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This study aims to address the issue of perfunctory sharing that arises in knowledge governance due to a lack of willingness to share knowledge between individuals within the same organization. This knowledge-sharing process does not occur simultaneously for both parties but follows a sequential progression. Additionally, this governance model fully considers the willingness of both parties to share and effectively addresses the two knowledge characteristics that influence their willingness to do so.

This study follows inductive logic and primarily adopts an interpretive case study approach to conduct a longitudinal exploratory case study. An incubator enterprise with active knowledge-sharing activities and significant knowledge governance effects is selected as the research subject. The governance system is explained through the lens of prospect theory at the mechanism level.

In the study of the knowledge-sharing process, the authors observed a new challenge: perfunctory behavior, whereby individuals engage in knowledge-sharing activities that lack substantial effects as a way to avoid genuine sharing. From this, a new knowledge-sharing model was extracted, the cold start and hot feedback model, which follows a sequential (rather than simultaneous) progression. Using the deterministic effect of prospect theory and the principle of reference dependence, the governance mechanism of corporate knowledge sharing was analyzed from the perspective of knowledge-sharing willingness.

Based on prospect theory, this study primarily explains how the governance mechanism influences the willingness to share knowledge from the perspective of four principles. In the future, threat rigidity theory and commitment escalation theory can be combined to further analyze the willingness to share knowledge from the perspectives of pressure and cost. Empirical research methods can also be used to test and enrich the research results of this paper.

After considering the willingness to share knowledge, a new knowledge-sharing model and corresponding knowledge-sharing governance model are proposed, and prospect theory is extended to the knowledge-based theory research field.

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.

This study aims to investigate the influence of parent company personnel embedding on the stock price crash risk (SPCR) of listed companies, along with the moderating effect of disparate locations between parent and subsidiary companies and other major shareholders.

This research empirically tests hypotheses based on a sample of listed subsidiaries in China during the period between 2006 and 2021.

Our results demonstrate that personnel embeddedness in the parent company significantly alleviates SPCR in subsidiaries. This effect is even more substantial when the parent and subsidiary companies are in different places. However, other major shareholders in the subsidiary company weaken it. Our additional analysis indicates that, relative to executive embeddedness, director embeddedness exerts a stronger effect on the SPCR of the subsidiary. Mechanism examination reveals that the information asymmetry and the level of internal control (IC) within the subsidiary are significant channels through which the personnel embeddedness from the parent company influences the SPCR of the subsidiary.

This study expands the literature on how personnel arrangements in corporate groups within emerging countries influence SPCR. We have extended the traditional concept of interlocking directorates to corporate groups, thereby broadening the understanding of the governance effects of interlocking directors and executives from a group perspective.

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.

This study aims to research the influence mechanism of microtextured geometric parameters of dry gas seal end face on the tribological behavior under dry frictional conditions.

The microtexture was processed using laser processing, while the diamond-like carbon (DLC) film was applied through magnetron sputtering; the experimental platform of friction vibration was established, the frictional and vibrational properties of different geometric parameters were tested; the data signals of vibrational acceleration and frictional torque were collected and processed using data acquisition instrument. The entropy characteristic parameters of 3D vibrational acceleration were extracted based on wavelet packet decomposition method. The end-face topography was measured with ST400 three-dimensional noncontact surface topography instrument.

The geometry of pits plays a key role in influencing friction performance; the permutation entropy and fuzzy entropy of the vibration acceleration signal changed with variations in microtextured parameters. A textured surface with appropriately size parameters can trap debris, enhance the dynamic pressure effect, reduce impact between the friction interfaces and improve the frictional vibrational performance. In this research, microtextured surface with Φ150 µm-10% and Φ200 µm-5% can effectively reduce friction and vibration between the end faces of a dry gas seal.

DLC film improves the hardness of seal ring end face, and microtexture improves the dynamic effect; the tribological behavior monitoring can be realized by analyzing the characteristics of vibration acceleration sensitive parameter with friction state. The findings will provide a basis for further research in the field of tribology and the microtexture optimization of dry gas seal ring end face.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0389/

This paper aims to analyze the characteristics of friction vibration signals and identify the vibration excitation source at the start and stop stage of microtextured end face of dry gas seals.

The friction pair consists of a diamond-like carbon (DLC) film microtextured seal ring and a spiral groove seal ring. Friction vibration signal feature extraction method based on harmonic wavelet packet and spectrum analysis was proposed. Signals were collected using acceleration sensor, acquisition card and LabVIEW software. Vibration acceleration signal was decomposed into 32 frequency bands using MATLAB wavelet packet transformation. The 32nd band coefficient was extracted for reconstruction, time-domain and spectral waveforms were obtained and spectra before/after denoising were compared.

