【作者】 王姝；

【导师】 陈劲；

【作者基本信息】 浙江大学 ， 管理科学与工程， 2012， 博士

【摘要】 当众包(Crowdsourcing)模式开启了一个微观参与的时代,大众智慧日益凸显出商业价值,当互联网可通过云端计算(Cloud Computing)实现端到端的连接方式而搭建了大众参与的创新平台,实现了协同自组织的新型网络工作环境,互联网已不仅仅是机器数码联网而是人类大脑的联网,网络也已不仅仅是信息技术的承载者而且是知识社会智力成果交易、传播扩散、开发并共享的领域,开放的在线环境为实现对于个人潜能和个体价值的普遍再挖掘提供了平台。本文面对信息社会现实的技术条件和商业环境,根据网商在线平台的实际运作情况,分别从集中化和分散化两种观点,即哈佛大学教授Daniel Bell所提倡的“从宏观和组织的层面寻求解决后工业社会面临的生产和服务问题”和美国社会学家Alvin Toffler指明的“第三次浪潮使人类回到以个体分散经营为主要经济形式的社会”的角度,从资源协同、运营协同和价值协同三个维度解构众包中介服务平台的协同创新模式,并探究不同产业和任务类型对众包协同效果的调节作用,构建“众包平台服务——个体、组织协同——协同效果”的平台运作机制模型和利用大众群体智慧实现开放式创新途径,寻求避免平台“有市无场”的信息交换、并能够实现有效率知识服务之切实可行的方法和路径。主要研究内容和创新点包括：(1)探讨了如何通过网商众包商务平台使更多“半专业半业余”人力资源参与到智力资本交易中,并提供高质量的知识服务,促进个体隐性知识的显性化,实现知识的价值化。从维基创新、大众创新的视角,根据成就动机理论、客户价值理论、互联网进化论等理论观点,基于客户满意度(ACSI)模型、客户需求Kano模型、客户服务感知(5GAP)模型的基础,突破以单纯的专业能力作为衡量标准,而从众包模式“产消合一”(Prosumer)和用户创新(User Innovation)的角度探讨如何发掘个体潜能、开发个人价值的“金矿”,采取问卷调查的方式,了解客户在众包模式下所关心的价值因素,如何提升客户满意度、建立客户忠诚度,揭示按提高效率和降低成本的途径实现平台系统整体协同效果。(2)通过与传统组织形式的比较,根据Clayton Christensen(2003)基于传统RBV理论提出的“RPV模型”(Resource,Process,Value)的组织特点,结合Web2.0-Web3.0环境和云端技术等网络信息化平台工具,从面向服务的技术架构的视角分析了众包平台协同运作的具体体现：跨组织的网络结构；互补共生的运营方式；基于知识共享的自组织管理,让个体在协同创新的系统中找到参与的位置,并能够选择理想的参与度,以商业组件的方式参与到众包模式的协同运营过程。使每个社会单元通过系统协调找到相对优越化的生存空间,实现多个行为主体在信息相对透明的环境中实现协同自组织,形成多目标经济活动的次优组合,从盈利模式层面,探讨分析了个体与各利益相关者该如何通过协同的方式和途径创造群体价值,实现基于众包价值网络的“产消合一”服务体系,塑造众包数字化生存和信息时代全新的工作形态。(3)运用SPSS20.0和AMOS19.0统计分析工具验证了众包平台协同创新中“资源与能力-赢利模式-价值协同”的逻辑模型和结构函数关系,实证结果的分析中采用与作业成本法(ABC)进行对比分析的方式,通过引入众包过滤、创意质量评估、从口碑与在线信誉作为数字资本的角度,诠释了众包网站完整的数字服务体验。从众包、众滤和众播的角度总结了用户需求驱动创新的众包实现过程。即在新的大众参与的机制作用下,突破传统思维中以企业为主体的模式,基于客户价值主张(Customer Value Proposition)探讨了如何在开放的环境中促进个体实现价值的过程中实现平台和相关利益者的价值协同,设计者又是如何秉承“先民主,后集中”过滤并分享的态度,本文从创新质量、协同的效率和成本考察众包平台如何同时有效连接了创新与创新服务的供给与需求。本文系统地梳理了众包相关领域的文献和理论模型,通过国内外知名众包模式的威客网站多案例研究并进行案例间的对比分析,探索了改善平台运营效率的网商众包模式的具体协作实施方案。实现了从微观个体的价值主张到行业中观层次的协同来理解个体行为、组织结构和众包平台协同效果的研究尝试,从而补充了新兴众包商业模式的案例研究,丰富了众包协同创新的理论内容,拓展了研究视角和思路,把后现代组织的理论方法应用于网商众包协同的研究,从研究视角、理论观点、模型分析到方法运用实现了一定程度的创新,有助于众包新兴研究领域的理论建设和为网商实践建议提供参考。更多还原

