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The purpose of this study is to present the overall trend and dynamics in global mergers and acquisitions activity while suggesting future research avenues in this domain. The analysis covers two aspects to examine the main contours of the domain, that is performance analysis followed by thematic cluster analysis.

Bibliometric analysis has been used for examining 1,433 publications extracted from the Scopus database to identify the research trend between 2000 and 2021. With the help of VosViewer (a bibliometric software), bibliographic coupling, citation, co-authorship, keyword and network analysis have been carried out.

The analysis reveals that most of the research on cross-border mergers and acquisitions (CBMA) is concentrated in the context of developed markets, USA and UK being the largest. Most of the research till date is confined to wealth effects, value creation, corporate governance, socio-cultural aspects and various determinants of CBMA, all from the standpoint of the acquirer.

The present study highlights numerous opportunities for future research based on empirical analysis. There exists a dearth of studies around CBMA in the context of emerging nations which provides a relatively unexplored field to carry out research work.

The study makes use of a comprehensive list of keywords to have an extensive analysis. This is a pioneering study that has used bibliographic coupling of documents for content analysis and to the best of authors’ knowledge, no previous works on cross-border acquisitions have performed bibliographic coupling for this.

The purpose of this study is to achieve a comprehensive understanding of how the intricate interconnections between oil price fluctuations, supply chain disruptions and shifting demand patterns collectively shape inflation dynamics within the Chinese economy, especially during critical periods such as the Covid-19 pandemic and geopolitical events like the Russia–Ukraine conflict. The importance of assessing the impact of oil price volatility on China’s inflation becomes particularly pronounced amidst these challenging circumstances.

This study uses the Markov Regime-Switching generalized autoregressive conditional heteroskedasticity (MRS-GARCH) family of models under student’s t-distributions to measure the uncertainty of oil prices and the inflation rate during the period spanning from 1994 to 2023 in China.

The results indicate that the MRS-GJR-GARCH-in-mean (MRS-GARCH-M) models, when used under student’s t-distributions, exhibit superior performance in modeling the volatility of both oil prices and the inflation rate. This finding underscores the effectiveness of these models in capturing the intricacies of volatility dynamics in the context of oil prices and inflation. The study has identified compelling evidence of regime-switching behavior within the oil price market. Subsequently, the author conducted an analysis by extracting the forecastable component, which represents the expected variation, from the best-fitted models. This allowed us to isolate the time series of oil price uncertainty, representing the unforecastable component. With this unforecastable component in hand, the author proceeded to estimate the impact of oil price fluctuations on the inflation rate. To accomplish this, the author used an autoregressive distributed lag model, which enables us to explore the dynamic relationships and lags between these crucial economic variables. The study further reveals that fluctuations in oil prices exert a noteworthy and discernible influence on the inflation rate, with distinct patterns observed across different economic regimes. The findings indicate a consistent positive impact of oil prices on inflation rate uncertainty, particularly within export-oriented and import-oriented industries, under both of these economic regimes.

This study offers original value by analyzing the impact of crude oil price volatility on inflation in China. It provides unique insights into the relationship between energy market fluctuations and macroeconomic stability in one of the world’s largest economies. By focusing on crude oil – a critical but often overlooked component – this research enhances understanding of how energy price dynamics influence inflationary trends. The findings can inform policymakers and stakeholders about the significance of energy market stability for maintaining economic stability and guiding inflation control measures in China.