Qing Guo, H. Holly Wang and Yongjun Chen
The purpose of this paper is to investigate market power in dairy industry in China. Specifically, we analyze market power for different firm size, locations of region and city…
Abstract
Purpose
The purpose of this paper is to investigate market power in dairy industry in China. Specifically, we analyze market power for different firm size, locations of region and city empirically.
Design/methodology/approach
We estimate the market power by controlling the unobserved price heterogeneity. The econometric model was developed through a typical production function. We added three dummy variables to differentiate firms of different sizes, at urban or rural locations, and in east or other regions, according to the characteristics of the dairy industry. A sample including 511 observations were used to do the regression.
Findings
Our results show that Chinese dairy industry as a whole is a competitive industry in general,while the large firms have gained considerable market power. The firms locate in the eastern area grow slower than firms locate in the middle and western area.
Originality/value
The authors believe that this is the first study to analyze the market power in China’s dairy industry by controlling the unobserved price heterogeneity. Dairy is usually thought to be competitive, while in our paper we found that large firms can exercise market power while small firms operate in a competitive market.
Jia Wang, Haiyang Sun, Ding Chen, Yongjun Huang, Tao Dong, Hai Li, Lingnan Shen and Ziyu Yang
The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It…
Abstract
Purpose
The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array.
Design/methodology/approach
First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments.
Findings
The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects.
Research limitations/implications
Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects.
Practical implications
It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions.
Social implications
The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials.
Originality/value
A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.
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Hamza Saleem, Yongjun Li, Zulqurnain Ali, Muhammad Ayyoub, Yu Wang and Aqsa Mehreen
This paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates…
Abstract
Purpose
This paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates the association between BDU and firm performance. Additionally, this research also seeks to explore the moderating effect of information sharing in the association between BDU and technological innovation.
Design/methodology/approach
Using survey methods and structural associations in AMOS 24.0., the proposed model was tested on SME managers recruited from the largest economic and manufacturing hub of China, Pearl River Delta.
Findings
The findings suggest that BDU is positively related to technological innovation (product and process) and organizational outcomes (e.g., supply chain and SMEs performance). Technological innovation (i.e., product and process) significantly mediates the association between BDU and organizational outcomes. Moreover, information sharing positively moderates the association between BDU and technological innovations.
Practical implications
This research provides deeper insights into how BDU is useful for SME managers in achieving the firm’s goals. Particularly, SME managers can bring technological innovation into their business processes, overcome the challenges of forecasting, and generate dynamic capabilities for attaining the best SMEs’ performance. Additionally, BDU with information sharing enables SMEs reduce their risk and decrease production costs in their manufacturing process.
Originality/value
Firms always need to adopt new ways to enhance their productivity using available resources. This is the first study that contributes to big data and performance management literature by exploring the moderating and mediation mechanism of information sharing and technological innovation respectively using RBVT. The study and research model enhances our insights on BDU, information sharing, and technological innovation as valuable resources for organizations to improve supply chain performance, which subsequently increases SME productivity. This gap was overlooked by previous researchers in the domain of big data.
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Yongjun Jin, Haihang Cui, Li Chen, Kai Sun, Haiguo Yin and Zhe Liu
This study aims to perform flow simulations inside the acinus with fine alveolar pores (Kohn pores) using hexagonal cells and bottom-up geometric modeling, which enabled the…
Abstract
Purpose
This study aims to perform flow simulations inside the acinus with fine alveolar pores (Kohn pores) using hexagonal cells and bottom-up geometric modeling, which enabled the elimination of invalid voids using previous top-bottom methods and spherical or circular cells.
Design/methodology/approach
Regular hexagonal cells were used to construct alveoli with no gaps via tessellation. Some hexagonal cells were fused to eliminate the inner boundaries to represent the structure of the bronchial tree. For the remaining hexagonal cells, the side lengths of the shared walls were adjusted to construct alveolar pores. Periodic moving boundaries with the same phase were set for all walls to describe synchronous contraction and expansion of the bronchi and alveoli.
Findings
More realistic flow characteristics in the distal lung were obtained. The effects of pore size and the mechanism of auxiliary ventilation of alveolar pores were revealed.
