服务质量敏感型空间信息服务引擎设计

为避免基于速率控制的TCP友好拥塞控制策略在调整多媒体流的发送速率时变化波动较大的问题,提出一种新的改进策略——延迟预警算法,通过在发送端设置延迟预警信号,对TFRC流的发送速率进行调整,使其在与TCP流的竞争中变得更加平滑。仿真实验结果表明,该算法能够有效改善TFRC的性能,具有良好TCP友好性及速率平滑性。     

An integrated framework of user experience-oriented smart service requirement analysis for smart product service system development

The rapid deployment of digital technologies drives the conventional product service system (PSS) to shift into a new paradigm known as smart PSS. Empowered with smart capabilities, smart PSS has great potential in creating positive user experience (UX). The requirements analysis is an essential task for successful development of smart PSS with strong UX. Nevertheless, there is still a lack of research on the requirement analysis of smart PSS by incorporating smart-enabled UX perspective. Hence, this paper proposes a framework of user experience-oriented smart service requirement (UXO-SSR) analysis for smart PSS development. At first, the relevant factors (e.g., user personas and activity journey) are integrated to conceptualize the UX in smart PSS context. Second, a four-phase model is proposed for identifying UXO-SSR, which can provide an effective tool for acquiring UX requirements of smart PSS from holistic perspective. Third, a novel asymmetric trapezium cloud-based uncertain linguistic BWM approach is developed to evaluate the priority of the identified UXO-SSRs. The approach can appropriately handle the hybrid uncertainties (i.e., hesitancy, fuzziness and randomness) of linguistic evaluation information, thereby improving the accuracy of evaluation results. Finally, a case study of smart sleep service system is presented to demonstrate the feasibility and reliability of the proposed framework.     

Combining fuzzy AHP and fuzzy Kano to optimize product varieties for smart cameras: A zero-one integer programming perspective

In an era of global customization, dominating the majority market with a single product has become increasingly difficult and almost impossible for most companies. In contrast, they must provide various product varieties that attract diverse customers, particularly when acquiring distinct market segments. In practice, however, most companies cannot effectively reduce the gap between customer requirements and design characteristics, although this impacts the profitability and future growth of companies. Meanwhile, companies often get stuck in the trade-offs between enhancing product varieties and controlling manufacturing costs. Accordingly, this paper proposes a hybrid framework that combines fuzzy analytical hierarchy process (AHP), fuzzy Kano model with zero-one integer programming (ZOIP) to incorporate customer preferences and customer perceptions into the decision-making process of product configuration. Specifically, fuzzy AHP is used to extract customer preferences for core attributes while fuzzy Kano model is utilized to elicit customer perceptions of optional attributes. Finally, by virtue of ZOIP, the optimal product varieties (smart cameras) for distinct segments are determined by maximizing overall customer utility (OCU) and taking a firm's pricing policy into account.     

A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

Nowadays, industrial companies are facing ever-increasing challenges to generate new value-in-use and maintain their high competitiveness in the market. With the rapid development of Information and Communication Technology (ICT), IT is embedded in the products themselves, i.e. smart, connected products (SCPs) to generate values. Hence, an emerging value proposition paradigm, smart product-service system (Smart PSS) was introduced, by leveraging both SCPs and its generated services as a solution bundle to meet individual customer needs. Unlike other types of PSS, in Smart PSS, massive user-generated data and product-sensed data are collected during the usage phase, where potential requirements can be elicited readily in a value co-creation manner with context-awareness. Nevertheless, only few scholars discuss any systematic manner to support requirement elicitation in such context. To fill the gaps, this research proposes a novel data-driven graph-based requirement elicitation framework in the Smart PSS, so as to assist engineering/designers make better design improvement or new design concept generation in a closed-loop manner. It underlines the informatics-based approach by integrating heterogeneous data sources into a holistic consideration. Moreover, by leveraging graph-based approach, context-product-service information can be linked by the edges and nodes in-between them to derive reliable requirements. To validate its feasibility and advantages, an illustrative example of smart bicycle design improvement is further adopted. As an explorative study, it is hoped that this work provides useful insights for the requirement elicitation process in today’s smart connected environment.     

