中国企业嵌入全球价值链的决策演变分析

Analysis on the Evolution of Chinese Enterprises’Decision of Embedding into Global Value Chain

产业升级对于推动我国现代化产业体系及社会主义现代化国家建设至关重要。1992年,施振荣先生提出微笑曲线理论,其是世界产业链分工的具体表现,是产业附加价值高低的客观划分,是企业参与全球竞争形态的意识导向,更是企业加快产业升级与转型的战略驱动。现有研究表明,产业升级与转型和管理者的风险偏好与升级预期紧密关联。受此影响,以往中国企业在参与全球价值链活动过程中,常常进入产业升级风险系数最小、期望值最大的生产加工环节。随着企业的持续发展,其逐渐意识到并承认产业升级的迫切性与重要性。机器学习以更精确、更全面的算法优化了管理者的决策环境,使其能够最大程度地规避不确定性风险,在微笑曲线两端谋求更为精准的价值增长点,在产业升级过程中充分提升生命活力与竞争力。研究发现,在新兴技术支持下,管理者决策环境经由“穷举数据集-略举数据集-极举数据集”特征转变。决策准则经由“完全理性-有限理性”向“智慧理性”演进。进一步分析,从组织学习到机器学习,实质上是管理者在价值链决策过程中实现由“有限理性决策者”向“智慧理性决策者”演变的过程,其所决策事项的最终结果也将由“满意解”向“相对最优解”进阶。

Industrial upgrading is very important to promote the modernization of our industrial system and the construction of modern socialist country.In 1992,Mr.Shi Zhenrong put forward the smile curve theory,which is the concrete manifestation of the division of the world industrial chain,the objective division of the level of industrial added value,the ideological guidance for enterprises to participate in the global competition,and the strategic drive for enterprises to accelerate industrial upgrading and transformation.Existing studies show that industrial upgrading and transformation are closely related to the managers’risk preferences and upgrading expectations.In the past,when Chinese enterprises participated in global value chain activities,they often entered the production and processing links,which has the lowest risk coefficient and the highest expectation of industrial upgrading.With the continuous development of enterprises,they gradually realize and admit the urgency and importance of industrial upgrading.Machine learning optimizes the decision-making environment of managers with more accurate and comprehensive algorithms,enabling them to avoid uncertainty risks to the greatest extent,which enables them to seek more accurate value growth points at both ends of the smile curve.Their vitality and competitiveness are fully enhanced in the process of industrial upgrading.It is found that,with the support of emerging technologies,the decision-making environment of managers changes through the pattern of“exhaustive data-set-slight data-set-extreme data-set”.The decision criterion evolves from“complete rationality-bounded rationality”to“intelligent rationality”.Further analysis shows that the transition from organizational learning to machine learning,in essence,is the transition of managers from“bounded rational decision maker”to“intelligent rational decision maker”in the value chain decision-making process.The final result of the decision will advance from“satisfactory solution”to“relative optimal solution”.