Weiping Guo, Diantong Liu and Wei Wang
Widely used in micro‐position devices and vibration control, the piezoelectric actuator exhibits strong hysteresis effects, which can cause inaccuracy and oscillations, even lead…
Abstract
Purpose
Widely used in micro‐position devices and vibration control, the piezoelectric actuator exhibits strong hysteresis effects, which can cause inaccuracy and oscillations, even lead to instability. If the hysteretic effects can be predicted, a controller can be designed to correct for these effects. This paper aims to present a neural network hysteresis model with an improved Preisach model to predict the output of piezoelectric actuator.
Design/methodology/approach
The improved Preisach model is given: A wiping‐out memory sequence is defined that is along a single axis only and at the same time the ascending and the descending extreme points are separated. The extended area variable is calculated according to wiping‐out memory sequence. The relationship between the two inputs (the extended area variable and variable rate of input signal) and the hysteresis output is implemented with a neural network to approximate the hysteresis model for the piezoelectric actuators.
Findings
Some experiments are carried out with a piezoelectric ceramic (PST150/7/40 VS12) and the results show the neural network hysteresis model can reliably predict the hysteretic behaviours in piezoelectric actuators.
Originality/value
The improved Preisach model is a simple model that is implemented by a neural network to reliably predict the hysteretic output in piezoelectric actuators.
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Guo Cheng, Xiaoyun Han, Weiping Yu and Mingli He
Oppositional brand loyalty poses a challenge to the management of virtual communities. This study aims to categorize these loyalty behaviors into positive (willingness to pay a…
Abstract
Purpose
Oppositional brand loyalty poses a challenge to the management of virtual communities. This study aims to categorize these loyalty behaviors into positive (willingness to pay a price premium and brand evangelism) and negative (schadenfreude and anti-brand actions) dimensions. It then explores how customer engagement and moral identity influence these dimensions in the context of brand competition.
Design/methodology/approach
Structural equation modeling was conducted to analyze the main and moderating effects, using survey data obtained from 498 valid responses out of a total of 636 responses from Xiaomi's virtual communities.
Findings
The results indicate that customer engagement significantly influences all four dimensions of oppositional brand loyalty. The relationship between customer engagement and brand evangelism is notably stronger among customers with a strong moral identity. Conversely, the effects of customer engagement on schadenfreude and anti-brand actions are attenuated for these customers.
Originality/value
Anchored in theories of brand tribalism, social identity and brand polarization, this study bifurcates oppositional brand loyalty into directions of preference and antagonism, empirically showcasing moral identity's moderating effect. It contributes to the literature on antagonistic loyalty and moral identity, offering strategic insights for companies to navigate schadenfreude and anti-brand actions in online communities.
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Xuyuan Zheng, Weiping Liu, Zhigang Xu, Ruiyao Ying and Chunhui Ye
The purpose of this paper is to analyze the heterogeneity of regional grain production distribution in China, by examining the regional heterogeneity of absolute and relative…
Abstract
Purpose
The purpose of this paper is to analyze the heterogeneity of regional grain production distribution in China, by examining the regional heterogeneity of absolute and relative changes in grain planting acreage, and explain it in terms of increasing labor costs and difficulties in agricultural inputs adjustment.
Design/methodology/approach
The study uses data from official statistical yearbooks and the satellite remote sensing image data of Landsat TM 30 m. Multivariate analysis is conducted to examine the effect of labor cost, difficulty in replacing agricultural input factors and other factors underpinning changes in grain acreage and grain structure adjustment.
Findings
The heterogeneity of changes in grain acreage and proportion of arable area for grain production are mainly determined using the labor cost and difficulties in the replacement of agricultural input factors.
Originality/value
To the best of the authors’ knowledge, this study is the first to systematically analyze the heterogeneity in restructuring grain production at provincial level and its causes. The results not only provide evidence of grain production restructuring at regional level, but also contribute to the understanding of the law of structural change in agricultural production.
