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Article
Publication date: 19 May 2022

Xixiong Xu, Cuiliang Lin and Lingling Duan

This study aims to investigate whether and how corporate seniority culture (a form of high power distance or hierarchy), a typical feature of Confucian norms, affects the…

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Abstract

Purpose

This study aims to investigate whether and how corporate seniority culture (a form of high power distance or hierarchy), a typical feature of Confucian norms, affects the corporate innovation efficiency in emerging markets.

Design/methodology/approach

This study defines and measures seniority culture through the ranking method of independent directors in company’s annual report. Unlike most companies in the USA where directors are listed alphabetically, the ranking of directors in China is meaningful and reflects hierarchy. This study considers a firm with seniority if independent directors are ranked according to their status, including age, social position and political connection. Using data from Chinese listed companies between 2009 and 2013, this study conducts multiple regressions to examine the impact of seniority on innovative efficiency.

Findings

The empirical results show that seniority culture is negatively associated with innovative efficiency. Moreover, the negative association between a corporate culture of seniority and innovative efficiency is more pronounced in firms with more male executives and knowledge-intensive firms. Further analysis reveals that seniority culture expands pay disparities among different classes, hinders their enthusiasm to communicate and ultimately damages the corporate efficiency of innovation.

Practical implications

Corporate seniority culture is an essential factor that may hinder employee communication and inhibit innovation efficiency. Therefore, companies should break the identity barrier at different levels and advocate a culture of equality to promote information exchange and knowledge sharing among employees.

Originality/value

This study extends the field of literature on the determinants of corporate innovation efficiency and deepens our theoretical understanding of the negative impact of corporate seniority culture.

Details

Chinese Management Studies, vol. 17 no. 3
Type: Research Article
ISSN: 1750-614X

Keywords

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Article
Publication date: 13 February 2017

Lingling Bao, Jiaying Wang, Jinggang Wang and Zheng Yu

Currently, China is the largest coal producer and consumer in the world. Underground mining is the main practice. In the process of deep mining, large amounts of low-temperature…

329

Abstract

Purpose

Currently, China is the largest coal producer and consumer in the world. Underground mining is the main practice. In the process of deep mining, large amounts of low-temperature waste heat are available such as in the mine return air (MRA), mine water (MW), bathing waste water (BWW), etc. Without recycling, the low-temperature waste heat is discharged directly into the atmosphere or into the drainage system. The temperature range of the MRA is about 15-25°C, the relative humidity (RH) of the MRA is above 90 per cent, the temperature range of MW is about 18-20°C and the temperature of the BWW is about 30°C. All of the above parameters are relatively stable throughout the year, and thus MRA, MW and BWW are proper low-temperature heat sources for water source heat pump (WSHP) systems. The study aims to introduce the schemes for recycling the different waste heat sources and the relevant key equipment and technology of each waste heat recycle system; analyze the heat recovery performances of the MRA heat recovery technology; and compare the economies between the MRA heat recovery system and the traditional system.

Design/methodology/approach

Based on the WSHP system, heat and mass transfer efficiencies were calculated and analyzed, the outlet air velocity diffusion of the heat and mass transfer units and the parameters including air flow rate, the MRA’s dry bulb temperatures and wet bulb temperatures at inlet and outlet of MRA heat exchanger were tested. Then, it was assessed whether this system can be applied to an actual construction. An actual reconstructive project of MRA heat recovery system is taken as an example, where the cost-saving effects of heat recovery of mine waste heat sources system are analyzed.

Findings

Analysis of field test reveals that when heat transfer is stable, heat transfer capacity can be achieved: 957.6 kW in summer, 681 kW in winter and a large amount of heat was recycled. In an economic analysis, by comparing initial investment and 10 years’ operation cost with the traditional boiler and central air conditioning system, the results show that although the MRA system’s initial investment is high, this system can save CNY 6.26m in 10 years.

Originality/value

MRA has a large amount of air volume and temperature that is constant throughout the year, and hence is a good low-temperature heat source for the WSHP system. It can replace boiler heating in winter and central air conditioning refrigeration in summer. The study reveals that this technology is feasible, and has good prospects for development.

Details

World Journal of Engineering, vol. 14 no. 1
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 28 November 2023

Wei Li, Yuxin Huang, Leilei Ji, Lingling Ma and Ramesh Agarwal

The purpose of this study is to explore the transient characteristics of mixed-flow pumps during startup process.

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Abstract

Purpose

The purpose of this study is to explore the transient characteristics of mixed-flow pumps during startup process.

Design/methodology/approach

This study uses a full-flow field transient calculation method of mixed-flow pump based on a closed-loop model.

Findings

The findings show the hydraulic losses and internal flow characteristics of the piping system during the start-up process.

Research limitations/implications

Large computational cost.

Practical implications

Improve the accuracy of current numerical simulation results in transient process of mixed-flow pump.

Originality/value

Simplify the setting of boundary conditions in the transient calculation.

