中外战略合作与中国企业创新——弱势方学习理论及实证研究

Sino-Overseas Strategic Alliance and Incremental Innovation among Chinese Enterprises—Testing a Model of Organizational Learning from the Partners with Weaker Power

摘要: 为实现从“中国制造”到“中国创造”的战略转型，中国需要通过各种方式增强自己的创新能力。这些方式的其中之一，是通过与外国企业的合作，实现渐进式创新。本项目以中国汽车行业为研究对象，探讨中国机械制造业的渐进式创新问题。依据资源依赖理论和近年的实地研究，我们提出一个新的理论模型——弱势方学习模型。这里我们将弱势者定义为在关键资源上依赖程度较高的一方，中国汽车企业今天仍可视为弱势方，因为他们在技术这种关键资源上要依赖西方。通过发展弱势方学习理论及实证研究，我们研究中国汽车制造业应如何通过学习增强自己的创新能力。通过发展弱势方学习理论及实证研究，我们研究中国汽车制造业应如何通过学习增强自己的创新能力。为了验证这一理论模型，我们计划从实地问卷调查及公开资料收集两个方面开展研究。并运用当今最先进的数理统计方法及电脑进行分析，验证所提出的理论模型, 并发展弱势方学习的新理论。

Abstract: To realize the transformation from a made-in-China strategy to a created-in-China one, China needs to adopt all feasible and effective approaches to increase its capability of innovation. One of such approaches is incremental innovation through cooperation with foreign enterprises. This research project deals with this issue by focusing on Chinese auto industry. Based on the resource-dependency theory (Pfeffer & Salancik, 1978) and our field work in recent years, we propose a new theoretical model, i.e., a theory of organizational learning by strategic partners with weaker power. Consistent with resource-dependency theory, we define strategic partners with weaker power (SPWP) as the partner or party that has heavy dependency on other partner(s) for key resource in the alliance. According to this definition, the majority of Chinese auto producers today can be seen as SPWP because of their heavy dependence on advanced technology from abroad, which is a piece of key resources for competitive advantage in the Chinese market today and is also mainly controlled by foreign partners. Through developing such a theory of organizational learning by SPWP and conducting related empirical studies, we should understand better how the Chinese firms, as SPWP, can achieve incremental innovation through its own way of organizational learning. To test the validities of our theoretical model, we plan to collect empirical data through both questionnaire surveys and coding panel data from publicly-available sources. After that, we will apply the most advanced statistic technology and computer software today to conduct data analyses so that we can test our theoretical hypotheses and develop the new theory.