3,556 research outputs found

    Submitting tentative solutions for platform feedback in crowdsourcing contests: breaking network closure with boundary spanning for team performance

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    Purpose To obtain optimal deliverables, more and more crowdsourcing platforms allow contest teams to submit tentative solutions and update scores/rankings on public leaderboards. Such feedback-seeking behavior for progress benchmarking pertains to the team representation activity of boundary spanning. The literature on virtual team performance primarily focuses on team characteristics, among which network closure is generally considered a positive factor. This study further examines how boundary spanning helps mitigate the negative impact of network closure. Design/methodology/approach This study collected data of 9,793 teams in 246 contests from Kaggle.com. Negative binomial regression modeling and linear regression modeling are employed to investigate the relationships among network closure, boundary spanning and team performance in crowdsourcing contests. Findings Whereas network closure turns out to be a negative asset for virtual teams to seek platform feedback, boundary spanning mitigates its impact on team performance. On top of such a partial mediation, boundary spanning experience and previous contest performance serve as potential moderators. Practical implications The findings offer helpful implications for researchers and practitioners on how to break network closure and encourage boundary spanning with the establishment of facilitating structures in crowdsourcing contests. Originality/value The study advances the understanding of theoretical relationships among network closure, boundary spanning and team performance in crowdsourcing contests

    Understanding the Role of Goals in Competitive Crowdsourcing Project Selection

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    Tournament based crowdsourcing, in which multiple individuals or teams compete on given tasks and compensation is based on winning submissions, requires crowd members to carefully consider their choice of task and allocation of resources. In this paper we explore two factors that potentially impact crowdsourcing task selection, namely perceived ability and perceived competition. We further explore a moderating effect of goal orientation on task participation intention. Our results show a positive link between perceived ability and participation intention, and a negative link between perceived competition and participation intention. Both effects were found to be stronger for those with performance orientation than for those with mastery orientation. Our results provide an important insight for crowdsourcing platforms in terms of balancing demand and submissions for competition to ensure all tasks are fulfilled

    Knowledge metamodel for crowdsourcing innovation intermediaries

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    Open innovation is a hot topic in innovation management characterized by a new form of interacting and collaborating with the external environment of a company to innovate more successfully and with less costs. Chesbrough (2006) advocates that firms can and should use external ideas as well as those from their own R&D departments, and both internal and external paths to the market in order to advance their technology. Crowdsourcing innovation presents as a derivation of this new paradigm taking advantage of the Web 2.0 tools to generate new ideas through the heterogeneous knowledge available in the global network of individuals with easy access to information and technology. So, crowdsourcing innovation brokers facilitate the access to a vast open and global knowledge community, and provide support in integrating contributions, as well as managing and motivating the crowd participants. This paper presents a literature review of open innovation models and innovation intermediaries functions' and proposes a knowledge's metamodel for crowdsourcing innovation intermediaries.- (undefined)To the Foundation for Science and Technology and the Polytechnic Institute of Oporto for financial support (SFRH/BD/49263/2008) of this research project

    Investigating the Non-Linear Relationships in the Expectancy Theory: The Case of Crowdsourcing Marketplace

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    Crowdsourcing marketplace as a new platform for companies or individuals to source ideas or works from the public has become popular in the contemporary world. A key issue about the sustainability of this type of marketplace relies on the effort that problem solvers expend on the online tasks. However, the predictors of effort investment in the crowdsourcing context is rarely investigated. In this study, based on the expectancy theory which suggests the roles of reward valence, trust and self efficacy, we develop a research model to study the factors influencing effort. Further, the non-linear relationships between self efficacy and effort is proposed. Based on a field survey, we found that: (1) reward valence and trust positively influence effort; (2) when task complexity is high, there will be a convex relationship between self efficacy and effort; and (3) when task complexity is low, there will be a concave relationship between self efficacy and effort. Theoretical and practical implications are also discussed

