Jinghuan Zhang, Shan Wang, Wenfeng Zheng and Lei Wang
By drawing on the research paradigm of collective action that occurs in physical space, the present study aims to explore the antecedent predictors of network social mobilization…
Abstract
Purpose
By drawing on the research paradigm of collective action that occurs in physical space, the present study aims to explore the antecedent predictors of network social mobilization – feeling of injustice – and discuss the emotional mechanism of this prediction: mediating effect of anger and resentment.
Design/methodology/approach
Micro-blog postings about network social mobilization were collected to develop the dictionary of codes of fairness, anger and resentment. Then, according to the dictionary, postings on Sina Weibo were coded and analyzed.
Findings
The feeling of injustice predicted network social mobilization directly. The predictive value was 27% and 33%, respectively during two analyses. The feeling of injustice also predicted social mobilization indirectly via anger and resentment. In other words, anger and resentment account for the active mechanism in which the feeling of injustice predicts network social mobilization. Mediating effect value was 29.63% and 33.33% respectively.
Research limitations/implications
This study is our first exploration to use python language to collect data from human natural language pointing on micro-blog, a large number of comments of netizen about certain topic were crawled, but a small portion of the comments could be coded into analyzable data, which results in a doubt of the reliability of the study. Therefore, we should put the established model under further testing.
Practical implications
In the cyberspace, this study confirms the mechanism of network social mobilization, expands and enriches the research on social mobilization and deepens the understanding of social mobilization.
Social implications
This study provides an empirical evidence to understand the network social mobilization, and it gives us the clue to control the process of network social mobilization.
Originality/value
This study uses the Python language to write Web crawlers to obtain microblog data and analyze the microblog content for word segmentation and matching thesaurus. It has certain innovation.
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Joo Hun Yoo, Hyejun Jeong, Jaehyeok Lee and Tai-Myoung Chung
This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be…
Abstract
Purpose
This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be applied to the medical field are presented. About 80 reference studies described in the field were reviewed, and the federated learning framework currently being developed by the research team is provided. This paper will help researchers to build an actual medical federated learning environment.
Design/methodology/approach
Since machine learning techniques emerged, more efficient analysis was possible with a large amount of data. However, data regulations have been tightened worldwide, and the usage of centralized machine learning methods has become almost infeasible. Federated learning techniques have been introduced as a solution. Even with its powerful structural advantages, there still exist unsolved challenges in federated learning in a real medical data environment. This paper aims to summarize those by category and presents possible solutions.
Findings
This paper provides four critical categorized issues to be aware of when applying the federated learning technique to the actual medical data environment, then provides general guidelines for building a federated learning environment as a solution.
Originality/value
Existing studies have dealt with issues such as heterogeneity problems in the federated learning environment itself, but those were lacking on how these issues incur problems in actual working tasks. Therefore, this paper helps researchers understand the federated learning issues through examples of actual medical machine learning environments.
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Graziella Pagliarulo McCarron and Aoi Yamanaka
According to the U.S. Department of Education’s National Center for Education Statistics, in the fall of 2020, 72.8% of U.S. postsecondary students were enrolled in distance…
Abstract
According to the U.S. Department of Education’s National Center for Education Statistics, in the fall of 2020, 72.8% of U.S. postsecondary students were enrolled in distance education courses—up from 36.3% in the fall of 2019. While this surge may be explained by a number of factors, one of the most significant factors is the COVID-19-induced pivot to online learning. The rapid and intense expansion in distance education due to COVID-19 offered learners some sense of continuity in their studies, but it also revealed stark inequities in learner resources and access—especially for students of Color and students from lower-income households. Further, as COVID-19 spread, the U.S. roiled in a “twin pandemic” of racial injustice that continued to metastasize—spawning more pain-points such as online environments where racism became unmasked when face-to-face norms were abandoned. These revelations about the shadow side of online learning are particularly concerning in the context of leadership education and its commitment to inclusion, collaboration, and holism. Given this new context for online leadership education, the purpose of this piece is to reflect on how the Journal of Leadership Education has shepherded the journey of online leadership education and what the future of this journey might look like for online leadership educators committed to change. Scaffolded by the Community of Inquiry model, we offer promising practices that address cognitive, social, teaching, and learner presence in the pursuit of culturally relevant/sustaining and equitable online leadership education.
Xiaoyue Chen, Bin Li, Tarlok Singh and Andrew C. Worthington
Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure…
Abstract
Purpose
Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.
Design/methodology/approach
We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.
Findings
Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.
Research limitations/implications
Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.
Originality/value
The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.
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Jingfeng Xie, Jun Huang, Lei Song, Jingcheng Fu and Xiaoqiang Lu
The typical approach of modeling the aerodynamics of an aircraft is to develop a complete database through testing or computational fluid dynamics (CFD). The database will be huge…
Abstract
Purpose
The typical approach of modeling the aerodynamics of an aircraft is to develop a complete database through testing or computational fluid dynamics (CFD). The database will be huge if it has a reasonable resolution and requires an unacceptable CFD effort during the conceptional design. Therefore, this paper aims to reduce the computing effort required via establishing a general aerodynamic model that needs minor parameters.
Design/methodology/approach
The model structure was a preconfigured polynomial model, and the parameters were estimated with a recursive method to further reduce the calculation effort. To uniformly disperse the sample points through each step, a unique recursive sampling method based on a Voronoi diagram was presented. In addition, a multivariate orthogonal function approach was used.
Findings
A case study of a flying wing aircraft demonstrated that generating a model with acceptable precision (0.01 absolute error or 5% relative error) costs only 1/54 of the cost of creating a database. A series of six degrees of freedom flight simulations shows that the model’s prediction was accurate.
