CHS: Small: Blending the Virtual and the Physical: Understanding and Designing Crowd-Based Open Innovation Systems for Physical Products

公司经常求助于外部贡献者来履行重要职能，包括“开放式创新”方案，在这种方案中，公司创造挑战或竞争，外部人群工作者开发并提交创造性想法。 该项目将研究围绕复杂物理产品的基于人群的开放式创新的一些开放性问题，这些问题构成了超越软件和简单设计背景的挑战，而开放式创新之前已经研究过。 这些问题包括：（1）外部贡献者如何成功地将他们的贡献与他们不属于的组织保持一致，并为他们无法轻松访问的物理环境提出设计？ (2)内部员工如何获取、导入和调整假设、流程和工具可能完全不同的外部贡献者的输入？(3)如何设计系统和实践来促进外部贡献者的创造性工作并有效地融入公司的流程？ 为了解决这些问题，项目团队将与一家使用先进工程技术开发和制造新车的公司密切合作，在几次创新挑战中观察该公司和相关的众包工作者社区。 他们还将为以工作的未来为中心的本科课程开发开放式创新材料，既教授工作中的发现，又为学生提供开发项目的实践经验，该项目将创造性的人群输入纳入团队的工作。团队将为每个挑战收集大量数据来源。 从群众平台本身，他们将收集所有的在线讨论，从挑战的开始到获胜想法的选择，群众和公司对这些想法的评估，以及围绕开发获胜设计的后续技术工作。 他们还将与在线社区成员进行访谈，试图了解为什么合作形成和解散，为什么有些设计最终没有提交给比赛，社区成员如何看待反馈，以及获奖者和非获奖者如何与获奖设计进行互动。 同时，他们将观察和采访合作伙伴公司的活动，参加与正在研究的挑战相关的具体会议和每周例会（概述挑战本身之外的相关讨论和决策）。 大部分分析将涉及应用社交网络和开放编码技术来跟踪公司内外参与者之间的互动模式和知识流，并研究这些模式和知识流如何在挑战过程中演变。 这些，沿着基于理论的访谈和观察数据分析，将突出关键的规律模式（如非文本工件的表示和操作）和重要的差距（如需要提供适当但不敏感或瘫痪的上下文水平），可能会受益于更好的工具支持。

Firms often turn to external contributors to perform vital functions, including "open innovation" scenarios in which firms create challenges or competitions where external crowd workers develop and submit creative ideas. This project will study a number of open questions around crowd-based open innovation around complex physical products, which pose challenges above and beyond the software and simple design contexts in which open innovation has been studied before. These include (1) How do external contributors successfully align their contribution to an organization of which they are not a part and propose designs for a physical context to which they do not have easy access? (2) How do internal employees source, import, and adapt the inputs of external contributors whose assumptions, processes and tools might be entirely different? (3) How can systems and practices be designed to facilitate creative work from external contributors and effective integration into the the firm's processes? To address these questions the project team will work closely with a firm that uses advanced engineering technologies to develop and manufacture new vehicles, observing the firm and related crowdworker communities during several innovation challenges. They will also develop material on open innovation for an undergraduate course centered the future of work that both teaches findings from the work and gives students hands-on experience developing a project that incorporates creative crowd input into the group's work.The team will collect a number of sources of data for each challenge. From the crowd platform itself, they will collect all of the online discussions from the inception of the challenge to the choice of winning ideas, evaluation of those ideas by both the crowd and the firm, and the subsequent technical work around developing the winning designs. They will also conduct interviews with online community members, seeking to understand why collaborations form and disband, why some designs are not ultimately submitted to the competition, how community members perceive feedback, and how both winners and non-winners engage with the winning designs. In parallel, they will observe and interview activity at their partner firm, attending both specific meetings related to the challenges being studied and general weekly meetings (to give an overview of relevant discussions and decisions outside of the challenge itself). Much of the analysis will involve applying social network and open coding techniques to track interaction patterns and knowledge flows between actors both inside and outside the firm, looking at how these evolve through the course of the challenge. These, along with grounded theory-based analysis of interviews and observational data, will highlight both key regular patterns (such as the representation and manipulation of non-textual artifacts) and important gaps (such as the need to provide an appropriate but not sensitive or paralyzing level of context) that might benefit from better tool support.