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Tiancong Hao, Weiping Wang, Geng Wang, Qiuyue Yang and Kang Ma
This paper examines students’ educational choices in vocational education and training (VET) to understand the low reputation of vocational education in China. By analysing the…
Abstract
Purpose
This paper examines students’ educational choices in vocational education and training (VET) to understand the low reputation of vocational education in China. By analysing the individualisation of these choices within structural and individual relationships, the study explores how the decline of state endorsement and the shift towards rational, individualistic actions influence students' decisions.
Design/methodology/approach
Multiple types of data were collected in this study, including administrative records, interviews and autobiographical stories, which were analysed using individualisation theory.
Findings
The research indicated three historical periods of the educational choice of Chinese VET students. Stage one (1978–1991) saw vocational education treated as “the first choice” for graduates. Stage two (1992–2000) was marked by the polarisation of educational choice during the social transition from a socialist planned economy to a market economy. During this period, more students started to choose academic high schools over vocational schools, even though the latter still had certain advantages for attracting the better-performing students. The third stage (2001-now) is a time in which vocational education is viewed as “the last choice” under the socialist market economy system. During this period, junior high school graduates prefer to enrol in academic high schools rather than in vocational schools. Aligned with the overall individualisation trend in Chinese society, vocational education decisions situated between societal structures and individuals are also experiencing a shift towards more micro-level individualized behaviours.
Research limitations/implications
The paper provides a historical analysis of education and training provision in China and the complexity of students’ educational choices, revealing the influencing factors across different stages.
Originality/value
This paper draws a comprehensive analysis of the developmental trajectory of vocational education in China across different historical periods, notably under the socialist planned economy and the socialist market economy systems.
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Rongjia Song, Weiping Cui, Jan Vanthienen, Lei Huang and Ying Wang
The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the…
Abstract
Purpose
The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the IoT-enabled Context-aware BPM (IoT-CaBPM) framework to bridge from the IoT infrastructure to context-aware business processes.
Design/methodology/approach
Motivated by the “Three Waves” of BPM research, IoT-enabled context-awareness is, therefore, expected to be achieved for enhancing the business process design, which pilots a new wave of BPR (Business Process Redesign/Reengineering) to enable the business process coevolve with IoT and analytics. This paper reports an illustrative case study of BPR in a Chinese bulk port, one of the hub seaports that widely adopted IoT technologies over the last few years.
Findings
The IoT implementation and data analytics has increased the efficiency and improve the monitoring effectively. The proposed IoT-CaBPM framework availably helps to identify and match nodes of IoT devices, business decisions and analytic models in order to redesign a business process towards context-aware variability. As IoT is rapidly becoming the new dominant IT paradigm is moving towards mature implementation in various industries, the corresponding BPR must be planned and executed strategically for achieving better benefits.
Originality/value
Despite some research extend BPM standard by integrating IoT devices as a sort of resources or report generically that the ports operations are affected by IoT, there is still a lack of layers from the IoT infrastructure to context-aware business processes. An industrial BPR case with business models in detail is also a lack for presenting the specific implications and effectiveness of the adoption of such technologies. This paper fills in this gap.
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Sheng Xu, Hao Wei Wang, Xing Zhang and Weiping He
The purpose of this paper is to investigate the corrosion behaviors of 2A12 aluminum alloy in NaCl and EXCO solution, and establish the relationship between the corrosion depth…
Abstract
Purpose
The purpose of this paper is to investigate the corrosion behaviors of 2A12 aluminum alloy in NaCl and EXCO solution, and establish the relationship between the corrosion depth and the time.
Design/methodology/approach
Alternate immersion corrosion test chamber was used to perform the corrosion test. The corrosion mediums were 3.5 percent NaCl solution and EXCO solution (NaCl 234 g/L, KNO3 50 g/L, 68 percent HNO3 6.8 mL/L). The surface morphology was studied using the digital microscope.
Findings
The average corrosion rate of aluminum alloy in NaCl solution decreased gradually at the initial stage and then went to a plateau value. The average corrosion rate of aluminum alloy in EXCO solution increased first, then showed a downward trend. The empirical function D=At B was verified.
