How does manufacturing service perceived value influence customer satisfaction? An investigation of global semiconductor industry

Customer satisfaction is an important strategic performance which is influenced by service experience and perceived value. This study proposed a model to postulate, and statistically test, the relationship between value drivers and customers’ perceived value of semiconductor manufacturing services, and the impact of perceived value on customer satisfaction. The research results showed that perceived value and value drivers are significantly different among services. Line services have a more significant influence on customer satisfaction than support services. Customer firm type and geographical location have a significant influence on value perception and preference, and on the relationship between service value and customer satisfaction. This study suggests that semiconductor manufacturing service providers should deliver right value proposition to enhance satisfaction for different customer firm types in varying regions, and design customised service portfolios with various value foci to differentiate them and gain a competitive advantage.     

Barriers in adoption of internet banking: A structural equation modeling - Neural network approach

Comparatively, less attention has been paid to the factors that obstruct consumers to use internet banking. Therefore, this study aims to analyze the barriers in the adoption of Internet banking in Karachi, Pakistan. A survey research questionnaire was adopted and, in total, 300 useable responses were used from the banks’ customers. First exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied for the establishment of measurement model and structural equation modeling (SEM) was used to find the significant influence barriers on Internet banking adoption. In the second phase, the neural network model was used to rank the relative influence of significant predictors obtained from SEM. The results indicate a significant positive relationship between value barrier, risk barrier, and image barrier with the usage of Internet banking. Only, the traditional barrier has a negative insignificant effect on the usage of Internet banking. The image barrier has a higher impact on usage of Internet banking followed by the value barrier and risk barrier. Results also indicate that males are facing high barriers in comparison with females. Findings provide guidelines to banks for developing facilities that enable the consumer to use Internet banking for their financial transactions. This study will be highly beneficial for the banking industry to improve their online services and revise their policies to facilitate consumers by meeting their needs.     

面向中小包装企业的云制造服务平台研发与应用

目的提高中小包装企业的综合竞争能力,满足客户的个性化需求。方法研发了一种采用多家企业、多个订单、多方协作、多维度服务交易的中小包装企业的云制造服务平台,基于创新智能服务的思想设计出了云制造服务平台的工作流程和核心功能。结果针对云制造服务平台的交易协同逻辑、供需智能匹配方法等关键问题进行了研究,实现了基于关键字的语义智能搜索、交易协同、订单跟踪以及全过程的协同化智能管理。结论以包装产品的研发、设计、生产、销售、物流过程应用为例,仿真分析订单完成效率提升20.5%,提高了整体包装效率、质量与顾客满意度,证明了云制造服务在包装行业的可行性和必要性。     

Iot based laundry services: an application of big data analytics,intelligent logistics management,and machine learning techniques

The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers’ security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well.     

基于N维云模型的客户共性与个体特征研究

依据所采集的客户服务属性数据和客户本体属性数据,运用多维正态云模型对客户群共性行为特征进行了描述,构建客户群数值特征矩阵。通过云相似性度量的方法,从质的层面上分析客户群之间的相似性,并依据相似度对客户群进行动态调整;确定各个客户群的标准型客户,运用多维X条件云发生器生成个体客户的特征属性值对客户群属性特征的激活强度,从量的层面上计算个体客户与客户群的标准型客户之间的差异。最后通过模拟分析,计算出客户群之间的相似度、个体与群体之间的差异值,证实运用多维云模型理论可以很好地进行客户行为分析。     

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain. Open Banking (OB) is one of the most important milestones since the beginning of financial technology innovation and service supply chain. As these are activities provided by traditional banks, non-bank financial institutions also provide financial service with access to consumer banking, transactional and other financial data to develop financial applications and services tailored to their customers. The development of financial technology, “Open banking”, promotes financial services to begin this transformation. However, evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored. Thus, the authors in this research proposed a hybrid multi-criteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) model and a Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) model with supports from seasoned domain experts. The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners. The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.     

