Xingdong Shi, Weili Han, Yinsheng Li and Ying Huang
An enterprise application can be quickly built up by service composition. Business process composition is the essence of service composition. To build up such service‐oriented…
Abstract
Purpose
An enterprise application can be quickly built up by service composition. Business process composition is the essence of service composition. To build up such service‐oriented enterprise application, the developer needs an integrated design tool. The purpose of this paper is to present and integrated business‐process driven design for service‐oriented enterprise applications.
Design/methodology/approach
In the approach, there are three phases: business environment modeling, business process modeling, and script compiling. Business environment modeling adopts a new modeling technique which combines both the advantages of use case diagram and sequence diagram in UML. Business process modeling builds a concrete model according to business environment modeling. The mapping algorithms from business environment model to business process model are also given. At script compiling phase, the business process model is compiled into several deployable files. And then the paper presents a demonstration which shows how to apply our approach to developing a supply chain management system for the retail industry.
Findings
The analysis shows that the approach can meet the requirement of service‐composition. The approach can help business expert freely express their business requirement at business environment modeling phase; and help IT expert quickly design service‐oriented enterprise application according to business environment model at business process modeling phase.
Originality/value
This paper proposes a novel integrated approach to model and implement business‐process driven service composition, and presents an integrated tool based Eclipse to implement this approach.
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Cong Zhou, Weili Xia and Taiwen Feng
This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration…
Abstract
Purpose
This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration (GCI), while investigating the moderating mechanisms of big data development and social capital.
Design/methodology/approach
Following hierarchical linear regression analysis, the authors examine hypothesized relationships by combining survey data from 206 Chinese manufacturers with secondary data.
Findings
The results show that relationship trust positively affects non-coercive influence strategy, while its impact on coercive influence strategy is insignificant. Non-coercive influence strategy has an inverted U-shaped impact on GCI. Furthermore, big data development flattens the inverted U-shaped relationship between non-coercive influence strategy and GCI. Conversely, social capital steepens the inverted U-shaped relationship between non-coercive influence strategy and GCI.
Practical implications
This study sheds light on managers on how to involve customers in GCI through friendly strategies that favor the involvement of customers and the willingness to develop environmentally friendly initiatives.
Originality/value
Although GCI has received widespread attention, how it can be enhanced remains unclear. These findings provide novel insights into the emerging GCI literature and complement social exchange theory.
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Hongbo Qiu, Wenfei Yu, Bingxia Tang, Weili Li, Cunxiang Yang and Yanfeng Wang
Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor…
Abstract
Purpose
Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor at limit conditions, and researched the variation mechanism of motor performance influenced by different driving modes.
Design/methodology/approach
A two-dimensional electromagnetic field model of the permanent magnet motor was established, and a rectangular-wave driving circuit was built. By using the finite element method, the electromagnetic field, current, harmonic content and eddy current loss were calculated when the motor operated at rated load and limit load. On the basis of the motor loss calculation, the temperature field of the motor operating at rated condition and limit condition was researched, and the factors that influence motor limit overload capacity were analyzed. By analyzing the motor loss variation at different load conditions, the change mechanism of the motor temperature field was determined further. Combined with the related experiments, the correctness of the above analysis was verified.
Findings
Permanent magnet synchronous motor (PMSM) driven by sine wave is better compared with brushless direct current motor (BLDCM) driven by rectangular wave in reducing the magnetic field harmonics, motor losses and optimizing the temperature distribution in the motor. The method driven by sine wave could improve the motor output performance including the motor efficiency and the motor overload capacity. The winding temperature is the most important factor that limits the output capability of PMSM operating for a long time. However, because of the large rotor eddy current losses, the permanent magnet temperature is the most important factor that limits the output capability of BLDCM operating for a long time.
Practical implications
The influence of driving modes on the motor magnetic field, losses and temperature distribution, efficiency and overload capacity was determined, and the influence mechanism was also analyzed. Combined with the analysis of the electromagnetic and temperature fields, the advantages of different driving modes were presented. This study could provide an important basis for the design of permanent magnet motors with different driving modes, and it also provides reference for the application of permanent magnet motor.
Originality/value
This paper presents the influence of driving modes on permanent magnet motors. The limit output capacity of the motor with different driving modes was studied, and the key factors limiting the motor output capability were obtained.
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Shakeel Sajjad, Rubaiyat Ahsan Bhuiyan, Rocky J. Dwyer, Adnan Bashir and Changyong Zhang
This study aims to examine the relationship between financial development (FD), financial risk, green finance and innovation related to carbon emissions in the G7 economies.
Abstract
Purpose
This study aims to examine the relationship between financial development (FD), financial risk, green finance and innovation related to carbon emissions in the G7 economies.
Design/methodology/approach
This quantitative study examines the roles that financial development [FD: Domestic credit to private sector by banks as percentage of gross domestic product (GDP)], economic growth (GDP: Constant US$ 2015), financial risk index (FRI), green finance (GFIN: Renewable energy public research development and demonstration (RD&D) budget as percentage of total RD&D budget), development of environment-related technologies (DERTI: percentage of all technologies) and human capital (HCI: index) have on the environmental quality of developed economies. Based on panel data, the study uses a novel approach method of moments quantile regression as a main method to tackle the issue of cross-sectional dependency, slope heterogeneity and nonnormality of the data.
Findings
The study confirms that increasing economic development increases emissions and negatively impacts the environment. However, efficient resource allocation, improved financial systems, and green innovation are likely to contribute to emission mitigation and the overall development of a sustainable viable economy. Furthermore, the study highlights the importance of risk management in financial systems for future emissions prevention.
