Hongbin Huang, Guanghui Jin and Jingnan Chen
The purpose of this paper is to expand the investor sentiment’s effect on investment efficiency to the layer of “credit financing,” studying whether investor sentiment can affect…
Abstract
Purpose
The purpose of this paper is to expand the investor sentiment’s effect on investment efficiency to the layer of “credit financing,” studying whether investor sentiment can affect credit financing level and the inner mechanism of the effect.
Design/methodology/approach
The authors obtain firm-level data from the Shanghai and Shenzhen stock markets and using panel estimation techniques examine whether investor sentiment can affect credit financing level and the inner mechanism of the effect.
Findings
This paper finds that credit financing plays the role of partial media in the process of investor sentiment affecting investment efficiency. Based on the funds increasing effect, with the high-investor sentiment and increasing credit financing, corporations alleviate the financing constraints, but also provide a convenient for the abuse of corporate funds. So, investor sentiment positively associates with enterprises’ overinvestment, while investor sentiment negatively associates with enterprises’ underinvestment. Relying on the particular system background and property right environment in China, this paper finds that investor sentiment has an effect on the overinvestment of state-owned enterprises and the underinvestment of private enterprises through credit financing channel, while it does not function in the overinvestment of private enterprises. The reason of the difference is that under the soft budget constraint in the country, the credit preference of state-owned enterprises and the creditor’s rights management of banks are partially absent.
Research limitations/implications
By fusing the special financial environment and institutional background, this thesis further includes in the analysis frame the difference in governance effect by credit financing between state-owned and privately owned listed companies, and further analyzes the difference in impact on investment efficiency in enterprises of different natures after investor sentiment has affected enterprise credit financing.
Practical implications
This paper has verified the constraint assumption and deepened the research work on bank credit supply and answered practical questions such as whether the banks in the country exercise supervision function over the listed companies and on which kind of listed companies the supervision function plays a more effective role.
Social implications
As an unofficial substitution mechanism, bank-enterprise relationship can elevate the investment efficiency by private owned enterprises. Based on the timely research results on credit financing, reference is provided for private listed companies to utilize investor sentiment to improve its investment efficiency.
Originality/value
This paper has proved the specific path which creates the dual effects on resources allocation by investor sentiment, that is, the intermediary transmission in credit financing, clarifying the mechanism of action by which investor sentiment affects the efficiency of enterprise investment and making incremental contribution to the research of how investor sentiment affects the efficiency of enterprise investment.
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Changjiang (Bruce) Tao, Songshan (Sam) Huang, Jin Wang and Guanghui Qiao
This study aims to explore the heterogeneity of the tourist market for people with a physical disability (PwPD) based on travel barriers, to serve them better, from a tourism…
Abstract
Purpose
This study aims to explore the heterogeneity of the tourist market for people with a physical disability (PwPD) based on travel barriers, to serve them better, from a tourism marketing perspective.
Design/methodology/approach
A market segmentation analysis was conducted on a sample of 480 PwPD in Sichuan Province, China, based on their perceived travel barriers. Data were obtained through three on-site and four online surveys. A four-step factor-item mixed segmentation, including factor analysis, cluster analysis, discriminant analysis and chi-square tests, was applied to examine the differences among PwPD tourist market segments in terms of various demographic characteristics, disability conditions (e.g. duration of disabilities and causes of impairment) and travel features (e.g. travel frequency and tourist destinations).
Findings
This study revealed that the PwPD tourist market is heterogeneous due to individual perceived travel barriers. Three market segments were identified, namely, the Explorer Moderates group, the Explorer Minimals group and the Explorer Intensives group. Additionally, the three market segments were found to have significant differences in terms of travel barriers, demographic characteristics, travel features and disability conditions.
Practical implications
This research provides suggestions for authorities and private entities to optimize the layout of accessible facilities in public areas for the benefit of all. It also offers crucial implications for tourism marketers to determine the key facets of marketing, for travel organizers to evolve the organization of travel groups for PwPD, and for practitioners to provide personalized tourism services.
Originality/value
To the best of the authors’ knowledge, this study is the first to apply perceived travel barriers as a market segmentation criterion in understanding PwPD as a heterogeneous travel market. The findings of this study initially expand the scope of application of the travel barrier model and deepen understanding of the Chinese PwPD tourist market from a marketing perspective. The study results elucidated the heterogeneity and characteristics of this market through a four-step factor-item mixed segmentation approach, offering new insights into the behaviors and experiences of travelers with disabilities.
