English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Research on crowdfunding success that incorporates CATA (computer-aided textanalysis) is quickly advancing to the big leagues (e.g., Parhankangas andRenko, 2017; Anglin et al., 2018; Moss et al., 2018) and is often theoreticallybased on information asymmetry, social capital, signaling or a combinationthereof. Yet, current papers that explore crowdfunding success criteria fail totake advantage of the full breadth of signals available and only very few suchpapers examine technology projects. In this paper, we compare and contrast thestrength of the entrepreneur's textual success signals to project backerswithin this category. Based on a random sample of 1,049 technology projectscollected from Kickstarter, we evaluate textual information not only fromproject titles and descriptions but also from video subtitles. We find thatincorporating subtitle information increases the variance explained by therespective models and therefore their predictive capability for fundingsuccess. By expanding the information landscape, our work advances the fieldand paves the way for more fine-grained studies of success signals incrowdfunding and therefore for an improved understanding of investordecision-making in the crowd.

It's all in the (Sub-)title? Expanding Signal Evaluation in Crowdfunding Research