Using Kano model to differentiate between future vehicle-driving services

Services are constantly changing with the introduction of new technologies, which affect the service systems of both conventional and autonomous driving. New theories and technologies are also key factors affecting the design and development trends of service models and solutions. Major automobile manufacturers aspire to provide customers with unique services and experiences, resulting in a growing demand for systematic approaches to characterize customer behaviors and scientific methods to accurately interpret data stored in databases. This study proposes a scientific engineering and operation framework for driving services that enables conventional automobile manufacturers to re-evaluate their service models and solutions as they expand into the domain of autonomous driving, integrating customized consumer interactions and mass production efficiency to develop new technologies, and subsequently applying these technologies to innovate their driving services, form service innovation guidelines, and accelerate the development of smart applications for the automobile industry. A Kano two-dimensional model of quality was employed. A Kano questionnaire was administered to analyze consumers' perceived satisfaction concerning different service quality elements; the elements were then ranked in the order of requiring improvement to determine the elements that are essential in conventional vehicles. Finally, suggestions were proposed for improving the service quality of driving products and evaluating driver satisfaction. A total of 56 valid questionnaires were collected from potential buyers of four-door sedans. The questionnaire evaluated respondents’ perceived value and satisfaction of 30 product elements categorized into two groups (specific functions and intangible value-added services) across eight major quality dimensions (basic safety functions, multimedia entertainment systems, information and communication systems, value-added systems, active matching, automatic service systems, hardware–software integration, and customer service and support). In addition, Kano quality categories were statistically analyzed to elucidate whether significant differences existed between groups. Using the Kano quality categories, 30 design elements were classified: 10 as “attractive,” 7 as “one-dimensional,” 3 as “must-be,” 4 as “indifferent,” and 6 as “reverse.” Enterprises can effectively reduce customer dissatisfaction and enhance customer satisfaction based on the quality category of the product and the product improvement order proposed in this study.Relevance to industryThis study determined that using the Kano quality categories, enterprises can effectively reduce customer dissatisfaction and enhance customer satisfaction based on the quality category of the product and the product improvement order proposed in this study.     

A digital smart product service system and a case study of the mining industry: MSPSS

Mining equipment products and services no longer meet the needs of future development in the mining industry due to high safety and operational risk. The deep integration of the product-service system (PSS) and digitization is required in the mining industry to promote industry transformation and safe and efficient production without changing the traditional operation mode. This paper proposes a smart product-service system for the mining industry (MSPSS) consisting of a smart product subsystem, stakeholders, smart service subsystem, and smart decision-making subsystem. The analytic hierarchy process (AHP) and virtual reality (VR) are used for decision-making, product selection, operation, and maintenance. The smart product subsystem outputs reliable digital products using three stages: digital design, virtual simulation and planning, and virtual debugging. The smart service subsystem is driven by data and digital technology and provides fault diagnosis and online maintenance services for complex mining products. A case study indicates that all stakeholders can participate seamlessly in the design process. The smart product subsystem uses iterative optimization (more than 100 iterations) to obtain the design results interactively. The smart service subsystem provides digitalized services throughout the entire process. Thus, a stable, reliable, and comprehensive product and service solution is provided for complex mining conditions. The output is used to guide the design, debugging, and operation of physical equipment. The MSPSS has higher design quality and efficiency, a shorter design time, and lower design cost (key performance indicator (KPI)) than the traditional design method.     

