Abstract
Purpose
Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.
Design/methodology/approach
Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.
Findings
The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.
Originality/value
This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.
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Miaolei He, Changji Ren, Jilin He, Kang Wu, Yuming Zhao, Zhijie Wang and Can Wu
Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control…
Abstract
Purpose
Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control algorithms to surmount an obstacle. Therefore, this paper aims to propose a new simple configuration of an all-terrain robotic vehicle with eight wheels including four-swing arms.
Design/methodology/approach
This vehicle is driven by distributed hydraulic motors which provide high mobility. It possesses the ability to change the posture by means of cooperation of the four-swing arms. This ensures that the vehicle can adapt to complex terrain. In this paper, the bionic mechanism, control design and steering method of the vehicle are introduced. Then, the kinematic model of the center of gravity is studied. Afterward, the obstacle surmounting performance based on a static model is analyzed. Finally, the simulation based on ADAMS and the prototype experiment is carried out.
Findings
The experiment results demonstrate that the robotic vehicle can surmount an obstacle 2.29 times the height of the wheel radius, which verifies the feasibility of this new configuration. Therefore, this vehicle has excellent uneven terrain adaptability.
Originality/value
This paper proposes a new configuration of an all-terrain robotic vehicle with four-swing arms. With simple mechanism and control algorithms, the vehicle has a high efficiency of surmounting an obstacle. It can surmount a vertical obstacle 2.29 times the height of the wheel radius.
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Xin Tian, Wu He, Yuming He, Steve Albert and Michael Howard
This study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social…
Abstract
Purpose
This study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social media messaging (firm-generated content and their local community's responses (user-generated content) evolved with the COVID-19 outbreak progression.
Design/methodology/approach
This research proposes a healthcare-specific social media analytics framework and studied 68,136 tweets posted from November 2019 to November 2020 from a geographically diverse set of ten leading hospitals' social media messaging on COVID-19 and the public responses by using social media analytics techniques and the health belief model (HBM).
Findings
The study found correlations between some of the HBM variables and COVID-19 outbreak progression. The findings provide actionable insight for hospitals regarding risk communication, decision making, pandemic awareness and education campaigns and social media messaging strategy during a pandemic and help the public to be more prepared for information seeking in the case of future pandemics.
Practical implications
For hospitals, the results provide valuable insights for risk communication practitioners and inform the way hospitals or health agencies manage crisis communication during the pandemic For patients and local community members, they are recommended to check out local hospital's social media sites for updates and advice.
Originality/value
The study demonstrates the role of social media analytics and health behavior models, such as the HBM, in identifying important and useful data and knowledge for public health risk communication, emergency responses and planning during a pandemic.
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Justin Zuopeng Zhang, Wu He, Sachin Shetty, Xin Tian, Yuming He, Abhishek Behl and Ajith Kumar Vadakki Veetil
Despite rapid growth in blockchains, there was limited discussion about non-technical and technical factors on blockchain governance in the extant literature. This study aims to…
Abstract
Purpose
Despite rapid growth in blockchains, there was limited discussion about non-technical and technical factors on blockchain governance in the extant literature. This study aims to contribute new knowledge to the literature on potential factors affecting the adoption, governance and scale-up of blockchain technologies in the health-care and energy sectors, presented in a holistic framework.
Design/methodology/approach
This study adopts the qualitative case study research methodology to research blockchain governance in practice. The authors contacted a national blockchain consortium to conduct their research on the governance issue of blockchain. Two leading case organizations, one from the health-care industry and another from the energy industry, were deliberately selected for their study for their active role and reputation in the consortium and practical experience in blockchain governance.
Findings
The developed framework helps identify potential research gaps or concerns on adopting a blockchain as well as assessing blockchain implementation and governance in other industries. Depending on the circumstances, some of the factors can be either drivers or obstacles to further blockchain development. The different forces may also be more or less evident over time as blockchains develop. The two real-world case studies contribute to the information technology governance literature on blockchain governance.
Originality/value
The results of this case studies will be beneficial for developing theories and empirical models to determine antecedents for achieving consensus and trust in blockchain and testing the relationship between these factors and blockchain governance at different levels. As a result, theories related to the governance of blockchain technologies could be further developed.
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Kai Liu, Yuming Liu and Yuanyuan Kou
Inter-organizational collaboration is the organizational guarantee and key link to achieve the goals of megaproject management. Project governance has always played an important…
Abstract
Purpose
Inter-organizational collaboration is the organizational guarantee and key link to achieve the goals of megaproject management. Project governance has always played an important role in the construction of megaprojects, but the relationship between project governance and organizational collaboration is unclear. The purpose of this study is to explore the role paths of different project governance mechanisms in influencing the collaborative behaviors of stakeholders and collaborative performance and to elucidate the mechanism of project governance on inter-organizational collaboration.
Design/methodology/approach
A conceptual framework was developed based on a comprehensive literature review, termed the structural equation model (SEM). The hypotheses of the model were tested based on data obtained from a questionnaire survey of 235 experts with experience in megaprojects within the construction industry in China.
Findings
The results show that project governance positively contributes to the collaborative behavior of megaproject stakeholders and the collaborative performance of the project team. Collaborative behavior acts as a partial mediator between project governance and the collaborative performance of the megaproject inter-organization alliance. The complexity of the project modulates the relationship between the governance mechanism of the project and the collaborative behavior of the stakeholders, which affects the collaborative performance of the megaproject inter-organization alliance.
