Enhancement mechanism of corporate green investment efficiency from the perspective of group decision making

Abstract

Corporate green investment is a crucial initiative for promoting high-quality economic development. However, vague decision-making scenarios imply that large-scale green investment entails significant economic risks such as resource misallocation and homogenized development. This paper develops a theoretical framework grounded in collective intelligence and organizational information processing theories. Using a research sample comprising Chinese listed companies from 2010 to 2020, we conduct an empirical analysis employing fixed-effects models and system GMM estimators, and measure green investment efficiency using the Richardson model. We find that the impact of peer effects on green investment efficiency is conditional. Under conditions of effective information-processing capabilities, peer effects significantly reduce the degree of green investment inefficiency. Peer effects may influence investment efficiency through two pathways: "blind imitation" and “rational information learning”. Only the latter effectively improves resource allocation, and this enhancing effect primarily depends on the support of enterprises' internal information transparency, information acquisition capability, and information analysis capability. Heterogeneity analysis further reveals that followers' imitation of leading enterprises does not necessarily enhance efficiency: simple replication of green-investment-scale leaders yields no significant benefits, whereas learning from corporate social responsibility (CSR) leaders significantly optimizes investment efficiency. Moderation analysis indicates that enhancing information transparency, information acquisition capability, and information analysis capability significantly strengthens the positive impact of peer effects on green investment efficiency. From the dual perspectives of government regulation and corporate governance, we propose targeted policy recommendations for optimizing group decision-making regarding green investments and improving investment efficiency.