Mingyi Liu, Zhiying Tu, Jingying Wang, Zhongjie Wang
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Different from traditional models which are usually focused on specific service types and granularity levels, our model comprehensively covers the interconnections between stakeholders, services delivery channels, service functional and non-functional features and business domains. “Event” and “event chains” which are extracted from public news corpus are imported into the model as triggers of service ecosystem evolution and evolutionary relations are introduced into the model delineate evolution traces. Elements, relations, and application scenarios of this model are introduced in detail. Qualitative comparison with state-of-the-art models shows that our model has a higher degree of coverage of fine-grained elements/relations of service ecosystem and higher interpretability. Supplementary materials are provided to help understand how to build the model based on external data. 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引用次数: 5
摘要
随着一切即服务(EaaS)的趋势,服务蓬勃发展。多年来,各服务之间的联系日益紧密,在业务和科技层面促进跨界合作,为客户创造和传递独特的新价值。这种现象被称为服务互联网(Internet of Services, IoS)。IoS的产生和发展是基于个体服务利益相关者做出的大量离散决策,其结构和演变与自然生态系统非常相似。本文提出了一种新的多层网络模型来描述服务生态系统的静态结构和动态演化轨迹。与传统模型通常关注特定的服务类型和粒度级别不同,我们的模型全面覆盖了涉众、服务交付渠道、服务功能和非功能特征以及业务领域之间的相互联系。将从公共新闻语料库中提取的“事件”和“事件链”作为服务生态系统演化的触发器导入模型,并将演化关系引入模型,描绘演化轨迹。详细介绍了该模型的构成要素、关系和应用场景。与最先进的模型进行定性比较表明,我们的模型对服务生态系统的细粒度元素/关系具有更高的覆盖程度和更高的可解释性。本文还提供了补充资料,帮助理解如何基于外部数据构建模型。我们认为,这项工作为探索IoS的结构特征和演化规律奠定了坚实的基础。
A Novel Multi-layer Network Model for Service Ecosystems
Services flourish drastically along with the trend of Everything as a Service (EaaS). Over the years, services have become more and more interconnected to facilitate trans-boundary collaboration in business and technology levels for creating and delivering distinct new values to customers. This phenomenon is called Internet of Services (IoS). IoS arises and evolves in terms of tremendous discrete decisions made by individual service stakeholders, and its structure and evolution show quite similar characteristics of the ones of natural ecosystems. We propose a novel multi-layer network model to describe the static structure and dynamic evolution traces of service ecosystems. Different from traditional models which are usually focused on specific service types and granularity levels, our model comprehensively covers the interconnections between stakeholders, services delivery channels, service functional and non-functional features and business domains. “Event” and “event chains” which are extracted from public news corpus are imported into the model as triggers of service ecosystem evolution and evolutionary relations are introduced into the model delineate evolution traces. Elements, relations, and application scenarios of this model are introduced in detail. Qualitative comparison with state-of-the-art models shows that our model has a higher degree of coverage of fine-grained elements/relations of service ecosystem and higher interpretability. Supplementary materials are provided to help understand how to build the model based on external data. In our opinion, this work lays a solid base for the exploration of structural characteristics and evolution laws of IoS.