Search results

Nowadays, online platforms which provide products or services try to implement their homegrown communities to facilitate users' social interactions. Reviewers' activities in these communities can reflect their interests. Based on the theory of homophily, the authors aim to explore the impacts of the reviewer preference similarity and opinion similarity on the rate of product diffusion.

First, the authors construct reviewer similarity network based on their common interests and propose typical network metrics to measure reviewer preference similarity. Second, the authors measure reviewer opinion similarity with natural language processing. Finally, based on a panel data from an online video platform in China, both the fixed-effect and random-effect panel data models are constructed.

The authors find that reviewer preference similarity has a positive effect on the product diffusion, whereas reviewer opinion similarity has a negative effect on the diffusion. Furthermore, temporal distance moderates the relationship between reviewer similarity and the product diffusion. As a double-edged sword, review preference similarity hinders product diffusion in the initial phase, whereas benefits it in the later phase. Reviewer opinion similarity is always detrimental to product diffusion, especially in the initial phase.

This paper extends the understanding of homophily from the micro peer level to the group level by constructing reviewers' similarity network and highlights the important role of reviewer preference similarity and opinion similarity in product diffusion. The results also provide important insights for managers to design and implement diversity strategies for better product adoption in the community context.

The purpose of this paper is to develop the efficiency of styrene-acrylate (SA) emulsions for polymer cement waterproof coatings with improved bacteria resistance and mechanical properties.

For effective bacteria resistance and excellent mechanical properties, various concentrations of methacryloxyethylhexadecyl dimethylammonium bromide (MHDB) were synthesised and incorporated into SA emulsions. The properties of SA emulsions modified with MHDB were characterised and compared with those of unmodified ones according to the formulations of polymer cement waterproof coatings.

The SA emulsions modified with MHDB exhibited significant enhancement of bacteria resistance and mechanical properties over the unmodified ones. The positive quaternary nitrogen and long-chain alkyl groups of MHDB in SA emulsions could attract phospholipid head groups of bacterial and insert them into the cell wall, which results in biomass leak and bactericidal effect. Moreover, MHDB as a softened monomer was beneficial to the synthesis of SA copolymer with low glass-transition temperature (T_g), then the copolymer and cement would form a more compact film which was the main reason for the enhancement of mechanical properties.

The modifier MHDB was synthesised from diethylaminoethyl methacrylate (DEAM) and 1-bromohexadecane. Besides, the congeners of MHDB could be synthesised from DEAM and 1-bromododecane, 1-tetradecyl dromide, 1-octadecyl bromide, etc. In addition, the efficiency of other modifications into SA emulsions for antibacterial polymer cement waterproof coatings could be studied as well.

The method provided a practical solution for the improvement of water-based antibacterial acrylate polymer cement waterproof coatings.

The method for enhancing bacteria resistance and mechanical properties of the waterproof coating was novel and valuable.

The purpose of this paper is to examine the volatility spillover and lead-lag relationship between the Chicago Board Options Exchange volatility index (VIX) and the major agricultural future markets before and during the Coronavirus disease 2019 (COVID-19) outbreak.

The methods used were the vector autoregression-Baba, Engle, Kraft and Kroner-generalized autoregressive conditional heteroskedasticity method, the Wald test and wavelet transform method.

The findings indicate that prior to the COVID-19 outbreak, there was a two-way volatility spillover impact between the majority of the sample markets. In comparison, volatility transmission between the VIX index and the agricultural future market was significantly lower following the COVID-19 outbreak, the authors observed greater coherence at higher frequencies than at lower frequencies, implying that the interdependence between the two VIX indices and the agricultural future market was stronger over a longer time-frequency domain and the VIX’s signalling effect on various agricultural future prices after the COVID-19 outbreak was significantly lower.

The authors conducted the first comprehensive investigation of the VIX’s correlation with major agricultural futures, especially during COVID-19. The findings contribute to a better understanding of the risk transmission mechanism between the VIX and major agricultural commodities futures contracts. And our findings have significant implications for investors and portfolio managers, as well as for policymakers who are concerned about the price of agricultural futures.