Details

Engineering Computations, vol. 41 no. 1
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 24 June 2020

Junkai Wang, Bowen Zheng, Hefu Liu and Lingling Yu

Although materializing the benefits of social media substantially depends on sustained user participation, social media service providers are experiencing a decline in the number…

1753

Abstract

Purpose

Although materializing the benefits of social media substantially depends on sustained user participation, social media service providers are experiencing a decline in the number of users. Despite the relevance of studying and managing discontinuance behaviors, a systematic empirical investigation remains lacking. The present study draws on the idea of a two-factor model and aims to examine the enabler, inhibitor and their antecedents in the context of social media discontinuance.

Design/methodology/approach

The proposed theoretical model was empirically validated through an online survey study of 238 social media users in China.

Findings

Findings indicated that two negative outcomes of social media use (i.e. social overload and invasion of privacy) induce regret experience and ultimately foster discontinuance intentions. The development of discontinuance intentions was undermined by the level of inertia, which is rooted in social media habit, sunk costs and affective commitment.

Originality/value

This study draws attention to the fundamental difference between continuance and discontinuance behaviors, advances the existing understanding of postadoption behaviors by focusing on discontinuance inhibitors (e.g. inertia) and develops the first two-factor model for social media discontinuance by integrating the regret and status quo bias literature.

Details

Information Technology & People, vol. 34 no. 1
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 24 January 2025

Yanfang Qiu, Kun Ma, Weijuan Zhang, Run Pan and Zhenxiang Chen

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most…

7

Abstract

Purpose

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most existing detection methods primarily focus on capturing language features from news content. However, these methods neglect the varying importance of different news entities. Additionally, these methods tend to overlook the auxiliary role of external knowledge, resulting in an incomplete understanding of the entity. To address these issues, this paper aims to propose a Dual-layer Semantic Information Extraction Network with External Knowledge (DSEN-EK) for fake news detection.

Design/methodology/approach

This approach is proposed to comprise three parts: Dual-layer Semantic Information Extraction Network, Entity Integration Network with External Knowledge and Classifier. Specifically, Dual-layer Semantic Information Extraction Network is designed to enhance relationships between entities and the influence of important entity representations. The Entity Integration Network with External Knowledge is proposed to extract entity descriptions from external knowledge bases.

Findings

The DSEN-EK model performs well on the Liar, Constraint, Twitter15 and Twitter16 data sets, achieving accuracy of 98.02%, 94.61%, 90.09% and 93.65%, respectively. These results highlight its effectiveness in detecting fake news across different types of content.

Originality/value

The Dual-layer Semantic Information Extraction Network is proposed to capture the relationships between entities and enhance the continuous semantic information of the news. The Entity Integration Network with External Knowledge is designed to enrich entity descriptions, leading to a more comprehensive capture of semantic details.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

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Article
Publication date: 1 November 2024

Anum Paracha and Junaid Arshad

Advances in machine learning (ML) have made significant contributions to the development of intelligent and autonomous systems leading to concerns about resilience of such systems…

10

Abstract

Purpose

Advances in machine learning (ML) have made significant contributions to the development of intelligent and autonomous systems leading to concerns about resilience of such systems against cyberattacks. This paper aims to report findings from a quantitative analysis of literature within ML security to assess current research trends in ML security.

Design/methodology/approach

The study focuses on statistical analysis of literature published between 2000 and 2023, providing quantitative research contributions targeting authors, countries and interdisciplinary studies of organizations. This paper reports existing surveys and a comparison of publications of attacks on ML and its in-demand security. Furthermore, an in-depth study of keywords, citations and collaboration is presented to facilitate deeper analysis of this literature.

Findings

Trends identified between 2021 and 2022 highlight an increase in focus on adversarial ML – 40\% more publications compared to 2020–2022 with more than 90\% publications in journals. This paper has also identified trends with respect to citations, keywords analysis, annual publications, co-author citations and geographical collaboration highlighting China and the USA as the countries with highest publications count and Biggio B. as the researcher with collaborative strength of 143 co-authors which highlight significant pollination of ideas and knowledge. Keyword analysis highlighted deep learning and computer vision as the most common domains for adversarial attacks due to the potential to perturb images whilst being challenging to identify issues in deep learning because of complex architecture.

Originality/value

The study presented in this paper identifies research trends, author contributions and open research challenges that can facilitate further research in this domain.

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Article
Publication date: 30 August 2024

Alba Manresa, Ammar Sammour, Marta Mas-Machuca, Weifeng Chen and David Botchie

This paper seeks to explore the influence of generative artificial intelligence (GenAI) on employee performance in the workplace, viewed from a managerial perspective. It…

790

Abstract

Purpose

This paper seeks to explore the influence of generative artificial intelligence (GenAI) on employee performance in the workplace, viewed from a managerial perspective. It concentrates on key elements such as employee engagement, trust in GenAI and attitudes toward its implementation. This exploration is motivated by the ongoing evolution of GenAI, which presents managers with the crucial task of understanding and integrating this technology into their strategic frameworks.