Factors affecting the behavioral intention to adopt mobile banking: An international comparison

Over the past decade, the markets for mobile and wireless services have been among the world's fastest-growing, especially in Asian countries, presenting financial institutions with significant opportunities to offer value-added services. Mobile banking has since emerged as a new channel enabling the banks to react strategically to changes in competitive forces and to enhance customer convenience.Based on Diffusion of Innovations (DOI) theory, the Technology Acceptance Model (TAM), the Decomposed Theory of Planned Behavior (DTPB) model, this study develops an integrated model to provide a fuller understanding of factors facilitating or impeding the adoption of mobile banking, focusing on consumers in Taiwan and Vietnam. While subjective norms had a significant effect on the intention to adopt, three attributes of mobile banking (compatibility, perceived usefulness, and perceived risk) were found to have indirect effects on intention to adopt mobile banking through attitude toward adoption for consumers in both Taiwan and Vietnam. Intention to adopt mobile banking was indirectly influenced by self-efficacy and facilitating conditions, and directly affected by perceived behavioral control in both nations. Some differences in intention to adopt mobile banking between Taiwanese and Vietnamese are also discussed. Based on the research findings, managerial implications for financial institutions and mobile service providers are discussed.     

Root-Of-Trust for Continuous Integration and Continuous Deployment Pipeline in Cloud Computing

Cloud computing has gained significant use over the last decade due to its several benefits, including cost savings associated with setup, deployments, delivery, physical resource sharing across virtual machines, and availability of on-demand cloud services. However, in addition to usual threats in almost every computing environment, cloud computing has also introduced a set of new threats as consumers share physical resources due to the physical co-location paradigm. Furthermore, since there are a growing number of attacks directed at cloud environments (including dictionary attacks, replay code attacks, denial of service attacks, rootkit attacks, code injection attacks, etc.), customers require additional assurances before adopting cloud services. Moreover, the continuous integration and continuous deployment of the code fragments have made cloud services more prone to security breaches. In this study, the model based on the root of trust for continuous integration and continuous deployment is proposed, instead of only relying on a single sign-on authentication method that typically uses only id and password. The underlying study opted hardware security module by utilizing the Trusted Platform Module (TPM), which is commonly available as a cryptoprocessor on the motherboards of the personal computers and data center servers. The preliminary proof of concept demonstrated that the TPM features can be utilized through RESTful services to establish the root of trust for continuous integration and continuous deployment pipeline and can additionally be integrated as a secure microservice feature in the cloud computing environment.     

云印刷企业的发展策略研究

基于市场营销学和传播学的相关理论,从企业品牌形象传播、印品质量保证、服务拓展、客户发掘、渠道布置、建立流畅的反馈机制等方面,探讨了传统印刷企业向云印刷企业转型的发展策略。在这一转型过程中,印刷企业需要整合具有相同或相似需求的客户群体,利用大数据分析,提供精准的差别化服务,以满足各个细分市场中客户群体多样化的需求;在保证印品质量的同时,云印刷企业应拓展印刷服务范围,建立流畅的反馈机制,实现传统印刷业的数字化生存。     

建筑施工企业顾客满意度模型实证分析

根据建筑施工项目的特征提出一个简化的建筑施工企业顾客满意度理论模型.在收集建筑施工企业顾客样本数据的基础上,利用结构方程模型软件对理论模型作了检验.研究结果表明:顾客感知质量对顾客满意度、顾客感知价值对顾客忠诚度、顾客满意度对顾客抱怨具有显著性的影响;顾客期望对顾客抱怨、顾客满意度对顾客忠诚度有正面影响;顾客抱怨对顾客忠诚度有负面影响.研究结论具有较高的精度,模型对该建筑施工企业顾客满意度有较好的解释力.     