This study discusses the tracking trajectory issue of the exoskeleton under the bounded disturbance and designs an useful tracking trajectory control method to solve it. By using the proposed control method, the tracking error can be successfully convergence to the assigned boundary. Meanwhile, the chattering effect caused by the actuators is already reduced, and the tracking performance of the pneumatic artificial muscles (PAMs) elbow exoskeleton is improved effectively.

A prescribed performance sliding mode control method was developed in this study to fulfill the joint position tracking trajectory task on the elbow exoskeleton driven by two PAMs. In terms of the control structure, a dynamic model was built by conforming to the adaptive law to compensate for the time variety and uncertainty exhibited by the system. Subsequently, a super-twisting algorithm-based second-order sliding mode control method was subjected to the exoskeleton under the boundedness of external disturbance. Moreover, the prescribed performance control method exhibits a smooth prescribed function with an error transformation function to ensure the tracking error can be finally convergent to the pre-designed requirement.

From the theoretical perspective, the stability of the control method was verified through Lyapunov synthesis. On that basis, the tracking performance of the proposed control method was confirmed through the simulation and the manikin model experiment.

As revealed by the results of this study, the proposed control method sufficiently applies to the PAMs elbow exoskeleton for tracking trajectory, which means it has potential application in the actual robot-assisted passive rehabilitation tasks.

This paper aims to mainly discuss how to suppress the disturbances accurately and effectively in the wind energy conversion system (WECS) of the direct drive surface mount permanent magnet synchronous generator (SPMSG).

The disturbances in wind energy conversion system have seriously negative influence on the maximum power tracking performance. Therefore, a model predictive control (MPC) method of model compensation active disturbance rejection control (ADRC) strategy in parallel connection is designed, which optimizes the speed tracking performance compared with the existing control strategy of MPC and ADRC in series connection. Based on the traditional ADRC, a multi parameter model compensation ADRC strategy is added to better estimate the disturbances. At the same time, a torque feedback strategy is added to compensate the disturbances caused by load torque and further optimize the speed loop tracking performance.

The simulation results show that the designed control method has advantages than the traditional control method in compensating the disturbances and tracking the maximum power more effectively.

The simulation results show that the designed control method is superior to the traditional proportional control method, which can better compensate the internal and external disturbances and track the maximum power more effectively.

Green innovation strategy is not only a new idea to achieve green development but also the inevitable choice for enterprises to upgrade. At present, the research on the driving forces of green innovation strategy mainly focus on direct impact of single factor, lacking the overall consideration of internal and external environment. At the same time, research on the contingency effect of top management’s environmental awareness is scarce. This paper aims to explore how external environment pressures (policy pressures and market pressures) and internal environment driving force (innovation resources and innovation capability) make enterprises to choose green innovation strategy with moderating effect of top management’s environmental awareness.

Based on the sample of 216 enterprises, this paper explores the relationship between policy pressure, market pressure, innovation resources, innovation capability and the green innovation strategy with moderating effect of top management’s environmental awareness from inside and outside driving angle.

The results of the hierarchical regression model show, first, the driving effect of factors in the external environment. The coercive policy has an inverted U-shaped impact on the green innovation strategy. The incentive policy and the market pressure both have a significant positive impact on the green innovation strategy. Second, the driving effect of factors in the internal environment. The innovation capability has a significant positive impact on the green innovation strategy. The innovation resources have no significant impact on the green innovation strategy. Third, the moderating effect of top management’s environmental awareness. The relationship between the green innovation strategy and the coercive policy is stronger when the top management’s environmental awareness higher. The relationship between the green innovation strategy and the market pressure is stronger when the top management’s environmental awareness higher. The relationship between the green innovation strategy and the innovation resources is stronger when the top management’s environmental awareness higher. Otherwise, the relationship between the green innovation strategy and the innovation capability is weaker when the top management’s environmental awareness higher. And there is no significant change about the relationship between the green innovation strategy and the incentive policy when the top management’s environmental awareness higher.