Configuration optimization of service solution for smart product service system under hybrid uncertain environments

Configuration of service solution is recognized as a crucial task for smart product service system (PSS) development, which provides an effective way to meet dynamic customer requirements. New smart attributes, broader stakeholder value and hybrid uncertainty occur inherently in the service solution configuration for smart PSS. These emerging characteristics lead to urgent updating need of the existing approaches to service solution configuration optimization. Therefore, the current study proposes a systematic approach to optimization of smart product service (SPS) solution configuration, aiming to achieve the best smart capability and value symbiosis among stakeholders of the configured SPS schemes. In the proposed approach, a new attributes system is proposed to describe the smart service module instances, and then employed as criteria to determine the configuration parameters. A novel rough-fuzzy data envelopment analysis (DEA) method is proposed to obtain the configuration parameters of each service module, with objective of effectively handling the hybrid uncertainties involved in the configuration environments. In addition, a bi-objective optimization model for SPS solution configuration considering smart capability efficiency and value symbiosis efficiency is proposed, and it is solved by an adaptive non-dominated sorting genetic algorithm II (ANSGA-II) to acquire a Pareto set of optimized configuration solutions. Finally, an application of this systematic approach to smart vehicle service demonstrates the feasibility and effectiveness of the proposed approach.     

Modularized design-oriented systematic inventive thinking approach supporting collaborative service innovations

The rapid evolution of new service systems raises crucial challenges for service design and requires effective methods. This study depicts a conceptual service design framework, called design-oriented systematic inventive thinking (DSIT) approach, which can be applied in different problem contexts. DSIT is presented as a new systematic and collaborative intelligence approach for creating and evaluating complex service systems using multi-criteria data analytics. DSIT synthesizes the current field of TRIZ service-design knowledge system and the emerging area of non-TRIZ service-design knowledge system. DSIT enables integrated development of service offerings at four dimensions and provides the matching integrated service design approach for each dimension. Four types of service design approaches are conceptualized as “human-independent service engineering,” “problem-clarified service engineering,” “solution-converged service engineering,” and “designing for service.” A new service computer-aided design system (service CAD) named DSIT explorer is developed consisting of customization, compatibility, and extensiveness of DSIT modules. A pervasive and smart collaborative service system (i.e., the smart MOS burger service solution) designed using DSIT explorer is illustrated. DSIT is a holistic, interdisciplinary, and collaborative service design concept, which is incorporated into a collaborative and intelligent service CAD framework to enable systematic inventive thinking throughout phases of service design lifecycle from problem definition, problem resolution, to solution evaluation.     

Analysing network uncertainty for industrial product-service delivery: A hybrid fuzzy approach

More and more manufacturers are transitioning from product-focused operations towards global service-oriented operations through approaches such as an industrial product-service system (IPS²). These systems deliver a blend of goods, equipment and services for improved value/revenue streams and there is a need to leverage the knowledge of domain experts in evaluating the uncertainties of IPS² adoption.Along these lines, this article proposes a hybrid fuzzy methodology that leverages the knowledge of domain experts for evaluating the uncertainty of service networks that deliver an IPS². The proposed methodology conceptualises a framework of network uncertainty metrics and applies a set of fuzzy-based techniques (fuzzy Delphi, fuzzy Analytical Hierarchy Process (fuzzy AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS)) to evaluate levels of fuzziness for transitions from traditional product-focused operations towards service-oriented operations. The applicability of the proposed methodology is demonstrated through a case study of a stainless steel manufacturer and the limitations and generalisation potentials of the research are used to highlight future research challenges for service-oriented uncertainty evaluation.     

Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach

This paper develops an integrated approach, combining quality function deployment (QFD), fuzzy set theory, and analytic hierarchy process (AHP) approach, to evaluate and select the optimal third-party logistics service providers (3PLs). In the approach, multiple evaluating criteria are derived from the requirements of company stakeholders using a series of house of quality (HOQ). The importance of evaluating criteria is prioritized with respect to the degree of achieving the stakeholder requirements using fuzzy AHP. Based on the ranked criteria, alternative 3PLs are evaluated and compared with each other using fuzzy AHP again to make an optimal selection. The effectiveness of proposed approach is demonstrated by applying it to a Hong Kong based enterprise that supplies hard disk components. The proposed integrated approach outperforms the existing approaches because the outsourcing strategy and 3PLs selection are derived from the corporate/business strategy.     

