A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry

Service sector is under pressure to deliver continuing performance and quality improvement while being customer-focused. In recent terms, there exists web based or electronic service quality (e-sq) concept. With the birth of electronic commerce, it has become important to be able to monitor and enhance e-sq. Therefore, this study will examine the e-sq concept and determine the key components of e-sq. The e-sq framework is employed by the aid of service quality (SERVQUAL) methodology as the theoretical instrument. Finally, proposed e-sq framework is illustrated with a web service performance example of healthcare sector in Turkey by using a combined multiple criteria decision making (MCDM) methodology containing fuzzy analytic hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS). The work presented in this paper shows the applicability of the e-sq framework in explaining the complexity of aspects observed in the implementation of healthcare services via internet.     

Strategic analysis of healthcare service quality using fuzzy AHP methodology

Managers in the service sector are under pressure to demonstrate that their services are customer-focused and that continuous performance improvement is being delivered. It is essential that customer expectations are properly understood and measured under the constraints that organizations must manage. The majority of the work to date has attempted to use the SERVQUAL (service quality) methodology in an effort to measure service quality. In this study, firstly the concept and factors of service quality are examined. Then a fuzzy AHP (analytic hierarchy process) is structured to evaluate the proposed service quality framework. A case study in healthcare sector in Turkey is presented to clarify the methodology.     

多源信息云服务质量的犹豫模糊优劣IPA评价方法

为有效评价多源信息云服务质量水平,在IPA框架下提出了一种以指标优劣水平为性能度量的犹豫模糊方法。首先,从用户满意角度构建了多源信息云服务质量评价的IPA层次结构框架;接着,以犹豫模糊集表述评价信息,基于参考解依赖评价规则,融合TOPSIS方法的最优与最劣参考解和EDAS方法的平均参考解,提出了一种以指标优劣水平为性能度量的犹豫模糊IPA分析方法,用于多源信息云服务质量评估。此外,考虑到现有的犹豫模糊距离测度无法度量不对称信息问题,构建了一种基于Squared-χ2的犹豫模糊测度。最后,以东莞A企业多源信息云服务质量评价为实例进行分析,结果表明了该方法的可行性,并通过与近似方法的对比分析可知,该方法能够有效评价多源信息云服务质量。     

Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment

The aim of this paper was to present an effective approach for evaluating service quality of Northeast-Asian international airports by conducting customer surveys. In general, evaluation of service quality is a complex multicriteria decision-making (MCDM) problem; therefore, a complex decision process is often involved in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. By combining concepts of VIKOR and grey relational analysis (GRA), a new fuzzy MCDM method was proposed to deal with the evaluation of service quality problems in the international airports. This model was solved by an effective algorithm, which incorporated the decision-maker’s attitude and/or preference for customers’ assessments on weights and performance ratings of each criterion. An empirical study for evaluating service quality of seven major Northeast-Asian international airports was put forth to illustrate an application of the proposed model. The study results showed that this approach is an effective means for tackling MCDM problems involving subjective assessments of qualitative attributes in a fuzzy environment.     

The evaluation of service quality using generalized Choquet integral

In view of the compatibility between psychology and linguistic terms, this study generalizes the standard Choquet integral, whose measurable evidence and fuzzy measures are real numbers. The proposed generalization can deal with fuzzy-number types of measurable evidence and fuzzy measures. In comparison with the previous research on service quality and fuzzy sets, this study integrates the three-column format SERVQUAL into the generalized Choquet integral. A numerical example evaluating the overall service quality of e-stores is provided to illustrate how the generalized Choquet integral evaluates service quality in the three-column format SERVQUAL. This integral is also compared with the possibility/necessity model when measuring service quality.     

Fuzzy application in service quality analysis: An empirical study

Service activities have become the fundamental and dominant factors of the economic system over the past three decades and the significance and influence of service quality have been recognized through the great effect on customer satisfaction and customer loyalty. It should be noted that the assessment results obtained from multiple attributes decision-making problems of diverse intensity, such as service quality evaluation, may be misleading if the fuzziness of subjective human judgment is not taken into account. This paper develops an analysis architecture, which consists of fuzzy measurement of P–I gap, modified P–I analysis for attributes and ranking order determination for subjects, to deal with service quality measurement more effectively. The fuzzy measurement of P–I gap takes advantage of including the vagueness of evaluators’ judgment. By using the results of modified P–I analysis, effective ways for improving service quality perceptions can be focused on the attributes of high importance yet poor quality; meanwhile, resources or efforts attached to the attributes of low importance and good quality can be shifted to those of high importance yet poor quality. According to the ranking order of subjects, managers could devote more efforts to assist the subjects with inferior rankings to improve the service activities. The proposed analysis architecture can be used to investigate service quality effectively and track the trends periodically. An empirical study is conducted by using the proposed approach.     

