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Evolution can be easily observed in nature world, and this phenomenon is a research hotspot no matter in natural science or social science. In crowd science and technology, evolutionary phenomenon exists also among many agents in crowd network systems. This kind of phenomenon is named as crowd co-evolutionary, which cannot be easily studied by most existing methods for its nonlinearity. This paper aims to proposes a novel simulation framework for co-evolution to discover improvements and behaviors of intelligent agents in crowd network systems.

This paper introduces a novel simulation framework for crowd co-evolutions. There are three roles and one scene in the crowd. The scene represented by a band-right to a ringless diagram. The three roles are unit, advisor and monitor. Units find path in the scene. Advisors give advice to units. Monitors supervise units’ behavior in the scene. Building a network among these three kinds member, influencing individual relationships through information exchange, and finally enable the individual to find the optimal path in the scene.

Through this simulation framework, one can record the behavior of an individual in a group, the reasons for the individual's behavior and the changes in the relationships of others in the group that cause the individual to do so. The speed at which an individual finds the optimal path can reflect the advantages and disadvantages of the relationship change function.

The framework provides a new way to study the evolution of inter-individual relationships in crowd networks. This framework takes the first-person perspective of members of the crowd-sourced network as the starting point. Through this framework, the user can design relationship evolution methods and mathematical models for the members of different roles, so as to verify that the level of public intelligence of the crowd network is actually the essence of the rationality of the membership relationship.

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.

To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.

The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.

This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.

Crowd network systems have been deemed as a promising mode of modern service industry and future economic society, and taking crowd network as the research object and exploring its operation mechanism and laws is of great significance for realizing the effective governance of the government and the rapid development of economy, avoiding social chaos and mutation. Because crowd network is a large-scale, dynamic and diversified online deep interconnection, its most results cannot be observed in real world, and it cannot be carried out in accordance with traditional way, simulation is of great importance to put forward related research. To solve above problems, this paper aims to propose a simulation architecture based on the characteristics of crowd network and to verify the feasibility of this architecture through a simulation example.

This paper adopts a data-driven architecture by deeply analyzing existing large-scale simulation architectures and proposes a novel reflective memory-based architecture for crowd network simulations. In this paper, the architecture is analyzed from three aspects: implementation framework, functional architecture and implementation architecture. The proposed architecture adopts a general structure to decouple related work in a harmonious way and gets support for reflection storage by connecting to different devices via reflection memory card. Several toolkits for system implementation are designed and connected by data-driven files (DDF), and these XML files constitute a persistent storage layer. To improve the credibility of simulations, VV&A (verification, validation and accreditation) is introduced into the architecture to verify the accuracy of simulation system executions.

Implementation framework introduces the scenes, methods and toolkits involved in the whole simulation architecture construction process. Functional architecture adopts a general structure to decouple related work in a harmonious way. In the implementation architecture, several toolkits for system implementation are designed, which are connected by DDF, and these XML files constitute a persistent storage layer. Crowd network simulations obtain the support of reflective memory by connecting the reflective memory cards on different devices and connect the interfaces of relevant simulation software to complete the corresponding function call. Meanwhile, to improve the credibility of simulations, VV&A is introduced into the architecture to verify the accuracy of simulation system executions.

This paper proposes a novel reflective memory-based architecture for crowd network simulations. Reflective memory is adopted as share memory within given simulation execution in this architecture; communication efficiency and capability have greatly improved by this share memory-based architecture. This paper adopts a data-driven architecture; the architecture mainly relies on XML files to drive the entire simulation process, and XML files have strong readability and do not need special software to read.

The synthetic application and interaction of/between the internet, Internet of Things, cloud computing, big data, Industry 4.0 and other new patterns and new technologies shall breed future Web-based industrial operation system and social operation management patterns, manifesting as a crowd cyber eco-system composed of multiple interconnected intelligent agents (enterprises, individuals and governmental agencies) and its dynamic behaviors. This paper aims to explore the basic principles and laws of such a system and its behavior.

The authors propose the concepts of crowd science and engineering (CSE) and expound its main content, thus forming a research framework of theories and methodologies of crowd science.

CSE is expected to substantially promote the formation and development of crowd science and thus lay a foundation for the advancement of Web-based industrial operation system and social operation management patterns.

This paper is the first one to propose the concepts of CSE, which lights the beacon for the future research in this area.