    USER CREATIVITY IN CROWDSOURCING COMMUNITY: FROM EXTRINSIC MOTIVATION PERSPECTIVE

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    Lack of creative ideas is always the biggest challenge that firms are facing in their innovative activity (Leimeister et al. 2009), and firms are increasing use crowdsourcing to capture diversity ideas from external people. Unfortunately, these crowdsourcing activities can sometime lead to ideas with less creativity than those ideas generated by internal employees (Blohm et al. 2011; Boudreau 2012; Leimeister et al. 2009). This research investigates the effect of users’ extrinsic motivation on idea creativity within the crowdsourcing community. Based on self-determination theory, we propose that four types of extrinsic motivation will positively affect the creativity of ideas generated by crowdsourcing community. Through a survey of 202 participants in China biggest crowdsourcing community, we find our research model is generally supported. We further observe the significant moderating effects of promotion focus on the relationship between extrinsic motivation and creativity. Our research provides both theory and practice implication

    Divergent Innovation: Directing the Wisdom of Crowd to Tackle Societal Challenges

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    Crowdsourcing is acknowledged as a promising avenue for addressing societal challenges by drawing on the wisdom of the crowd to offer diverse solutions to complex problems. Advancing a new conceptual framework of ‘divergent innovation’ which delineates between topic and quality divergence as focal metrics of performance when crowdsourcing for solutions to societal challenges, this study investigates the impacts of four ideation stimuli on divergent innovation. These four stimuli include task description concreteness, resource richness, topic entropy, and judging criteria comprehensiveness. Empirical analysis based on data sourced from an online crowd-ideation platform reveals that task description concreteness negatively affects topic divergence but positively influences quality divergence, whereas resource richness positively affects topic divergence but negatively influences quality divergence. Additionally, the relationship between topic entropy and topic divergence is U-shaped, with no significant impact on quality divergence. These findings contribute to extant literature on crowdsourcing and offer invaluable insights for practitioners

    The Impact of Helping Others in Coopetitive Crowdsourcing Communities

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    Organizations are increasingly engaging the community through crowdsourcing platforms to evolve innovative solutions to challenging business problems. Participants on such platforms often simultaneously cooperate and compete with one another to earn top honors. This paper addresses the imperative to understand the dynamics of knowledge sharing in such a coopetitive environment. Specifically, our study relies on the conceptual foundations of social exchange and social capital theories to investigate how help rendered (e.g., exchanging ideas or sharing knowledge) by participants in an online coopetitive crowdsourcing setting affects their performance. Furthermore, the study examines the moderating effects of the intensity of competition. Results of our econometrics analyses suggest that help given in a highly competitive contest, as opposed to a less competitive one, is more likely to be reciprocated, but less likely to improve the contributor’s contest performance. In addition, our study found that help received by participants positively impacts their contest performance, and partially mediates the relationship between help rendered and contest performance. This research also provides insight into what motivates participants to share knowledge under conditions of coopetition. The findings of our study have strong implications for both theory and practice

    In Their Shoes: A Structured Analysis of Job Demands, Resources, Work Experiences, and Platform Commitment of Crowdworkers in China

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    Despite the growing interest in crowdsourcing, this new labor model has recently received severe criticism. The most important point of this criticism is that crowdworkers are often underpaid and overworked. This severely affects job satisfaction and productivity. Although there is a growing body of evidence exploring the work experiences of crowdworkers in various countries, there have been a very limited number of studies to the best of our knowledge exploring the work experiences of Chinese crowdworkers. In this paper we aim to address this gap. Based on a framework of well-established approaches, namely the Job Demands-Resources model, the Work Design Questionnaire, the Oldenburg Burnout Inventory, the Utrecht Work Engagement Scale, and the Organizational Commitment Questionnaire, we systematically study the work experiences of 289 crowdworkers who work for ZBJ.com - the most popular Chinese crowdsourcing platform. Our study examines these crowdworker experiences along four dimensions: (1) crowdsourcing job demands, (2) job resources available to the workers, (3) crowdwork experiences, and (4) platform commitment. Our results indicate significant differences across the four dimensions based on crowdworkers\u27 gender, education, income, job nature, and health condition. Further, they illustrate that different crowdworkers have different needs and threshold of demands and resources and that this plays a significant role in terms of moderating the crowdwork experience and platform commitment. Overall, our study sheds light to the work experiences of the Chinese crowdworkers and at the same time contributes to furthering understandings related to the work experiences of crowdworkers
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