Search results

The study explores the relationship between self-control and various online promotional methods faced by consumers simultaneously, simulating how consumers with distinct levels of self-control act in the current Chinese Internet market.

The sample was collected from response of participants to the survey containing a self-control test and attitudes towards different promotional methods. This is a quantitative study using regression and analysis of variance (ANOVA).

Initially, the empirical study focuses on discount margin for both price-discounts and full-discounts, which implies that high discount margin has a negative impact on the quality perception of consumers. However, this impact is weakened under full-discounts. Subsequently, the study identifies that the negative influence of high discounts on quality perception is insignificant for the high self-control group facing various promotional activities simultaneously. Furthermore, it is found that consumers with a high level of self-control rely more on their quality perception rather than the discount margin of products.

The study covers self-control of consumers, a variety of promotional methods and simulation of the present Chinese online market, enriching the research topic of consumer behavior as well as Internet marketing.

This study aims to present the critical role of knowledge management in digital entrepreneurship by reviewing the literature and proposing future research directions for digital entrepreneurship and knowledge management through an interdisciplinary framework.

This study uses the Derwent Data Analyzer to identify and visualise the extant studies on digital entrepreneurship. This study qualitatively analyses the hot topics and trends in digital entrepreneurship research to understand digital entrepreneurship from the knowledge management perspective.

The authors found two dominant trends in existing research: logical and development trend exploration at the theoretical background and empirical research at the practical dimension. To understand digital entrepreneurship from a knowledge management perspective, the authors summarised the theoretical logic and internal and external reasons why knowledge management is required in digital entrepreneurship. Moreover, the authors analysed the new features of digital entrepreneurship under five aspects: management concept, object, content, scope and focus. The authors concluded that existing research on integrating knowledge management and digital entrepreneurship is primarily conducted from three perspectives: technology, platform and ecosystem.

This study provides an in-depth analysis of digital entrepreneurship from a knowledge management perspective. The findings can further promote the theoretical research and practical development of digital entrepreneurship and knowledge management. This approach provides a new direction for interdisciplinary study and enriches entrepreneurship research. In addition, this study proposes a knowledge management framework for digital entrepreneurship research. The findings contribute to understanding the role and function of knowledge management in digital entrepreneurship.

The study aims to analyze how the characteristics of intellectual capital (IC) facilitate green entrepreneurship development in the context of ecology, environment and sustainability. Specifically, the evolution of IC and green entrepreneurship was explored through a systematic review, including the relationships and interactions between human, structural and relational capital and green entrepreneurship.

Meticulously combing the Web of Science Core Collection, the researcher conducted a bibliometric analysis of 800 English-language articles from 2002 to 2023. Employing co-word analysis and visualization, the literature on IC and green entrepreneurship was synthesized and systematized, exploring core topics, knowledge architectures and their evolutionary trajectories.

The IC elements such as human, structural and relational capital interact with green entrepreneurship; IC enhances the innovation and competitiveness of green entrepreneurship, while green entrepreneurship orientation influences the accumulation and reshaping of IC. The flow of IC impacts the establishment of green start-ups and the emergence of green industries, promoting sustainable growth.

The dynamic interplay between IC and green entrepreneurship is marked by intricate relationships and diverse attributes. Currently, no comprehensive theoretical model has been established to address the complexities intrinsic to this study. The evidence suggests that the green entrepreneurial orientation influences corporate initiatives to bolster human and structural capital, with structural capital serving as both a constraint and catalyst for human capital. The paper presents an embryonic framework of IC for green entrepreneurship, highlighting its critical role in the aggregation and reconfiguration of IC or venture creation and industry evolution. This contributes to a more profound understanding of IC in entrepreneurial contexts, providing a basis for future research and practical strategy.

Academic social network site (ASNS) is a new form of academic service in the social media age, and the study of ASNS user behavior is of great significance to academic librarians due to its recent popularity. This research explores the influencing factors of the continuous usage intention of ASNSs.

