Search results

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 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 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.

Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development.

Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis.

The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses.

This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas.

The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.

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.

Working conditions on many digital work platforms often contribute to the grand challenge of establishing decent work. While research has examined the public regulation of platform work and worker resistance, little is known about private regulatory models. In this paper, we document the development of the “Crowdwork Agreement” forged between platforms and a trade union in the relatively young German crowdworking field. We find that existing templates played an important role in the process of negotiating this new institutional infrastructure, despite the radically new work context. While the platforms drew on the corporate social responsibility template of voluntary self-regulation via a code of conduct focusing on procedural aspects of decent platform work (i.e., improving work conditions and processes), the union contributed a traditional social partnership template emphasizing accountability, parity and distributive matters. The trade union’s approach prevailed in terms of accountability and parity mechanisms, while the platforms were able to uphold the mostly procedural character of their template. This compromise is reflected in many formal and informal interactions, themselves characteristic of a social partnership approach. Our study contributes to research on institutional infrastructures in emerging fields and their role in addressing grand challenges.

The purpose of this study is to provide a review of the emergent literature to advance the current understanding of the business model (BM) concept in a context in which more than one actor is actively involved in the development and delivery of a joint offer based on information and communication technologies.

The paper uses a systematic literature review approach. The review is based on 25 systematically selected publications published from 2000 to 2018 and retrieved from bibliographic databases and through a process of snowballing.

The authors found several alternative conceptualizations of a BM at a network level, which highlighted different elements as core components. Based on this, authors’ findings suggest the literature has a fragmented view of what the BM concept entails at a network level, and of which actors are relevant. Conversely, there is a consensus that a single-firm view is inadequate for describing and studying joint value architectures because of its inability to consider all involved actors and their activities and resources. Therefore, a network-oriented view, as a relational aggregator, is seen as a possible way forward.

The study contributes to the current understanding of a BM concept at a network level and suggests three viewpoints from which to interpret value architectures at different levels of analysis: single-firm view, dyadic-level view and network-oriented view. Furthermore, the authors highlight several gaps to be studied and provide avenues for future research opportunities for scholars.