Seeking Certainty in Uncertainty: Could Enterprises’ Intelligent Transformation Help to Reduce the Perception of Trade Policy Uncertainty?
Song Huasheng1,2,3, Cao Tingting2, Zhou Jianjun2,3
1.CRPE, Zhejiang University, Hangzhou 310058, China 2.School of Economics, Zhejiang University, Hangzhou 310058, China 3.Institute of State System Research, Zhejiang University,Hangzhou 310058, China
Abstract：Currently, Chinese firms face the primary challenge of trade policy uncertainty (TPU) as a significant external risk. The occurrence of events such as the US-China trade war and the Russia-Ukraine conflict has instigated anti-globalization sentiments, leading to increased trade barriers and protectionist measures. This intricate international economic landscape severely impacts the operational landscape of Chinese firms. The perception of TPU refers to the extent to which a firm feels the impact of TPU. Increased TPU generally affects firm decision-making by disrupting corporate expectations, thereby negatively impacting corporate operations. The emergence of artificial intelligence has not only spearheaded a new wave of technological revolution but also provided enterprises with new strategic opportunities to address TPU. Through intelligent operations and big data predictions, enterprises can achieve intelligent transformation, which not only reduces costs but also enhances the efficiency of various stages in the operational process, thereby improving the transparency and certainty of the business environment.Therefore, the pivotal research question emerges: How can firms achieve intelligent transformation to approach certainty amid an environment of uncertainty? Utilizing the annual reports of public listed firms from 2012 to 2020, this study employs textual analysis and machine learning tools to quantify the perception of TPU and the degree of intelligent transformation, both of which withstand rigorous effectiveness tests. Subsequently, the study empirically tests the impact of company intelligent transformation on the companies’ perception of TPU and unravels its underlying mechanisms. Empirical evidence indicates that intelligent transformation of firms can significantly reduce the perceived TPU, which has been consistently upheld through various robustness checks. To mitigate potential endogeneity concerns, the study adopts instrumental variable two-stage least-squares regression estimator and leverages exogenous policy shocks as quasi-natural experiments, ensuring that the identified relationship can be credibly interpreted as causal. The mechanism analysis further elucidates that intelligent transformation achieves this reduction by cost-saving effects, such as diminishing adjustment cost and information asymmetry, and by efficiency enhancement effect, including improving efficiency of organizational collaboration, management decision, production and marketing. Heterogeneity analysis suggests that the effect of intelligence transformation on the perception of TPU is more pronounced for non-state-owned companies, those firms in technology-intensive industries, as well as firms situated in the eastern and southern regions of China. Extensive analysis further underscore that intelligent transformation can effectively enhance the positive affective tendencies of management, which is important for improving the competitive advantage of firms and facilitating market expansion. Furthermore, the effect of intelligent transformation on the perception of TPU is more prominent for firms with higher risk transfer ability.The main contributions of this study are as follows first, this study refines the indicators for the perception of TPU and the degree of intelligent transformation at the firm level, thereby addressing the existing measurement inadequacies; second, it enriches the understanding of the effects of company intelligent transformation from the perspective of TPU. Furthermore, we also expand the analysis framework of the influencing factors and countermeasures of the perception of TPU, providing valuable insights for firms in managing the risks associated with TPU; third, in practical terms, the research assists firms in reformulate strategies for intelligent transformation to achieve “cost reduction and efficiency improvement”, thereby helping the firms to better cope with the uncertainties of trade policy and mitigate the negative impacts. On macro level, the study elucidates the essential role of intelligent transformation, enabling China to draw on its preeminent position in the field of artificial intelligence, facilitating the smooth transition of foreign trade dynamics, achieving strategic goals for stable foreign trade, and propelling high-quality development in the international trade.
宋华盛, 曹婷婷, 周建军. 在不确定性中寻找确定性：企业智能化转型能降低贸易政策不确定性感知吗？[J]. 浙江大学学报(人文社会科学版), 2025, 55(1): 5-25.
Song Huasheng, Cao Tingting, Zhou Jianjun. Seeking Certainty in Uncertainty: Could Enterprises’ Intelligent Transformation Help to Reduce the Perception of Trade Policy Uncertainty?. JOURNAL OF ZHEJIANG UNIVERSITY, 2025, 55(1): 5-25.
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