A survey of academics in China was conducted, and 361 responses were collected and analyzed with a structural equation model, which involves satisfaction, continuous usage intention, expectation confirmation, perceived usefulness (PU), social identity, referent network size and perceived interactivity (PI).

Satisfaction, expectation confirmation, PU, referent network size, social identity and PI significantly impact continuous usage intention. Satisfaction is a mediating variable by which expectation confirmation, PU, referent network size, social identity and other influencing factors affect continuous usage intention. Expectation confirmation and referent network size are two endogenous variables that can explain and predict the continuous usage intention of ASNSs.

Existing research does not consciously distinguish between adoption, use and continuous use, and only scant studies have conducted empirical research. Further, despite the widespread ASNS usage in China, Chinese scholars' studies are few, as existing studies have mainly focused on users of the UK, the US and India.

The paper aims to present a modeling method for multi‐layer, multi‐material printed circuit boards (PCBs) in both micro‐structure and board levels.

The method incorporates a multilayer finite element model that is established in two parts: the first part is an elasto‐plastic damaging model, which is presented to model metallic plies in the multi‐layer PCBs, while the second is a bi‐phase model for glass‐fiber/epoxy‐resin composite ply with fiber/matrix structure.

Numerous composite parts and complex material properties of multi‐layer PCBs complicate the reliability of the simulation. Therefore, the board level simulation and the micro‐structure modeling cannot be performed at the same time. A multi‐layer FEM code can solve this problem: with the use of bi‐phase and elasto‐plastic plies in this code, the micro‐structure and board‐level modeling for multi‐layer PCBs can be incorporated.

With the implementation of a virtual boundary method, the current multi‐layer model can be combined with the unit‐cell modeling method to perform detailed analysis at the micro‐structure level.

This paper presents a method for multi‐layer PCB modeling at both the micro‐structure and board levels. It provides a way to individually design the fabric types and the properties of glass fibers, epoxy resin, and copper foil in PCBs, to meet specific reliability requirements. With the proposed modeling, the static and shock responses of optimized PCBs can be analyzed with less computation.

This study aims to introduce an innovative approach that uses a decoder with multiple layers to accurately identify Chinese nested entities across various nesting depths. To address potential human intervention, an advanced optimization algorithm is used to fine-tune the decoder based on the depth of nested entities present in the data set. With this approach, this study achieves remarkable performance in recognizing Chinese nested entities.

This study provides a framework for Chinese nested named entity recognition (NER) based on sequence labeling methods. Similar to existing approaches, the framework uses an advanced pre-training model as the backbone to extract semantic features from the text. Then a decoder comprising multiple conditional random field (CRF) algorithms is used to learn the associations between granularity labels. To minimize the need for manual intervention, the Jaya algorithm is used to optimize the number of CRF layers. Experimental results validate the effectiveness of the proposed approach, demonstrating its superior performance on both Chinese nested NER and flat NER tasks.

The experimental findings illustrate that the proposed methodology can achieve a remarkable 4.32% advancement in nested NER performance on the People’s Daily corpus compared to existing models.

This study explores a Chinese NER methodology based on the sequence labeling ideology for recognizing sophisticated Chinese nested entities with remarkable accuracy.

This study aims to examine the risk-resistant role of environmental, social and governance (ESG) performance in the capital market, focusing on an organizational standpoint. Furthermore, it aims to offer management decision advice to companies seeking protection against stock market risks. Conclusions obtained through this research have the potential to enrich the economic consequences of ESG performance, provide practical implications for enhancing corporate ESG performance, improving corporate information quality and stabilizing capital market development.

Based on the data of Chinese A-share listed companies from 2009 to 2020, this study examines the risk-resistant function of ESG performance in the capital market. The impact of ESG performance on management behavior is analyzed from the perspective of organizational management and the three mechanisms of pre-event, during the event and post-event.

This paper demonstrates that companies that effectively implement ESG practices are capable of effectively mitigating risks associated with stock price crashes. Heterogeneity analysis reveals that the inhibitory effect of ESG performance on stock price crash risk is more pronounced in nonstate-owned enterprises and enterprises with higher levels of marketization. After controlling for issues such as endogeneity, the conclusions of this paper are still valid. The mechanism analysis indicates that ESG performance reduces the risk of stock price crash through three paths of organizational management: pre-event, during the event and post-event. That is, ESG performance plays the role of restraining managers’ opportunistic behavior, reducing information asymmetry and boosting investor sentiment.

