Jihong Chen, Renjie Zhao, Wenjing Xiong, Zheng Wan, Lang Xu and Weipan Zhang
The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter…
Abstract
Purpose
The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.
Design/methodology/approach
The paper used the vector error correction model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.
Findings
The conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.
Originality/value
This paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.
Details
Keywords
The purpose of this paper is to develop some grey models to analyze and control the poor information systems, or grey systems.
Abstract
Purpose
The purpose of this paper is to develop some grey models to analyze and control the poor information systems, or grey systems.
Design/methodology/approach
The grey system theory has been a more widespread application in recent years and the authors have solved many forecast problems of incomplete information with it. However, the establishment of gray control models still needs certain prerequisites.
Findings
Based on incomplete information or poor information, by using the viewpoint of the grey system theory and the integral generation operation in this paper, six kinds of grey control models have been established.
Research limitations/implications
The paper offers very useful advice for incomplete (or poor) information control.
Originality/value
The paper is aimed at control engineers and offers a new approach to the optimal choice of information control models.
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Keywords
Yingying Yu, Wencheng Su, Zhangping Lu, Guifeng Liu and Wenjing Ni
Spatial olfactory design in the library appears to be a practical approach to enhance the coordination between architectural spaces and user behaviors, shape immersive activity…
Abstract
Purpose
Spatial olfactory design in the library appears to be a practical approach to enhance the coordination between architectural spaces and user behaviors, shape immersive activity experiences and shape immersive activity experiences. Therefore, this study aims to explore the association between the olfactory elements of library space and users’ olfactory perception, providing a foundation for the practical design of olfactory space in libraries.
Design/methodology/approach
Using the olfactory perception semantic differential experiment method, this study collected feedback on the emotional experience of olfactory stimuli from 56 participants in an academic library. From the perspective of environmental psychology, the dimensions of pleasure, control and arousal of users’ olfactory perception in the academic library environment were semantically and emotionally described. In addition, the impact of fatigue state on users’ olfactory perception was analyzed through statistical methods to explore the impact path of individual physical differences on olfactory perception.
Findings
It was found that users’ olfactory perception in the academic library environment is likely semantically described from the dimensions of pleasure, arousal and control. These dimensions mutually influence users’ satisfaction with olfactory elements. Moreover, there is a close correlation between pleasure and satisfaction. In addition, fatigue states may impact users’ olfactory perception. Furthermore, users in a high-fatigue state may be more sensitive to the arousal of olfactory perception.
Originality/value
This article is an empirical exploration of users’ perception of the environmental odors in libraries. The experimental results of this paper may have practical implications for the construction of olfactory space in academic libraries.
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Yamin Xie, Zhichao Li, Wenjing Ouyang and Hongxia Wang
Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political…
Abstract
Purpose
Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.
Design/methodology/approach
Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.
Findings
Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.
Originality/value
Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.
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Wenjing Wu, Caifeng Wen, Qi Yuan, Qiulan Chen and Yunzhong Cao
Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the…
Abstract
Purpose
Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.
Design/methodology/approach
The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.
Findings
The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.
Originality/value
The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.
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Bingzi Jin and Xiaojie Xu
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly…
Abstract
Purpose
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.
Design/methodology/approach
In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.
Findings
Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.
Originality/value
Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.
Details
Keywords
Xuesong Cao, Xican Li, Wenjing Ren, Yanan Wu and Jieya Liu
This study aims to improve the accuracy of hyperspectral estimation of soil organic matter content.
Abstract
Purpose
This study aims to improve the accuracy of hyperspectral estimation of soil organic matter content.
Design/methodology/approach
Based on the uncertainty in spectral estimation, 76 soil samples collected in Zhangqiu District, Jinan City, Shandong Province, were studied in this paper. First, the spectral transformation of the spectral data after denoising was carried out by means of 11 transformation methods such as reciprocal and square, and the estimation factor was selected according to the principle of maximum correlation. Secondly, the grey weighted distance was used to calculate the grey relational degree between the samples to be estimated and the known patterns, and the local linear regression estimation model of soil organic matter content was established by using the pattern samples closest to the samples to be identified. Thirdly, the models were optimized by gradually increasing the number of modeling samples and adjusting the decision coefficient, and a comprehensive index was constructed to determine the optimal predicted value. Finally, the determination coefficient and average relative error are used to evaluate the validity of the model.
Findings
The results show that the maximum correlation coefficient of the seven estimated factors selected is 0.82; the estimation results of 14 test samples are of high accuracy, among which the determination coefficient R2 = 0.924, and the average relative error is 6.608%.
Practical implications
Studies have shown that it is feasible and effective to estimate the content of soil organic matter by using grey correlation local linear regression model.
Originality/value
The paper succeeds in realizing both the soil organic matter hyperspectral grey relation estimating pattern based on the grey relational theory and the estimating pattern by using the local linear regression.
Details
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Wenjing Zhang, Mengdi Wang and Dong Li
As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale…
Abstract
Purpose
As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale for its benefits, MHC still faces consumer resistance. MHC is a technology-enabled service, so an in-depth analysis of consumer resistance from the perspective of technology is crucial to enhance service adoption. This study sought to determine the mechanism by which two information technology (IT)-specific traits – IT affordance and IT identity – influence consumer resistance to MHC during consumer–platform interactions.
Design/methodology/approach
We used the Credamo platform to gather data from 786 users with medical consulting experience to validate the resulting relationships.
Findings
Based on partial least squares structural equation modeling, three of the six IT affordances (visibility, searching and guidance shopping) exerted a significant positive influence on IT identity, while trigger attending and association affordance had no significant effect on IT identity. Persistence affordance was negatively associated with IT identity, and IT identity negatively influenced consumer resistance to MHC.
Originality/value
Academically, this empirical paper primarily contributes to the MHC literature and the theory of IT affordance and IT identity. Practically, several valuable guidance for MHC platforms is provided.
Details
Keywords
Wenjing Li and Zhi Liu
In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized…
Abstract
Purpose
In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective.
Design/methodology/approach
This study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019.
Findings
The results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities.
Originality/value
Few policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.
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Keywords
Gong-Bing Bi, Wenjing Ye and Yang Xu
Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined…
Abstract
Purpose
Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.
Design/methodology/approach
From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.
Findings
The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.
Originality/value
To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.