Lei Gan, Anbin Wang, Zheng Zhong and Hao Wu
Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data…
Abstract
Purpose
Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data requirements, they are cost-prohibitive and underperforming for application scenarios with limited data. Therefore, it is essential to develop an advanced model with good applicability to small-sample problems for multiaxial fatigue life assessment.
Design/methodology/approach
Drawing inspiration from the modeling strategy of empirical multiaxial fatigue models, a modular neural network-based model is proposed with assembly of three sub-networks in series: the first two sub-networks undergo pretraining using uniaxial fatigue data and are then connected to a third sub-network trained on a few multiaxial fatigue data. Moreover, general material properties and necessary loading parameters are used as inputs in place of explicit damage parameters, ensuring the universality of the proposed model.
Findings
Based on extensive experimental evaluations, it is demonstrated that the proposed model outperforms empirical models and conventional data-driven models in terms of prediction accuracy and data demand. It also holds good transferability across various multiaxial loading cases.
Originality/value
The proposed model explores a new avenue to incorporate uniaxial fatigue data into the data-driven modeling of multiaxial fatigue life, which can reduce the data requirement under the promise of maintaining good prediction accuracy.
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While the determinants of voluntary political spending disclosure have been extensively studied in the literature, there remains a lack of clear evidence regarding the specific…
Abstract
Purpose
While the determinants of voluntary political spending disclosure have been extensively studied in the literature, there remains a lack of clear evidence regarding the specific impacts of managerial ability and political risk on such disclosure. Thus, the purpose of this study is to shed light on whether and how managerial ability and political risk influence firms’ political spending disclosure.
Design/methodology/approach
This study uses a sample of 2,242 firm-year observations of S&P 500 companies between 2013 and 2021.
Findings
This study finds that firms with high-ability managers generally disclose more information about political spending. This positive relationship between managerial ability and political spending disclosure holds even after conducting additional tests to address potential endogeneity concerns. Furthermore, this study finds that firms operating in high-risk political environments also exhibit a greater propensity to disclose information regarding their political spending. The results remain robust to alternative measures of managerial ability and political risk.
Practical implications
This study suggests that when designing policy to motivate firms to disclose political spending information, policy makers need to be aware of the critical role of managerial ability and idiosyncratic political risk the firm faces. In addition, this study offers insights to shareholders, advocacy groups, regulators and academics interested in understanding the determinants of political spending disclosure.
Originality/value
This study is among the first to provide empirical evidence that political spending disclosure can be explained by managerial ability and political risk. In addition, this study complements the literature on the consequences of managerial ability and political risk. Focusing on voluntary political spending disclosure, this study contributes to a deeper understanding of the factors shaping the overall corporate information environment.
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Ragia Shelih and Li Wang
This study aims to empirically explore the influence of managerial ability on crash risk and the moderating effect of financial constraints on this interrelationship.
Abstract
Purpose
This study aims to empirically explore the influence of managerial ability on crash risk and the moderating effect of financial constraints on this interrelationship.
Design/methodology/approach
Using a sample of listed corporations in the Egyptian Stock Exchange during 2018–2021, the authors test the hypotheses by using the measures and methods well established in prior literature. The authors also conduct multiple robustness analyses to ensure the validity of the empirical results.
Findings
The findings suggest that managerial ability can effectively inhibit crash risk. In addition, the authors report that financial constraints significantly dampen this relationship. Thus, financial restrictions play a striking role in hampering the managerial ability to prevent stock crashes. Furthermore, the authors document that the moderating role of severe financing constraints is more prominent during the Covid-19 pandemic period.
Originality/value
The originality of this study stems from the following considerations. First, this study enriches relevant studies on crash risk by providing evidence from one of the emerging markets in the Middle East; thereby, contrasting with those in developed economies. Second, to the best of the authors’ knowledge, this is the first study investigating the moderating impact of financing constraints on the managerial ability and crash risk nexus. Therefore, this work adds value to the extant knowledge by scrutinizing this important issue and providing novel empirical evidence.
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Xia Liu, Yuli Wang, Shanshan Li, Lei Chen, Fanbo Li and Hongfeng Zhang
The objective of this study is to utilize empirical research and analysis to examine the coupling coordination relationship between new quality productivity and higher vocational…
Abstract
Purpose
The objective of this study is to utilize empirical research and analysis to examine the coupling coordination relationship between new quality productivity and higher vocational education sustainable development.
Design/methodology/approach
To this end, an evaluation index system for the new quality productivity and higher vocational education sustainable development was constructed. The panel data of 30 Chinese provinces from 2016 to 2022 were then analyzed using the entropy method, the coupling coordination degree model, the Tobit regression model and Dagum’s Gini coefficient.
