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Top1. Introduction
To generate superior business performance from innovation, companies must unleash their innovation and knowledge streams to drive new growth, and openly leverage untapped external knowledge to unlock new revenue and business opportunities. Nowadays, innovation crowdsourcing communities are increasingly used to lead companies to breakthrough business advancements and transformations (Chesbrough, 2019). Thanks to technological leaps, it is now possible for companies to tap into the collective intelligence of online crowds to expand their innovation capabilities and portfolio (Canh, Liem, Thu, & Khuong, 2019; Cheng et al., 2020). As a result, a growing number of companies are now outsourcing the process of generating and evaluating innovations and new ideas to online crowds from diverse backgrounds to mitigate the risk of sticking to the known and overcome traditional product and service development by R&D departments (Daradkeh, 2021b). Innovation crowdsourcing communities such as the Microsoft Power BI community, Tableau community, and Qlik community serve as intermediaries to elicit new innovations and solutions from the crowd of experts, customers, developers, and technical evangelists for business intelligence (BI) and analytics technologies and tools (Daradkeh, 2019, 2021c; Halawani, Soh, & Halawani, 2022; Zhou, 2022).
Previous research on innovation crowdsourcing has emphasized the intrinsic value of using online communities to create, redesign, validate, and ultimately sustain innovative ideas and solutions (Bi, Liu, & Usman, 2017; Bogers et al., 2017; Boon & Edler, 2018). Thus, various crowdsourcing mechanisms have been advocated to shape and improve the process and quality of innovation. These mechanisms include the use of social networks that allow users to communicate and share interests and/or activities, the formation of collaborative groups that allow ideators to easily develop their own ideas and create solutions together, and finally the organization of ideation activities that include a mix of individual and various collaborative groups (Q. Liu, Du, Hong, Fan, & Wu, 2020; X. Liu, Wang, Fan, & Zhang, 2020; Muller & Peres, 2019). In most cases, however, simply creating new innovations is not enough to achieve successful innovation crowdsourcing results. Moreover, innovation crowdsourcing is typically the first phase of an innovation crowdsourcing process. Collaborative innovation crowdsourcing also requires continuous crowd engagement to refine and improve innovations already created and identify innovative ideas and solutions that deserve further attention and implementation (Luo, Lan, Luo, & Li, 2021). Together, these innovation activities are referred to as innovation crowdsourcing mechanisms (Majchrzak & Malhotra, 2020; Qin & Liang, 2019; Wu & Gong, 2019).