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Vehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.

This paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.

Experiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.

To reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

The purpose of this study is to address a significant gap in the understanding of entrepreneurship at the microfoundation level. It focuses on how individual entrepreneurs, specifically Hongbang entrepreneurs in China from 1896 to 1949, shape and transform their contexts. The aim is to provide a deeper understanding of the mechanisms that facilitate entrepreneurial success.

The study adopts a microhistorical approach, investigating the case of Hongbang entrepreneurs in China during 1896-1949. It involves an in-depth examination of historical records to explore the strategic interactions between these entrepreneurs and core stakeholders such as consumers, financial intermediaries, government regulators, and human resources. The research methodology emphasizes a process-oriented view, examining the evolution of personalized networks into extensive connections.

The research reveals that Hongbang entrepreneurs successfully reshaped their unfavorable embedded contexts by strategically collaborating with key stakeholders. They influenced consumer tastes, allied with financial intermediaries, negotiated with governments on regulation policies, and developed human resource stocks. The transformation was facilitated by the evolution of their networks from personalized to extensive connections. These findings highlight the localized strategies such as cronyism in resource acquisition within China’s private property development industry.

This study contributes to the field by offering insights into entrepreneurial contextualization and networking. It sheds light on the complex interplay between entrepreneurs and their contexts, providing a nuanced understanding of localized strategies in the Chinese context. The findings add value to the discourse on entrepreneurship by elucidating the strategic and processual acts through which entrepreneurs engage with stakeholders and reshape their environments.

The purpose of this study is to explore the relationship between environmental, social and governance (ESG) performance and tone management in the annual report. This is based on the notion that managers, driven by personal interests, may use their ESG accomplishments by using an abnormal positive tone to enhance their reputation or career prospects.

Using panel data from Chinese listed companies from 2010 to 2022, this study first investigates the relationship between ESG performance and abnormal tone management. The study then uncovers this relationship is mediated through the mechanisms of equity-based incentive and analyst coverage. The conclusions of this paper hold even after a series of robustness tests, such as propensity score matching, Heckman two-stage method and two-stage least squares with instrumental variables.

This study finds a positive correlation between ESG performance and the presence of abnormal positive tone in annual reports. Furthermore, the mechanistic analysis reveals that managers in companies with strong ESG performance are motivated to use an overly positive tone, largely due to their vested interests in equity-based compensation. Moreover, in an effort to alleviate the pressure stemming from heightened financial analyst coverage and enhance the impression conveyed through analysts' reports, managers with superior ESG performance also tend to inflate the tone within their annual reports.

This study provides significant insights into the ongoing dialogue surrounding ESG-related equity incentives, which incentivize managerial manipulation of stock prices through the use of abnormal positive tone. The findings call upon investors to exercise greater vigilance in examining narrative information in annual reports, as abnormally positive tones may not always faithfully represent performance but rather reflect managerial self-interest.

There is an emphasis on the importance of robust oversight mechanisms within corporate governance bodies to curb the manipulation of tone for managers’ personal gain.

This study enhances the theoretical foundation of ESG studies, offering a holistic perspective on the intricate interplay among ESG performance, managerial behavior and financial markets, with potential implications for researchers, investors and regulators.

This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of memory dependence period, ultimately enhancing the model's predictive accuracy.

This paper enhances the traditional grey Bernoulli model by introducing memory-dependent derivatives, resulting in a novel memory-dependent derivative grey model. Additionally, fractional-order accumulation is employed for preprocessing the original data. The length of the memory dependence period for memory-dependent derivatives is determined through grey correlation analysis. Furthermore, the whale optimization algorithm is utilized to optimize the cumulative order, power index and memory kernel function index of the model, enabling adaptability to diverse scenarios.

The selection of appropriate memory kernel functions and memory dependency lengths will improve model prediction performance. The model can adaptively select the memory kernel function and memory dependence length, and the performance of the model is better than other comparison models.

The model presented in this article has some limitations. The grey model is itself suitable for small sample data, and memory-dependent derivatives mainly consider the memory effect on a fixed length. Therefore, this model is mainly applicable to data prediction with short-term memory effect and has certain limitations on time series of long-term memory.

In practical systems, memory effects typically exhibit a decaying pattern, which is effectively characterized by the memory kernel function. The model in this study skillfully determines the appropriate kernel functions and memory dependency lengths to capture these memory effects, enhancing its alignment with real-world scenarios.

Based on the memory-dependent derivative method, a memory-dependent derivative grey Bernoulli model that more accurately reflects the actual memory effect is constructed and applied to power generation forecasting in China, South Korea and India.

This study aims to research the erosion wear characteristics and sealing performance of V-regulating ball valve in coal chemical process pipelines, which provides a theoretical reference for improving its antiwear and sealing performance.

Taking the V-regulating ball valve as the research object, based on the computational fluid dynamics and the theory of erosion wear, the authors studied its erosion characteristics under different medium parameters and analyzed the sealing performance under the heat-fluid–solid coupling working condition.

The erosion wear mechanism of the valve sealing surface is the simultaneous action of cutting and deformation. When the medium flow velocity, particle mass flow rate and particle size increase, the maximum erosion rate and average erosion rate in the V-regulating valve increase. The inner diameter Mises contact stress of the sealing surface is symmetrically distributed in a “wing shape,” and the contact stress of the outer diameter is distributed in a “butterfly shape.” Due to the superposition of thermal stress and pressure stress in the contact transition zone to produce a significant stress concentration.

The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

V-type regulating ball valve is widely favored by coal chemical enterprises and petrochemical enterprises because of its wide adjustment ratio and good erosion resistance.

