The social process of innovation: The role of novelty and social cues in idea evaluation
The social process of innovation: The role of novelty and social cues in idea evaluation
批准号:
411843692
负责人:
Professor Dr. Linus Dahlander, Ph.D.
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2018
资助国家:
德国
项目状态:
已结题
起止时间:
2017-12-31 至 2022-12-31
中文摘要
拟议中的研究项目旨在推动对创新的研究。我们希望促进对创新过程中一个重要但尚未得到充分研究的阶段的理解:对创新建议的评估。为了理解为什么有些想法获得了支持,而另一些却没有,我们将重点关注(1)想法新颖性的作用和(2)社会线索在想法评估过程中的作用。由于我们打算为管理者如何评估想法提供因果证据,我们将在两个组织中进行两个实地实验,在两个组织中,员工产生创新想法,高级管理者评估这些想法并决定它们的实施。我们的研究项目将结合定性和定量方法,分三步进行。第一步是在两个组织内部进行定性预研究,我们将在其中进行实地实验。我们进行预研究是为了更好地了解公司的创新过程,这将有助于我们设计有效和适当的实验干预措施。第二步,我们将收集员工的想法,并通过主题建模来衡量他们的新颖性;一种源自计算机科学的文本分析方法,可用于根据描述一个想法的实际文本来衡量想法的新颖性。在第三步,我们将进行实地实验,分析新颖性和社会线索在想法评估过程中的作用。为此,我们将实验性地改变管理者评估建议的条件。虽然评价和选择创意已经成为成功创新的一个关键方面,但对创意评价过程的研究仍在发展中,远未完成。在提出的研究中,我们试图在三个方面推进文献。首先,通过实地实验研究设计,我们为创意新颖性和社会线索对创意评价的影响提供了因果证据。大多数先前的研究都提出了基于相关性的证据,因此没有达到这个“黄金标准”。其次,我们通过基于描述一个想法的实际文本来衡量想法的新颖性,这在方法论上做出了重要贡献。早期的研究在很大程度上依赖于使用预先建立的图式(如专利类别)来衡量组合新颖性。相比之下,我们将使用主题建模来派生基于内容的新颖性度量。第三,我们通过平行研究社会关系和内容的影响来推进创新研究。鉴于网络创新研究因缺乏对内容的考虑而受到批评,内容研究与社会结构脱节,我们寻求将社会关系与内容结合起来。拟议的项目将推进关于想法新颖性和社会线索的理论,并将通过将计算机科学方法与能够进行因果推理的现场实验设计相结合,推动研究前沿。
英文摘要
The proposed research project seeks to push the study of innovation. We look to advance the understanding of an important, yet understudied, phase of the innovation process: the evaluation of ideas proposed for innovation. To understand why some ideas gain support while others do not, we will focus on (1) the role of idea novelty and (2) the role of social cues in the idea evaluation process. As we intend to provide causal evidence on how managers evaluate ideas, we will conduct two field experiments within two organizations where employees generate ideas for innovation and senior managers evaluate them and decide on their implementation.Our research project will combine qualitative and quantitative methods and will proceed in three steps. The first step is a qualitative pre-study within the two organizations in which we will conduct the field experiments. We conduct the pre-study to gain a better contextual understanding of the companies’ innovation processes, and it will help us to design effective and appropriate experimental interventions. In the second step, we will collect the employees’ ideas and measure their novelty by topic modeling; a text-analytic method stemming from computer science that can be used to measure idea novelty based on the actual text describing an idea. In the third step, we will conduct the field experiments that analyze the role of novelty and social cues in the idea evaluation process. To do so, we will experimentally vary the conditions under which managers evaluate the proposed ideas.While evaluating and selecting ideas has become a key aspect of successful innovation, research on the idea evaluation process is still developing and far from complete. With the proposed research we seek to advance the literature on three accounts. First, the field experimental research design enables us to provide causal evidence on the effect of idea novelty and social cues on idea evaluation. Most of prior research has presented evidence based on correlations and has thus fallen short of this “gold standard.” Second, we make an important methodological contribution by measuring idea novelty based on the actual text describing an idea. Earlier research has largely relied on measures of combinatorial novelty using pre-established schemata, such as patent classes. In contrast, we will employ topic modeling to derive a content-based novelty measure. Third, we advance innovation research by studying the impact of social relationships and content in parallel. Whereas network research on innovation has been criticized for lacking consideration for content, and content studies have been disconnected from social structure, we seek to integrate social relations and content.The proposed project will advance theory on idea novelty and social cues, and it will push the research frontier by combining methods from computer science with field experimental designs enabling causal inference.
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