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The purpose of this paper is to aim mainly at social public decision-making problems, studies the corresponding relationship between different voting rule combinations and the final results, and discusses the quantitative relationships between group intelligence (final votes) and individual intelligence (everyone) to defend democracy under the circumstance of rapid development of network technology, and crowd intelligence becomes more complicated and universal.

After summarizing the crowd co-decisions of related studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations.

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations.

This paper will help researchers solve the social public decision-making problems in large-scale simulations.

This paper aims to provide a comprehensive view of the different competition-based approaches that policymakers can exploit to foster external knowledge search and their positioning among innovation policy measures. A growing number of companies have implemented initiatives to access external knowledge to increase their innovativeness, consistently with the open innovation paradigm. Competition-based approaches have received increasing attention by the private sector as a way to access external knowledge. However, despite their potential role as innovation policy measures, a limited attention has been devoted so far to investigate them from the policymakers’ perspective.

To this aim, a two-stage empirical analysis has been carried out to develop a taxonomy of competition-based approaches. The first stage leveraged a multiple case study methodology including a sample of 20 competition-based approaches, while the second one leveraged interviews with Italian and European key informants.

This paper proposes a novel taxonomy including eight competition-based approaches, which differ among each other in terms of policy strategy, scope breadth and output required. Moreover, this paper enriches a well-established taxonomy of innovation policy instruments with the identified competition-based approaches.

This study contributes to the current debate on innovation policy by providing a taxonomy that includes eight competition-based approaches that can be exploited by policymakers to foster external knowledge search as well as their positioning among the innovation policy instruments. The taxonomy will hopefully support policymakers in identifying of the most suitable instruments in the light of their policy strategy and objectives.

The purpose of this paper is to study the operation mechanism of the ecosystem of crowd innovation space. Though the crowd innovation space is a new product of China's innovation-driven strategy, there are some barriers in operation. So, this problem is worthy of study.

In this study, data were obtained through four-month field investigation and semistructured interview, then classified and analyzed through grounded theory, because grounded theory is conducive to the exploration and discovery of new theories.

This study finds that the relationship between makerspace and entrepreneurs is strong social relational embeddedness. The relationship between crowd innovation space and governments and investment institutions is economic relational embeddedness. Under these social network ties, entrepreneurs, crowd innovation space, social investment institutions and so on can interact directly with each other to different degrees, carry out value cocreation activities and improve the benefits of all elements in the ecosystem and the ecosystem itself.

This study researches the operation mechanism of crowd innovation space ecosystem and identifies the ties between various elements in the ecosystem on the perspective of social network, which is conducive to improve the self-generating capacity of crowd innovation space and enhance the success rate of entrepreneurship.

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 unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.

This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.

Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.

This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.

This paper analyzes how the distribution and structure of employees' attention influence idea survival in an organizational internal crowdsourcing session.

Data from an online internal crowdsourcing session carried out within a multinational company with headquarters in Sweden were used to explore how idea attention influenced idea survival.

Our findings indicate that the positive relationship between attention allocation and idea survival is mediated by idea appreciation, i.e. positive comments and suggestions that employees provide in response to ideas. In addition, we find that competition for attention negatively moderates the relationship between idea attention and positive comments. Finally, our results indicate that ideas are more likely to survive if they are submitted earlier in the crowdsourcing process and when the elapsed time since previously posted ideas in the session is longer.

This study provides organizers of internal crowdsourcing sessions with new insights about factors influencing idea survival and about potential systematic biases in idea selection due to timing and competition between ideas.

This paper contributes to the literature highlighting the relevance of attention-based theory in the context of crowd-based creativity and innovation management.

This paper aims to contribute to the scientific debate concerning the impact of equity crowdfunding on the performance of crowdfunded firms after campaigning. To this aim, the purpose of this paper is to investigate the relationship between the characteristics of the campaign and the subsequent firm innovativeness.

This study adopts a quantitative research approach to evaluate if the entrepreneurial choices affecting the characteristics of the equity crowdfunding campaigns have an impact on the post-campaign firm innovativeness.

The results of the models show that the campaign characteristics have a direct impact on the firm innovativeness, both in terms of offering and communication and the campaign performance.

This paper presents one of the first studies to investigate the relationship between the choice of campaign characteristics and the post-campaign firm innovativeness. As such, the study contributes to both the literature concerning start-up innovation and the literature about the impact of equity crowdfunding.

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.

This paper aims to investigate the intersection between crowdfunding (CF), open innovation (OI) and responsible innovation (RI) and identify the emerging trends and gaps in research and new paths for CF research in the future. In addition, this paper proposes a conceptual framework and propositions.

This paper is structured in line with the systematic literature review protocol. After reading all the titles, keywords and abstracts, 172 papers focused on OI and RI were selected for this research. Finally, 27 papers that are based on dimensions related to responsible OI were selected for the study.

Due to CF's multidisciplinary nature, the scientific literature on the role of CF in endorsing responsible OI for shared value co-creation appears fragmented and redundant. Several emerging trends and gaps of research and new paths for CF research in the future arise regarding research methodology and theoretical perspective.

To the best of the authors' knowledge, this is the first study investigating the intersection between CF OI and RI.

This study furthers one’s understanding of the motivations of the crowdfunding crowd by empirically examining critical factors that influence the crowd's decision to support a crowdfunding project.

Backer's comments from a sample of the top 100 most funded technology product projects on KickStarter were collected. A latent Dirichlet allocation (LDA) analysis strategy was adopted to investigate critical motivational factors. Three experts mapped those factors to the known theoretical constructs of social exchange theory (SET).

Although backers are motivated by value, they are also motivated by far less tangible social factors including trust and a feeling of psychological ownership. Findings suggest that the crowd is far more than a passive group of investors or customers and should be viewed as participatory stakeholders. This study serves as guidance for project owners hoping to motivate the crowd and for future investigators examining backer motivations in other types of crowdsourcing projects.

Online chatter in the form of user-generated comments is an excellent data source for researchers to mine for value and meaning.

Given strong feelings of psychological ownership, project owners should actively engage the crowd and solicit the crowd for advice and help in order to motivate them.

The study presents the first empirical exploration of backer motivations using LDA guided by theory and the knowledge of experts. A framework of latent motivational factors is proposed.