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When emergencies occur, the attention of the public towards emergency information on social media in a specific time period forms the emergency information popularity evolution patterns. The purpose of this study is to discover the popularity evolution patterns of social media emergency information and make early predictions.

We collected the data related to the COVID-19 epidemic on the Sina Weibo platform and applied the K-Shape clustering algorithm to identify five distinct patterns of emergency information popularity evolution patterns. These patterns include strong twin peaks, weak twin peaks, short-lived single peak, slow-to-warm-up single peak and slow-to-decay single peak. Oriented toward early monitoring and warning, we developed a comprehensive characteristic system that incorporates publisher features, information features and early features. In the early features, data measurements are taken within a 1-h time window after the release of emergency information. Considering real-time response and analysis speed, we employed classical machine learning methods to predict the relevant patterns. Multiple classification models were trained and evaluated for this purpose.

The combined prediction results of the best prediction model and random forest (RF) demonstrate impressive performance, with precision, recall and F1-score reaching 88%. Moreover, the F1 value for each pattern prediction surpasses 87%. The results of the feature importance analysis show that the early features contribute the most to the pattern prediction, followed by the information features and publisher features. Among them, the release time in the information features exhibits the most substantial contribution to the prediction outcome.

This study reveals the phenomena and special patterns of growth and decline, appearance and disappearance of social media emergency information popularity from the time dimension and identifies the patterns of social media emergency information popularity evolution. Meanwhile, early prediction of related patterns is made to explore the role factors behind them. These findings contribute to the formulation of social media emergency information release strategies, online public opinion guidance and risk monitoring.

Therefore, this study aims to explore the relationships among OC, KS, OCB and OI “Organization” is often seen as a company and few studies pay much attention to tribes and other related organizations and communities of Indigenous peoples. However, Indigenous peoples production organizations (IPPOs) would be certainly influenced by factors from the internal/external, including organizational culture (OC), organizational citizenship behavior (OCB), knowledge sharing (KS) and organizational innovation (OI). Therefore, this study aims to explore the relationships among OC, KS, OCB and OI.

Based on valid 139 Indigenous workers in IPPOs, this study used structural equation modeling to validate the relationships among OC, OCB, KS and OI.

The empirical findings indicate that OC would significantly influence OCB and OI, whereas KS would not have significant impact on OI. In addition, OC would not influence KS as usual, whereas OCB would do. Finally, OCB would impact KS.

As OCB acts as a complete mediator in OC–KS relationship, it means that these IPPOs already have OCB to motivate their staffs to do KS, but not enough to achieve more excellent performance on innovation.

Compared to past studies, this study aims to investigate the theory of organizational behavior and whether it is suitable between general businesses and IPPOs.

Utilizing the expectation states theory in sociology, this study probes into the influence of the board's informal hierarchy on the quality of enterprise innovation, originating from the perspective of internal directorial interactions, while analyzing the boundary effects exhibited by the nature of property rights and the intensity of geo-culture.

The study selects China's A-share listed companies from 2008 to 2021 as the research sample, employing the Tobit regression analysis method to scrutinize the hypotheses presented in the text.

The regression results demonstrate a positive correlation between the board's informal hierarchy and the enterprise innovation quality (EIQ). Upon introducing variables specific to property rights and geographical culture, the authors found that in comparison to non-state-owned enterprises (non-SOEs), the influence of the board's informal hierarchy on the quality of corporate innovation is diminished in SOEs. Conversely, the intensity of geo-culture across Chinese provinces enhances their mutual positive influence. In the additional analysis, the authors also found that the elevation of corporate risk tolerance is a significant pathway for the positive effect of the board's informal hierarchy on EIQ. Moreover, this positive influence is more profound in high-tech enterprises, businesses implementing equity incentive plans and companies that have subscribed to director and officer liability insurance.

The findings not only deepen the understanding of how the board's internal status characteristics influence corporate decision-making but also enrich the application scope of expectation states theory. Furthermore, this study offers valuable guidance for optimizing innovation decision-making by adjusting the personnel structures of corporate boards.

Due to the internationalization that has occurred during the past few decades, the living conditions of people around the island of Taiwan have gradually changed, especially their eating habits. Among them, the growth of the coffee market has been very significant. To date, many studies have been devoted to exploring the application of experiential marketing (EM) in a variety of industries. Many experimental results have proven that a positive brand image (BI) will lead to brand loyalty (BL). In services, the best at the practice of EM is Starbucks. Therefore, this paper aims to assess the role of BI in EM and BL for Taiwan’s most popular brand, Starbucks.

In the formal test stage, 225 questionnaires were given to respondents in Starbucks located in four districts (Da-An, Zhong-Zheng, Nei-Hu and Xi-Yin), which have many more stores than the other districts in Taipei City. Two hundred valid samples were obtained. This study used structural equation modelling (SEM) to validate the relationships among EM, BI and BL.

The findings show that EM cannot directly impact BL as expected, as it needs BI to do so. In other words, BI acts a complete mediator in the relationship between EM and BL.

In this study, BI acts a complete mediator. This means that if Starbucks expects to improve consumers’ loyalty to the brand, it only needs to rely on the good overall image of the brand. Facing such business style homogeneity, people need some available information to help them to execute their following purchase decisions. Though Starbucks can bring me to its locations, meaning that Starbucks has made its first move in comparison with other competitors, I still decide to leave without any impressive image of this brand. Accordingly, we can refer to BI as a powerful endorsement of a qualified relationship between EM and BL.

Compared to past studies on Taiwan’s/Taipei’s Starbucks, this paper simultaneously inputs EM, BI and BL into the model. Though Starbucks has achieved great EM success, this study finds that EM is no longer exclusive to BL, and BI is a powerful endorsement of a qualified relationship between EM and BL. For Starbucks, it must strengthen consumer perceptions of its BI to create customer loyalty.

The purpose of this paper is to discuss recent developments in school developmental supervisory evaluation in the Pudong New Area of Shanghai in the Chinese Mainland.

The main research approach is qualitative, using documentary analysis and interviews of an inspector, principals and teachers from two primary schools.

There were perceived positive and negative impacts of school supervision and evaluation.

The paper highlights the implications for fostering a shared school‐government community of school supervision and evaluation, promoting a dynamic approach for addressing contextual differences as well as achieving better coherence among educational reform, supervision and evaluation policies.

The study examines the effect of natural resources (NRs) and the control of corruption, voice and accountability and regulatory quality on carbon emissions in Africa. Aside from their individual effects, the moderation effect of institutional quality is assessed.

Data from 32 African countries from 2002 to 2021 and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression methods were used for the investigation.

In the long term, the NRs effect is sensitive to the estimation technique employed. However, quality regulatory framework, robust corruption control and voice and accountability abate any positive effect of NRs on carbon emissions. Institutional quality can be argued to moderate the CO2-emitting potentials of resource extraction in the selected African countries.

Enhancing regulation quality, enforcing corruption control and empowering citizens towards greater participation in governance and demanding accountability are essential catalyst to effectively mitigate CO2 emissions resulting from NRs.

The moderation effect of control of corruption, voice and accountability and regulatory quality on the NR–carbon emission nexus is examined.