An integrated application of Kano’s model and AHP to Korean online open market services

With the advancement in wireless and mobile technologies, online open markets decrease intermediate distribution margins and play the key intermediary role between sellers and consumers. While offline store sales remain stagnant, online open market sales have been growing steadily. We investigated the service quality of Korean online open market providers such as “Gmarket”, “Auction”, and “11st”, based on an integrated application of Kano’s model and the Analytic Hierarchy Process (AHP). The contributions of this study are as follows: (1) We conducted acritical review of previous literature to develop each analysis method. (2) We categorized the service quality factors of the Korean open market using Kano’s model and identified the most important service quality factor by AHP analysis. (3) Then, we conducted a comparison between the results from the Kano model and AHP analysis. (4) Lastly, based on the results of the integrated application of both Kano model and AHP analysis, this study provided specific implications for improving the service quality of the online open market in Korea.     

Implementation path and reference framework for Industrial Internet Platform (IIP) in product service system using industrial practice investigation method

With the development of intelligent sensing, edge computing, fog computing, cloud computing, parallel computing, smart grid, big data, block chain, 5G, cyber-physical systems, digital twins, machine learning and other technologies, the industrial internet has undergone control network stage, sensor network stage, internet stage, Internet of Things (IoT) stage, Industrial Internet of Things (IIoT) stage, and Industrial Internet (II) stage, etc. In the existing research, scholars focus on a local dot, such as: technology, function, elements and application based on industrial internet. However, there is a lack of an overall framework to study the top-level planning of Industrial Internet Platform (IIP) from a systematic perspective. On the other hand, there are few studies on the detailed path and steps for implementing IIP in a specific enterprise in a specific industry. The objective of this paper is to study a reference framework and industrial implementation path for IIP in product service system using industrial practice investigation method, which meets the needs of industry on the basis of existing theory and industrial practice, and to provide reference for government and industry planning, design, implementation and promotion of IIP. In addition, the proposed reference framework and industrial implementation for IIP in product service system can enhance the core value of the enterprise and increase benefits.     

The emergence of smart service ecosystems—The role of socio-technical antecedents and affordances

As physical products are increasingly augmented with digital technology, manufacturing firms have become part of the development of so-called smart products and smart services. As such, manufacturing firms are challenged by new market participants and ecosystem partners, particularly from the software development industry, and by the dynamic nature of business relationships. While the academic literature on the distinctive characteristics of ecosystems, particularly digital ecosystems, is rich, the effect of smart service ecosystems' emergence on the foundation of smart products remains uncertain. This study reports on case study research based on 47 semi-structured interviews with four companies that participate in an industrial smart service ecosystem. Taking an affordance-theoretic perspective, we uncover the antecedents of and the process of emergent smart service ecosystems. We find that smart service ecosystems have three socio-technical antecedents: a shared worldview, structural flexibility and integrity, and architecture of participation. We explain the emergence of smart service ecosystems as the result of specialisation in shared affordances and integration of idiosyncratic affordances into collective affordances. We derive seven propositions regarding the emergence of smart services, outline opportunities for further research, and present practical guidelines for manufacturing firms.     

Integrating crowd-/service-sourcing into digital twin for advanced manufacturing service innovation

In order to support advanced collaborations among smart products, services, users and service providers in a smart product and service ecosystem (S-PSS), this paper proposed a service-oriented hybrid digital twin (DT) and digital thread platform-based approach with embedded crowd-/service-sourcing mechanism for enabling advanced manufacturing services. This approach is well supported by the ecosystem interaction intelligence of digitally connected products, services, users, and service providers via Internet of Beings (IoB) (Things, Users and Service providers). First, driven by industrial application needs in heating industry, a conceptual model of the service-oriented hybrid platform integrated with crowdsourcing mechanism is developed, which supports the concepts of product DT, service DT and human user DT. Second, the key system realization techniques are developed to integrate service crowdsourcing and service recommendation for realizing smart services. Finally, a case study is carried out for evaluating and confirming its feasibility.     