First, the authors have promoted the integrated research on the drivers of the enterprise’s green innovation strategy. From the perspective of internal and external environment driving forces, this paper analyzes the key factors influencing the decision-making of the green innovation strategy. Second, the study has contributed to the strategic choice theory. This paper studies the driving mechanism of the green innovation strategy from a new perspective of the strategic choice theory.

The purpose of this paper is to enable autonomous door-opening with unknown geometrical constraints. Door-opening is a common action needed for mobile manipulators to perform rescue operation. However, it remains difficult for them to handle it in real rescue environments. The major difficulties of rescue manipulation involve contradiction between unknown geometrical constraints and limited sensors because of extreme physical constraints.

A method for estimating the unknown door geometrical parameters using coordinate transformation of the end-effector with visual teleoperation assists is proposed. A trajectory planning algorithm is developed using geometrical parameters from the proposed method.

The relevant experiments are also conducted using a manipulator suited to extreme physical constraints to open a real door with a locked latch and unknown geometrical parameters, which demonstrates the validity and efficiency of the proposed approach.

This is a novel method for estimating the unknown door geometrical parameters with coordinate transformation of the end-effector through visual teleoperation assists.

The purpose of this paper is to review the literature on information technology adoption in organizations to understand the need of integrated models for technology adoption. It further makes an attempt to identify key parameters to integrate technology acceptance model (TAM) and technology-organization-environment (TOE) framework for firm level technology adoption. This integration is intended to improve predictive power of resulting model.

The research papers are accessed from the popular databases from 2000 to 2012. The selected papers have addressed technology adoption in context of recent technologies such as e-commerce, ERP, RFID, EDI and knowledge management, etc. The paper attempts to review the studies based on TAM model and TOE framework to identify relevant set of variables for the adoption of these technologies in organizations.

TAM and its extended versions have high capability to explain the technology adoption while the significance of TOE framework is similarly recognized in explaining technology adoption. This review presents a holistic picture of a set of variables which can be used in the adoption of similar technologies in future. Further, the study has advocated the integration of TAM model and TOE framework to improve their explanatory power in technology adoption. The identified set of variables of TAM model and TOE framework can be used to integrate the two. Guidelines for integrating the two are also explained.

This study provides a platform for studying adoption of similar technologies using integration of TAM and TOE.

The researchers and managers can use the set of variables identified for adoption of similar technologies in organizations.

The review presents a set of variables which can be used to study adoption of similar technologies in future.

The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil.

Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula.

It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value.

The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.

The increasing social media use has been widely recognized for its adverse effects, such as social media fatigue. With the continuously increasing friends on social media, the dissimilarity of individuals in terms of age, personality, and values has increased. It is unclear whether perceived dissimilarity with others is associated with social media fatigue. The authors attempted to bridge this gap by constructing a “perception–emotion–behavioral” research framework. This study investigated the influence of individual perceived dissimilarity on social media fatigue. The authors further investigated the mechanisms mediating the three dimensions of social anxiety in the model.

This study examined the mechanisms by which individual perceived dissimilarity influences social media fatigue, particularly using WeChat application. A field survey study conducted in China with 408 subjects of WeChat app users was used in this study to analyze the study model.

The obtained results demonstrate that individual perceived dissimilarity has a significant positive effect contributing to social media fatigue, perceived dissimilarity is positively correlated to social anxiety. Social anxiety positively affects social media fatigue, and social anxiety partially mediates the positive effect between perceived dissimilarity and social media fatigue.

First, the study confirmed the influence of perceived dissimilarity on social media fatigue, which may enrich the antecedent mechanisms of social media fatigue. Second, the authors demonstrated the social anxiety-mediated development of fatigue. The findings provide an in-depth understanding of users' fatigue. Third, the findings of this study provide valuable insights for preventing of social media fatigue.