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Article
Publication date: 18 July 2023

Nilesh Kumar, Yanghua Jin and Zhiqiang Liu

This study, based on motivated information processing theory and theories of leadership (contingency and functional), investigates how servant leadership (SL) could be an…

Abstract

Purpose

This study, based on motivated information processing theory and theories of leadership (contingency and functional), investigates how servant leadership (SL) could be an effective leadership style for employee creative deviance engagement (CDE) to foster radical (RC) and incremental creativity (IC) in two different goal-oriented organizations: learning (LGO) and performance (PGO) goal-oriented organizations.

Design/methodology/approach

This study employed descriptive and comparative approaches and surveyed two sources (leaders and team members). Using multi-source data involving 486 LGO-based and 498 PGO-based employee–supervisor dyads from 104 LGO-based and 104 PGO-based high-tech firms in China, the authors distinguish comparative support for assumed hypotheses by using the Monte Carlo simulation technique for the indirect effects and Mplus for multilevel path analysis.

Findings

The study outcomes found that SL transmits the effects of employee CDE directly and nurtures RC and IC indirectly. It identified that an organization's LGO strengthens the direct and indirect relationships between SL and creativity via employee's CDE when the organization's LGO is high. However, an organization's PGO strengthens the direct relationship when it's low and strengthens the indirect link between SL and IC when it's high. In addition, the organization's PGO demonstrated an insignificant effect on the indirect relationship between SL and RC.

Originality/value

This study is the first to verify SL as the specific leadership style for responding employee's CDE and identify its distinctive effects on RC and IC. Additionally, there has been no effort to associate SL with employee's CDE for nurturing distinctive types of creativity under the different organizational dispositions (LGO and PGO).

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 7 September 2023

Syed Mudasser Abbas, Zhiqiang Liu and Muhammad Khushnood

This study aims at investigating how hybrid intelligence might enhance employee engagement in breakthrough innovation. Specifically, it empirically examines the mediating role of…

Abstract

Purpose

This study aims at investigating how hybrid intelligence might enhance employee engagement in breakthrough innovation. Specifically, it empirically examines the mediating role of self-extinction and moderating role of social intelligence.

Design/methodology/approach

This study, using the lens of socio-technical system (STS) theory, collected data from 317 employees through cross-sectional survey. The hypotheses were tested using MPlus 8.3 by applying Structural Equation Modelling (SEM).

Findings

The results support the proposed model, suggesting that hybrid intelligence fosters employees' breakthrough innovation engagement and such a relationship is fully mediated by self-extinction. Besides, the findings provide support for the positive moderating impact of social intelligence on such indirect relationships in a way that high social intelligence will further strengthen the relationship.

Originality/value

As a pioneering contribution, the study uncovers the social mechanism that underlies hybrid intelligence–breakthrough innovation engagement relationship via self-extinction. The research suggests managers leveraging employees' social intelligence for playing a critical role in countering the negative impact of self-extinction by enhancing the employees' engagement in the breakthrough innovation process.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 11 April 2023

Qi Yang, ZhiQiang Feng, RuanBing Zhang, YunPu Wang, DengLe Duan, Qin Wang, XiaoYu Zou and YuHuan Liu

This study aims to develop a green, economical and efficient ultrasonic-/microwave assisted extraction (UMAE) process for the extraction of anthocyanins.

Abstract

Purpose

This study aims to develop a green, economical and efficient ultrasonic-/microwave assisted extraction (UMAE) process for the extraction of anthocyanins.

Design/methodology/approach

After optimizing the extraction conditions by response surface methodology, three assays including DPPH, ABTS·+, FRAP were applied to analyze the antioxidant activity of the extracted anthocyanins. The stability under different temperatures, reductant concentrations and pHs was also discussed. The components of anthocyanins in blueberry were analyzed by HPLC-QTOF-MS2.

Findings

The optimal extraction parameters were ultrasonic power of 300 W, microwave power of 365.28 W and solid–liquid ratio of 30 (g/mL). The possible structures can be speculated as Delphinidin-3-O-galactoside, Delphinidin, Petunidin, Delphinidin-3-O-glucoside, Petunidin-3-O-glucoside, Cyanidin-3-O-glucoside. The results demonstrated that the UMAE can improve the yield of anthocyanins in shorter extraction time with higher activity.