目的
本研究旨在探索肢体残障人士旅游市场的异质性, 以便从旅游营销的角度更好地为他们服务。
设计/方法/途径
基于对中国四川480名肢残人士出游障碍感知的问卷调查, 探索了肢残人士的旅游市场细分。数据是通过七次现场和在线调查获得; 采用四步因子-项目混合细分法, 根据残障状况、人口统计特征和旅游特征, 识别出肢残群体旅游细分市场之间的差异。
研究结果
研究发现, 基于个体感知的出游障碍, 肢残群体旅游市场是异质的, 研究确定了三个细分市场, 即低度、中度和高度受限群体。三个细分市场在出行障碍、人口特征、出游特征和残障状况方面存在显著差异。
实践意义
这项研究有助于政府管理部门优化公共区域无障碍设施布局; 旅游营销者确定营销的重点, 并为旅游组织者设计肢残旅游团体成员构成, 以及从业者提供个性化旅游服务提供重要的启示。
原创性/价值
论文首次将感知出游障碍作为市场细分标准, 用以理解肢残群体作为异质游客市场。本研究的发现拓展了出游障碍模型的应用范围, 并从市场营销的角度加深了对中国肢残游客市场的理解。研究结果通过四步因子-项目混合细分方法阐明了该市场的异质性和特点, 为肢残游客的行为和体验研究提供了新见解。
Propósito
Este estudio explora la heterogeneidad del mercado turístico de las personas con discapacidad física (PcDF) en función de las barreras percibidas para viajar, con el fin de prestarles un mejor servicio desde una perspectiva de marketing turístico.
Diseño/metodología/enfoque
Se realizó un análisis de segmentación de mercado en una muestra de 480 PcDF en Sichuan, China, en función de las barreras que percibían para viajar. Los datos se obtuvieron a través de tres encuestas in situ y cuatro encuestas en línea. Se aplicó una segmentación mixta factor-ítem de cuatro pasos que incluye análisis factorial, análisis de conglomerados, análisis discriminante y pruebas de chi-cuadrado para examinar las diferencias entre los segmentos del mercado turístico de PcDF, en términos de diversas características demográficas, condiciones de discapacidad (por ejemplo, duración de la discapacidad, causas de la discapacidad) y características de los viajes (por ejemplo, frecuencia de viaje, destinos turísticos).
Hallazgos
Este estudio reveló que el mercado turístico de las PcDF es heterogéneo debido a las barreras de viaje percibidas por cada individuo. Se identificaron tres segmentos de mercado, a saber, el grupo de Exploradores Moderados, el grupo de Exploradores Mínimos y el grupo de Exploradores Intensivos. Los tres segmentos de mercado presentaban diferencias significativas en cuanto a las barreras para viajar, las características demográficas, las características del viaje y las condiciones de discapacidad.
Originalidad/valor
Este estudio es el primero en aplicar las barreras percibidas para viajar como criterio de segmentación de mercado para comprender a las PcDF como un mercado turístico heterogéneo. Los hallazgos de este estudio amplían inicialmente el ámbito de aplicación del modelo de barreras para viajar y profundizan en la comprensión del mercado turístico chino de PcDF desde una perspectiva de marketing. Los resultados de nuestro estudio explicaron la heterogeneidad y las características de este mercado a través de un enfoque de segmentación mixta factor-ítem de cuatro pasos, contribuyendo a la literatura sobre el comportamiento y las experiencias de los viajeros con discapacidad.
Implicaciones prácticas
Esta investigación proporciona sugerencias para que las autoridades y las entidades privadas puedan optimizar la disposición de instalaciones accesibles en zonas públicas en beneficio de todos. También ofrece implicaciones importantes a los comercializadores turísticos para que determinen aspectos clave del marketing, a los organizadores de viajes para que evolucionen en la organización de grupos de viaje para PcDF y a los profesionales para que presten servicios turísticos personalizados.
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Yanhui Sun, Junkang Guo, Jun Hong and Guanghui Liu
This paper aims to develop a theoretical method to analyze the rotation accuracy of rotating machinery with multi-support structures. The method effectively considers the…
Abstract
Purpose
This paper aims to develop a theoretical method to analyze the rotation accuracy of rotating machinery with multi-support structures. The method effectively considers the geometric errors and assembly deformation of parts.
Design/methodology/approach
A method composed of matrix and FEA methods is proposed to do the analysis. The deviation propagation analysis results and external loads are set as boundary conditions of the model which is built with Timoshenko beam elements to calculate the spatial pose of the rotor. The calculation is performed repeatedly as the rotation angle increased to get the rotation trajectories of concerned nodes, and further evaluation is done to get the rotation accuracy. Additionally, to get more reliable results, the bearing motion errors and stiffness are analyzed by a static model considering manufacturing errors of parts.
Findings
The feasibility of the proposed method is verified through a case study of a high-precision spindle. The method reasonably predicts the rotation accuracy of the spindle.
Originality/value
For rotating machinery with multi-support structures, the paper proposes a modeling method to predict the rotation accuracy, simultaneously considering geometric errors and assembly deformation of parts. This would improve the accuracy of tolerance analysis.
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Zhixu Zhu, Hualiang Zhang, Guanghui Liu and Dongyang Zhang
This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.