A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality

Managing service quality is vital to retain customer satisfaction and augment revenues for any business organization. Often it is difficult to assess service quality due to lack of quantifiable measures and limited data. In this paper, we present a hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating service quality of urban transportation systems. The proposed approach consists of three steps. The first step involves development of a SERVQUAL based questionnaire to collect data for measuring transportation service quality. The participants provide linguistic assessments to rate the service quality criteria and the alternatives. In step 2, the linguistic ratings are combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the decision making process.The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. An application of the proposed approach for evaluation of service quality of metro in Montreal is provided.     

Applying fuzzy hierarchy multiple attributes to construct an expert decision making process

The main objective of this paper is to propose an approach within the AHP framework for tackling the uncertainty and imprecision of service evaluations during pre-negotiation stages, where the expert’s comparison judgments are represented as fuzzy triangular numbers. A fuzzy prioritization method, which derives crisp priorities from consistent and inconsistent fuzzy comparison matrices, is described. The fuzzy analytic hierarchy process (FAHP)-based decision-making method can provide decision makers or buyer a valuable reference for evaluating software quality. A case study demonstrates the effectiveness of the proposed scheme. Importantly, the proposed scheme can assist decision makers in assessing the feasibility of digital video recorder system to management public space, making it highly applicable for academic and commercial purposes.     

Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system

In manufacturing grid (MGrid) system, according to functional requirements of a task, there exist a lot of resource services which have similar functional characteristics. Multiple resource services with similar functional characteristics raise the concern over resource service optimal-selection (RSOS). It is important to select the optimal resource service according to their non-functionality characteristics or quality of service (QoS). However, QoS attributes are not easy to measure due to their complexity and involvement of ill-structured information. In this study, user’s feeling is taken into account in RSOS in an MGrid system. The non-functionality QoS evaluation of resource services is based on users’ feeling and transaction experiences using intuitionistic fuzzy set (IFS). Furthermore, the dynamics of non-functionality QoS is considered, and a time-decay function is introduced into non-functionality QoS evaluation. A new method is proposed for RSOS based on IFS and non-functionality QoS, and the procedures are presented in detail. A practice case study is used to illustrate the proposed method and procedure. The performance and advantage of the proposed method are discussed.     

Logistics service provider selection decision making for healthcare industry based on a novel weighted density-based hierarchical clustering

In recent years, Industry 4.0 makes a significant impact on the manufacturing industry, which enables the business more intelligent and efficient, all while minimizing costs. As known, the logistics concerns in the supply chain always play an important role to a manufacturing company, and decision on the selection of logistics service provider is a key point, especially for healthcare manufacture whose products are the medical devices or equipment of fragility and high cost. Practically there are so many logistics service providers with varieties in service quality, effectiveness, punctuality and reliability, that the manufacturers often encounter the challenge on the provider selection, and healthcare industry is no exception. However, the research on provider selection for healthcare manufacturers is quite limited. In order to help them to make the decision, this paper designs a logistics service provider selection scheme based on a novel weighted density-based hierarchical cluster analysis with integration of the analytic hierarchy process (AHP) for healthcare industry. Initially an evaluation index system reflecting the capability of the candidate providers in all aspects is established. To improve the clustering within the scheme, the density concept and the obtained weights are introduced into the traditional hierarchical cluster analysis (HCA) to shape a novel Weighted Density-Based HCA (WDBHCA). To validate the feasibility of the scheme, a case study on a specified healthcare industry manufacturer is carried out, and results fulfill the case company’s requirement which shows the feasibility of the proposed provider selection scheme. In addition, this scheme can be applied to the provider selection in other fields, as well.     

Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing

Cloud computing promises to provide high quality, on-demand services with service-oriented architecture. However, cloud service typically come with various levels of services and performance characteristics, which makes Quality of Cloud Service (QoCS) high variance. Hence, it is difficult for the users to evaluate these cloud services and select them to fit their QoCS requirements. In this paper, we propose an accurate evaluation approach of QoCS in service-oriented cloud computing. We first employ fuzzy synthetic decision to evaluate cloud service providers according to cloud users’ preferences and then adopt cloud model to computing the uncertainty of cloud services based on monitored QoCS data. Finally, we obtain the evaluation results of QoCS using fuzzy logic control. The simulation results demonstrate that our proposed approach can perform an accurate evaluation of QoCS in service-oriented cloud computing.     

An evaluation approach to logistics service using fuzzy theory,quality function development and goal programming

Logistics customer service is an important factor in the success of supply chain management. The aim of this study is to propose a novel approach for customer service management. For the improvement of logistics service operations, the proposed method integrates quality function development (QFD), fuzzy extended analytic hierarchy process (FEAHP), and multi-segment goal programming (MSGP). The advantage of the method includes the consideration of various logistics goals and the flexibility of setting multi-aspiration levels of evaluation criteria.     

Using the extension of DEMATEL to integrate hotel service quality perceptions into a cause–effect model in uncertainty

This study proposes an evaluation approach on assessing service quality perceptions based on the fuzzy measure and extension of decision-making trial and evaluation laboratory (EDEMATEL). This research comprises the perception of two study groups, namely, customers and employees, which include 22 evaluation criteria assessed by two groups from the top four English hotels in Taiwan. The human perception on service quality usually involves in imprecision and vagueness. The triangular fuzzy numbers presents the vagueness and subjectivity information, and use defuzzification method to handle the vagueness linguistic information into a crisp value. This study applies fuzzy set theory and EDEMATEL method to evaluate the interrelationships of service quality evaluation criteria and to compromise the group perceptions into a cause and effect model in uncertainty. The proposed approach is an effective method for assessing the group perceptions, and it integrates the different perceptions into a compromised cause and effect model of hotel service quality in uncertainty. The managerial implications are discussed.     

基于客服对话的产品和服务质量分析

现有的产品和服务质量分析常通过问卷调查或利用商品评论,但存在问卷收集难度大、商品评论中存在无效数据等问题。客服对话作为顾客与商家之间沟通的桥梁,包含了丰富的顾客意见,覆盖了从产品到服务的多个方面,然而现在利用客服对话分析产品和服务质量的研究还较少。提出了一种基于客服对话的产品和服务质量分析方法,首先结合产品特征和服务蓝图,确定产品和服务质量的评价要素,并结合重要性?满意度分析（IPA）法定义评价要素的重要性和满意度指标;然后对客服对话进行主题提取和情感分析,定量分析产品和服务的重要性和满意度。以某消毒除菌产品淘宝旗舰店的真实客服对话为例应用了该方法,建立了18个评价要素,并基于90余万条真实的历史客服对话对评价要素的重要性和满意度进行了量化,从而分析旗舰店产品和服务的质量。最后通过对专业客服的问卷调研,验证了所提方法的有效性。     

Hybrid classification engine for cardiac arrhythmia cloud service in elderly healthcare management

The self-regulation ability of the elderly is largely degenerated with the age increases, and the elderly often expose to great potential hazards of heart disorders. In practice, the electrocardiography (ECG) is one of the well-known non-invasive procedures used as records of heart rhythms and diagnosis of unusual heart diseases. In this paper, we propose a healthcare management system, named CardiaGuard, which is specialized in monitoring and analysis the heart disorder events for the elderly. The CardiaGuard cloud service is an expert system designed based on the hybrid classifier implemented using support vector machine (SVM) and random tree (RT) classification algorithm. We conduct a comprehensive performance evaluation which shows the proposed hybrid classification engine are able to detect six types of cardiac disorders with higher accuracy rate than the SVM-based classifier alone. CardiaGuard poses a great solution to enhance the quality of good clinical practice on the healthcare management for the elderly in cardiology.     