Originality/value
To the best of the authors’ knowledge, this is the first numerical simulation study on the function of multiple alveolar pores at the level of pulmonary acini, which will be helpful for simulating the dynamic process of cough and sputum excretion in the future.
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Yinglong Chen, Wenshuo Li and Yongjun Gong
The purpose of this paper is to estimate the deformation of soft manipulators caused by obstacles accurately and the contact force and workspace can be also predicted.
Abstract
Purpose
The purpose of this paper is to estimate the deformation of soft manipulators caused by obstacles accurately and the contact force and workspace can be also predicted.
Design/methodology/approach
The continuum deformation of the backbone of the soft manipulator under contact is regarded as two constant curvature arcs and the curvatures are different according to the fluid pressure and obstacle location based on piecewise constant curvature framework. Then, this study introduces introduce the moment balance and energy conservation equation to describe the static relationship between driving moment, elastic moment and contact moment. Finally, simulation and experiments are carried out to verify the accuracy of the proposed model.
Findings
For rigid manipulators, environmental contact except for the manipulated object was usually considered as a “collision” which should be avoided. For soft manipulators, an environment is an important tool for achieving manipulation goals and it might even be considered to be a part of the soft manipulator’s end-effector in some specified situations.
Research limitations/implications
There are also some limitations to the presented study. Although this paper has made progress in the static modeling under environmental contact, some practical factors still limit the further application of the model, such as the detection accuracy of the environment location and the deformation of the contact surface.
Originality/value
Based on the proposed kinematic model, the bending deformation with environmental contact is discussed in simulations and has been experimentally verified. The comparison results show the correctness and accuracy of the presented SCC model, which can be applied to predict the slender deformation under environmental contact without knowing the contact force.
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Yongjun Jin, Haihang Cui, Li Chen, Zhe Liu and Kai Sun
The purpose of this paper is to study the mechanism of efficient sputum excretion from the distal lung by using a tessellationally distal lung model with alveolar pores.
Abstract
Purpose
The purpose of this paper is to study the mechanism of efficient sputum excretion from the distal lung by using a tessellationally distal lung model with alveolar pores.
Design/methodology/approach
First, a two-dimensional tessellational composite structure of the bronchus, alveoli and alveolar pores (Kohn pore) is constructed with the tessellational splitting and fusion of regular hexagonal elements. Then, the level set method is used to study the effects of alveolar pores and their sizes, expiratory cycles and respiratory intensity.
Findings
The existence of alveolar pores is the prerequisite for sputum excretion, and there is an optimal size of alveolar pores for sputum excretion. Strong asymmetric respiration can break the reversibility of the flow at a low Reynolds number and causes significant net displacement of sputum. The expiratory cycle is negatively correlated with the net displacement of sputum. The respiratory intensity is positively correlated with the net displacement of sputum.
Originality/value
This research is helpful for understanding the complex sputum excretion process in diseases, such as pneumonia, and developing corresponding adjuvant therapy.
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Meen Chul Kim, Yuanyuan Feng and Yongjun Zhu
Library Hi Tech is one of the most influential journals that publish leading research in library and information science (LIS). The present study aims to understand the scholarly…
Abstract
Purpose
Library Hi Tech is one of the most influential journals that publish leading research in library and information science (LIS). The present study aims to understand the scholarly communication in Library Hi Tech by profiling its historic footprint, emerging trends and knowledge diffusion.
Design/methodology/approach
A total of 3,131 bibliographic records between 1995 and 2018 were collected from the Web of Science. Text mining, graph analysis and data visualization were used to analyze subject category assignment, domain-level citation trends, co-occurrence of keywords, keyword bursts, networks of document co-citation and landmark articles.
Findings
Findings indicated that published research in the journal was largely influenced by the psychology, education and social domain as a unidisciplinary discipline. Knowledge of the journal has been disseminated into multiple domains such as LIS, computer science and education. Dominant thematic concentrations were also identified: (1) library services in academic libraries and related to digital libraries, (2) adoption of new information technologies and (3) information-seeking behavior in these contexts. Additionally, the journal has exhibited an increased research emphasis on mixed-method user-centered studies and investigations into libraries' use of new media.
Originality/value
This study provides a promising approach to understand scientific trends and the intellectual growth of journals. It also helps Library Hi Tech to become more self-explanatory with a detailed bibliometric profile and to identify future directions in editorship and readership. Finally, researchers in the community can better position their studies within the emerging trends and current challenges of the journal.
