Jiawei Xu, Baofeng Zhang, Jianjun Lu, Yubing Yu, Haidong Chen and Jie Zhou
The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and…
Abstract
Purpose
The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.
Design/methodology/approach
The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.
Findings
The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.
Practical implications
Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.
Originality/value
This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.
Details
Keywords
Yubing Yu, Haohui Li, Jiawei Xu, Min Zhang, Xiuru Zhang, Justin Zuopeng Zhang and Ye Wu
This study aims to examine the joint effect of internal quality integration and product innovation on financial performance by considering the mediating roles of incremental and…
Abstract
Purpose
This study aims to examine the joint effect of internal quality integration and product innovation on financial performance by considering the mediating roles of incremental and radical product innovation.
Design/methodology/approach
A theoretical framework was developed using the organizational capability view. Based on empirical survey data collected from 209 Chinese manufacturing firms, this research uses structural equation modeling and the bootstrapping method to test hypotheses.
Findings
The results show that internal quality integration positively impacts incremental and radical product innovation and financial performance. Further, incremental product innovation can promote radical product innovation. Both incremental and radical product innovation partially mediate the relationship between internal quality integration and financial performance.
Practical implications
The findings provide practical guidance for manufacturing companies to engage in quality integration and product innovation. Managers should encourage the internal functional departments to coordinate quality integration while promoting incremental and radical product innovation to occupy a larger market and achieve higher performance.
Originality/value
This research contributes to the literature in two ways. First, this study expands the theoretical research framework of the joint effects of quality integration and product innovation on financial performance. Second, through testing the mediating role of product innovation, this study provides empirical evidence for the intermediate role of internal quality integration for improving financial performance.
Details
Keywords
Jiawei Xu, Yubing Yu, Ye Wu, Justin Zuopeng Zhang, Yulong Liu, Yanhong Cao and Prajwal Eachempati
The paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of…
Abstract
Purpose
The paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of relational capital on these relationships.
Design/methodology/approach
The authors conduct an empirical study with a structural equation modeling approach to investigate the relationship between corporate social responsibility—constructed by the quality and environmental responsibility, green supply chain management—including green supplier and customer management and operational performance—manifested by quality, cost, flexibility, and delivery performance using data from 308 manufacturers in China. Besides, the authors explore the moderating effect of supplier and customer relational capital on these relationships.
Findings
The findings indicate that a company's quality and environmental responsibility significantly impacts its green supply chain management practices, which further improve its operational performance in quality, cost, flexibility, and delivery. In addition, supplier and customer relational capital strengthens the influence of environmental responsibility on green supply chain management. While supplier relational capital reinforces the impact of green supplier management on flexibility and delivery performance, customer relational capital only strengthens the influence of green customer management on flexibility performance.
Originality/value
The study enriches the extant literature by developing a holistic framework integrating corporate social responsibility, green supply chain management, relational capital, and operational performance and unraveling their intricate relationships. The authors’ findings help practitioners prioritize proactive steps in environmental conservation more than achieving operational performance.
Details
Keywords
Fangxin Li, Xin Xu, Jingwen Zhou, Jiawei Chen and Shenbei Zhou
Current practices for inspecting highway construction predominantly rely on manual processes, which result in subjective assessments, errors and time inefficiencies. The purpose…
Abstract
Purpose
Current practices for inspecting highway construction predominantly rely on manual processes, which result in subjective assessments, errors and time inefficiencies. The purpose of this study is to address the inefficiencies and potential inaccuracies inherent in manual highway construction inspections. By leveraging computer vision and ontology reasoning, the study seeks an automated and efficient approach to generate structured construction inspection knowledge in the format of checklists for construction activities on highway construction job sites.
Design/methodology/approach
This study proposes a four-module framework based on computer vision and ontology reasoning to enable the automatic generation of checklists for quality inspection. The framework includes: (1) the interpretation of construction scenes based on computer vision, (2) the representation of inspection knowledge into structured checklists through specification processing, (3) the connection of construction scenes and inspection knowledge via ontology reasoning and (4) the development of a prototype for the automatic generation of checklists for highway construction.
Findings
The proposed framework is implemented across four distinct highway construction scenarios. The case demonstrations show that the framework can interpret construction scenes and link them with relevant inspection knowledge automatically, resulting in the efficient generation of structured checklists. Therefore, the proposed framework indicates considerable potential for application in the automatic generation of inspection knowledge for the quality inspection of highway construction.
Originality/value
The scientific and practical values of this study are: (1) the establishment of a new method that promotes the automated generation of structured inspection knowledge for highway construction by integrating computer vision and ontology reasoning and (2) the development of a novel framework that provides efficient and immediate access to inspection knowledge related to what needs to be inspected at highway construction job sites.
Details
Keywords
Xiangdi Yue, Yihuan Zhang, Jiawei Chen, Junxin Chen, Xuanyi Zhou and Miaolei He
In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and…
Abstract
Purpose
In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.
Design/methodology/approach
This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.
Findings
This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.
Originality/value
To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.
Details
Keywords
Md Rajibul Hasan, Assem Abdunurova, Wenwen Wang, Jiawei Zheng and S.M. Riad Shams
The purpose of this study is to gather insights into digital consumer behaviour related to Chinese restaurents by examining visual contents on Tripadvisor platform.