Customer demand prediction of service-oriented manufacturing incorporating customer satisfaction

With the emergence of individualised and personalised customer demands, the interaction of service and product has come into the sight of manufacturers and thus promoted the arising of service-oriented manufacturing (SOM), a new business mode that combines manufacturing and service. Be similar to the conventional manufacturing, the customer demand prediction (CDP) of SOM is very important since it is the foundation of the following manufacturing stages. As there are always tight and frequent interactions between service providers and customers in SOM, the customer satisfaction would significantly influence the customer demand of the following purchasing periods. To cope with this issue, a novel CDP approach for SOM incorporating customer satisfaction is proposed. Firstly, the structural relationships among customer satisfaction index and the influence factors are quantitatively modelled by using the structural equation model. Secondly, to reduce the adverse effect of multiple structural input data and small sample size, the least square support vector mechanism is employed to predict customer demand. Finally, the CDP of the air conditioner compressor which is a typical SOM product is implemented as the real-case example, and the effectiveness and validity of the proposed approach is elaborated from the prediction results analysis and comparison.     

Integrated DSL Test, Analysis, and Operations

This paper describes methods of integrating the digital subscriber line (DSL) automated test, data from network elements, analyses, and DSL operations, including work-force administration. Fiber-to-the-node systems using very-high-rate DSL 2 will particularly need the integrated DSL test to increase customer satisfaction and streamline operations to reduce costs. The integrated DSL test extends beyond copper tests to encompass all elements of DSL service, all through the network and at higher layers. An integrated test system queries multiple test points, including network elements, allowing physical and higher layer problems to be identified. Diagnosis, fault isolation, and even suggested reconfigurations are all automated in software. A number of techniques, which are implementable in software, are described, which can show the root cause of many intricate troubles to relatively unskilled technicians. Automated maintenance routines can isolate faults in flowthrough testing, automatically issuing trouble tickets toward the correct work center: Internet service providers, central offices, outside plants, user PCs, etc. New triple-play services have high customer expectations for easy-to-use TV and voice services, with demanding bit rates and reliability requirements that can be ensured with an integrated test.     

云制造模式下基于多目标非合作博弈的服务租赁定价策略

传统的制造企业通过销售产品和一定的售后服务获得利润,而在云制造模式下,关注产品质量、延长使用寿命,将产品作为服务租赁给客户成为一种新的盈利模式。本文将云服务平台中的服务提供方和服务需求方作为博弈双方,从供需Stackelberg博弈角度,结合大数据分析预测产品剩余使用寿命(remaining useful life, RUL),建立了云制造服务平台服务租赁的双层规划模型。双层规划问题是一类具有主从递阶结构的复杂决策问题,具有NP-hard性。本文使用带精英策略的非支配排序遗传算法(nodominated sorting genetic algorithm II, NSGA-II,)对模型进行求解,并使用某刀具厂案例验证模型实用性和有效性。     

Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning

Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet. The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric. In a hyperconverged cloud ecosystem environment, building high-reliability cloud applications is a challenging job. The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings. The emergence of cloud computing is significantly reshaping the digital ecosystem, and the numerous services offered by cloud service providers are playing a vital role in this transformation. Hyperconverged software-based unified utilities combine storage virtualization, compute virtualization, and network virtualization. The availability of the latter has also raised the demand for QoS. Due to the diversity of services, the respective quality parameters are also in abundance and need a carefully designed mechanism to compare and identify the critical, common, and impactful parameters. It is also necessary to reconsider the market needs in terms of service requirements and the QoS provided by various CSPs. This research provides a machine learning-based mechanism to monitor the QoS in a hyperconverged environment with three core service parameters: service quality, downtime of servers, and outage of cloud services.     