Findings
The findings indicate that the coupling coordination degree of new quality productivity and higher vocational education sustainable development exhibited an upward trend, though significant regional disparities were observed, with the highest coupling coordination degree recorded in the eastern region and the lowest in the northeastern region.
Originality/value
The study’s findings further suggest that the three factors of technological innovation level, rationalization of industrial structure and advanced industrial structure have a significant positive influence on the coupling coordination degree, while the level of government intervention has a significant negative influence on the Coupling Coordination Degree. The study posits that augmenting policy support, optimizing the government’s role, reinforcing the drive for technological innovation, and enhancing regional cooperation and exchange are imperative to foster high-quality development of the integration of industry and education between new quality productivity and higher vocational education.
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Malak Hamade, Khaled Hussainey and Khaldoon Albitar
This systematic review aims to comprehensively explore the existing literature on the use of corporate communication within the realm of social media.
Abstract
Purpose
This systematic review aims to comprehensively explore the existing literature on the use of corporate communication within the realm of social media.
Design/methodology/approach
A total of 136 peer-reviewed journal articles are explored and analysed using both performance and bibliometric analysis.
Findings
This review identifies five main findings: (1) trends in corporate social media research that highlight the growth trajectory of research on social media use for corporate disclosure, (2) geographical coverage of studies indicating the concentration of research in certain regions, such as the USA, followed by China and the UK, with notable gaps in others, such as developing countries, (3) theoretical frameworks employed demonstrate that various theoretical frameworks are utilized, although a significant portion of the studies do not specify any theoretical underpinning, (4) social media platforms studied, confirming Twitter to be the most studied channel followed by Facebook and (5) thematic analysis of articles on disclosure type that categorized the articles using bibliometric analysis into five themes of disclosure: general disclosure, corporate social responsibility-related information, financial information, CEO announcements and strategic news communication. A subsequent cross-theme analysis classifies disclosure determinants and consequences of corporate social media usage.
Originality/value
Through a comprehensive and systematic analysis of existing research, this review offers novel insights into the current state of corporate communication on social media. It consolidates current knowledge, highlights under-explored areas in the existing literature and proposes new directions and potential avenues for future research.
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Hao Zhang, Weilong Ding, Qi Yu and Zijian Liu
The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing…
Abstract
Purpose
The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing data, ensuring reliable analysis outcomes.
Design/methodology/approach
The Conv-DMSA model employs a combination of self-attention mechanisms and convolutional networks to handle the complexities of multivariate time series data. The convolutional network is adept at learning features across uneven time intervals through an imputation feature map, while the Diagonal Mask Self-Attention (DMSA) block is specifically designed to capture time dependencies and feature correlations. This dual approach allows the model to effectively address the temporal imbalance, feature correlation and time dependency challenges that are often overlooked in traditional imputation models.
Findings
Extensive experiments conducted on two public data sets and a real project data set have demonstrated the adaptability and effectiveness of the Conv-DMSA model for imputing missing data. The model outperforms baseline methods by significantly reducing the Root Mean Square Error (RMSE) metric, showcasing its superior performance. Specifically, Conv-DMSA has been found to reduce RMSE by 37.2% to 63.87% compared to other models, indicating its enhanced accuracy and efficiency in handling missing data in multivariate time series.
Originality/value
The Conv-DMSA model introduces a unique combination of convolutional networks and self-attention mechanisms to the field of missing data imputation. Its innovative use of a diagonal mask within the self-attention block allows for a more nuanced understanding of the data’s temporal and relational aspects. This novel approach not only addresses the existing shortcomings of conventional imputation methods but also sets a new standard for handling missing data in complex, multivariate time series data sets. The model’s superior performance and its capacity to adapt to varying levels of missing data make it a significant contribution to the field.
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Wenqian Feng, Xinrong Li, Jiankun Wang, Jiaqi Wen and Hansen Li
This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for…
Abstract
Purpose
This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.
Design/methodology/approach
In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.
Findings
Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.
Originality/value
This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.
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Sadashiva Tandur, Adarsh Garg and Mujibur Rahman
The primary objective of this research is to identify and analyze the influence of digital marketing practises on performance of business of manufacturing enterprises in…
Abstract
The primary objective of this research is to identify and analyze the influence of digital marketing practises on performance of business of manufacturing enterprises in Delhi-NCR. A quantitative and descriptive research design was implemented in this study. 368 participants from various enterprises were chosen. Questionnaires were used to collect data on the benefits and challenges which are perceived of digital marketing, as well as usage and business performance of these enterprises. SPSS v24.0 is utilized to carry out statistical analysis on the collected data. The study discovered that advantages and problems of digital marketing practices influenced the usage of digital marketing. Furthermore, the execution of digital marketing had a prominent influence on sales and total number of customers of these enterprises, and this relationship was moderated by type and size of businesses. It was discovered that using digital marketing strategies increased business profits by raising digital marketing awareness among consumers and various industries. It made digital marketing easier to implement in various businesses. However, research should be conducted for appropriate generalization in a larger scale.
