The impact of governmental COVID‐19 measures on manufacturers' stock market valuations: The role of labor intensity and operational slack

When does digital merger and acquisition create shareholder value? An empirical investigation in the Chinese context

In China, acquiring firms are increasingly focused on the immediate financial returns that digital mergers and acquisitions (DM&A) can help them achieve in the stock market, but there is little literature that examines which acquiring firms achieve greater returns. Based on signaling theory, this study conceptualizes DM&A announcements as signals released by the acquiring firms to the stock market and explores the factors influencing the Chinese stock market's reaction to such signals. This research empirically investigates potential influencing factors using a short-term event methodology together with regression analysis based on the data collected in China's Shanghai and Shenzhen stock markets during 2012-2021. The research finds that the Chinese stock market reacts more positively to DM&A announcements for acquiring firms with high executive shareholdings, high executive openness, strong digital innovation capabilities, and in regions with higher levels of investor protection. This study is the first attempt to explore the factors influencing the stock market's response to DM&A in the Chinese context.

Carbon reduction attention and financial market stress: A network spillover analysis based on quantile VAR modeling

As climate change intensifies, attention to the issue of carbon emission reduction has gradually increased. This research constructs a complete set of indicators of carbon reduction attention and financial market stress and applies the quantile VAR method to calculate the volatility spillover between carbon reduction attention and financial market stress. We conclude with the following. Firstly, a relatively close volatility spillover association exists between carbon reduction attention and financial market stress. In the research system, carbon reduction attention mainly assumes the role of information receiver. Additionally, when examining the spillover status in different quantiles, the total spillover level shows an irregular "bowl" structure, while the net spillover level of each variable has different shapes. Secondly, the dynamic spillover level in the extreme quantile condition maintains a connectivity range of 60-80%, significantly higher than that of the median condition. Finally, this study finds two sets of significant complementary spillovers within the system, namely, "carbon reduction attention - crude oil market stress" and "stock market stress - real estate market stress", which provide investors with an opportunity to explore the potential of the carbon reduction attention and real estate market stress in the future.

Analyzing the varied impact of COVID-19 on stock markets: A comparative study of low- and high-infection-rate countries

The global health crisis initiated by the COVID-19 pandemic triggered unparalleled economic upheavals. In this comprehensive study of 16 countries categorized by their infection rates, we scrutinize the impact of a range of variables on stock market indices and calculate four critical ratios derived from those variables. Our regression analyses reveal striking differences in how the variables influenced stock indices in countries with low and high infection rates. Notably, in countries with low infection rates, all variables exhibited significant effects on stock returns. An increase in infection numbers and fatalities correlated with greater stock market declines, underscoring the market's sensitivity to the health and economic risks posed by the pandemic. Recovery and testing rates also displayed positive associations with stock returns, reflecting investor optimism concerning potential recovery scenarios. Conversely, nations grappling with high infection rates experienced notably weaker effects from these variables. Although fatalities had a negative impact on stock indices, other factors, including recoveries, infections, and testing rates, did not result in significant effects. This suggests the likelihood that markets in high-infection countries had likely factored pandemic conditions into their pricing, thereby reducing the immediate impact of these metrics on stock returns. Our findings underscore the intricacies of the COVID-19 pandemic's impact on stock markets and highlight the importance of tailored strategies and policies for distinct country categories. This study offers valuable insights for policymakers and investors navigating financial markets during global health crises and preparing for future epidemics.

Blockchain-enabled supply chain operations and financing: the perspective of expectancy theory

Purpose

This study examines the cognitive factors of adopting blockchain technology in various supply chain scenarios and its role in reframing the distinctive values of supply chain financing. Based on expectancy theory, this study explores the different profiles underlying the components of expectancy, valence and instrumentality.

Design/methodology/approach

This is a multiple-case study of four Fintech companies using blockchain technology to promote the performance of supply chain operations and financing.

Findings

The results show that blockchain-enabled supply chain finance (BSCF) can be classified into four scenarios based on the scope and purpose of blockchain technology applications. The success of BSCF depends on the profiles of BSCF expectancy (the recognized purpose and scope of BSCF), instrumentality (identified blockchain attributes and other technology combinations) and valence (the perceived distinctive value of BSCF). Blockchain attributes help solve information asymmetry problems and enhance financing performance in two ways: one is supporting transparency, traceability and verification of transmissions and the other entails facilitating a transformation to new business models.

Originality/value

This research applies a new perspective based on expectancy theory to study how cognitive factors affect Fintech companies' blockchain solutions under a given supply chain operation or financing activity. It explains the behavioral antecedents for applying blockchain technology, the situations appropriate for the different roles of blockchain technology and the profiles for realizing the value of blockchain technology.

The impact of corporate social responsibility decoupling on financial performance: the role of customer structure and operational slack

Purpose

Corporate social responsibility (CSR) decoupling indicates a misalignment between how firms report CSR and what firms actually practice with respect to CSR. The purpose of this paper is to examine the relationship between CSR decoupling and financial performance and the factors affecting this relationship.

Design/methodology/approach

This paper collects and combines secondary panel data from multiple sources of Chinese listed firms from 2008 to 2020 to test the direct impact of CSR decoupling on firms’ financial performance and the moderating role of customer structure and operational slack.

Findings

This paper finds that CSR decoupling is negatively associated with firms’ financial performance. These findings further suggest that the negative relationship can be suppressed by customer stability and operational slack, but amplified by customer concentration. These conclusions remain robust to alternate measures of independent and dependent variables and narrower samples.

Originality/value

In the literature, the effect of CSR on firms’ financial performance is inconclusive. This is the first study to examine the impact of CSR decoupling on firms’ financial performance and the factors affecting this relationship. This paper contributes to the CSR decoupling literature from an operations and supply chain management perspective.

Supply chain learning and performance: a meta-analysis

Purpose

This paper aims to provide a comprehensive understanding of the supply chain learning (SCL)–performance relationship based on the existing empirical evidence.

Design/methodology/approach

We sampled 54 empirical studies on the SCL–performance relationship. We proposed a conceptual research framework and adopted a meta-analytical approach to analyse the SCL–performance relationship.

Findings

The results of the meta-analysis confirm the positive effects of SCL on the performance of both firms and supply chains. In addition, building on the knowledge-based view, we found that learning from customers has a stronger positive effect on performance than does learning from suppliers, while joint learning has a stronger positive effect on performance than does absorptive learning. Business knowledge had a greater effect on performance than did general knowledge, process knowledge or technical knowledge, while explicit knowledge had a stronger effect than tacit knowledge. Moreover, the SCL–performance relationship is moderated by performance measure and industry type but not by regional economic development, highlighting the broad applicability of SCL.

Originality/value

This study is the first meta-analysis on the SCL–performance relationship. It differentiates between learning from customers and learning from suppliers, examines a more comprehensive list of performance measures and tests five moderators to the main effect, significantly contributing to the SCL literature.