This paper provides new insights into the relationship between ESG performance and stock price crash risk from an organizational management perspective. This study establishes three impact mechanisms (governance effect, information effect and insurance effect), offering a theoretical basis for strategic corporate decisions of risk management. Additionally, it comprehensively examines the contextual differences in the role of ESG performance, shedding light on the specific domains where ESG practices are influential. These findings offer valuable insights for promoting stable development in the capital market and fostering the healthy growth of the real economy.

The purpose of this study is to develop a 3D wheel-rail adhesion model under wet condition, which considers the generated surface roughness topography and the traditional braking procedure for high-speed trains.

Wheel-rail adhesion has an important effect on the braking ability of railway vehicle. Based on the deterministic mixed lubrication approach, the model was solved to get the adhesion characteristics of the train during braking. The elastic deformation was calculated with the discrete convolution and fast Fourier transform method. The simulation results of adhesion coefficient were compared with the experimental values. The wheel-rail adhesion characteristics of train braking at several different initial speeds were investigated. The effects of the time-step length and roughness orientation on the contact load ratio were also discussed.

The results show that the adhesion coefficient of the numerical model is in good agreement with the experimental results. At the instant of braking, the adhesion coefficient drops to a lower adhesion level, the value of adhesion coefficient is lower than 0.06, especially at a higher speed (200, 300 and 400 km/h).

It can provide a better understanding of the low adhesion phenomenon of train braking under wet condition.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0040/

Based on social cognitive theory, this study aims to investigate the influence of perceived overqualification (POQ) on employees’ cyberloafing behavior. The mediating role of moral disengagement and the moderating roles of organizational identification (OID) and organizational decline are further examined.

The authors collected 740 valid questionnaires from participants across multiple organizations. To minimize common method bias (CMB) and enhance the reliability of the findings, data were gathered at two different time points, with a 30-day interval.

POQ positively impacts cyberloafing through the mechanism of moral disengagement. Additionally, the indirect relationship between POQ and cyberloafing via moral disengagement is moderated by OID and organizational decline. Specifically, a higher degree of OID weakens the indirect effect of POQ on cyberloafing, while a higher level of perceived organizational decline strengthens this effect.

While most existing studies on cyberloafing focus on insufficient resources, such as role conflict and workload, the authors propose that surplus personal resources, exemplified by POQ, can also lead to cyberloafing. This research contributes to a broader understanding of antecedents of cyberloafing, highlighting the mechanism of ethical considerations and the interplay between personal qualifications, organizational identification and organizational decline.

To present a method to model woven fibre reinforced metal matrix composite for multilayer circuit boards.

This paper presents a hybrid modelling method to model multilayer multimaterial composites with the combination of metallic and woven composite plies. Firstly, 3D unit cells of woven composite are idealized as orthotropic plies, while metallic layers are taken as isotropic plies. Secondly, the idealized composite plies and metallic plies are modelled into a 2D multilayer finite element (FE). Lastly, scalar damage parameters are used for damage modelling.

Based on this method, static and dynamic analysis of multilayer composite can be performed at both micro and board levels. Meanwhile, the hybrid model illustrates a good agreement with the experimental results and good computational efficiency required for FE simulation. Conceptually, this study is aimed to provide an efficient damage modelling techniques for laminate composites and flexible modelling methodology for further development of new composite material systems.

Damaging testing and simulation is not involved, although damaging modelling method is presented.

This model has high flexibility and efficiency: the micro structure and properties of reinforced fibres, polymer matrix and metallic plies can be changed conveniently in 3D mechanics unit‐cell model; the 2D structure of geometry model provides a high‐computational efficiency in the numerical simulation. The presented work also provides the damage modelling methods, multi‐linear damage law and scalar damage parameters, to simulate damage behaviour after impact.