Large volumes of product reviews generated by online users have important strategic value for development. Prior studies often focus on the influence customers' purchasing decisions through word-of-mouth effect. However, little is known about how developers respond to these reviews. This study adopts a big data analytical approach investigate impact customer agility and subsequently performance. We develop singular decomposition-based semantic keyword similarity method quantify using...

Abstract In collaborative crowdsourcing communities for open innovation, users generate and submit ideas as idea co‐creators. Firms then select implement valuable new product development. Despite the popularity success of these innovation communities, relatively little is known about factors that determine implementation user‐generated ideas. Based on research individual creativity, we propose a conceptual model integrating users' previous experience, presentation characteristics feedback...

Maliciously false information (disinformation) can influence people's beliefs and behaviors with significant social economic implications. In this study, we examine news articles on crowd‐sourced digital platforms for financial markets. Assembling a unique dataset of that were investigated prosecuted by the Securities Exchange Commission, along propagation data such performance focal firm, develop well‐justified machine learning system to detect disinformation published media platforms. Our...

The emergence of generative artificial intelligence (AI) tools such as ChatGPT has substantially increased individuals' productivity. In this study, we adopt a difference-in-differences approach to analyze large dataset research preprints systematically examine whether the advent AI distinct effects on productivity male and female academic researchers. We find that after ChatGPT, increase in researchers is 6.4% higher than researchers, implying widening gap between them. then conduct survey...

Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from capture “crowd wisdom” begun play an important role in financial markets. Existing research confirms importance crowd wisdom stock predictions, but fails investigate factors influencing performance (that is, prediction accuracy). In order help improve performance, our strives impact...

An online review is composed of various information components (e.g., reviewer profile, rating, and text), which may have impacts on its user simultaneously. However, while there a growing interest in understanding the value reviews, potential interaction effects between different rarely been examined. This study aims to explore individual perception rating text hotel context. We conducted an analytical exercise using actual reviews collected from three major websites understand that took...

Abstract Project success is critical in the crowdfunding domain. Rather than existing project‐centric prediction methods, we propose a novel backer‐centric method. We identify each backer's preferences based on their pledge history and calculate cosine similarity between project as persuasibility. Finally, aggregate all backers' persuasibility to predict success. To validate our method, crawled data 183,886 projects launched during or before December 2014 Kickstarter, website. selected 4,922...

Abstract Establishing open innovation communities has evolved as an important product and development strategy for companies. Yet, the success of such relies on successful implementation many user‐submitted ideas. Although extant literature examined impact user experience idea characteristics implementation, little is known from information input perspective, example, feedback. Based overload theory knowledge content framework, we propose that amount types feedback have different effects...

The rise of inappropriate content (e.g., misinformation, spam, hate speech, etc.) has become a major concern for social media platforms. To deal with such challenges, platforms adopt various strategies to moderate the on their websites. This study focuses user bans, common but controversial moderation strategy that suspends rule-violating users from further participation platform predetermined period. Specifically, we investigate impacts bans banned users’ content-generating behavior (both...

This paper studies the information content of a subtle writing style, expression confidence. We use unsupervised machine learning to generate new lexicons for three aspects writer’s level confidence in expressing opinions: certainty, intensity expression, and emotional overstatement. Using them capture mutual fund managers’ letters shareholders, we show contains important about skill: underperforming managers with strong certainty significantly outperform other next six months, whereas top...

In this study, we investigate the problem of aggregating crowd opinions for decision making. The Wisdom Crowds (WoC) theory explains how should be aggregated in order to improve performance Crowd independence and a weighting mechanism are two important factors wisdom. However, most existing opinion aggregation methods fail build differential identifying expertise individuals appropriately accounting dependence when their judgments. We propose new model, namely CrowdIQ, that has accounts...