The main purpose of this research is to construct a generalized set of innovation processes that occur at the ecosystem level based on the academic research. The study analyzes the cultural and creativity-driven over-the-top (OTT) platform that encompasses diverse network of ecosystem members by utilizing the four cooperation practices.

This study begins with the literature review that discusses various topics related to ecosystem (e.g. service innovation, innovative ecosystem). Then, this study introduces a new conceptual framework that describes how cooperations occur in the ecosystem. Finally, a qualitative and explorative case study of the OTT platforms in the global context is conducted.

The application of the framework reveals how co-innovative business ecosystems demonstrate co-evolution through different structures and directions. An ecosystem can evolve by incorporating other industries (i.e. horizontal growth or broadening strategy) to deepen and broaden the industry integration.

As an explorative approach that opens the discussion on how co-innovation and co-evolution occur at the ecosystem level, particularly in the culture and creativity-driven industry, the value of this research extends to other similar industries where diverse actors such as technology firms, Internet firms, direct consumers, government and even the society impact the type of product and service and shape the evolution of the entire ecosystem.

The ubiquity of digitally intermediated interactions is changing the ways in which social interaction creates the cognitive and institutional underpinnings of new markets. Logics that define markets used to be localized, but they now emerge from crowds that span – and persist – across time and space. This article builds a theory of how crowds emerge and evolve in a way that influences the emergence of shared logics and helps explain why some markets are viable while others are not. What is revealed is that a crowd has a hidden niche structure that determines the fate of a new market.

The purpose of this paper is to better understand and study the architecture and system characteristics of the underlying support platform for crowd system, by recognizing the characteristics of service internet is similar to the coordination characteristics between the massive units in the underlying platform of crowd system and studying the form, nature and guidelines of the service internet.

This paper points out the connection between the underlying support platform of crowd system and service internet, describes the framework and ideas for researching service internet and then proposes key technologies and solutions for service internet architecture and system characteristics.

The research unit in the underlying support platform of crowd system can be regarded as a service unit. Therefore, the platform can also be regarded as service internet to some extent. The ideas and technical approaches for the study of service internet’s form, criteria and characteristics are also provided.

According to this paper, relevant staff can be guided to better build the underlying support platform of crowd system. And it can provide a highly robust and sustainable platform for research studies of crowd science and engineering in the future.

This research investigates the nature of regulatory-focused effectuation (as the basis of entrepreneurial behavior) in absorptive capacity development for open innovation implementation, the role of crowds or communities management practices in the effectuation-based open innovation process, and open innovation performance as the output of the open innovation process in digital multi-sided platform (MSP) startups context.

In order to verify the hypothesis, the researcher conducts a quantitative study that is based on a self-administered questionnaire and employs the PLS-SEM approach. The sample comprises of 70 Indonesian digital MSP businesses that have been operational for at least three years and have used open innovation approaches with their audiences, communities or complementors.

The research findings imply that there is a connection between promotion-focused effectuation and the open innovation process. This connection is particularly strong when it comes to the incorporation of absorptive capacity and crowds or communities management practices. On the other hand, prevention-focused effectuation shows insignificant effect toward open innovation process in digital MSP startups context.

The research findings imply that with limited resources and experiences, young entrepreneurs can still implement open innovation strategy for their digital MSP platform through effectuation principles that leverage the external resources from digital platform ecosystem members.

In digital MSP startups context that perform promotion-based effectuation principles, innovation performance can be achieved by analyzing new insight, transforming the existing activities with the new insight, creating new offering afterward, as well as strengthening crowds or communities management practices through co-creation activities with platform ecosystem members that may lead into new business model.

The originality of this work is to make a contribution to the literature on strategic entrepreneurship by describing the phenomena of the paradox of resource-based theory; adopting open innovation strategy under constrained initial resources and capabilities scenario.

This paper aims to review the challenges of urban foresight via an analytical method: apply this to the city demonstrations on the UK Foresight Future of Cities: and explore the implications for ways forward.

The methodology is based on the principles of co-evolutionary complex systems, a newly developed toolkit of “synergistic mapping and design”, and its application in a “synergy foresight” method.

The UK Foresight Future of Cities is work in progress, but some early lessons are emerging – the need for transparency in foresight method – and the wider context of strategic policy intelligence.

The paper has practical recommendations, and a set of propositions, (under active discussion in 2015), which are based on the analysis.

The paper aims to demonstrate an application of “synergy foresight” with wide benefits for cities and the communities within them.