The role of complaint management in the service recovery process

BACKGROUND: Patient satisfaction and retention can be influenced by the development of an effective service recovery program that can identify complaints and remedy failure points in the service system. Patient complaints provide organizations with an opportunity to resolve unsatisfactory situations and to track complaint data for quality improvement purposes. SERVICE RECOVERY: Service recovery is an important and effective customer retention tool. One way an organization can ensure repeat business is by developing a strong customer service program that includes service recovery as an essential component. The concept of service recovery involves the service provider taking responsive action to "recover" lost or dissatisfied customers and convert them into satisfied customers. Service recovery has proven to be cost-effective in other service industries. THE COMPLAINT MANAGEMENT PROCESS: The complaint management process involves six steps that organizations can use to influence effective service recovery: (1) encourage complaints as a quality improvement tool; (2) establish a team of representatives to handle complaints; (3) resolve customer problems quickly and effectively; (4) develop a complaint database; (5) commit to identifying failure points in the service system; and (6) track trends and use information to improve service processes. SUMMARY AND CONCLUSIONS: Customer retention is enhanced when an organization can reclaim disgruntled patients through the development of effective service recovery programs. Health care organizations can become more customer oriented by taking advantage of the information provided by patient complaints, increasing patient satisfaction and retention in the process.     

基于KANO模型和PCSI指数的大学生心理健康服务设计研究

目的 KANO模型作为需求质量和满意度分析工具,在分析满意度影响时存在不足。拟将KANO模型与潜在顾客满意度改善指数(PCSI指数)进行混合式使用,来填补KANO模型的局限性。方法 通过阐明KANO模型、顾客满意度系数、PCSI指数之间的关系,探究三种工具在服务设计中的混合式使用模式,为调查分析服务中顾客的需求质量和满意度影响提供流程化分工,并针对大学生心理健康服务实施案例实证研究。结论 KANO模型与PCSI指数的混合式使用能更深入、全面地解析顾客的需求分布、满意度水平及两者的相互影响关系。经调查,大学生心理健康服务在满足学生需求和提升满意度上存在较大改善空间。为其纳入匿名咨询服务具有潜在的满意度改善作用,能推动服务组织转变为以关怀学生为中心。     

Cloud Security Service for Identifying Unauthorized User Behaviour

Recently, an innovative trend like cloud computing has progressed quickly in Information Technology. For a background of distributed networks, the extensive sprawl of internet resources on the Web and the increasing number of service providers helped cloud computing technologies grow into a substantial scaled Information Technology service model. The cloud computing environment extracts the execution details of services and systems from end-users and developers. Additionally, through the system’s virtualization accomplished using resource pooling, cloud computing resources become more accessible. The attempt to design and develop a solution that assures reliable and protected authentication and authorization service in such cloud environments is described in this paper. With the help of multi-agents, we attempt to represent Open-Identity (ID) design to find a solution that would offer trustworthy and secured authentication and authorization services to software services based on the cloud. This research aims to determine how authentication and authorization services were provided in an agreeable and preventive manner. Based on attack-oriented threat model security, the evaluation works. By considering security for both authentication and authorization systems, possible security threats are analyzed by the proposed security systems.     

顾客满意的可靠性模型研究

随着时代的发展, 质量的概念发生了很大的变化, 其判断标准由原来的符合技术标准转而成为满足顾客需求,顾客成为质量的最终判断者.对顾客满意的评测问题是企业质量管理工作中的一个重要方面,并越来越引起人们的关注.本文采用可靠性和冗余经济学的原理对顾客满意可靠度进行了一定的研究,并给出了一个提高顾客满意可靠度的冗余方案设计模型.     

Technological innovation and the U.S. banking industry: Innovation in the U.S. retail and wholesale banking sectors

In this paper, case studies of “best practice” retail and wholesale banks are used to explore the influence of technological change on the banking industry. The impact that specific technologies are having on the retail and whole-sale sectors is discussed. Briefly, the evidence shows that there is tremendous pressure on the banking industry to restructure at the current level of technology and competition. Retail banks are looking to client-server, open systems, groupware, workflow software, and imaging technology to restructure and consolidate their operations. Wholesale banks are using information technology to support specialized fee-income generating strategies. Nonetheless, in both the retail and wholesale banking sectors, nonbank financial service providers such as pension funds, insurance companies, money market funds and mutual funds are gaining market share. As these competitors expand their role, I find that the financial services competitor with the best strategy and technology is increasingly no longer a traditional bank.