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As an important participant in capital market, institutional investors play a principal role in improving corporate governance. Most existing studies have focused on institutional ownership and its economic consequences. Nevertheless, they have not provided sufficient insight on the governance behavior of institutional investors as well as the underlying incentive mechanism. This paper aims to analyze the governance role of institutional investors in information disclosure and provide related evidence.

The authors propose a novel theory to analyze the institutional investors’ behavior of active governance and shows that such behavior significantly improves the quality of corporate information disclosure. The authors then conduct an empirical test by using the hand-collected data of institutional investors’ corporate visits during 2009-2014 in ChiNext.

This paper finds that the firms visited by institutional investors are more likely to have a greater tendency of disclosing more information than the firms that have never been visited. In particular, a higher frequency of visits or a larger number of participating institutional investors leads to a higher degree of disclosure. Consistent with the notion that on-site visits endow institutional investors with more frequent and active interaction with the firms, the authors find that the results are stronger for firms which are visited on-site, when compared with other information acquisition activities such as online meetings, conference calls and investor meetings. In addition, the effect of a site visit is greater when the site visit is conducted by securities companies or funds rather than insurance companies or QFIIs. Finally, the test of the direction of causality suggests that visits conducted by institutional investors leads to more information disclosure, rather than the reverse. Collectively, these results show that institutional investors’ participation enhances corporate information disclosure.

This paper explores the internal mechanism that institutional investors affect corporate governance by improving information disclosure through their corporate visits. This is the first study to investigate the influence of institutional investors’ corporate visits and their economic consequences.

This paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately.

The initial weights and thresholds of BP neural network are improved by genetic algorithm on MATLAB 2014 a platform.

Genetic algorithm–back propagation (GA-BP) neural network is more stable. The generalization performance of the complex is better.

The GA-BP neural network based on the training sample data can better realize the strength prediction of recycled aggregate thermal insulation concrete and reduce the complex orthogonal experimental process. GA-BP neural network is more stable. The generalization performance of the complex is better.

Since its inception in 2009, the growth of real-time bidding (RTB) advertising has been dramatic. Yet, there is a dearth of research in the information system (IS) literature despite the potential for negative e-commerce outcomes. The purpose of this paper is to identify salient antecedents of users’ attitude toward RTB advertisements.

A research model was constructed and tested with data from 437 respondents. SmartPLS 3.0, a partial least square (PLS) structural equation modeling (SEM) tool, was used to evaluate the research model and test the hypotheses.

The findings indicate that user attitude is determined by opposing influences from the cognitive and affective attributes of an RTB advertisement. A surprise is found to elicit greater perception of advertisement personalization, timeliness and relevance, as well as privacy and intrusiveness concerns. While RTB advertisement relevance appears to lessen the effect of advertisement intrusiveness, privacy concern is exacerbated when the advertisement is more personalized. The authors discuss the implications of this study for click-through intentions and e-commerce.

At this point in the evolution of RTB advertising, the findings indicate that the surprise generated by the appearance of an RTB advertisement is not currently a “bad” surprise. In addition, the formation of positive user attitude toward RTB is complex because cognitive factors interact with users' concerns to strengthen or weaken the negative effects. The authors also demonstrate that attitude and stimulus–organism–response (S–O–R) theories are useful theoretical bases for the development of causal models to predict RTB attitude and click-through intentions.

This study aims to report the preparation, selective laser sintering (SLS) processing and properties of a new nylon elastomer powder. The effects of solvent, dissolution temperature and time and cooling method and speed on the particle size and morphologies of the prepared nylon elastomer powder are investigated.

The prepared nylon elastomer power possesses the particle size of around 50 mm and is spherical in shape, indicating that this study provides the feasible dissolution-precipitation process, a distillation cooling method and a suitable solvent to prepare nylon elastomer powders.

Compared to pure nylon 12, the nylon elastomer has a lower part bed temperature and a wider sintering window for the SLS process. The wider sintering window indicates the better SLS processibility. The lower part bed temperature is beneficial to the recycling of material and the decrease in the requirement of SLS equipment.

The nylon elastomer in this study has a lower part bed temperature and a wider sintering window for the SLS process. The wider sintering window indicates better SLS processibility. The lower part bed temperature is beneficial to the recycling of material and the decrease in the requirement of SLS equipment.

The purpose of this paper is to investigate the effect of selective laser sintering (SLS) method on morphology and performance of polyamide 12.

Crystallization behavior is critical to the properties of semi-crystalline polymers. The crystallization condition of SLS process is much different from others. The morphology of polyamide 12 produced by SLS technology was investigated using scanning electron microscopy, polarized light microscopy, differential scanning calorimetry, X-ray diffraction and wide-angle X-ray diffraction.

Too low fill laser power brought about bad fusion of powders, while too high energy input resulted in bad performance due to chain scission of macromolecules. There were three types of crystal in the raw powder material, denoted as overgrowth crystal, ring-banded spherulite and normal spherulite.

In this work, SLS samples with different sintering parameters, as well as compression molding sample for the purpose of comparison, were made to study the morphology and crystal structure of sintered PA12 in detail.

The purpose of this study is to fabricate and compare the mechanical and thermal properties of Sansevieria and Kaans fiber reinforced polyester matrices composites.

Treated Sansevieria and Kaans fiber was used as reinforcement for the fabrication of polymer matrix composites. Kaans fiber, which was available plenty in the delta region, but physical and mechanical properties of Kaans fiber were low when it compared with Sansevieria fiber. To make use of Kaans fiber for the fabrication of composite, the physical and mechanical properties have to be enhanced. So Egg shell powder was selected as a filler material to enhance the Kaans fiber reinforced composite. The selected fibers were properly weaved after alkali treatment. A three-layered (0°/45°/0°) Sansevieria fiber reinforced polymer (S-FRP) and Kaans fiber reinforced polymer (K-FRP) composite plates were fabricated using the compression molding method. As per American Society for Testing and Materials standards, the specimens were cut and mechanical, thermal and absorption properties of Sansevieria and Kaans fiber composites were investigated experimentally.

Tensile and flexural test reveals that K-FRP composite has good ductility and bending property than S-FRP composite plate. But from the other test results, S-FRP possesses high elongation capability than K-FRP. Thermo gravimetric analysis, moisture absorption and swelling test too done which clearly appeared S-FRP composite plate has prevalent execution than K-FRP composite plate.

This original research study enlists the mechanical, thermal properties and absorption properties of fabricated S-FRP and K-FRP composite plates.

Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.

To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.

Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.

This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.