Originality/value
This method proposed a new way to simplify the model and recursive sampling. It is a low-cost way of obtaining high-fidelity models during primary design, allowing for more precise flight dynamics analysis.
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Tran Thai Ha Nguyen, Gia Quyen Phan, Wing-Keung Wong and Massoud Moslehpour
This research examines the relationship between market power and liquidity creation in the specific context of bank profitability in the Vietnamese banking sector.
Abstract
Purpose
This research examines the relationship between market power and liquidity creation in the specific context of bank profitability in the Vietnamese banking sector.
Design/methodology/approach
The study applies the methodology proposed by Berger and Bouwman (2009) to demonstrate the creation of bank liquidity through a three-step procedure for investigating the relationship between market power and liquidity creation. The three steps include non-fat liquidity (NFLC), fat liquidity (FLC) and system generalized method of moments estimation for panel data.
Findings
This study finds that liquidity creation increases when a bank has high market power. Further, highly profitable banks positively impact the market power of banks with regard to liquidity creation, relative to less profitable banks. Moreover, bank size, capital, economic growth and interest rate negatively influence bank liquidity creation, while credit risk positively relates to bank liquidity creation.
Research limitations/implications
Measurements used in this study are based on the works of Berger and Bouwman (2009). There are specific variations, relative to Basel III. In addition, other variables significantly impact bank liquidity creation that have not been considered in the models, and a quadratic model should have been considered to measure market power and bank liquidity creation.
Practical implications
This study suggests that managers should control the liquidity of their banks by supervising vulnerable characteristics that have been mentioned herein and emphasizing improvements in profitability. Further, the government may consider encouraging banks to generate more liquidity by modifying regulations concerned with market power or reinforcing policies about improving the transparent business environment.
Originality/value
This study characterizes an attempt to examine the influence of market power on the liquidity creation of banks in Vietnam, which represents one of the most dynamic systems in Asia, with several varied participating banks. The current study also examines the same within the specific context of the modifying impact of the profitability of banks.
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Juliano Pelegrina, Timo Stoeber and Nuno Manoel Martins Dias Fouto
Due to dramatic transformation of the auto industry, governments are implementing innovation policies to ensure the domain of sustainable technologies. According to the…
Abstract
Purpose
Due to dramatic transformation of the auto industry, governments are implementing innovation policies to ensure the domain of sustainable technologies. According to the literature, developing countries that depend on multinational subsidiaries must invest in complementary innovation to be part of their research and development (R&D) headquarters' long-term plans. This study analyses the Brazilian auto industry innovation policy (Rota 2030) to evaluate if it targets complementarity with the German's one (NPE). It also compares the institutional arrangements of the former against the latter to check for governance gaps.
Design/methodology/approach
It applies a case-oriented comparative method (Ragin, 2014) for the analysis of qualitative evidence on secondary data. It investigates evidence of complementarity between Rota 2030 and national platform for electric mobility (NPE) objectives and checks for governance gaps in Rota 2030 using NPE as a reference.
Findings
The results confirmed a loose fitting between the innovation policies mainly for a lack of determinism of Rota 2030 objectives. Governance gaps were also found on Rota 2030 policy formulation and operationalization.
Practical implications
It contributes for the improvement of Rota 2030, and its analytical frame may be used for the formulation or adjustment of other developing countries' innovation policies.
Originality/value
It contributes with innovation system and policy field development with a theoretical extension coming from the New Institutional Economics (NIE) (Menard, 2018). By examining the performance of “institutional arrangements” during the process of formulation and operationalization of innovation policies, it shows the importance of coordination for their effectiveness.
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Warot Moungsouy, Thanawat Tawanbunjerd, Nutcha Liamsomboon and Worapan Kusakunniran
This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face…
Abstract
Purpose
This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.
Design/methodology/approach
The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.
Findings
The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.
Originality/value
The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.
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Tomasz Mucha, Sijia Ma and Kaveh Abhari
Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities…
Abstract
Purpose
Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.
Design/methodology/approach
Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.
Findings
The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.
Originality/value
This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.
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Xiaoman Li, Xinxin Yang and Qi Zheng
Based on traditional Chinese filial piety, this article examines the impacts and mechanisms of the two-dimensional filial piety concept “Qinqin – Zunzun” on gender wages in China…
Abstract
Purpose
Based on traditional Chinese filial piety, this article examines the impacts and mechanisms of the two-dimensional filial piety concept “Qinqin – Zunzun” on gender wages in China via China Family Panel Studies (CFPS) conducted in 2014 and 2018.
Design/methodology/approach
This article construct regression models to examine the relationship between filial piety concepts and wages. Also, it uses unconditional quantile regression and decomposition to explore the impact of filial piety concepts on the wage gap.
Findings
It is found that: (1) The effects of two-dimensional filial piety are heterogeneous in terms of gender. Specifically, authoritarian filial piety significantly suppresses individual wages and has a stronger suppressive effect on women’s wages, whereas affinity filial piety significantly enhances individual wages without gender heterogeneity; (2) Parents' time support in the intergenerational exchange model is a crucial mechanism by which filial piety affects wages, exhibiting significant gender heterogeneity; (3) Regarding wage distribution, authoritarian filial piety mainly widens the gender income gap in the low and middle income-groups, while affinity filial piety narrows the gender wage gap by “raising the floor”, with its converging effect being most significant in the middle and high-income groups. This article deepens the understanding of the gender wage gap and intergenerational income mobility, providing policy references for better utilizing the social governance function of culture.
Originality/value
The article deepens the understanding and mechanisms of the gender wage gap and inter-generational income mobility, providing policy reference for better utilizing the social governance function of culture.