Location

Online

Event Website

https://hicss.hawaii.edu/

Start Date

3-1-2023 12:00 AM

End Date

7-1-2023 12:00 AM

Description

Today's digital era facilitates the rise of crowdfunding markets by allowing entrepreneurs to seek funding directly from crowds. Crowdfunding, as IT-enabled disintermediation, lowers entry barriers for crowds to invest in business projects and entrepreneurs to obtain funding, yet may exacerbate information asymmetry and absorb investor attention to process information about the potential projects. We develop a model wherein investors with limited attention aggregate personalized information about (reward-based) crowdfunding projects and conduct comparative analyses on how rises in investors’ unit attention cost (associated with greater distractions) affect investor attention, investment decisions, and crowdfunding performance. We then exploit a novel measure of distraction---news pressure---to test the effects of distraction on investor engagement and crowdfunding performance empirically, and the results support our model predictions.

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Jan 3rd, 12:00 AM Jan 7th, 12:00 AM

Investor Attention and Crowdfunding Performance

Online

Today's digital era facilitates the rise of crowdfunding markets by allowing entrepreneurs to seek funding directly from crowds. Crowdfunding, as IT-enabled disintermediation, lowers entry barriers for crowds to invest in business projects and entrepreneurs to obtain funding, yet may exacerbate information asymmetry and absorb investor attention to process information about the potential projects. We develop a model wherein investors with limited attention aggregate personalized information about (reward-based) crowdfunding projects and conduct comparative analyses on how rises in investors’ unit attention cost (associated with greater distractions) affect investor attention, investment decisions, and crowdfunding performance. We then exploit a novel measure of distraction---news pressure---to test the effects of distraction on investor engagement and crowdfunding performance empirically, and the results support our model predictions.

https://aisel.aisnet.org/hicss-56/os/sites/4