Originality/value
The results could provide a reference for the establishment of accelerated environmental spectrum in the laboratory and give instructions on the application of aluminum alloy in alternated dry and wet environment.
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Lei Xie, Jonathan Wilson and Todd Sherron
The empirical findings of the roles of emotions in teams are mixed. This study, a scoping literature review, aims to synthesize extant research on the roles of emotions in work…
Abstract
Purpose
The empirical findings of the roles of emotions in teams are mixed. This study, a scoping literature review, aims to synthesize extant research on the roles of emotions in work teams and offers future research directions.
Design/methodology/approach
Sixty-nine empirical studies from the past ten years (2012 to 2021) were identified and reviewed. The authors then analyzed these 69 papers based on their research design, focus and nomological network of emotions.
Findings
The authors found that there is a clear increasing research trend of studying emotions in a team setting. In the extant literature, team emotions were studied from three major perspectives: emotions, emotional management and emotion measurement. The authors also summarized findings into the nomological network of team emotions. Last but not least, future research directions regarding the research context, focus and design and analysis were recommended.
Originality/value
The role of emotions in teams has not been extensively reviewed or synthesized, and the empirical findings are mixed. This paper synthesized the role of emotions in teams and critical factors that affect emotions in teams. In particular, the research recommendations for critical human resource development scholars cover three aspects: research context advancement, research focus advancement and research design and analysis advancement.
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With the growing climate problem, it has become a consensus to develop low-carbon technologies to reduce emissions. Electric industry is a major carbon-emitting industry…
Abstract
Purpose
With the growing climate problem, it has become a consensus to develop low-carbon technologies to reduce emissions. Electric industry is a major carbon-emitting industry, accounting for 35% of global carbon emissions. Universities, as an important patent application sector in China, promote their patent application and transformation to enhance Chinese technological innovation capability. This study aims to analyze low-carbon electricity technology transformation in Chinese universities.
Design/methodology/approach
This paper uses IncoPat to collect patent data. The trend of low-carbon electricity technology patent applications in Chinese universities, the status, patent technology distribution, patent transformation status and patent transformation path of valid patent is analyzed.
Findings
Low-carbon electricity technology in Chinese universities has been promoted, and the number of patents has shown rapid growth. Invention patents proportion is increasing, and the transformation has become increasingly active. Low-carbon electricity technology in Chinese universities is mainly concentrated in individual cooperative patent classification (CPC) classification numbers, and innovative technologies will be an important development for electric reduction.
Originality/value
This paper innovatively uses valid patents to study the development of low-carbon electricity technology in Chinese universities, and defines low-carbon technology patents by CPC patent classification system. A new attempt focuses on the development status and direction in low-carbon electricity technology in Chinese universities, and highlights the contribution of valid patents to patent value.
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Nadeen Aboudahab, Jesús del Brío and Eman Abdelsalam
This study presents a comprehensive investigation of turnover intention within the context of higher education, specifically focusing on private universities in Egypt, to develop…
Abstract
Purpose
This study presents a comprehensive investigation of turnover intention within the context of higher education, specifically focusing on private universities in Egypt, to develop a robust conceptual framework to explore this phenomenon.
Design/methodology/approach
The study sample comprised both male and female tenured faculty members from private universities, and data were collected through questionnaires, resulting in 396 completed responses. Statistical analysis was conducted using SPSS and partial least squares structural equation modeling (PLS-SEM) software.
Findings
The study highlights the significant impact of work-life balance (WLB) and organizational commitment on turnover intention, with job satisfaction as a mediating factor. Additionally, the research reveals that emotional intelligence (EI) does not directly influence turnover intention, but its effects are fully mediated by job satisfaction.
Originality/value
This research not only advances the theoretical understanding of why academics contemplate leaving their positions but also underscores the significance of this topic. Moreover, by exploring turnover intention in the private education sector of the Middle East, the study addresses a notable gap in the existing literature.
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Yuxiang Shan, Qin Ren, Gang Yu, Tiantian Li and Bin Cao
Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards…
Abstract
Purpose
Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.
Design/methodology/approach
Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.
Findings
Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.
Originality/value
This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.