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The purpose of this paper is to investigate the influence rule and mechanism of three degrees of freedom film thickness disturbance on the transient performance of spiral groove, upstream pumping spiral groove dry gas seal (UP-SDGS) and double-row spiral groove dry gas seal (DR-SDGS).

The transient performance of spiral groove, UP-SDGS and DR-SDGS are obtained by solving the transient Reynolds equation under different axial and angular disturbance coefficients. The transient and steady performance of the above-mentioned DGSs are compared and analyzed.

The film thickness disturbance has a remarkable impact on the sealing performance of DGS with different structures and the calculation deviations of the leakage rate of the UP-DGS will increase significantly if the film thickness disturbance is ignored. The axial and angular disturbance jointly affect the film thickness distribution of DGS, but there is no significant interaction between them on the transient sealing performance.

The influence mechanism of axial disturbance and angular disturbance on the transient performance of typical SDGSs behavior has been explained by theory. Considering small and large disturbance, the interaction between axial disturbance and angular disturbance on the transient performance have been studied.

The purpose of this paper is to investigate the effect of different PHS on the surface chemistry of fumed silica treated with aminopropyltrimethoxysilane (APTMS).

The reaction conditions involved variation of pH ranging from acidic to alkaline. Different analytical techniques including FT‐IR spectroscopy, thermogravimetric analysis (TGA), CHN and Zeta potential analyses were employed to investigate the surface chemistry of treated particles. In addition, the stability of silanised silica dispersions were studied using turbidimetric and rheometric measurements.

It was revealed that in all conditions silica was more or less chemically grafted by the silane. When the pH of treating bath was adjusted to 1‐2 prior and during the reaction, 58 percent grafting was observed, as obtained by CHN and TGA analyses. At very alkaline conditions, however, the grafting content declined to 29 percent. The variations in grafting were dependent on the silane hydrolysis and its further condensation with the silica surface. Zeta potential measurements showed a drastic change from −7.1 mv to +18.01 mv (at pH 7) for the untreated particle and the one with the highest grafting, respectively. The dispersion stability of differently treated particles varied in solvents with different Hansen solubility parameters (HSP). Moreover, due to the variations of surface chemistry of particles, their rheological behaviours were significantly influenced.

The results obtained in this work showed that the surface chemistry of fume silica could be tuned with treating method. The highest content of grafting led to a better dispersion in solvents having greater hydrogen bonding component and to an inferior dispersion in solvents with higher polar component.

The purpose of this paper is to investigate the relations between the directors' and officers' (D&O) insurance and digital transformation of Chinese-listed companies to provide insights into triggers of digital transformation from the perspective of D&Os' incentive plan.

Based on a panel dataset of 2,590 listed manufacturing companies in China from 2017 to 2020, and using a textual analysis of annual reports, this paper empirically examines the impact of D&O insurance on digital transformation. The authors investigate the mechanism through a mediating model and apply a series of robustness tests including firm fixed effect model, propensity score matching and changing key measures.

The research shows that the digital transformation has been negatively influenced by D&O insurance. The long coverage duration of D&O insurance significantly lowers the level of digital transformation. The moral hazard problem caused by D&O insurance has hampered digital transformation through reducing explorative innovation, while there has been no significant change in innovation quantity. Under the coverage of D&O insurance, firms with worse internal governance and state-owned firms are more reluctant to invest in risky transformation than their counterparts.

Based on a textual analysis of annual reports, this paper empirically tests the influential mechanism of D&O insurance coverage on digital transformation. The authors provide insights into non-tech triggers of digital transformation and uncover how incentive plans influences D&Os' behaviors. This paper provides a new angle to the debate on governance-strengthening and governance-weakening role of D&O insurance.

The present study aims to further research the theory of attractive quality for new offers by analyzing the HWWP (Health, Weapon, Wealth, Prospect) model and testing its uniformity. The purpose is to extend and refine the HWWP model based on meridian elasticity curves with the final scope of building a map for better understanding the potential value of the quality attributes in new product or strategic service design.

After a thorough analysis of the HWWP model for prepurchase value judgment, it has been observed that the classical form often presents a concentration of the quality attributes in its graphic representation, which limits managerial decision making. This paper presents a new methodology for testing the uniformity of the current HWWP model and a generalized approach for understanding the potential lifecycle of the new offer's features.

The results of the presented case study validate the novel tool’s applicability and can serve as a reference for managers to adequately classify customer requirements as the first step toward strategic design.

The author’s main contributions are: to have analyzed the current HWWP model and observed the limitations of this approach; to have proposed a statistical simple method used to test the uniformity of the HWWP model; to have developed a generalized new HWWP model that adequately explores each feature value and potential lifecycle base on meridian slices and elasticity orbits.

This paper aims to determine how the level of logistics service quality facilitates logistics performance in emerging markets. The authors chose Ecuador because it is an emerging economy with relatively stable economic development, making it an attractive research platform in a challenging environment for logistics services. The authors empirically test the influence on performance and one another of five dimensions of service quality: reliability, responsiveness, empathy, assurance and tangibility.

SERVQUAL and partial least squares structural equation modeling was undertaken to test the proposed relationships empirically.

The performance was positively related to assurance, tangibility and reliability but negatively related to the responsiveness and empathy dimensions. The findings suggest the order of priority for improvement actions. The findings highlight that the existing relationships in developed markets do not apply in the same manner in emerging markets.

