Search results

The aim of this study was to conduct a systematic literature review (SLR) on vlog marketing. The focus was to analyse the major themes in this field and provide insights for future research directions.

The authors reviewed a total of 49 peer-reviewed publications that include the search terms “vlog” or “video blog” in their titles, keywords and abstracts, retrieved from digital databases Scopus and Web of Science, up to the end of July 2023. Thematic analysis was used to examine and synthesise the articles.

The authors found 19 sub-themes and identified four major themes that emerged from the literature: (1) endorsement outcomes, (2) vlogger characteristics, (3) consumer credibility and (4) vlog content crafting.

There are many unanswered questions in the literature, suggesting that vlog marketing research is still in its infancy, and that in-depth further studies are required for a more comprehensive understanding of the field. This study has identified potential avenues for future research that may contribute to the existing body of knowledge and valuable insights on vlog marketing.

In order to further optimize the methods of modern urban planning, the philosophical basis, planning theory, planning measures and practice are analyzed, and some discussions are made in connection with China's planning practice. The research results show that the core of modern urban planning is constructed by traditional rationalism with classical physics as its core. Urban planning is both a technology and a social science. Whether it is traditional or modern urban planning, it has been closely linked with the legal system since its birth. It is an important direction to promote the development of urban planning discipline. The most influential rational ideas of city planning are instrumental rationality, bounded rationality and communicative rationality. Instrumental rationality derives from rational comprehensive planning, systematic planning and procedural planning; the separation-gradualism and hybrid inspection model are developed under the influence of bounded rationality and are amendments to instrumental rationality; communication planning, collaborative planning and consultative planning are developed on the basis of communicative rationality, which is one of the important development directions at present.

In real working condition, signal is highly disturbed and even drowned by noise, which extremely interferes in detecting results. Therefore, this paper aims to provide an effective de-noising method for the debris particle in lubricant so that the ultrasonic technique can be applied to the online debris particle detection.

For completing the online ultrasonic monitoring of oil wear debris, the research is made on some selected wear debris signals. It applies morphology component analysis (MCA) theory to de-noise signals. To overcome the potential weakness of MCA threshold process, it proposes fuzzy morphology component analysis (FMCA) by fuzzy threshold function.

According to simulated and experimental results, it eliminates most of the wear debris signal noises by using FMCA through the signal comparison. According to the comparison of simulation evaluation index, it has highest signal noise ratio, smallest root mean square error and largest similarity factor.

The rapid movement of the debris particles, as well as the lubricant temperature, may influence the measuring signals. Researchers are encouraged to solve these problems further.

This paper includes implications for the improvement in the online debris detection and the development of the ultrasonic technique applied in online debris detection.

This paper provides a promising way of applying the MCA theory to de-noise signals. To avoid the potential weakness of the MCA threshold process, it proposes FMCA through fuzzy threshold function. The FMCA method has great obvious advantage in de-noising wear debris signals. It lays the foundation for online ultrasonic monitoring of lubrication wear debris.

This paper aims to provide an effective method so that the ultrasonic technique can be applied to the online debris particle detection. It proposes utilizing the waveshape features in discriminating the debris particle in lubricant.

The finite element model has been developed to investigate the scattering of the ultrasonic waves in lubricant containing single scatterer, such as the debris particle and the air bubble. The simulation results show that the results verify that different scatterers differ in the waveshape features. The static experiments were carried out on a specially fixture. The single spherical debris, long debris and air bubble were measured. The fast Fourier transform (FFT) method was applied to the analysis of the echo signals to obtain the features implicated in the waveshape.

The research of this paper verifies that different scatterers differ both in their shape features and in the FFT analysis features.

The rapid movement of the debris particles as well as the lubricant temperature may influence the measuring signals. Besides, the measuring signals are usually corrupted by noise, especially for the tiny debris. Therefore, researchers are encouraged to solve those problems further.

The paper includes implications for the improvement in the online debris detection and the development of the ultrasonic technique applied in online debris detection.

The paper provides a promising way that the ultrasonic waveshape features can be utilized to the identify debris particle online.

It is our pleasure to present this regular issue of Open House International. In this issue (Vol.44, No. 3, 2019), we selected 33 papers which have gone through several rounds of review and revision, and represent a cross-section of research in building management, construction management, house economics & management, urban planning areas that touch upon both building and housing issues. Open House International is only this outsourced issue supplier as the publisher. This editorial remark also indemnifies the Open House International from any responsibility for the content and presentation of this issue.

Soft grippers have safer and more adaptable human–machine and environment–machine interactions than rigid grippers. However, most soft grippers with single gripping postures have a limited gripping range. Therefore, this paper aims to design a soft gripper with variable gripping posture to enhance the gripping adaptability.

This paper proposes a novel soft gripper consisting of a conversion mechanism and four spring-reinforced soft pneumatic actuators (SSPAs) as soft fingers. By adjusting the conversion mechanism, four gripping postures can be achieved to grip objects of different shapes, sizes and weights. Furthermore, a quasi-static model is established to predict the bending deformation of the finger. Finally, the bending angle of the finger is measured to validate the accuracy of the quasi-static model. The gripping force and gripping adaptability are tested to explore the gripping performance of the gripper.

Through experiments, the results have shown that the quasi-static model can accurately predict the deformation of the finger; the gripper has the most significant gripping force under the parallel posture, and the gripping adaptability of the gripper is highly enhanced by converting the four gripping postures.

By increasing the gripping posture, a novel soft gripper with enhanced gripping adaptability is proposed to enlarge the gripping range of the soft gripper with a single posture. Furthermore, a quasi-static model is established to analyze the deformation of SSPA.

This study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science.

Using publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi.

The health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior.

To the best of the authors’ knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research.

Knowledge sharing is an important way to improve the knowledge system of industrial construction, and the supervision mechanism is an important way to improve the efficiency of knowledge sharing. However, some research works and practices indicate that the effects of applying the supervision mechanism are not obvious. Therefore, the purpose of this paper is to propose an incentive method of knowledge sharing based on the supervision mechanism for promoting knowledge sharing among member enterprises in the industrial construction supply chain.

A basic incentive model and an optimization model of knowledge sharing in the industrial construction supply chain based on the supervision mechanism were developed via the principal–agent theory. Weighted coefficients of explicit and implicit knowledge sharing were introduced into the basic model, while the supervision reward was added into the basic model of the optimization model. The effect of these two models was compared and analyzed via numerical simulation.

The optimal incentive coefficient and effort level of knowledge sharing can be obtained by solving the two aforementioned models. The results of the comparison between the two models indicate that the introduction of a supervisory reward improved the effort level and expected earnings produced by knowledge sharing, but reduced the confirmed equal earnings of member enterprises in the industrial construction supply chain.

Mutual transformation between tacit and explicit knowledge was not considered, and supervisory costs were also not considered, in the estimation of the output of knowledge sharing.

The new models proposed by this study provide theoretical guidance for the design of knowledge sharing incentive measures in the industrial construction supply chain based on the supervision mechanism. The findings suggest that member enterprises should pay attention to the costs of knowledge sharing, in order to obtain more benefits.

This study introduced the weight coefficients of explicit and implicit knowledge sharing into a previous incentive model, proposed an incentive optimization model of knowledge sharing in the industrial construction supply chain based on a supervisory mechanism, and revealed the change rules of related variables that affect the model with the change in weight coefficients. The findings verify the effectiveness of introducing supervisory reward measures and extend the range of theoretical application.

Exploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.

Based on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.

The findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.

Although domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.