Stakeholder requirement evaluation of smart industrial service ecosystem under Pythagorean fuzzy environment for complex industrial contexts: A case study of renewable energy park

This study focuses on ways to systematically evaluate stakeholder requirements when developing a smart industrial service ecosystem (SISE) in a complex industrial context. The SISE development requires considering the service requirement from both the complex industrial context and service ecosystem manners. This study proposes a systematic framework for stakeholder requirement evaluation in SISE. The first part of the framework is the industrial context-viable system model with ecological thinking (IC-VESM) to elicit the service requirements for the SISE, which facilitates a systematic analysis of the service value proposition and service requirement elicitation in the operational lifecycle of an entire industrial context. This second part of the framework proposes a method for evaluating service requirements that is both feasible and systematic. This is achieved by combining the Fuzzy Kano and AHP methods in a Pythagorean fuzzy (PF) environment. The PF Kano computes the categories and determines the weights of service requirements from a consumer perspective, while the PF AHP hierarchically analyzes the service requirements and provides pairwise comparison paths for design experts. Finally, an illustrative case study in a renewable energy context was used to demonstrate the feasibility and effectiveness of the methodology. The proposed theoretical model provides more reliable and systematic outcomes than traditional methods when eliciting service requirements and evaluating complex smart industrial service solutions. The study has practical implications by providing useful insights for companies to recognize key smart service requirements in complex industrial contexts and to improve sustainable development.     

QoS需求驱动的服务配置框架

为支持服务质量敏感的基于组件的分布式应用的开发,中间件需要为组件提供并配置各种服务质量服务的非功能性属性.目前的组件架构提供的服务配置方式大多是静态的,且没有考虑不同客户的需求.在对EJB架构进行研究的基础上,提出一种服务质量需求驱动的服务配置框架.研究了根据客户的服务质量需求,在组件实例级别自动生成服务配置决策并实施,实现对不同客户服务差分处理.框架是一个基于服务配置的决策模型,通过多选择背包问题生成服务配置策略.最后通过一个应用实例对框架进行了验证.     

Towards a lightweight framework for service management evaluation in SMEs

Small and Medium-sized Enterprises (SMEs) are currently immersed in Volatility, Uncertainty, Complexity and Ambiguity (VUCA) environments and need to adapt and innovate both their services and their management practices and processes. Unfortunately, models and standards for service management are focused on large organisations, therefore, their application in SMEs is expensive and, generally, unfeasible. In order to contribute to the sustained success and development of SMEs, this paper presents a framework for service management evaluation. The objective of this framework, which is based on international standards and the main models for service management, is to be a roadmap containing well-defined and formalised processes that helps SMEs to improve the quality of their customer services. The proposal is validated in this work by means of its application to a real case study.

     

Service composition model and method in cloud manufacturing

This study optimizes service composition on the basis of task requirements to solve the problem of multitask corresponding multi-service selection. First, the basic path structure and the implementation steps of cloud manufacturing (CMfg) service composition are analyzed, and service composition is divided into four patterns. Second, the quality of service (QoS) index system of service composition is proposed by combining the six goals of time, composability, quality, usability, reliability, and cost; the calculation expressions of QoS under different composition structures are listed; and the mathematical model of CMfg service composition is established. Then, the weight of each index value in QoS evaluation is determined using an improved fuzzy comprehensive evaluation method. Finally, the optimal selection scheme of service composition is proposed by using gray relational analysis method(GM), and the validity of the optimal selection scheme is verified by an example of mold manufacturing.     

Hybrid approach for context-aware service discovery in healthcare domain

Context-awareness computing is a research field which often refers to healthcare as an interesting and rich area of application. Context aware computing attains environments monitoring by means of sensors to provide relevant information or services according to the identified context. In particular, wireless ad hoc sensor networks for medical purposes are playing an increasing role within healthcare. Body Sensor Networks (BSN) are being designed for prophylactic and follow-up monitoring of patients in e.g. their homes, during hospitalization, and in emergencies. This work presents an integrated environment aimed at providing personalized healthcare services which appropriately meet the user?s context. Deploying the semantics embedded in web services and context models is a mandatory step in the automation of service discovery, invocation and composition. Nevertheless, in a context aware domain purely logic-based reasoning on respectively context and services may not be enough. The main idea of this work is related to enrich with qualitative representation of context underling data by means of Fuzzy Logic in order to automatically recognize the context and to consequently find the right set of healthcare services among the available ones. Semantic formalisms (e.g., OWL, OWL-S, etc.) enable the context and services modeling in terms of domain ontology concepts. On the other hand, soft computing techniques support activity of unsupervised context analysis and healthcare semantic service discovery. Goal is to define context-aware system whose quality of retrieved services relies on the acquisition of user context by means of a robust theoretical approach. Moreover, this work defines hybrid architecture which attains a synergy between the agent-based paradigm and the fuzzy modeling. Specifically, the system exploits some task oriented agents in order to achieve context recognition, services matchmaking and brokerage activities.