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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.

The purpose of the paper is to conduct a review of the literature on human-robot collaboration across different functions and activities of human resource management (HRM) and discuss its importance for change readiness in organizations.

A bibliometric analysis was conducted to identify emerging research themes in the fields of human resources (HR) and robotics, including change readiness. Based on the initial results of the bibliometric analysis, a systematic literature review was subsequently performed to gain a more specific understanding of research across various HRM functions and change readiness.

The results from bibliometric analysis and systematic review highlight that technological progression in HRM, such as AI-driven staffing and training techniques, improves effectiveness and personalization but raises concerns about privacy and job scrutiny. AI and robotics in performance evaluation enhance objectivity and reduce subjectivity, which can lead to disengagement. Generational differences, cultural factors and emotional quotient complicate readiness to adopt new technologies. The research emphasizes balancing technological effectiveness with employee involvement and meaningfulness to ensure successful implementation and engagement.

This paper synthesizes existing research, including literature, theoretical concepts and models, to identify best practices and successful strategies for implementing human-robot collaboration in HRM functions. It highlights gaps in the current literature and suggests areas for future research to advance the field of human-robot collaboration in HRM. By doing so, this paper enhances theoretical understanding while offering practical insights essential for effective change management.

As sustainability concerns become increasingly influential in shaping wineries’ strategies at the production and processing stages, this study aims to investigate the anticipated benefits, incentives and constraints associated with a territorial sustainability certification in the wine industry.

Focusing on wine producers from the Romagna Consortium (Italy), the research explores the influence of firm characteristics on sustainability attitudes and explores the Consortium potential role in facilitating the ecological transition. Data are collected through an online survey and analyzed by means of factor and cluster analysis.

Findings reveal the Consortium capacity to expand its scope, incorporating elements of sustainability, resilience and territorial development. In addition, it emerges that the perception of sustainability among local producers extends beyond environmental concerns, encompassing the economic and social domains.

Acting as a cluster constituent, the Consortium can stimulate collaborative behavior and promote knowledge dissemination contributing to a mature collaborative environment. A territorial sustainability certification is thus viewed as multifunctional tool, enhancing economic performance and collective reputation, while addressing the numerous environmental challenges faced by the sector.

The study’s originality lies in its direct engagement with a considerable number of producers in a geographic area boasting a mature wine industry but with limited research focusing on coordinated efforts for improved sustainability performance.