 87.08%, as reported by 80 participants. The findings prove that a new soccer shoe business model can be launched using the proposed system, linking the semantic customer requirements to the soccer shoe-form categories.     

Exploring the influence of personal schema on trust transfer and switching costs in brick-and-click bookstores

Due to competition, most firms try to retain and lock in customers; this is likely to ensure a greater market profit than that gained by acquiring new customers. While many studies have investigated customer satisfaction and retention in online and offline firms, scant research exists on customer satisfaction and customer retention in the context of brick-and-click firms: i.e., those that conduct business both online and in stores. Such firms encourage trust transfer among their customers. However, most studies have failed to consider the role of personal schema in trust transfer. Based on social exchange, investment, and information integration theories, we analyzed the impact of trust transfer, switching costs, and personal schema on customer satisfaction and repurchase intentions in the context of an offline bookstore that has now launched an online business. Our results indicated that trust transfer and switching costs had a small effect on customer satisfaction and repurchase intentions. Personal schema, however, affected both customer satisfaction and repurchase intention.     

The priority factor model for customer relationship management system success

As the market competition becomes keen, constructing a customer relationship management system is coming to the front for winning over new customers, developing service and products for customer satisfaction and retaining existing customers. However, decisions for CRM implementation have been hampered by inconsistency between information technology and marketing strategies, and the lack of conceptual bases necessary to develop the success measures. Using a structural equation analysis, this study explores the CRM system success model that consists of CRM initiatives: process fit, customer information quality, and system support; intrinsic success: efficiency and customer satisfaction; and extrinsic success: profitability. These constructs underlie much of the existing literature on information system success and customer satisfaction perspectives. We found the empirical support for CRM implementation decision-making from 253 respondents of 14 companies which have implemented the CRM system. These findings should be of great interest to both researchers and practitioners.     

Impact analysis of logistics facility relocation using the analytic hierarchy process (AHP)

Facility relocation has a long‐term impact on business competitiveness in terms of cost efficiency, service level, and accessibility to marketplace. This paper investigates the impacts of relocating a company's logistics facility. Specifically, a case study of a logistics service provider for a bank, whose services include cash pick‐up and deliveries, and ATM refill, is conducted. Some of the major logistics issues caused by the relocation of the company's distribution center are identified through process observation and in‐depth interview. The analytic hierarchy process (AHP) is implemented to evaluate and rank the importance of the logistics issues according to the needs and requirements of the company's policy makers. Four criteria considered in the AHP include cost, responsiveness, reliability, and utilization. Results show that, from the company's perspective, the development of logistics key performance indices is given the highest priority, followed by improvement of internal process, vehicle routing, network design, and inventory management, respectively.     

An investigation into affective design using sorting technique and Kohonen self-organising map

In this paper, a prototype system that focuses on affective design perspective for iterative product concept development is proposed and described. The prototype system, which emphasises the solicitation of affective attributes from customers, employs a sorting technique, i.e. picture sorts, for acquiring customer's affective requirements and a hierarchical structure for representing designer's formal elements to meet customer's affective requirements in product conceptualisation. As hierarchical structure alone contains qualitative and uncertain inherence, a self-organised algorithm known as Kohonen self-organising map (SOM) neural network is employed to consolidate the relationship between affective requirements from customers and formal elements from designers so as to formulate a customer-oriented product concept. The performance of the prototype system is illustrated by using a case study on the design of a mobile hand phone.     

Breaking away from the conventional ‘usability lab’: the Customer-Centered Design Group at Tektronix,Inc.

Abstract

The conventional usability lab is primarily responsible for testing prototypes and products to determine if customers will accept a new design. Often this testing comes too late in the development cycle to allow major design or product changes to occur. In the Customer-Centered Design Group at Tektronix Labs, the usability lab is a small part of our group's involvement in the entire design life cycle of a Tektronix product. We work with design groups to bring the benefits of a usability lab to all phases of design, beginning with understanding our customer's current system and work processes to assessing the competitor's strengths and weaknesses to simulating and evaluating design alternatives. Our ‘lab’ is often on the road; meeting with customers where they work, working with design teams to simulate and prototype designs, and evaluating designs with our customers. To keep in touch with customers and to keep product development focused, we feel a usability group must break down the barriers inherent in a conventional testing suite. By breaking these barriers we can better determine what customers need and how these needs are addressed throughout the entire product life cycle.     

Satisfaction Benchmarking and Customer Classification: An Application to the Branches of a Banking Organization

Banking services constitute a highly competitive market and indicate a representative example of customer–oriented organizations. For this reason, customer satisfaction is of vital importance, offering a quantitative measure for current and future performance of these organizations. On the other hand, classifying customers according to their satisfaction behavior may indicate different client clusters with distinctive preferences and expectations. This approach serves the development of a truly customer–focussed culture by determining a set of improvement strategies that best fit the different customer segments. In this paper, the multi–criteria method MUSA is implemented in order to measure and analyze customer satisfaction in different branches of a banking organization. These results are also used to benchmark these branches according to the provided services. Moreover, segmentation analysis is performed in order to identify the different groups of customers and estimate the homogeneity of preferences in distinct customer segments. Data are based on a pilot customer–satisfaction survey, while the most important results are focussed on the determination of the critical service dimensions.