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Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.

This study examines the market reaction to the World Health Organization (WHO) announcement of the novel coronavirus disease 2019 (COVID-19) as a global pandemic on the emerging equity markets and compares the reaction with developed markets. This study also compares the market reactions to the COVID-19 pandemic with the market reactions to the 2008 global financial crisis.

Using the Morgan Stanley Capital International daily stock indices data and the Carhart and the GARCH(1,1) models for an event study, the authors examine the cumulative abnormal returns during 30 and 10 trading days and the extended 60 days before and after the WHO pandemic announcement. It also compares the market reactions during the COVID-19 pandemic with the reactions to the Lehman Brothers' bankruptcy announcement during the 2008 global financial crisis.

This study finds that the COVID-19 pandemic had a significantly greater negative impact to the stock markets in emerging countries than in the developed countries. The negative impact on the emerging markets is more pronounced for firms with small market capitalizations and for growth stocks. The negative impact of the COVID-19 pandemic is stronger in the energy and financial sectors in both emerging and developed markets. The positive impact of the COVID-19 pandemic occurred in healthcare and telecommunications for the emerging markets and information technology for the developed markets. This study also finds that the equity markets in both emerging and developed countries recovered faster from the COVID-19 pandemic relative to the 2008 global financial crisis.

Investors' desire to diversify their risks across different countries and sectors in the emerging markets could bring superior returns. The diversification strategies bring critical financial supports to forestall the contagion of COVID-19, to protect lives, and to save the emerging economies, especially for those financially constrained countries that are facing twin health and economic shocks by channeling their investments to countries with weak healthcare systems.

This study extends the literature that examines market reactions to stock market shocks by examining the market reactions to the COVID-19 outbreak on the emerging and developed equity markets across different market capitalizations, valuation and sectors. This study also finds that the markets recovered quicker from the COVID-19 pandemic announcement than during the 2008 global financial crisis.

This study aims to explore the impact of supply chain quality event (SCQE) announcements on enterprises’ stock market value.

This study adopts the event study approach and analyzes the changes in shareholder value of companies listed in China based on data from 118 SCQE announcements. In the event study, the market, market-adjusted and Carhart four-factor models are used to estimate abnormal stock market returns, and a cross-sectional regression model is performed to examine the effects of SCQE announcements on enterprises’ stock market value.

SCQE announcements have a negative impact on shareholder value. From the perspective of the supply chain network structure, the market reacts more negatively to SCQE announcements issued by the enterprises with higher supply chain concentration. From the perspective of companies’ characteristics, announcements that do not reflect the establishment of supply chain quality cooperation have a more negative effect on stock market value, which indicates that the supply chain network structure and firm-level characteristic can moderate the market reaction.

The findings demonstrate a quantitative evaluation of how SCQE announcements affect the stock market value of listed companies and provide guidance for managers to enhance the value of SCQE announcements.

This study fills the research gap on the impact of SCQE announcements on stock market value by using secondary data and first explores the relationship between SCQE announcements and stock market value from the perspective of supply chain network. Furthermore, this study contributes to the literature on SCQE using an empirical study in China.

This study aims to explore the impact of blockchain announcements on enterprises' stock market value.

Based on resource-based theory, this study constructs a complete framework of the impact mechanism of blockchain announcements on the stock price of the announcing firm using the data of 143 blockchain announcements. An event study methodology is used in this research, and the market model, market-adjusted model and Carhart four-factor model are used to estimate stock abnormal returns after the blockchain announcement; and the cross-sectional regression model is used to test the influencing factors.

Blockchain announcements elicit a significantly positive market reaction on the release day. Compared to announcements not pertaining to technical innovation, blockchain technical innovation announcements exhibit a more positive market reaction towards the announcing companies. Strategic-level announcements exhibit a more positive market reaction than operational-level announcements. Enterprise characteristics, such as enterprise-scale and enterprise innovation ability, do not affect stock market reactions to blockchain announcements.