Abstract
Purpose
The purpose of this study is to gather insights into digital consumer behaviour related to Chinese restaurents by examining visual contents on Tripadvisor platform.
Design/methodology/approach
Using the deep learning approach, this research assessed consumer-posted online content of dining experiences by implementing image analysis and clustering. Text mining using word cloud analysis revealed the most frequently repeated keywords.
Findings
First, 4,000 photos of nine Chinese restaurants posted on Tripadvisor’s website were analyzed using image recognition via Inception V3 and Google’s deep learning network; this revealed 12 hierarchical image clusters. Then, an open-questionnaire survey of 125 Chinese respondents investigated consumers’ information needs before visiting a restaurant and after purchasing behavior (motives to share).
Practical implications
This study contributes to culinary marketing development by introducing a new analysis methodology and demonstrating its application by exploring a wide range of keywords and visual images published on the internet.
Originality/value
This research extends and contributes to the literature regarding visual user-generated content in culinary tourism.
Details
Keywords
Xiangdi Yue, Jiawei Chen, Yihuan Zhang, Siming Huang, Jiaji Pan and Miaolei He
Over the decades, simultaneous localization and mapping (SLAM) techniques have been extensively researched and applied in robotic mapping. In complex environments, SLAM systems…
Abstract
Purpose
Over the decades, simultaneous localization and mapping (SLAM) techniques have been extensively researched and applied in robotic mapping. In complex environments, SLAM systems using a single sensor, such as a camera or light detection and ranging (LiDAR), often cannot meet the accuracy and map consistency requirements. This study aims to propose a tightly-coupled LiDAR-inertial SLAM system, which aims to achieve higher accuracy and map consistency for robotic mapping in complex environments.
Design/methodology/approach
This paper presents TC-Mapper, a tightly coupled LiDAR-inertial SLAM system based on LIO-SAM. The authors introduce the normal distribution-based loop closure detection method to the original one (i.e. the radius search-based method), which can enhance the accuracy and map consistency for robotic mapping. To further suppress map drift in complex environments, this paper incorporates a gravity factor into the original factor graph. In addition, TC-Mapper introduces incremental voxels (iVox) as the point cloud spatial data structure.
Findings
Extensive experiments in public and self-collected data sets demonstrate that TC-Mapper has high accuracy and map consistency.
Originality/value
TC-Mapper has two types of loop closure detections: the normal distribution-based method for correcting large drifts and the radius search-based method for fine-stitching, which can achieve higher accuracy and map consistency. The authors introduce iVox as the point cloud spatial data structure, which strives to attain a balance between precision and efficiency to the greatest extent feasible.
Details
Keywords
Liang Xiao, Jiawei Wang and Xinyu Wei
Value co-creation (VCC) helps platforms establish competitive advantages. Unlike their traditional counterparts, social attribute is a key concept of social e-commerce platforms…
Abstract
Purpose
Value co-creation (VCC) helps platforms establish competitive advantages. Unlike their traditional counterparts, social attribute is a key concept of social e-commerce platforms. This study integrates VCC and social network theories, introduces relational embeddedness and divides this variable into economic and social relational embeddedness to explore its impact on VCC intention. This study also explores the mediating and moderating roles of customers' psychological ownership (CPO) and regulatory focus, respectively.
Design/methodology/approach
A questionnaire survey was conducted among users of mainstream social e-commerce platforms in China, and the relationship among the variables was revealed through a structural equation modeling of 464 valid responses.
Findings
The dimensions of relational embeddedness positively affect CPO and VCC intention, with social relational embeddedness exerting the strongest effect. CPO positively affects VCC intention and partially mediates the relationship between relational embeddedness and VCC intention. Promotion and prevention focus positively and negatively moderate the relationship between CPO and VCC intention, respectively.
Originality/value
This study expands the VCC research perspective and links the VCC concepts to social network dynamics. From the relational embeddedness perspective, this study identifies the type and intensity of relational embeddedness that promotes users' VCC intention and contributes to theoretical research on VCC and relational embeddedness. This study also introduces CPO as an intermediary variable, thus opening the black box of this mechanism, and confirms the moderating role of regulatory focus as the key psychological factor motivating users' VCC intention.
Details
Keywords
Jiansan Li, Yali Li, Yanqin Chen, Jiawei Sun, Chunxiao Wang, Yingcai Zheng and Huiting Zhong
This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.
Abstract
Purpose
This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.
Design/methodology/approach
These phosphate coatings were obtained by immersing magnesium alloys in phosphate baths with HMTA. The morphology and composition of the phosphate coatings were investigated via scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction.
Findings
The phosphate coatings were mainly composed of CaHPO4·2H2O. The HMTA concentration in the phosphate bath influenced the crystallization and corrosion resistance of the phosphate coating.
Originality/value
The polarization curve shows that the anti-corrosion qualities of the phosphate coating were optimal when the HMTA concentration was 1.0 g/L in the phosphate bath. Electrochemical impedance spectroscopy (EIS) shows that the electrochemical impedances increased gradually when the HMTA concentration varied from 1.0 to 3.0 g/L.
Details
Keywords
Ming Qi, Jiawei Zhang, Jing Xiao, Pei Wang, Danyang Shi and Amuji Bridget Nnenna
In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.
Abstract
Purpose
In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.
Design/methodology/approach
By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.
Findings
The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.
Practical implications
Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.
Originality/value
This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.