The right kind of people: Characteristics of successful ideators' online behaviour

Abstract

Open online idea calls are an increasingly popular way to crowdsource ideas. Such calls tend to attract a diverse crowd who suggest a variety of ideas. To detect the most promising from this mass of ideas, we identify online behavioural characteristics of successful ideators, i.e. those who suggest ideas that are implemented. Our study is based on binary logistic regression analyses of a dataset from a call for ideas crowdsourced by the city of Munich. We found that characteristics linked to suggesting possible solutions and to showing positive attention towards other ideas are key features of how successful ideators behave online. We also found that the first is a characteristic of ideators who are likely to suggest an idea that is implemented but not novel. The latter is a characteristic of ideators who are likely to suggest an idea that is implemented and novel. Paying attention to other ideas before suggesting one's own and providing constructive input to other ideas are not found to be characteristic for successful ideators. The findings contribute to a better understanding of successful ideators' online behaviour and thereby open up new opportunities for the detection of ideas that the idea‐seeker wants to implement.

The effects of crowdsourcing contribution type and temporal consistency on new product development success

“…Descriptive statistics from our sample reveal that these participants were significantly more likely to make scoring than commenting contributions. This insight is consistent with prior studies that have also observed a higher volume of scoring versus commenting activity across various crowdsourcing platforms (Hoornaert et al, 2017;Schemmann et al, 2017). However, aside from a single, small-scale study (Schemmann et al, 2017), prior research investigating the impact of participants' own evaluative contributions on submission success has concentrated almost solely on commenting activity and has virtually ignored the potential influence of scoring on submission success.…”

“…A growing body of crowdsourcing research has examined how participants' own creative and evaluative contributions can provide them with new knowledge, insights, and resources and thereby enhance their NPD performance (Bayus, 2013;Hoornaert et al, 2017;Zhu et al, 2019;Zhang et al, 2020). With few exceptions, (e.g., Schemmann et al, 2017;Zhu et al, 2019) most recent studies have used web scraping techniques to create expansive data sets comprising archival data on the The effects of crowdsourcing contribution type and temporal consistency R&D Management 52, 1, 2022 135 creative and evaluative contributions of thousands of crowdsourcing participants (Bayus, 2013;Li et al, 2016;Hoornaert et al, 2017). Our paper adopts a similar approach and derives its findings from an empirical analysis of archival data encompassing 10,722 participants, who submitted creative contributions on Threadless.com.…”

“…A parallel research stream has investigated how crowdsourcing participant's own evaluative contributions influence their submission success. For example, Chen et al (2019) and Schemmann et al (2017) find no relationship between a participant's commenting activity and submission success. In contrast, other studies find that individuals who make a large number of comments are more likely to create a commercializable new product concept (Schemmann et al, 2016;Hoornaert et al, 2017).…”

“…Although scoring does not allow participants to interact with one another, it plays an essential role in helping firms select the most promising crowdsourcing submissions (Ogawa and Piller, 2006;Martineau and Arsel, 2017). Participants who engage in scoring may also be more likely to develop new, NPD-relevant knowledge (Schemmann et al, 2017). Specifically, when participants score others' submissions, they are exposed to their peers' original ideas and can gain insights into the types of submissions that are popular with the crowd.…”

Collective firm-internal online idea development

“…However, they also pose new managerial challenges to firms, and this is also the case for online idea management programs. Specifically, the collective online efforts have generally resulted in an increased number of novel ideas (Hoornaert et al, 2017;Schemmann et al, 2017), but this does not necessarily transform into successful innovation outcomes (Chan et al, 2018). Recent studies highlight the need to better understand the collective process taking place after innovation ideas have been generated (Beretta, 2019;Berg, 2014;Zhu et al, 2019), and then in particular the idea development process (Hoornaert et al, 2017;Ogink and Dong, 2019) when crowdsourcing principles are employed inside firms (Malhotra et al, 2017).…”