The end face of the DLC film microtextured seal ring generates a good dynamic pressure effect, and the friction and vibration reduction effects are obvious. The harmonic wavelet packet can decompose the vibration signal conveniently and precisely. In the case of this experiment, the frequency of vibration of the seal ring is 7500 HZ.

The results show that the method is effective for the processing of friction vibration signal and the identification of vibration excitation source. The findings will provide ideas for the frictional vibration signal processing and basis for further research in the field of tribology of dry gas seal ring.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0084/

We seek to contribute to the literature by comparing and analyzing the relationship between Australian and Taiwanese students regarding environmental value attitude, action intention and green marketing intention. Specifically, by comparing the green marketing intention of hospitality and tourism (H&T) students in the East with that in the West.

A well-designed curriculum examines student thinking and behavior (learn). This study compares and analyzes the value and attitude and the application of big data to green marketing among Taiwanese and Australian university students using the stimulus-organism-response (S-O-R) model. Structural equation modeling (SEM) was used to test the hypotheses in a sample of 633 H&T students in Taiwan (389) and Australia (244).

This study also shows how the national differences between Australia and Taiwan have interference effects on the relationship between value attitudes and action intentions and between action intentions and the green marketing intention. We also combined the application of big data and related variables and estimated the mediating effect of related variables to evaluate the impact on action intentions and green marketing of big data applications.

There are significant differences in the sustainable behavior and intentions of H&T higher education students that reflect the educational differences between the East and the West. These different results may be due to a lack of natural resources and the relatively smaller size of Taiwan. With the strengthening of environmental action intention (AI) and green marketing intention (GMI), Taiwanese hospitality and management (H&M) students' sense of crisis increases, and their performance in GMI is slightly higher than that in Australia.

These findings indicate that it is necessary to consider students' ecological concepts, environmental knowledge, environmental value attitude and environmental action intention to improve their intentions to engage in green marketing under the stimulus-organism-response (S-O-R) framework. We also found that environmental knowledge has a mediating effect on the relationship between ecological concepts and environmental value attitude.

This study aims to analyse the potential impacts of free trade agreement (FTA) between Indonesia and Organisation of Islamic Cooperation (OIC) countries by eliminating import tariffs in the halal food sector on welfare, gross domestic product (GDP) and trade balance. OIC countries as the second-largest organisation after the United Nations are the potential markets for the halal food industry.

This study used the Global Trade Analysis Project database version 10 by adopting a computable general equilibrium (CGE) model for two scenarios. The first scenario stated that Indonesia should conduct an FTA with ten potential OIC countries as export destination, while the second one stated that it should be conducted with all OIC countries.

Indonesia is predicted to get the highest increase in welfare by making an FTA with all OIC countries. Scenario 2 showed that Indonesia had much higher changes in real GDP with a positive change of 0.0018%. Even though it is projected to experience a surplus in the trade balance in both scenarios, Indonesia is predicted to experience a decline in exports for the particular halal food sector. The findings contribute some new insights to the existing literature, revealing an alignment between economic integration and the concept of international trade in Islam.

The limitation of this study is the available data that cannot describe the population of all OIC countries. Only 31 countries out of a total of 56 OIC countries can be used in research. The scope of research is limited to analysing FTAs between Indonesia and OIC countries in the form of abolishing import tariffs and does not include non-tariff barrier issues such as halal certification.

The preferential trade agreement is considered relevant as Indonesia’s initial commitment to conduct a bilateral trade with ten selected OIC countries. The Indonesia Government, however, still needs to make several mitigation efforts in various sectors experiencing losses as a result of economic integration, such as by creating a more conducive business climate, supporting the sources of capital, facilitating bureaucratic affairs, as well as providing tax incentives.

This paper contributes to the literature by focusing on the critical aspects of the FTA’s impacts on halal food sectors by optimizing the reduction of import tariffs of OIC countries. Different from previous studies, this study applied a static CGE model to examine the impacts of FTA on macroeconomic indicators.

In the process of making agricultural production decisions in rural households, severe weather conditions, either extreme cold or heat, may squeeze the labor input in the agricultural sector, leading to a reallocation of labor between the agricultural and non-agricultural sectors. By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, reveal the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

This study utilizes data from Chinese meteorological stations and two waves of China Household Income Project to examine the impact and behavioral mechanism of extreme temperatures on rural labor reallocation.

(1) Extremely high and low temperatures had led to a reallocation of labor force from agricultural activities to non-farm employment, with a more pronounced effect from extreme high temperature events. (2) Extreme temperatures influence famers’ decision in abandoning farmland and reducing investment in agricultural machinery, thus creating an interconnected impact on labor mobility. (3) The reallocation effect of rural labor induced by extreme temperatures is particularly evident for males, persons that perceives economic hardship or labor in economically active areas.

By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, and reveals the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.