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Dat Tien Doan, Tuyet Phuoc Anh Mai, Ali GhaffarianHoseini, Amirhosein Ghaffarianhoseini and Nicola Naismith
This study aims to identify the primary research areas of modern methods of construction (MMC) along with its current trends and developments.
Abstract
Purpose
This study aims to identify the primary research areas of modern methods of construction (MMC) along with its current trends and developments.
Design/methodology/approach
A combination of bibliometric and qualitative analysis is adopted to examine 1,957 MMC articles in the Scopus database. With the support of CiteSpace 6.1.R6, the clusters, leading authors, journals, institutions and countries in the field of MMC are examined.
Findings
Offsite construction, inter-modular connections, augmenting output, prefabricated concrete beams and earthquake-resilient prefabricated beam–column steel joints are the top five research areas in MMC. Among them, offsite construction and inter-modular connections are significantly focused, with many research articles. The potential for collaboration, among prominent authors such as Wang, J., Liu, Y. and Wang, Y., explains the recent rapid growth of the MMC field of research. With a total of 225 articles, Engineering Structures is the journal that has published the most articles on MMC. China is the leading country in this field, and the Ministry of Education China is the top institution in MMC.
Originality/value
The findings of this study bear significant implications for stakeholders in academia and industry alike. In academia, these insights allow researchers to identify research gaps and foster collaboration, steering efforts toward innovative and impactful outcomes. For industries using MMC practices, the clarity provided on MMC techniques facilitates the efficient adoption of best practices, thereby promoting collaboration, innovation and global problem-solving within the construction field.
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Svitlana Magalhães de Sousa Ostapenko, Ana Paula Africano and Raquel Meneses
This study aims to further develop the CLC stage/path’s identification model that distinguishes between path’s emergence (emergence stage), path’s development (growth stage)…
Abstract
Purpose
This study aims to further develop the CLC stage/path’s identification model that distinguishes between path’s emergence (emergence stage), path’s development (growth stage), path’s sustainment (maturity stage), path’s decline (decline stage) and path’s transformation (renewal stage), and by applying it, define the current stage/path of the Demarcated Douro Region (DDR) cluster. The Port wine industry, which is the dominant industry of the DDR cluster, is at the maturity/decline stage – is the same for the cluster itself?
Design/methodology/approach
It is a case study with a longitudinal perspective based on the analysis of the dynamics of the parameters of cluster evolution using available secondary sources (cluster identity/brand; number of firms; number of employees; network; innovation; policies and regulations; and external markets – exports), especially addressing the past decade, that represent the stage of maturity/decline of the cluster’s dominant Port wine industry.
Findings
The conclusion is that since the 1990s the Demarcated Douro Region has gone through a “path transformation” where during the following 20 years new “anchors” for the cluster were gradually introduced, such as Doc Douro Wines, new forms of consumption of Port wine, tourism and olive oil. Since 2010 the cluster has entered a growth stage/(new) path’s development, where these “anchors” are in steady growth. The Douro brand is becoming more internationally recognized and established, the number of firms and employees is increasing, the network is restructuring with the creation of cluster-specific official institutions, innovation is especially reflected with increasing heterogeneity through diversification of the clusters into new activities and regulations and policies are supportive for expansion – all these parameters are indicating the rise of the new cycle for the cluster. Thus, the DDR cluster represents an attractive business environment and requires attention from regional policymakers to support the cluster’s development. Especially institutions have been highlighted as internal factors driving clusters growth, European integration as an external factor and firms’ strategies of diversification and internationalization as an appropriate de-locking mechanism for new path’s development.
Research limitations/implications
This research contributes to the CLC theory by further developing and applying a CLC stage/path identification model. It provides a better understanding of the dynamics of the DDR cluster that diverge from its dominant industry life cycle, which is relevant for regional policies and firms’ strategies. This study has its limitations. It provides an exploratory application of the theoretical framework proposed, and consequently, no general conclusions are possible yet. More empirical studies with different clusters in different stages are necessary to test the framework.
Practical implications
These findings are useful to policymakers when designing their policies for cluster development but also for clusters’ entities and actors when making their strategic decisions as it allows based on the verification of the established parameter of CLC to identify its current stage/path of development.
Originality/value
The paper presents a theoretically grounded model for CLC identification and for the first time to the best of the authors’ knowledge applies it to a cluster case – the DDR cluster. This case applies the proposed model and illustrates its usefulness. The model provides the tools for a better understanding of cluster dynamics.