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In crowdsourcing contests, the capabilities and performance of individual workers (solvers) determine whether seeker firms can obtain satisfactory solutions from the platform. It is noted that solvers may learn such skills in crowdsourcing from doing (experiential learning) or observing (vicarious learning). However, it remains unclear if such learning can be materialized into improved performance considering the unique settings of crowdsourcing contests. The study aims to understand how experiential learning and vicarious learning enhance solver performance and under what conditions.

The model was tested using survey and archival data from 261 solvers on a large contest platform in China.

Results support the premise that experiential learning and vicarious learning separately and jointly enhance solver performance. Moreover, perceived task uncertainty strengthens the effect of vicarious learning but weakens the effect of experiential learning, whereas perceived competition uncertainty weakens the effect of vicarious learning.

The current study enriches the understanding of the impacts of experiential learning and vicarious learning and offers a more nuanced understanding of the conditions under which solvers can reap the performance benefits from learning in crowdsourcing contests. The study also provides practical insights into enhancing solver performance under perceived task uncertainty and perceived competition uncertainty.

Since their inception in late 2007, the Qualified Domestic Institutional Investor (QDII) funds, which help Chinese investors to invest in foreign capital markets, have experienced significant portfolio losses and persistent fund outflows. While these losses are large in absolute terms, QDII funds, on average, performed better than Chinese A-share funds, but slightly worse than a group of foreign mutual funds. Our study focuses on the QDII industry, and asks three interrelated questions: (1) why have there been large fund outflows from the industry? (2) what explains QDII funds’ poor performance? and (3) why have QDII funds been so heavily exposed to the Hong Kong market? Our empirical analysis shows that the persistent capital outflows were primarily a result of disappointing fund performance. This poor performance can, in turn, be explained by the deficiency of knowledge required of QDII fund managers to successfully invest in foreign capital markets and manage global portfolios. Finally, our study goes some way to explain the phenomenon of QDII funds’ large asset allocation in the Hong Kong market. This ‘Hong Kong bias’ is shown to be consistent with the well-documented ‘home bias’ behaviour in cross-border portfolio investment, but is greatly exacerbated by the lack of global investing experience of QDII managers.

Crowdsourcing platforms have emerged as an innovative way to generate ideas and solving problems. However, promoting sustained participation among crowdworkers is an ongoing challenge for most crowdsourcing platform providers. Drawing on self-determination theory, this study investigates the impacts of job autonomy on crowdworkers' sustained participation intention.

A survey of 212 crowdworkers from a leading crowdsourcing platform in China was conducted to empirically validate the model.

The empirical results lead to several key findings. First, the taxonomy of job autonomy in crowdsourcing contains three archetypes: work-scheduling autonomy, work-task autonomy, and work-method autonomy. Second, work-scheduling autonomy and work-method autonomy have more significant positive effects on temporal value than work-task autonomy, and this increase in temporal value increases crowdworkers' sustained participation intention. Third, work-task autonomy exerts a stronger influence on hedonic value than work-scheduling autonomy or work-method autonomy, and this increase in hedonic value also increases crowdworkers' sustained participation intention.

This study extends the crowdsourcing literature by examining the formation of crowdworkers' sustained participation and highlighting the role of differential effects of multidimensional job autonomy on crowdworkers' sustained participation. We believe that this study provides actionable insights into measures that promote crowdworkers' sustained participation in the crowdsourcing platform.