Ant-based service selection framework for a smart home monitoring environment

Selecting ambient media services in a smart home monitoring environment is challenging. Services in such an environment should be ubiquitous, adaptive, and robust with respect to access and delivery. Many different techniques exist for selecting services in smart environments, for example, dynamic programming, genetic algorithms, and fuzzy logic. However, existing approaches to service selection fail to address the dynamic nature of the services and the requirement of considering the user context and user satisfaction. We address this issue by proposing an ant-inspired service selection framework based on dynamic user preferences and satisfaction. This ant-inspired approach is robust to failures and adaptive to dynamic context. The proposed framework enables different categories of residents (e.g., elderly people, fathers with children, mothers, and so on) to access various media services in such a way that their experiences are optimized with regard to their surrounding environment. Experimental results demonstrate the viability of the proposed framework.     

Conceptual design of a user-centric smart product-service system using self-organizing map

As an emerging IT-driven business paradigm, smart product-service system (Smart PSS), which offers not only the smart, connected product (SCP) but also its generated service as a solution bundle, has become a vital research topic. Many research efforts have been devoted to constructing the conceptual design framework by considering SCPs and services simultaneously. However, the following critical issues in Smart PSS conceptual design have not been well addressed: how to improve the solution of Smart PSS in the conceptual design stage to meet user emotional requirements. Aiming to fill the gap, this work proposes a conceptual design method for Smart PSS from the perspective of analyzing user-generated emotions/feelings. Specifically, the relevant traditional products are identified, and their public review data is used to analyze user emotions/feelings in user-product interaction. Interactive emotion board as a new design tool is presented to organize the user-generated emotions/feelings, associated design elements, and the potential design points of the initial solution. And the analytic hierarchy process (AHP) is utilized to evaluate the improved solution. To ensure the efficiency of the analysis process, the self-organizing map (SOM) algorithm is utilized in the process of clustering product samples and Kansei words. A case study of smart electric bicycle service system (SEBSS) design is used to demonstrate the performance of the proposed method. Based on the case study, the proposed approach appears effective in helping with Smart PSS conceptual design.     

A systematic literature review of stakeholder identification methods in requirements elicitation

This paper presents a systematic review of relevant published studies related to topics in Requirements Engineering, specifically, concerning stakeholder identification methods in requirements elicitation, dated from 1984 to 2011. Addressing four specific research questions, this systematic literature review shows the following evidence gathered from these studies: current status of stakeholder identification in software requirement elicitation, the best practices recommended for its performance, consequences of incorrect identification in requirements quality, and, aspects which need to be improved. Our findings suggest that the analyzed approaches still have serious limitations in terms of covering all aspects of stakeholder identification as an important part of requirements elicitation. However, through correctly identifying and understanding the stakeholders, it is possible to develop high quality software.     

Transforming an enterprise model into a use case model in business process systems

One of the responsibilities of requirements engineering is to transform stakeholder requirements into system and software requirements. For enterprise systems, this transformation must consider the enterprise context where the system will be deployed. Although there are some approaches for detailing stakeholder requirements, some of them even considering the enterprise context, this task is executed manually. Based on model-driven engineering concepts, this study proposes a semi-automatic transformation from an enterprise model to a use case model. The enterprise model is used as a source of information about the stakeholder requirements and domain knowledge, while the use case model is used as software requirements model. This study presents the source and target metamodels, a set of transformation rules, and a tool to support the transformation. An experiment analyzes the use of the proposed transformation to investigate its benefits and if it can be used in practice, from the point of view of students in the context of a requirements refinement. The results indicate that the approach can be used in practice, as it did not influence the quality of the generated use cases. However, the empirical analysis does not indicate benefits of using the transformation, even if the qualitative results were positive.     

基于区块链的智能服务交易跨链服务框架与通信机制

由于不同区块链上的区块链服务间缺乏有效通信机制,链与链之间难以形成有效互联互通.在智能服务交易过程中,交易主客体之间不仅仅是数据资产的单项转移,而且其服务范围扩展涵盖到更为广阔的数字资产转移场景.设计一种智能服务交易的跨链通信服务框架,并采用基于组件式、模块化设计,使智能服务交易主客体较为容易地接入服务框架,实现跨链可...