Although representative, data were only collected in one specific market.

The results reveal a mix of activities that managers should develop to improve the services they provide, relationships with customers and performance.

Few other works have explored logistics service quality in South America's emerging markets. According to contingency theory, various combinations of service quality dimensions can influence performance, suggesting that managers should aim for optimal fit between dimensions according to internal and external situations. An efficient and effective combination in one case may be unsuccessful in another. The approaches presented can improve relationships within global supply chains, especially regarding logistics management.

The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India.

Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location.

Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region.

Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model.

The findings provide valuable results to be considered for controlling air pollution in the region.

The purpose of this paper is to identify the effective measures for heterogeneity and to uncover the relationship between investor heterogeneity and stock returns.

The paper employs dispersion in analysts’ earnings forecasts and unexpected trading volume as proxies of heterogeneity. Portfolio strategies and Fama-Macbeth regression are used to uncover the relationship between the two proxies and stock returns in the Chinese A-share market.

The result indicates that stock returns are significantly related to unexpected trading volume, i.e., higher unexpected trading volume implies higher stock returns now but lower future stock returns. In contrast, there is no statistically significant relationship between analysts’ forecast dispersion and stock returns.

The findings suggest that unexplained trading volume is an effective measure for investor heterogeneity in the Chinese A-share market.

Consistency and consensus are two important research issues in group decision-making (GDM). Considering some drawbacks associated with these two issues in existing GDM methods with intuitionistic multiplicative preference relations (IMPRs), a new GDM method with complete IMPRs (CIMPRs) and incomplete IMPRs (ICIMPRs) is proposed in this paper.

A mathematically programming model is constructed to judge the consistency of CIMPRs. For the unacceptably consistent CIMPRs, a consistency-driven optimization model is constructed to improve the consistency level. Meanwhile, a consistency-driven optimization model is constructed to supplement the missing values and improve the consistency level of the ICIMPRs. As to GDM with CIMPRs, first, a mathematically programming model is built to obtain the experts' weights, after that a consensus-driven optimization model is constructed to improve the consensus level of CIMPRs, and finally, the group priority weights of alternatives are obtained by an intuitionistic fuzzy programming model.

The case analysis of the international exchange doctoral student selection problem shows the effectiveness and applicability of this GDM method with CIMPRs and ICIMPRs.

First, a novel consistency definition of CIMPRs is presented. Then, a consistency-driven optimization model is constructed, which supplements the missing values and improves the consistency level of ICIMPRs simultaneously. Therefore, this model greatly improves the efficiency of consistency improving. Experts' weights determination method considering the subjective and objective information is proposed. The priority weights of alternatives are determined by an intuitionistic fuzzy (IF) programming model considering the risk preference of experts, so the method determining priority weights is more flexible and agile. Based on the above theoretical basis, a new GDM method with CIMPRs and ICIMPRs is proposed in this paper.

The purpose of this study is to explore how digital transformation helps enterprises achieve high-quality development, including the mediating mechanism of information transparency, innovation capacity and financial stability, the moderating role of financing constraints and government subsidies, and the heterogeneous effects of property rights, size and growth.

This study conducts two-way fixed-effect model using 780 samples of China's Shanghai-Shenzhen A-share listed companies from 2012 to 2019.

The results show that digital transformation can effectively improve the total factor productivity (TFP) of enterprises through the triple channels of information transparency, innovation capability and financial stability. Meanwhile, financing constraints significantly inhibited the contribution of digital transformation to TFP, while government subsidies significantly increased the contribution of digital transformation to TFP. In addition, state-owned enterprises (SOEs), large enterprises and high-growth enterprises are more able to achieve high-quality development by increasing their digital transformation.

In the process of implementing digital transformation, companies should actively improve information transparency, financial stability and innovation capabilities, and choose differentiated paths based on intrinsic characteristics such as property rights, scale and growth. At the same time, the government should actively improve not only the digital institutional environment but also the financial policy and credit system.

This study enriches the theoretical research framework of digital transformation and high-quality development by identifying the channel mechanisms and boundary conditions through which digital transformation affects high-quality development and expands the consequences of digital transformation and the antecedents of high-quality development.

Focusing on municipalities, this study aims to examine whether citizens’ engagement with local public administration activities on Facebook can have a positive effect on citizens’ trust.

Using data from 333 citizens and resorting to structural equation modelling, a conceptual model is tested.

The results show that communicating directly with citizens through social media can enhance the citizens’ involvement in social issues and their identification with their city council. The effect of citizen engagement on trust propensity is mediated by citizens’ identification with the city council and by citizens’ involvement in social issues.

The study provides a conceptual model that can be used by practitioners to improve practices that enhance citizen engagement and build trust in the local government. City councils should promote activities on social media that encourage identification and citizens’ involvement. Furthermore, the findings suggest that municipalities can increase trust by involving citizens in social issues.

This study contributes to a better understanding of the government social media phenomenon, highlighting and empirically testing the effect of citizen engagement on institutional trust. In doing so, a process to build citizens’ trust in their city council through social media is unpacked. The findings show that communicating directly with citizens through social media can enhance the citizens’ involvement in social issues and their identification with the city council. The important role of identification to build institutional trust is emphasized.