The findings reveal the economic value of conducting blockchain activities in the Chinese stock market. Findings of this study can help managers understand the value of implementing blockchain activities in a different market environment and guide them on how to improve the market value of their enterprises through the active implementation of blockchain activities.

To the best of the authors’ knowledge, this is the first event study to focus solely on the value of pure blockchain announcements in an emerging market. This study considers multiple resource and capability factors that would influence blockchain technology adoption, improve the current understanding of how blockchain announcements affect corporate stock prices and provide directions for future comparative studies of market reactions to blockchain announcements in different stock markets.

This paper aims to use the Covid-19 pandemic situation to conduct an experiment-like study that focuses on industry reactions under stress. Particularly, this study analyzes stock response to eight pandemic related news in 2020 across different industries. This study also investigates the role that the market risk, beta, plays in such stock reactions.

This study computes the cumulative abnormal returns (CAR) around COVID-19 events using adjusted daily stock returns of all stocks in the S&P 500 index between January 2, 2020 and December 31, 2020. This study also sorts all stocks by beta into quintiles and measures the CAR [0, +3] for each quintile around each event date.

This study finds that low beta portfolios exhibit greater abnormal returns (in absolute value) than high beta portfolios during down markets while high beta portfolios exhibit greater abnormal returns (in absolute values) when the market starts to recover. However, this study finds that beta does not seem to explain the abnormal returns reported in various industries during times of negative sentiment. During times of positive sentiment, both the beta effect and industry effect are present.

Extant literature almost unanimously concurs that the COVID-19 pandemic has brought about negative stock reactions to financial markets across the globe. Nevertheless, three interrelated issues have not been explored: market reactions during the subsequent recovery, industry heterogeneity and individual stocks’ risk profile. The study addresses these matters.

The purpose of this paper is to examine the correspondence between the stock market's immediate reactions to new product introduction announcements and those products' subsequent commercial performance.

The main study uses standard event study methodology.

The paper finds that the stock market reacts “incorrectly” to announcements of new product introductions more often than one would expect from a market that is assumed to be highly efficient.

The paper's findings raise questions about the appropriateness of using daily stock returns to assess the profitability of marketing actions with highly uncertain outcomes.

Event studies of stock prices have been a popular method to assess the profit impact of marketing actions in a timely manner; yet, there has been surprisingly little research addressing the stock market's ability to react immediately to firm actions in a manner consistent with how effective the actions actually turn out to be. The authors' intended contribution is to guide marketing researchers investigating determinants of firm profitability.

The purpose of this paper is to provide evidence about the effects of the MILA agreement in terms of improving financial market efficiency.

The authors measure efficiency by studying the stock reaction to earnings announcements using a conditional heteroscedasticity generalized autoregressive conditional heteroscedasticity-adjusted market model and the most commonly implemented event study tests for 3,399 events across four countries in the Latin American Integrated Market (MILA).

Contrary to expectations, the results show that the MILA agreement has isolated gains in terms of reaction to corporate earnings announcements, which translates into partial improvements in market efficiency. However, the evidence indicates that the MILA agreement favored cointegration, which is in line with other studies.

This paper provides evidence for policymakers and regulators that a stock market agreement is a condition that promotes market cointegration, but it is not an element that in itself ensures an improvement in market efficiency. To achieve greater MILA benefits, regulatory and market-level changes are required.

This is the first study that analyses the effect of a stock market agreement on the efficiency of markets, expanding on what has been studied in the finance literature regarding the influence of these agreements on cointegration.

Esta investigación entrega evidencia sobre los efectos del acuerdo MILA respecto a mejoras en la eficiencia de los mercados accionarios involucrados.

Medimos eficiencia estudiando la reacción de los mercados accionarios tras anuncios de resultados utilizando un modelo de mercado ajustado por heteroscedasticidad condicional (GARCH). Además, consideramos las pruebas de estudios de evento más utilizadas en la literatura para 3,399 eventos en los 4 países involucrados en el acuerdo MILA.

