Convergence in Crossover Service

With the development of crossover in the modern service industry (MSI), various traditional boundaries have been broken, and the cross-integration of services has led to the need for crossover services. A crossover service is the deep convergence and model innovation of services that cross the boundaries of different industries, organizations, and value chains, aiming to provide users with high quality and high value services. The key to achieving crossover service is convergence, which includes the deep multidimensional convergence of patterns, requirement design, runtime environment, quality, and value.

A service pattern is the overall description of a service-coordination mechanism, participant interaction pattern, and data/resource/value-allocation scenario in a business service. For crossover services, service patterns are service-delivery methods that support the realization of business models. Service patterns describe how service enterprises provide services in the industrial chain and the methods of cross-domain participant collaboration, including value acquisition, resource allocation, data transmission, activity organization, and stakeholder collaboration. In short, a service pattern is the implementation of the service business model in the context of the service industry. Crossover service pattern modeling refers to the description of the participants, workflows, data, resources, and value in crossover services. Thus, service pattern computation concerns the simulation, evaluation, and deep convergence of multiple patterns to analyze and improve service efficiency, reduce costs, and increase the competitiveness of crossover service providers. Service patterns are usually the most important parts of enterprise service implementation as well as key factors that determine the competitiveness of enterprises and the development of the MSI. To combine resources and services from different fields, achieve upstream and downstream integration, and clarify the value flow, the effective and comprehensive service pattern computation theory and methodology are necessary.

Crossover services often span multiple industry boundaries, and user requirements are typically diverse and personalized, leading to many challenges in requirements analysis and system design. In essence, crossover services are developed to meet user requirements across multiple domains. An approach of requirements convergence-analysis, design and evolution is proposed to support the convergence process in service requirements analysis and design.

Although enterprises in the crossover service ecosystem open their own internal services, they also need to invoke open services from the other service participants to collaborate and complete the complex BP. The collaboration of services between crossover businesses requires microservices to invoke each other. The myriad microservices, which are distributed across multiple organizations, form a heterogeneous, complex, and distributed service-invocation and -operation network, which we call a service network. Crossover service collaboration must shield this heterogeneous environment and provide a virtual transparent and virtual unified convergence environment for service governance.

Under the background of deep convergences in crossover services, the start point and end point of multi-participant collaboration are all to achieve the win-win of service values. In crossover services, service providers in different domains give full play to their advantages of service capability and quality to create rich service values, which are further transmitted and transformed based on complex service collaboration patterns and business interaction processes, and finally realize the capability complementarity and value co-creation of multi-stakeholders. At the same time, it also provides consumers with more abundant service functions and more reliable service value guarantees. Therefore, the focus of this chapter is on how to fully utilize the service capabilities of multiple participants and maximize the service value/quality of multiple stakeholders. The main challenges of crossover services optimization are the complex dependencies between multiple participants and their differentiated service expectations. This chapter focuses on the three stages of service design, configuration and operation, and gives a total of 7 optimization methods that define different optimization objectives and give different solutions for the global crossover service, local multi-participants and consumers.

Crossover services breach the boundaries of different industries, organizations, and value chains to achieve in-depth convergence and pattern innovation, providing users with multidimensional, high-quality, and value-rich services. It is not only the inevitable development of technology, but also an important innovation for the development of the MSI. Currently, crossover services are developing and innovating very rapidly. However, due to the lack of effective methods and tools, this development still has many problems. The practice of crossover service integration without adequate theoretical guidance hinders the innovative development of the MSI. With the establishment of theoretical and technical bases, research has been conducted to solve crossover service convergence. The previous chapters of this book build a theoretical and technical system from multiple dimensions of the service pattern, service requirement, service environment, and service value/quality. However, further research is required to determine how to apply these methods systematically to industrial development and provide an effective aid to industrial innovation. Based on existing theories and methods, we have developed a design and support platform for crossover service convergence. With an awareness of the nature of crossover services and theoretical approaches to crossover service convergence, this platform enables the convergence of crossover service patterns, requirements, networks, qualities, and values. It consists of four modules to support the design, analysis, deployment, and optimization of crossover services.