Design/methodology/approach

We collected 251 responses from managers and senior managers representing companies that have embraced GenAI in Spain. A hierarchical regression analysis was employed to examine the hypotheses. Subsequently, mediating effects and moderated mediation effects were scrutinized using the bias-corrected bootstrapping method.

Findings

The data analysis suggests a significant enhancement in employee engagement and performance from a managerial perspective, attributed to improved attitudes and trust toward the adoption of GenAI. This conclusion is drawn from our research conducted with samples collected in Spain. Notably, our findings indicate that while positive attitudes toward GenAI correlate with enhanced engagement and performance, there exists a weakening effect on the significant positive impact of GenAI adoption in the workplace. This suggests that GenAI is still in its early stages of adoption within these companies, necessitating additional time for managers to develop greater confidence in its efficacy.

Originality/value

This study represents one of the pioneering investigations centered on the implementation of GenAI within the workplace context. It contributes significantly to the existing body of literature concerning the stimulus-organism-response (S-O-R) model in technology innovation adoption within work environments.

Details

Journal of Managerial Psychology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0268-3946

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Article
Publication date: 1 February 2022

Xiangfeng Chen, Chenyu Wang and Shuting Li

Agriculture and cultivation firms are facing severe competition in the saturated market. Due to the characteristics of heavy assets, low investment return, long cycle and high…

2540

Abstract

Purpose

Agriculture and cultivation firms are facing severe competition in the saturated market. Due to the characteristics of heavy assets, low investment return, long cycle and high price fluctuation, agri-food firms require innovations for capital support. The purpose of this paper is to provide valuable insights on how firms in the food/agricultural industry approach innovations and reinforce their advantages through functional and structural innovations by adopting supply chain finance (SCF).

Design/methodology/approach

This research adopts a single-case study methodology to investigate the innovations and mechanisms taking place at H Corp Agriculture Group (H Corp hereafter), a Chinese egg company.

Findings

The findings of this paper indicate that SCF could have a great impact on supply chain management through functional and structural innovations throughout the supply chain and solve the capital constraint problems in the agricultural development process, promoting the implementation of the integration strategy as well as innovation in the agricultural industry chain. The research also shows that supply chain structural and functional innovations could promote corporate social responsibility (CSR) and creating shared value (CSV).

Research limitations/implications

The research contributes to the application of SCF mechanisms and the realization of CSV and CSR jointly – both in the literature and in firms’ practices. It also contributes to the extension of structural and functional innovations and vertical integration of the supply chain. However, generalizability and universality are insufficient for a single case study in the specified industry. Data collection and quantitative analysis could be extended for further research.

Originality/value

The study addresses the need for comprehensive research on SCF and its applications. It proposes effective and efficient strategies for agri-food firms applying SCF to overcome industry capital constraints and develop competitiveness. It also provides a balanced and positive circulation between economic value and social value, realizing CSR and CSV.

Details

Supply Chain Management: An International Journal, vol. 28 no. 2
Type: Research Article
ISSN: 1359-8546

Keywords

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Article
Publication date: 11 March 2014

A. Garg, K. Tai and M.M. Savalani

The empirical modelling of major rapid prototyping (RP) processes such as fused deposition modelling (FDM), selective laser sintering (SLS) and stereolithography (SL) has…

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Abstract

Purpose

The empirical modelling of major rapid prototyping (RP) processes such as fused deposition modelling (FDM), selective laser sintering (SLS) and stereolithography (SL) has attracted the attention of researchers in view of their contribution to the overall cost of the product. Empirical modelling techniques such as artificial neural network (ANN) and regression analysis have been paid considerable attention. In this paper, a powerful modelling technique using genetic programming (GP) for modelling the FDM process is introduced and the issues related to the empirical modelling of RP processes are discussed. The present work aims to investigate the performance of various potential empirical modelling techniques so that the choice of an appropriate modelling technique for a given RP process can be made. The paper aims to discuss these issues.

Design/methodology/approach

Apart from the study of applications of empirical modelling techniques on RP processes, a multigene GP is applied to predict the compressive strength of a FDM part based on five given input process parameters. The parameter setting for GP is determined using trial and experimental runs. The performance of the GP model is compared to those of neural networks and regression analysis.

Findings

The GP approach provides a model in the form of a mathematical equation reflecting the relationship between the compressive strength and five given input parameters. The performance of ANN is found to be better than those of GP and regression, showing the effectiveness of ANN in predicting the performance characteristics of the FDM part. The GP is able to identify the significant input parameters that comply with those of an earlier study. The distinct advantages of GP as compared to ANN and regression are highlighted. Several vital issues related to the empirical modelling of RP processes are also highlighted in the end.

Originality/value

For the first time, a review of the application of empirical modelling techniques on RP processes is undertaken and a new GP method for modelling the FDM process is introduced. The performance of potential empirical modelling techniques for modelling RP processes is evaluated. This is an important step in modernising the era of empirical modelling of RP processes.

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