The V-regulating ball valve wear mechanism for cutting and deformation simultaneously, and its wear rate is positively correlated with the medium flow rate, particle mass flow rate and particle size. After the valve is opened, there is a significant stress concentration occurs in the contact transition zone due to the superposition of thermal stress and compressive stress. The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0205/

Given the inevitable transition to renewable resource utilization and the urgent need to reduce carbon emissions, this study conducted quasi natural experiments to assess the impact of renewable resource utilization on carbon emissions based on the national “urban mining” demonstration bases (NUMDB).

This study uses panel data from 275 prefecture-level cities in China from 2006 to 2019. The paper selects NUMDB as the proxy variable and conducts a quasi-natural experiment using a multi-period differences-in-differences model. We examine the impact of NUMDB on reducing carbon emissions, and then deeply explore its mechanism and spatial spillover effect.

This study found that: (1) the construction of NUMDB can significantly decrease the carbon emission in the host cities; (2) NUMDB’s construction has more significantly reduced the carbon emission in regions with higher levels of circular economy development, green technology innovation, regional environmental pollution, digital economy development and financial development; (3) by means of green technology innovation, optimized energy structure, and high-quality talent aggregation, NUMDB reduces urban carbon emissions; (4) NUMDB construction positively affects the carbon reduction efficiency of neighboring regions.

We propose corresponding policy suggestions to further promote the carbon emission reduction effect of NUMDB and develop the renewable resources industry in China based on the research findings.

The contributions of this paper are as follows. Our study contributes to expanding the research scope on the environmental impact of the renewable resource industry, as there are few quantitative studies in this area.

We further consider the spatial heterogeneity of policies and analyze the carbon reduction effect of the NUMDB from the city level, which is beneficial to exploring more targeted and operable carbon reduction paths.

This study on identifying the causal relationship between renewable resource utilization and carbon emission reduction helps to explore the sustainable development path of renewable resource more comprehensively. Meanwhile, this paper provides a reference for other countries to improve the utilization of renewable resource and effectively reduce carbon emissions.

Given the scarcity of research exploring the influence of emotional dimensions on knowledge hiding (KH), this paper aims to examine how various facets of emotional intelligence (EI) affect teachers’ tendencies to hide knowledge. Additionally, the study delves into the mediating influence of organizational cynicism (OC) and explores the moderating role of servant leadership (SL) in this context.

The non-probability sampling method was used to gather data from 542 university teachers teaching in India. Structural equation modelling using Smart-PLS has been used to test the hypothesis.

The study revealed that EI negatively influences KH. Additionally, OC mediates the relationship between EI and KH. Furthermore, SL moderates the relationship between OC and KH.

As per the authors’ knowledge, the present study makes an additional contribution by investigating the mediating role of OC in the relationship between EI and KH. Moreover, it also investigates the moderating role of SL in the relationship between OC and KH.

This paper aims to investigate the preparation of AlN and Al₂O₃, as well as the effect of nano-AlN and nano-Al₂O₃, on friction and wear properties of copper-steel clad plate immersed in the lubricants.

Nano-AlN or nano-Al₂O₃ (0.1, 0.2, 0.3, 0.4 and 0.5 Wt.%) functional fluids were prepared. Their tribological properties were tested by an MRS-10A four-ball friction tester and a ball-on-plate configuration, and scanning electron microscope observed the worn surface of the plate.

An increase in nano-AlN and Al₂O₃ content enhances the extreme pressure and anti-wear performance of the lubricant. The best performance is achieved at 0.5 Wt.% of nano-AlN and 0.3 Wt.% of nano-Al₂O₃ with PB of 834 N and 883 N, a coefficient of friction (COF) of approximately 0.07 and 0.06, respectively. Furthermore, the inclusion of nano-AlN and nano-Al₂O₃ particles in the lubricant enhances its extreme pressure performance and reduces wear, leading to decreased wear spot depth. The lubricating effect of the nano-Al₂O₃ lubricant on the surface of the copper-steel composite plate is slightly superior to that of the nano-AlN lubricant, with a COF reaching 0.07. Both lubricants effectively fill and lubricate the holes on the surface of the copper-steel composite plate.

AlN and Al₂O₃ as water-based lubricants have excellent lubrication performance and can reduce the COF. It can provide some reference for the practical application of nano-water-based lubricants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0255/

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.

Research on corporate social responsibility (CSR) within the real estate sector is limited, and the precise workings of its impact are still unclear. Under the premise that real estate enterprises face environmental uncertainty in China, this study explored the impact of CSR on real estate enterprise value.

To investigate the impact of CSR on enterprise value, we studied 111 real estate enterprises with A-shares listed on Shanghai and Shenzhen stock exchanges from 2010 to 2020, and performed empirical tests to determine the moderating effect of environmental uncertainty on this relationship.

(1) The fulfillment of corporate social responsibility (CSR) significantly influences the value of real estate enterprises. A sub-dimensional analysis reveals that fulfilling stakeholder and social welfare responsibilities within CSR positively impacts enterprise value, whereas environmental responsibility does not exert a notable effect. (2) The uncertainty associated with environmental changes profoundly affects the relationship between CSR and the value of real estate enterprises. More precisely, as environmental uncertainty increases, it amplifies the beneficial impact of CSR on enterprise value.

These findings are valuable for real estate enterprises as they navigate the transition towards sustainable development, and they also provide insight for the government in formulating policies aimed at regulating the real estate sector.

This study complements the existing discussion and research on corporate social responsibility (CSR) and enterprise value in the real estate industry, while elucidating the underlying mechanism of how environmental uncertainty mediates the relationship between the two.