Originality/value

The present study may provide a promising and feasible route for extracting anthocyanins from blueberries and studying their physicochemical properties, ultimately promoting the utilization of blueberry anthocyanins.

Details

Pigment & Resin Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 20 March 2024

Gang Yu, Zhiqiang Li, Ruochen Zeng, Yucong Jin, Min Hu and Vijayan Sugumaran

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due…

25

Abstract

Purpose

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Design/methodology/approach

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

Findings

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

Originality/value

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 26 December 2023

Asad Ullah Khan, Zhiqiang Ma, Mingxing Li, Liangze Zhi, Weijun Hu and Xia Yang

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding…

Abstract

Purpose

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Design/methodology/approach

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Findings

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

Originality/value

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

Article
Publication date: 17 October 2022

Xinmin Tian, Zhiqiang Zhang, Cheng Zhang and Mingyu Gao

Considering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country…

Abstract

Purpose

Considering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country, China's research can provide meaningful reference for the research of financial markets in other new countries.

Design/methodology/approach

From the perspective of behavior, establishing a direct link between individual investor attention and stock price overvaluation.

Findings

The authors find that there is a significant idiosyncratic volatility puzzle in China's stock market. Due to the role of mispricing, individual investor attention significantly enhances the idiosyncratic volatility effect, that is, as individual investor attention increases, the greater the idiosyncratic volatility, the lower the expected return. Attention can explain the idiosyncratic volatility puzzle in China's stock market. In addition, due to the role of information production and dissemination, securities analysts can reduce the degree of market information asymmetry and enhance the transparency of market information.

Originality/value

China is the second largest economy in the world, and few scholars analyze it from the perspective of investors' attention. The authors believe this paper has the potential in contributing to the academia.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 16 January 2024

Afees Adebare Salisu, Aliyu Akorede Rufai and Modestus Chidi Nsonwu

This study aims to construct alternative models to establish the dynamic relationship between exchange rates and housing affordability by estimating both the short- and long-run…

Abstract

Purpose

This study aims to construct alternative models to establish the dynamic relationship between exchange rates and housing affordability by estimating both the short- and long-run relationship between exchange rates and housing affordability for 18 OECD countries from 1975Q1 to 2022Q4. After that, this study demonstrates how this nexus behaves during high and low inflation regimes and turbulent times.

Design/methodology/approach

This study uses the panel autoregressive distributed lag technique to examine the nexus between housing affordability to capture the distinct characteristics of the sample countries and estimate various short- and long-run dynamics in the relationship between housing affordability and exchange rate.

Findings

Exchange rate appreciation improves housing affordability in the short run, whereas this connection tends to dissipate in the long run. Moreover, inflation can worsen housing affordability during turbulent times, such as the global financial crisis, in both the short and long run. Ignoring these changes in the relationship between exchange rates and housing affordability during turbulent times can lead to incorrect conclusions.

Originality/value

To the best of the authors’ knowledge, this study is the first to examine the association between exchange rates and housing affordability by demonstrating how these variables behave in high and low inflation regimes and turbulent times.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

Open Access
Article
Publication date: 15 March 2024

Di Cheng, Yuqing Wen, Zhiqiang Guo, Xiaoyi Hu, Pengsong Wang and Zhikun Song

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Abstract

Purpose

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Design/methodology/approach

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

Findings

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Originality/value

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Details

Railway Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2755-0907

Keywords

Article
Publication date: 16 June 2023

Xin Feng, Xu Wang and Mengxia Qi

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an…

Abstract

Purpose

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

Design/methodology/approach

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

Findings

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Originality/value

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 5 December 2023

Jun Liu, Sike Hu, Fuad Mehraliyev, Haiyue Zhou, Yunyun Yu and Luyu Yang

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into…

Abstract

Purpose

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

Design/methodology/approach

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

Findings

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

Research limitations/implications

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

Originality/value

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

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