Contrario a lo esperado, los resultados muestran que el acuerdo MILA genera aumentos marginales en la reacción frente a anuncios corporativos, lo cual se traduce en mejoras parciales de la eficiencia de mercados accionarios. Sin embargo, la evidencia muestra que el MILA sí favorece a la cointegración, lo cual va en línea con estudios previos.

Esta investigación entrega evidencia para reguladores de que un acuerdo de integración bursátil promueve cointegración entre mercados, pero no es un elemento que por sí solo asegure una mejora en eficiencia. Para alcanzar mayores beneficios del acuerdo MILA, se requieren cambios adicionales a nivel de mercado accionario y de regulación.

Este es el primer estudio que analiza el efecto de un acuerdo de integración bursátil en la eficiencia de los mercados accionarios, expandiendo lo que ha sido ya encontrado en la literatura financiera respecto a la influencia de estos acuerdos en cointegración.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

This study empirically examines the impact of announcements on supply chain strategic collaboration (SCSC) on companies' shareholder value.

This study analyzes changes in shareholder value of companies listed in China based on data of 208 SCSC announcements. The signaling theory is applied to determine correlation among SCSC announcements and the market. An event study is used to estimate the stock market reaction to SCSC announcements. The common market model estimates stock abnormal returns after the event. The least squares method and regression model calculate the model parameter value.

There is a positive and statistically significant relationship between SCSC announcement and shareholder value. Market reaction to product development collaboration is significantly higher than to technology-sharing collaboration, market collaboration, and other SCSC types. The market reacts more positively to suppliers and companies with greater supply chain control power than to buyers and companies with lower control power. Announcements from the service supply chain can lead to stronger market reactions than those from manufacturing supply chains.

The findings provide a systematic assessment of how SCSC announcements contribute to firms' shareholder value. The result provides a benchmark of value promotion that can be expected from SCSC announcements.

This study fills the research gap that using secondary data to assess changes in companies’ shareholder value caused by SCSC announcements and firstly examines these changes by constructing the signaler–signal–receiver progress based on signaling theory. The research results provide a new reference and inspiration for deeper understanding of the impact mechanism of SCSC. Furthermore, this study contributes to the development of the signaling theory using an empirical study in an emerging market, China.

This study aims to examine whether the publication of analyst recommendations has reaction in the Russian stock market. This study also aims to determine the other factors that influence the reaction.

Event study analysis (ESA) and regression models are used in this study.

The study finds that Russian stock market significantly reacts to analyst recommendations publications. Then study deeply investigates about the influence of other factors on the Russian market when an analyst's recommendations are published such as changes in recommendation levels, companies' size and general economic situation. The analysis done in the context of three types of recommendations: “buy,” “hold” and “sell.” The study finds that the market reacts not only to separate forecasts and subsequent recommendations, but also to the changes in recommendations' levels as well. Interestingly, the study finds that the impact of crises is not found to be a significant factor in the context of the Russian market.

Analysts used to spend much more resources on conducting a fundamental analysis than ordinary investors do. Therefore, they usually possess valuable privileged information that is supposed to influence stock prices when published. However, the present study argues that the direction, extent and period of a reaction of an analyst's recommendations are highly complicated and depend on what factors are under consideration in a particular research. Very often, the authors who dedicate their papers to develop and study markets choose a couple of (or even one) factors and delve into them. Nevertheless, to the author's best knowledge, few frequently cited and well-conducted research focused on such an emerging market as the Russian one. Thus, it seems reasonable that there is a gap in the literature that needs to be filled while considering other important factors. The study findings have a significant investment policy content.

In several senses, the present study is unique. First, it investigates whether analyst recommendations sufficiently affect the Russian stock market; second, it determines whether the significant factors such as changes in recommendation levels, companies' size and general economic situation have influence on the reaction. Finally, the study discusses about whether there is an impact of crises in the present study findings.