Practical implications
The study uses a reliable estimation procedure, which extends the discussion on climate policy from a COP-27 perspective and offers practical implications for policymakers in developing more effective emission mitigation strategies.
Social implications
The study offers policy suggestions for a sustainable economy, focusing on both COP-27 and the G7 countries. Recommendations include implementing carbon pricing, developing carbon capture and storage technologies, investing in renewables and energy efficiency and introducing financial instruments for emission mitigation. From a COP-27 standpoint, the G7 should prioritize transitioning to low-carbon economies and supporting developing nations in their sustainability efforts to address the pressing challenges of climate change and global warming.
Originality/value
In comparison to the literature, this study examines the importance of financial risk for G7 economies in promoting a sustainable environment. More specifically, in the context of FD and national income with carbon emissions, previous researchers have disregarded the importance of green innovation and human capital, so the current study fills the gap in the literature related to G7 economies by exploring the link between the identified variables related to carbon emissions.
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This study examines the complex relationship between price stability, monetary growth and renewable energy investments. The pursuit of environmentally sustainable economies is…
Abstract
Purpose
This study examines the complex relationship between price stability, monetary growth and renewable energy investments. The pursuit of environmentally sustainable economies is intertwined with the need to maintain price stability and poses a complex challenge for global policymakers.
Design/methodology/approach
Through a comprehensive review, this study seeks answers to how price stability affects pollution, particularly carbon emissions, through various economic channels. Employing panel data analysis for 84 countries between 1999 and 2020, we find a multifaceted effect of price instability on carbon emissions.
Findings
According to system-GMM estimation results, we find (1) price stability has no significant direct effect on carbon emissions. However, it emerges as a crucial environmental factor through consumption, investment and monetary policy channels. (2) Moreover, price stability reverses the positive effects of renewable energy investments on carbon emissions, and it slows down the carbon emissions-increasing effect of energy consumption. (3) Monetary expansion combined with price stability increases environmental pollution. These findings underscore the complexity of balancing economic stability and environmental sustainability and highlight the need for comprehensive policy approaches to address these global challenges effectively.
Originality/value
There is a significant gap in the existing literature examining the impact of price stability on carbon emissions. Most of the studies observe the impact of carbon emissions on inflation. However, the complex interaction between economic and environmental factors reveals inflation as a factor affecting pollution, particularly the amount of carbon emissions.
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Alexandre Coussa, Philippe Gugler and Jonathan Reidy
The purpose of this paper is to develop a comprehensive overview of green innovation (GI) in China, which is carried out by reviewing the evolution of GI from 2000 to 2019, and…
Abstract
Purpose
The purpose of this paper is to develop a comprehensive overview of green innovation (GI) in China, which is carried out by reviewing the evolution of GI from 2000 to 2019, and the main type of technology, actors and localizations. When appropriate, GI is compared to non-GI.
Design/methodology/approach
The study uses patent data from the European Patent Office database (PATSTAT); these data are processed to map trends and identify the main contributors to GI and the location of such innovation. The findings are then discussed and complemented with academic literature.
Findings
Key findings reveal an increasing divergence between GI and nongreen innovation after the 2008 crisis. It is also observed that solar energy appears to be the main component of GI in China, with a shift from photovoltaic thermal energy to solar photovoltaic energy after 2008. Other areas, such as waste management, greenhouse gases capture and climate change adaptation, are less innovative. Companies play an essential role in the development of all types of innovation. In terms of location, green patents are mainly filed in China’s three main megacities. The study also highlights the significant role of the Chinese state, which led policies shaping the trajectories and forms of GI.
Originality/value
This study expands knowledge on GI in China, highlighting its main specificities and the role of key actors. It provides to the reader a comprehensive picture of China’s green policies and innovation realities. The results can therefore be used to improve the understanding of GI evolution in China and facilitate the formulation of new research questions.
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This study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is…
Abstract
Purpose
This study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.
Design/methodology/approach
Firstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.
Findings
Through a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.
Originality/value
The comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.
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Sana Bougharriou, Fayçal Hamdaoui and Abdellatif Mtibaa
This paper aims to study distance determination in vehicles, which could allow an in-car system to provide feedback and alert drivers, by either prompting the driver to take…
Abstract
Purpose
This paper aims to study distance determination in vehicles, which could allow an in-car system to provide feedback and alert drivers, by either prompting the driver to take preventative action or prepare the vehicle’s safety systems for an imminent collision. The success of a new system's deploying allows drivers to oppose the huge number of accidents and the material losses and costs associated with car accidents.
Design/methodology/approach
In this context, this paper presents estimation distance between camera and frontal vehicles based on camera calibration by combining three main steps: vanishing point extraction, lanes detection and vehicles detection in the field of 3 D real scene. This algorithm was implemented in MATLAB, and it was applied on scenes containing several vehicles in highway urban area. The method starts with the camera calibration. Then, the distance information can be calculated.
Findings
Based on experiment performance, this new method achieves robustness especially for detecting and estimating distances for multiple vehicles in a single scene. Also, this method demonstrates a higher accuracy detection rate of 0.869 in an execution time of 2.382 ms.
Originality/value
The novelty of the proposed method consists firstly on the use of an adaptive segmentation to reject the false points of interests. Secondly, the use of vanishing point has reduced the cost of using memory. Indeed, the part of the image above the vanishing point will not be processed and therefore will be deleted. The last benefit is the application of this new method on structured roads.