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Deyong Ma and Yongjun Ma
The purpose of this paper is to test if the digital economy improves the quality of life of our residents. Furthermore, if this finding is confirmed, what would be the mechanism…
Abstract
Purpose
The purpose of this paper is to test if the digital economy improves the quality of life of our residents. Furthermore, if this finding is confirmed, what would be the mechanism behind its effect? Does the impact of the digital economy on quality of life vary according to its level of development?
Design/methodology/approach
A comprehensive index of the digital economy, income gap and quality of life was constructed empirically based on data from 220 cities in China from 2011–2020. A multi-dimensional empirical analysis was conducted in this paper.
Findings
The analysis of the pathways of action shows that narrowing the income gap is an important mechanism through which the digital economy actively contributes to the quality of life. The results of the threshold model show that the “marginal effect” of the digital economy on quality of life is non-linear and increasing. The results show that after a series of robustness tests, including instrumental variables, the digital economy still significantly enhances people’s quality of life.
Research limitations/implications
This paper reveals the intrinsic link between the digital economy and quality of life and provides a theoretical basis for further improving people’s well-being.
Practical implications
Encouraging the development of the digital economy is a useful way to improve the quality of life by narrowing the income gap.
Originality/value
Data analysis of the digital economy from 2011–2020 in China to get an insight into what would be the mechanism behind the digital economy improving the quality of life of our residents.
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Yongjun Zhu, Woojin Jung, Fei Wang and Chao Che
Drug repurposing involves the identification of new applications for existing drugs. Owing to the enormous rise in the costs of pharmaceutical R&D, several pharmaceutical…
Abstract
Purpose
Drug repurposing involves the identification of new applications for existing drugs. Owing to the enormous rise in the costs of pharmaceutical R&D, several pharmaceutical companies are leveraging repurposing strategies. Parkinson's disease is the second most common neurodegenerative disorder worldwide, affecting approximately 1–2 percent of the human population older than 65 years. This study proposes a literature-based drug repurposing strategy in Parkinson's disease.
Design/methodology/approach
The literature-based drug repurposing strategy proposed herein combined natural language processing, network science and machine learning methods for analyzing unstructured text data and producing actional knowledge for drug repurposing. The approach comprised multiple computational components, including the extraction of biomedical entities and their relationships, knowledge graph construction, knowledge representation learning and machine learning-based prediction.
Findings
The proposed strategy was used to mine information pertaining to the mechanisms of disease treatment from known treatment relationships and predict drugs for repurposing against Parkinson's disease. The F1 score of the best-performing method was 0.97, indicating the effectiveness of the proposed approach. The study also presents experimental results obtained by combining the different components of the strategy.
Originality/value
The drug repurposing strategy proposed herein for Parkinson's disease is distinct from those existing in the literature in that the drug repurposing pipeline includes components of natural language processing, knowledge representation and machine learning for analyzing the scientific literature. The results of the study provide important and valuable information to researchers studying different aspects of Parkinson's disease.
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Hui Zhai, Wei Xiong, Fujin Li, Jie Yang, Dongyan Su and Yongjun Zhang
The prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for…
Abstract
Purpose
The prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for gas dispatch and reduce the production cost of enterprises.
Design/methodology/approach
In this paper, a new method using the ensemble empirical mode decomposition (EEMD) and the back propagation neural network is proposed. Unfortunately, this method does not achieve the ideal prediction. Further, using the advantages of long short-term memory (LSTM) neural network for long-term dependence, a prediction method based on EEMD and LSTM is proposed. In this model, the gas consumption series is decomposed into several intrinsic mode functions and a residual term (r(t)) by EEMD. Second, each component is predicted by LSTM. The predicted values of all components are added together to get the final prediction result.
Findings
The results show that the root mean square error is reduced to 0.35%, the average absolute error is reduced to 1.852 and the R-squared is reached to 0.963.
Originality/value
A new gas consumption prediction method is proposed in this paper. The production data collected in the actual production process is non-linear, unstable and contains a lot of noise. But the EEMD method has the unique superiority in the analysis data aspect and may solve these questions well. The prediction of gas consumption is the result of long-term training and needs a lot of prior knowledge. Relying on LSTM can solve the problem of long-term dependence.