【Abstract】 In the era of Crowdsourcing Innovation, the service role of information society in streamlining opportunities for construction permitting in intellectual capital transaction, Crowdsourcing Systems (CS) enlist a multitude of humans to help solve a wide variety of problems. Over the past decade, numerous such systems have appeared on the World-Wide Web.Some contents of the research have been argued that service innovations comprise unique attributes which distinguish them from resource collaboration, business operation or value creation, such as their intangible nature, inseparability, and enhanced interactivity between client and website firm (Chapman and Hyland,2003).As is typical business model for an emerging area, this effort has appeared under many names, including peer knowledge service, user-powered systems, user-generated content, collaborative systems, community systems, etc.Consequently, the researches do not restrict the type of collaboration nor the target problem. Rather, it view CS as "a general-purpose problem-solving method", a system is a Crowdsourcing platform if it enlists a crowd of humans to help solve a problem defined by the system owners or solution-wanted clients, and if in doing so, it addresses the following four fundamental challenges:how to recruit and retain users; what can users do; how to combine their inputs; and how to evaluate and select them.(1) Crowdsourcing, mass collaboration and co-creation are becoming increasingly important vehicles for clients looking to engage the voices of consumers with innovation or diffusion of innovation. At home and abroad at last count there were more than100Crowdsourcing platforms available for some kind of design or marketing work. And how to pick the right one is the key problem for clients. There are many factors to consider, from who is in a particular crowd to how talent is paid or how intellectual property is handled. Many times success will come from breaking a project into smaller pieces and tapping different crowds for the various different elements as well as for the platform selected(John Winsor,2009).(2) In the open and collaborative innovation framework of (Chesbrough,2003) This application of our model is the first in what is intended to be a series of empirical applications, The approach has, probably, led to some progress with respect to the mainstream analysis of collaborative innovation. However, in order to delve deeper into the collaborative innovation process, and to capture its complexity, one needs to include other aspects and features in addition to those of individual and organization.Consequently, we do not restrict the type of collaboration nor the target problem. Rather, we view Crowdsourcing System as a general-purpose problem-solving method. As a system that is a Crowdsourcing System if it enlists a crowd of humans to help solve a problem, and if in doing so, it addresses the following fundamental challenges:(3) In the case of an intangible service, the ability to provide a service and its quality depends on "the ability to implement and organise the various competences required which is why, in certain services, the design of organisation systems, and collaborative innovation in that area, is so important". This model takes into account the interactions among human, technology, organizational and value proposition "inputs"; behavior of individuals and groups; and "outcomes" of all partners in Crowdsourcing progress. In a survey of intangible business service, it is found that external sourcing of knowledge, especially from customers and competitors, positively affected both the probability and extent of open innovation, for participants, while in-house innovation intensity had no discernible effect.Crowdsourcing empowers followers which include platform owner and clients. As the RPV (Resource, Process, Value) for Crowdsourcing program continues, we expect that academic probe discovery efforts will have an increasingly high impact in the collaborative innovation of website platform service.更多还原