Abstract
Purpose
This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.
Design/methodology/approach
First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.
Findings
The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.
Practical implications
The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.
Originality/value
The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.
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Yingbo Gao, Bo Yan, Hanxu Yang, Mao Deng, Zhongbin Lv, Bo Zhang and Guanghui Liu
A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper…
Abstract
Purpose
A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper aims to propose a data-driven identification method for bolt looseness of complicated tower structures based on reduced-order models and numerical simulations to perceive and evaluate the health state of a tower in operation.
Design/methodology/approach
The equivalent stiffnesses of three types of bolt joints under various loosening scenarios are numerically determined by three-dimensional finite element (FE) simulations. The order of the FE model of a tower structure with bolt loosening is reduced by means of the component modal synthesis method, and the dynamic responses of the reducer-order model under calibration loads are simulated and used to create the dataset. An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed.
Findings
An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed and the applicability of the model is investigated. It is shown that the proposed method has a high identification accuracy and strong robustness to data noise and data missing. Meanwhile, the method is less dependent on the number and location of sensors and is easier to apply in real transmission lines.
Originality/value
This paper proposes a data-driven identification method for bolt looseness of a complicated tower structure based on reduced-order models and numerical simulations. Non-linear relationships between equivalent stiffness of bolted joints and bolt preload depicting looseness are obtained and reduced-order model of tower structure with bolt looseness is established. Finally, this paper investigates applicability of identification model for bolt looseness.
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Guanghui Ye, Songye Li, Lanqi Wu, Jinyu Wei, Chuan Wu, Yujie Wang, Jiarong Li, Bo Liang and Shuyan Liu
Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them…
Abstract
Purpose
Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them find valuable answers efficiently. Existing works mainly use content and user behavioural features for expert recommendation, and fail to effectively leverage the correlation across multi-dimensional features.
Design/methodology/approach
To address the above issue, this work proposes a multi-dimensional feature fusion-based method for expert recommendation, aiming to integrate features of question–answerer pairs from three dimensions, including network features, content features and user behaviour features. Specifically, network features are extracted by first learning user and tag representations using network representation learning methods and then calculating questioner–answerer similarities and answerer–tag similarities. Secondly, content features are extracted from textual contents of questions and answerer generated contents using text representation models. Thirdly, user behaviour features are extracted from user actions observed in CQA platforms, such as following and likes. Finally, given a question–answerer pair, the three dimensional features are fused and used to predict the probability of the candidate expert answering the given question.
Findings
The proposed method is evaluated on a data set collected from a publicly available CQA platform. Results show that the proposed method is effective compared with baseline methods. Ablation study shows that network features is the most important dimensional features among all three dimensional features.
Practical implications
This work identifies three dimensional features for expert recommendation in CQA platforms and conducts a comprehensive investigation into the importance of features for the performance of expert recommendation. The results suggest that network features are the most important features among three-dimensional features, which indicates that the performance of expert recommendation in CQA platforms is likely to get improved by further mining network features using advanced techniques, such as graph neural networks. One broader implication is that it is always important to include multi-dimensional features for expert recommendation and conduct systematic investigation to identify the most important features for finding directions for improvement.
Originality/value
This work proposes three-dimensional features given that existing works mostly focus on one or two-dimensional features and demonstrate the effectiveness of the newly proposed features.
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Lakshmi Devaraj, Thaarini S., Athish R.R. and Vallimanalan Ashokan
This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It…
Abstract
Purpose
This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It evaluates the current state of the art, addressing both low- and high-temperature sensors, and explores the potential applications across various fields. The study also identifies challenges and highlights emerging trends that may shape the future of this technology.
Design/methodology/approach
This study systematically examines existing literature on TTS, categorizing the materials and fabrication methods used. The study compares the performance metrics of different materials, addresses the challenges encountered in thin-film sensors and reviews the case studies to identify successful applications. Emerging trends and future directions are also analyzed.
Findings
This study finds that TTS are integral to various advanced technologies, particularly in high-performance and specialized applications. However, their development is constrained by challenges such as limited operational range, material degradation, fabrication complexities and long-term stability. The integration of nanostructured materials and the advancement of wireless, self-powered and multifunctional sensors are poised to drive significant advancements in this field.
Originality/value
This study offers a unique perspective by bridging the gap between material science and application engineering in TTS. By critically analyzing both established and emerging technologies, the study provides valuable insights into the current state of the field and proposes pathways for future innovation in terms of interdisciplinary approaches. The focus on emerging trends and multifunctional applications sets this review apart from existing literature.
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Usman Tariq, Ranjit Joy, Sung-Heng Wu, Muhammad Arif Mahmood, Asad Waqar Malik and Frank Liou
This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive…
Abstract
Purpose
This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.
Design/methodology/approach
This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.
Findings
A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.
Originality/value
Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.