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This study aims to investigate the responses of young Chinese consumers with different cultural characteristics to negative brand information about electric vehicles.

The current study is quantitative research with an experimental method. It shows two different levels of severity for negative publicity and asks participants to self-report through questionnaires.

Chinese young consumers, being collectivist and of high uncertainty avoidance, tend to search for and spread information; consumers with low power distance search and share information more under low information severity. In addition, information search positively affects brand attitude under lower severity; negative word-of-mouth intention negatively affects brand attitudes at both severity levels.

The current study examines the influence of personal cultural values on information searching and negative information dissemination among young consumers, providing insights to complement previous studies. Furthermore, it explores how such exposure influences young consumers’ brand attitude and intention to purchase. Limitations include simple sample scopes and single-product stimuli.

This research highlights the importance of cultural dimensions in shaping young consumers’ responses to negative publicity. Marketers worldwide should consider cultural influence and develop specific strategies to address negative information about different products. Understanding customers’ unique characteristics and preferences can help marketers effectively tailor their approaches to counter negative publicity.

This study originally provides a supplement to prior studies on cultural dimensions and consumer behavior and provides suggestions to marketers on young Chinese consumers.

This paper aims to propose a hybrid method based on polynomial fitting bias self-compensation, grey forward-backward linear prediction (GFBLP) and moving average filter (MAF) for error compensation in micro-electromechanical system gyroscope signal especially under motion state.

The error compensation can be divided into two processes: bias correction and noise reduction. A polynomial drift angle fitting algorithm is used to correct bias before denoising processing. For noise reduction, operation can be taken in two stages: detection and processing. First, sample variances are used to judge motion state. According to the detection results, algorithmic system switches between grey GFBLP and MAF to ensure fast convergence rate and small steady-state error.

Experimental results show that the proposed method can correct bias effectively for practical gyroscope signal, and can eliminate noise effectively for both practical gyroscope signal and synthetic signal, which indicates the effectiveness of the proposed method.

Bias correction and noise reduction are considerations. Noise contained in practical or synthetic signal can be reduced rapidly and effectively, which benefits from the new idea of combination grey GFBLP, MAF and sample variances. And most importantly, it is applicable for signal denoising under arbitrary motion state condition, which is different from other methods where the convergence performance is seldom analyzed.

This study aims to introduce an important temporal dimension to the research on institution and entrepreneurship in the transition period. This study develops the concept of pre-reform institutional embeddedness, and explores its impact on entrepreneurial reinvestment of private firms in China’s transition economy.

The authors used secondary data of a nationally representative sample of China’s private firms collected in the early days of the institutional transition period and applied ordinary least squares regressions and the Baron and Kenny approach to test the theoretical model.

Pre-reform institutional embeddedness has a negative impact on entrepreneurial reinvestment of private firms in the transition period. This relationship is mediated by guanxi-induced employment, such that pre-reform institutional embeddedness promotes guanxi-induced employment, which in turn discourages a private firm to reinvest. Additionally, the negative impact of guanxi-induced employment on entrepreneurial reinvestment is reduced when decentralization of decision-making is used.

First, entrepreneurs should be aware of pre-reform institutional embeddedness’ negative influence on firms’ risk-taking abilities and incentives. Private firms already constrained by this connection could alleviate the negative impacts through a widespread delegation of decision-making authority. Second, policymakers should be cautious about improper government-business relationships, which may discourage private firms from fully pursuing entrepreneurial growth opportunities.

This paper makes theoretical contributions to the literature on entrepreneurial reinvestment, embeddedness perspective of entrepreneurship and imprinting theory.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.