Consumer product valuation and interorganizational collaboration and innovation in small manufacturing

本项目将解释消费者评级在小型制造企业如何选择合作伙伴中所起的作用，以及随着时间的推移，合作的最终模式如何塑造一个行业。合作是企业相互学习和创新的重要途径。与此同时，消费者通过评级平台（比如在线零售网站上的评级平台）表示对创新产品的认可。精酿行业是一个战略研究站点，用于研究小规模制造背景下的行业-消费者动态。在这个行业中，组织间协作是很常见的。这个行业还有一个消费者社区，他们在公共网站上积极地给产品打分。与许多行业的组织一样，小规模制造商的合作策略各不相同：有些公司与许多其他公司合作；多次与同一公司合作的；还有一些人只合作一次就再也不合作了。随着时间的推移，组织间协作的模式构建了行业。该项目将构建和分析来自两个产品评级网站的数据集，以模拟美国三个州制造商之间的合作网络。结合对数据集中随机抽样的组织成员的访谈，分析将显示消费者评级如何影响小规模制造商之间的合作决策，并最终塑造行业。研究结果将汇集并有助于经济社会学评估和组织科学合作方面的文献，并为管理者提供信息。关于合作及其预期结果的战略决策。本项目确定并解释了行业结构的一个关键机制：消费者评级和组织间合作之间的递归关系。当组织以一种非等级关系进行合作，以共享知识和资源，并以风险太大而无法独立完成的方式进行创新时，就会发生组织间协作。在企业选择与某些人合作的原因中，地位起着重要作用。消费者群体越来越多地利用在线平台对生产商和产品进行评级，创造了一种衡量公司和产品估值和地位的替代方法。本项目将通过确定和解释消费者评级在合作战略决策中的作用，汇集有关组织间合作和评估的文献。该项目的数据将来自2009年至2016年间对加利福尼亚州、科罗拉多州和伊利诺伊州三个州的小型制造业进行的混合方法研究。这些州被选为提供可靠的合作样本。时间框架反映了该行业在全国的指数级增长。定量数据将来自两个评级网站，这将提供合作的证据以及消费者对合作产生的产品的评估。对这些数据的分析将提供行业的动态网络模型以及企业之间地位的具体措施。这些数据将用从样本中的组织成员收集的主要数据进行补充。调查人员还将对随机样本进行关键线人访谈，以确定合作者选择背后的不可测量的地位和动机特征。

This project will explain the role that consumer ratings play in how small-scale manufacturing firms choose partners with whom to collaborate and how resultant patterns of collaboration shape an industry over time. Collaboration is an important way for firms to learn from one another and innovate. At the same time, consumers signal approval of innovations through ratings platforms, such as those found on online retail websites. The craft brewing industry is a strategic research site for examining such industry-consumer dynamics in the context of small-scale manufacturing. Interorganizational collaboration is common within this industry. This industry also has a community of consumers who actively rate products on public websites. Like organizations in many industries, small-scale manufactures vary in their strategies for collaborating: some collaborate with many other firms; others with the same firm repeatedly; still others collaborate once and never again. Over time, patterns of interorganizational collaboration structure industries. This project will construct and analyze a dataset from two product rating sites to model the network of collaborations among manufactures in three states in the U.S. Combined with interviews with a random sample of organizational members from the dataset, analyses will show how consumer ratings influence decisions to collaborate among small-scale manufactures and ultimately shape the industry. Findings will bring together and contribute to the literatures on valuation in economic sociology and collaboration in organization science as well as inform managers? strategic decisions regarding collaborations and their prospective outcomes. This project identifies and explains a key mechanism by which industries are structured: the recursive relationship between consumer ratings and interorganizational collaborations. Interorganizational collaboration takes place when organizations cooperate in a non-hierarchical relationship to share knowledge and resources and to innovate in ways that would be too risky to do independently. Status plays an important role in why firms choose certain others with whom to collaborate. Communities of consumers increasingly take advantage of online platforms to rate producers and products, creating an alternative measure of firm and product valuation and status. This project will bring together the literatures on interorganizational collaborations and valuation by determining and explaining the role of consumer ratings in strategic decisions about collaboration. Data for this project will come from a mixed methods study of the small manufacturing industry in three states: California, Colorado, and Illinois between 2009 and 2016. These states have been selected to provide robust samples of collaborations. The time frame reflects the exponential growth in the industry nationally. Quantitative data will come from two rating websites, which will provide evidence of collaborations along with consumer valuations of the products resulting from collaborations. Analyses of this data will provide dynamic network models of the industry as well as concrete measures of status among firms. This data will be supplemented with primary data collected from organizational members in the sample. Investigators will also conduct key informant interviews with a random sample to identify non-measurable features of status and motivations behind choices of collaborators.