Originality/value
The findings provide theoretical and practical implications for promoting positive collaborative behavior among stakeholders in megaproject selection and improving the collaborative performance of megaproject inter-organization alliances.
Details
Keywords
Yunfei Xing, Yuming He and Justin Z. Zhang
The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and…
Abstract
Purpose
The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.
Design/methodology/approach
Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.
Findings
Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.
Originality/value
Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.
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Sheng Chen, Yuming Xing, Xin Liu and Liang Zhao
The purpose of this study is to investigate the effect of the injection angle α on the spray structures of an air-blast atomizer and help enhance the understanding of droplet-gas…
Abstract
Purpose
The purpose of this study is to investigate the effect of the injection angle α on the spray structures of an air-blast atomizer and help enhance the understanding of droplet-gas mixing process in such atomizers in the engineering domain.
Design/methodology/approach
The phenomena in the air-blast atomizer were numerically modelled using the computational fluid dynamics software Fluent 17.2. The Euler-Lagrange approach was applied to model the droplet tracking and droplet-gas interaction in studied cases. The standard k-ε model was used to simulate the turbulent flow. A model with a modified drag coefficient was used to consider the effects of the bending of the liquid column and its penetration in the primary breakup region. The Kelvin-Helmholtz, Rayleigh-Taylor model was applied to consider the secondary breakup of the droplets.
Findings
The basic spatial distribution and spray structures of the droplets corresponding to the angled liquid jet (α = 60°) were similar to those reported in liquid jets injected transversely into a gaseous crossflow studies. The injection angle α did not considerably influence the averaged Sauter to mean diameter (SMD) of the cross-sections. However, the spray structures pertaining to α = 30°, α = 60° and α = 90° were considerably different. In the case of the atomizer with multiple injections, a “collision region” was observed at α = 60° and characterized by a higher ci and larger averaged SMD in the central parts of the cross-sections.
Originality/value
The injection angle α is a key design parameter for air-blast atomizers. The findings of this study can help enhance the understanding of the droplet-gas mixing process in air-blast atomizers. Engineers who design air-blast atomizers and face new challenges in the process can refer to the presented findings to obtain the desired atomization performance. The code has been validated and can be used in the engineering design process of the gas-liquid jet atomizer.
Details
Keywords
Kai Liu, Yuanyuan Kou, Yuming Liu and Xiaoxu Yang
Construction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However…
Abstract
Purpose
Construction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However, how to cope with the dilemma of the unclear relationship of construction safety resilience elements at the practice level and promote the harmonization of construction safety goals and resilience enhancement paths has become an urgent challenge for safe construction.
Design/methodology/approach
This study analyzes the components of construction safety resilience elements. A relationship network model of construction safety resilience elements is developed by using the social network analysis method. The location and influence of each element in the network and the interrelationships among the elements are explored in depth.
Findings
The findings reveal a robust interconnection among the elements of safety resilience in the construction industry. Key components such as safety behavior, risk prevention and control mechanisms, disaster prevention and mitigation technologies as well as information technology, are positioned at the core of the network. Notably, safety behavior exerts the most significant influence over the other elements, serving as the linchpin of safety management in the construction industry. Moreover, the interplay among safety resilience elements in the construction sector can alter the structure of the relationship network.
Originality/value
This study adopts the social network approach to solve the problem that it is difficult to quantitatively analyze the elements of construction safety resilience and their interrelationships and to clarify the interactions among the core elements, which can help to further assist the construction project manager to continuously optimize safety resilience and improve construction safety.
Details
Keywords
Ruan Wang, Jun Deng, Xinhui Guan and Yuming He
With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data…
Abstract
Purpose
With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.
Design/methodology/approach
Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.
Findings
The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.
Originality/value
This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.
Details
Keywords
Xixian Lin, Yuming Zhang, Yimeng Zhang and Guangjian Rong
The purpose of this study is to design a more flexible and larger range of the dimming circuit that achieves the independence of multiple LED strings drive and can time-multiplex…
Abstract
Purpose
The purpose of this study is to design a more flexible and larger range of the dimming circuit that achieves the independence of multiple LED strings drive and can time-multiplex the power circuit.
Design/methodology/approach
The state-space method is used to model the BUCK circuit working in Pseudo continuous conduction mode, analyze the frequency characteristics of the system transfer function and design the compensation network. Build a simulation platform on the Orcad PSPICE platform and verify the function of the designed circuit through the simulation results. Use Altium Designer 16 to draw the printed circuit board, complete the welding of various components and use the oscilloscope, direct current (DC) power supply and a signal generator to verify the circuit function.
Findings
A prototype of the proposed LED driver is fabricated and tested. The measurement results show that the switching frequency can be increased to 1 MHz, Power inductance is 2.2 µH, which is smaller than current research. The dimming ratio can be set from 10% to 100%. The proposed LED driver can output more than 48 W and achieve a peak conversion efficiency of 91%.
Originality/value
The proposed LED driver adopts pulse width modulation (PWM) dimming at a lower dimming ratio and adopts DC dimming at a larger dimming ratio to realize switching PWM dimming to analog dimming. The control strategy can be more precise and have a wide range of dimming.