M&A goodwill, information asymmetry and stock price crash risk

The collapse of stock prices have a huge negative impact on financial markets and the real economy, the mechanism and prevention methods of stock market crashes have become the focus of academic attention. This article takes Chinese A-share listed companies from 2008 to 2016 as samples and investigates the impact of M&A goodwill on the risk of stock price crashes. The study finds that, compared with non-goodwill companies, companies with goodwill have a greater risk of future stock price crashes; with the increase of goodwill value (GW), the risk of future stock price crashes increases significantly. Further research shows that the GW affects the risk of stock price crashes through information asymmetry at the corporate and market levels. This article not only deepens the research on the factors influencing the risk of stock price crashes, but also has great significance in understanding the role of M&A goodwill in the capital market and how to prevent stock price crashes and promote the orderly development of the capital market

Knowledge spillovers along the sustainable supply chain of China's listed companies: The role of long-term orientation

A new industrial development paradigm, the Fifth Industrial Revolution or ‘Industry 5.0’ is expected to humanise green technological innovation (GTI), social resilience, and sustainable development of industrial ecosystems. Emphasising the supplier-customer interaction, ‘Industry 5.0’ is technological revolution, which is a value-driven initiative that drives knowledge spillovers along the sustainable supply chain (SSC). In this context, enterprises are incorporating more GTI activities into their partners’ SSC strategies. This study employs samples of China's A-share listed companies covering the period from 2010 to 2021 to examine the spillover effects between customers’ GTI and suppliers total factor productivity (TFP). Both GTI and TFP indicators are important representations of ‘Industry 5.0’, with our major concerning on the enhancement of supplier's long-term orientation (LTO). We calculated TFP by the Olley-Pakes and Levinsohn-Petrin methods, dividing GTI indicators into three levels: substantial green technological innovation (SGTI), non-substantial green technological innovation (NGTI), and overall green technological innovation (OGTI). Our empirical results show that 1) Customer's GTI contributes to supplier's TFP, and supplier's LTO including environmental, social & governance (ESG) performance, and R&D input can strengthen this beneficial link; 2) customer's NGTI represents a significant differentiation in comparison with SGTI, where R&D investment weakens the positive relationship between customer's NGTI and supplier's TFP; 3) heterogeneity analysis indicates that the spillovers of customer's GTI on supplier's TFP are more pronounced among state-owned enterprises, high-tech enterprises, and non-polluting enterprises. Notably, the connectedness demonstrates dynamic patterns through 2SLS and GMM regressions, highlighting the importance of enterprises' SSC and LTO being the shock transmitters to their TFP. Our study is prone to benefit lawmakers, regulators, and firm executives responsible for analysing and assessing the SSC, providing more policy implications with future prospects for sustainable transformation in the upcoming ‘Industry 5.0’ era