User Behavior Investigations Based On Collaboration Engineering In Idea Crowdsourcing Community

In the digital era,mass innovation driven by the development of information and communication technologies has broke organizational boundaries,and plays a critical role in business process optimization and organizational innovative competitiveness improvement.By making the best of collective intelligence,online idea crowdsourcing communities provide external wisdom on innovative solutions for organizational internal problems or challenges.Online idea crowdsourcing community is a digital platform for mass collaboration that provides solutions for open innovative problems or challenges.The new business model of crowdsourcing has attracted wide attention from both academia and the industries.Existing work on crowdsourcing community mostly focused on motivation factors investigation,crowdsourcing task design and reward structure,and the matching mechanisms between both sides in crowdsourcing communities,few research focus on the effect of intervention and facilitation on idea generation and selection quality.However,idea generation quality and idea selection quality are both important for the success of crowdsourcing effort.Therefore,the topic of idea generation and selection is worthy of investigation.This research explores the core question of ‘how to improve idea generation quality and idea selection quality in online idea crowdsourcing community'.Based on information processing theory,cognitive load theory,schema theory and crowdsourcing engagement theory,this study explores mass collaboration related user behaviors in online idea crowdsourcing community.Specifically,referring to the collaboration patterns denoted by Collaboration Engineering,this research focus on idea selection and idea generation behaviors in idea crowdsourcing community.This study was conducted in the combination of qualitative case study and laboratory experiments.Firstly,I conducted qualitative analysis on three online idea crowdsourcing communities to better understand the effect of platform design and facilitation mechanisms on user collaborative behaviors,including OpenIDEO,Jovoto and IdeaScale.This study investigated multiple existing idea selection interventions and idea generation facilitation.Through cross-case examinations,this researchsummarized the merits and demerits of the current idea selection interventions and idea generation facilitations,and offers several thoughts on how to better facilitate crowd collaboration and improve idea creativity in crowdsourcing communities.Secondly,I designed a 2x2x2 between group design,and conducted two rounds of laboratory experiments using ThinkTank.Content analysis was used to measure the idea generation quality and idea convergence quality.Three input variables respectively are task complexity,idea presentation and instructional guidance.The goal of the experiments is to explore which interventions could decrease intrinsic cognitive load and extraneous cognitive load,improve germane cognitive load,and thus facilitate idea generation quality,idea selection quality,participants' satisfaction with process,and participants' satisfaction with outcome from the perspective of cognitive load theory and information processing theory.During the experiment,the subjects were randomly divided into 8 groups to finish the task.Participants were asked to fill in the questionnaires as soon as they finalized the tasks.I conducted manipulation check with the questionnaire data.Through two rounds of experiment,I got 264 valid samples that has been used to test the research models.Both experiment data and survey data were used to test three research models.Model 1: The direct effect of intrinsic cognitive load,extraneous cognitive load and germane cognitive load on idea generation quality,idea selection quality and perceived satisfaction.Results show that the higher germane cognitive load,the better idea selection quality but the worse idea generation quality.Both intrinsic cognitive load and extraneous cognitive load have negative influence on satisfaction with process.Satisfaction with outcome was negatively determined by intrinsic cognitive load and positively influenced by germane cognitive load.Model 2: An in-depth investigation on the relationships between germane cognitive load and idea selection quality by testing the moderator role of knowledge self-efficacy,goal clarity and need for cognition.Results show that the positive influence of germane cognitive load on idea selection quality was positively moderated by knowledge self-efficacy,goal clarity and need for cognition.Model 3: An in-depth investigation on the relationships between germane cognitive load and idea generation quality by testing the mediator role of emotional engagement,cognitive engagement and behavioral engagement.This research finds that the influence of germane cognitive load on idea generation quality was partially mediated by emotional engagement and behavioral engagement.Compared with existing studies,this research enriches previous research in the following perspectives.Firstly,traditional crowdsourcing studies mostly focused on crowdsourcing competition platforms,crowdsourcing micro-task platforms and crowdsourcing logo design platforms,this study emphasizes on the open innovative idea crowdsourcing community.Online crowds dynamically collaborate in idea crowdsourcing community.Therefore,the research context has its novelty.Secondly,online crowds generate a lot of ideas that are diversed in terms of quality and categories,effective idea selection and evaluation mechanisms are important on organizational innovative management.This research set out to investigate the influencing mechanisms of idea selection quality from cognitive psychology perspective.Thirdly,this paper investigates the suitability of a new idea generation method,conceptual combination,in idea crowdsourcing community context.This research explores the influencing mechanism of germane cognitive load on idea generation quality from emotional engagement,cognitive engagement and behavioral engagement perspectives.Overall,this research conducted user behavioral investigations in idea crowdsourcing community from cognitive load perspective,the research findings contribute to the idea selection and idea generation mechanisms,and provide implications for both crowdsourcing community regulators and organizational managers to better provide facilitation for idea creativity.Since idea crowdsourcing community is still in its nascent stage in the open innovation era,there is still lack of systematic theoretical investigations on idea generation and selection behaviors.In future research,I aim to conduct further in-depth investigations on the collaboration related user behaviors in crowdsourcing communities.