Yanghao Zhu, Lirong Long, Wenxing Liu, Peipei Shu and Siyuan Chen
In the period of organizational change and transformation, the attitude of employees towards change has become a key factor in the success of organizational change. Based on the…
Abstract
Purpose
In the period of organizational change and transformation, the attitude of employees towards change has become a key factor in the success of organizational change. Based on the uncertainty management theory (UMT), the paper considers authentic leadership as an important antecedent of employee resistance to change and explores the mediating role of perceived uncertainty and the moderating role of uncertainty avoidance between authentic leadership and employee resistance to change.
Design/methodology/approach
The paper conducted a questionnaire survey study and a scenario experimental study. In study 1, the authors collected two stages of data from 256 employees in Central China, one month apart. In study 2, the authors designed a scenario experiment and invited 130 Chinese adults to participate.
Findings
The authors find that authentic leadership can effectively reduce employee resistance to change by reducing employee perceived uncertainty. In addition, for individuals with a higher (vs lower) degree of uncertainty avoidance, the direct impact of authentic leadership on perceived uncertainty and the indirect impact of authentic leadership on resistance to change through perceived uncertainty are both stronger (vs lower).
Originality/value
The presented results reveal the mechanism between authentic leadership and employee resistance to change from cognitive perspective and depict an important step toward understanding how authentic leadership and employee uncertainty avoidance interact and how they interact with employee resistance to change.
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Xiaobo Wu, Liping Liang and Siyuan Chen
As various different and even contradictory concepts are proposed to depict a firm's capabilities related to big data, and extant relevant research is fragmented and scattered in…
Abstract
Purpose
As various different and even contradictory concepts are proposed to depict a firm's capabilities related to big data, and extant relevant research is fragmented and scattered in several disciplines, there is currently a lack of holistic and comprehensive understanding of how big data alters value creation by facilitating firm capabilities. To narrow this gap, this study aims to synthesize current knowledge on the firm capabilities and transformation of value creation facilitated by big data.
Design/methodology/approach
The authors adopt an inductive and rigorous approach to conduct a systematic review of 185 works, following the “Grounded Theory Literature-Review Method”.
Findings
The authors introduce and develop the concept of big data competency, present an inductive framework to open the black box of big data competency following the logic of virtual value chain, provide a structure of big data competency that consists of two dimensions, namely, big data capitalization and big data exploitation, and further explain the evolution of value creation structure from value chain to value network by connecting the attributes of big data competency (i.e. connectivity and complementarity) with the transformation of value creation (i.e. optimizing and pioneering).
Originality/value
The big data competency, an inclusive concept of firm capabilities to deal with big data, is proposed. Based on this concept, the authors highlight the significant contributions that extant research has made toward our understanding of how big data alters value creation by facilitating firm capabilities. Besides, the authors provide a future research agenda that academics can rely on to study the strategic management of big data.
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Wenxing Liu, Kong Zhou, Xi Ouyang, Siyuan Chen and Kai Gao
In recent years, organizations have progressively adopted electronic performance monitoring (EPM) to obtain accurate employee performance data and improve management efficiency in…
Abstract
Purpose
In recent years, organizations have progressively adopted electronic performance monitoring (EPM) to obtain accurate employee performance data and improve management efficiency in response to the growing complexity of the work environment. However, existing research has primarily focused on examining the effect of EPM on employee behaviors within established job designs, neglecting the consequential role of EPM in shaping employees’ bottom-up job redesign (i.e. job crafting). This study aims to explore whether and how EPM affects employee job crafting.
Design/methodology/approach
To test proposed hypotheses, we conducted two time-lagged surveys across different cultural contexts and a scenario experiment on an online platform in China.
Findings
The results revealed the negative indirect relationship between EPM and employee job crafting via role breadth self-efficacy. This indirect relationship was moderated by constructive supervisor feedback and job complexity, with the above relationships being weak (versus strong) when constructive supervisor feedback was high (versus low) or job complexity was low (versus high).
Practical implications
The results have crucial implications for organizational practices, suggesting that managers should provide constructive feedback to break the trade-off between EPM and job crafting. Additionally, managers may need to give employees with high job complexity more autonomy rather than intense monitoring.
Originality/value
This study is the first to clarify the effect of EPM on employee job crafting. As job crafting captures the important value of employees in organizational job design, our effort helps to enrich the understanding of EPM effectiveness.
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Philip Andrews-Speed, Xiangyang Xu, Dingfei Jie, Siyuan Chen and Mohammad Usman Zia
This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.
Abstract
Purpose
This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.
Design/methodology/approach
The analysis applies ideas relating to national and sector systems of innovation to explain why China’s strategies to support research and technological innovation have failed to stimulate the desired progress in coalbed methane production. It also provides a counter-example of the USA that implemented a number of measures in the 1970s that proved very effective.
Findings
The deficiencies of China’s research and development strategies in support of coalbed methane development reflect the national and sectoral systems of innovation. They are exacerbated by the structure of the national oil and gas industry. Key constraints include the excessively top-down management of the national R&D agenda, insufficient support for basic research, limited collaboration networks between companies, research institutes and universities and weak mechanisms for diffusion of knowledge. The success of the USA was based on entirely different systems for innovation and in quite a different industrial setting.
Originality/value
The originality of this analysis lies in placing the challenges facing research and innovation for China’s coalbed methane development in the context of the national and sectoral systems for innovation and comparing with the approach and success of the USA.
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Yangdong Liu, Siyuan Lu, Hongyi Tu, Boyuan Zhang, Yaqin Zhao, Jiasheng He, Liangliang He and Zhenbin Chen
To save the economic cost and improve the performance of enterprises, this study aims to synthesize high performance immobilized penicillin G acylase (PGA) carriers with fast…
Abstract
Purpose
To save the economic cost and improve the performance of enterprises, this study aims to synthesize high performance immobilized penicillin G acylase (PGA) carriers with fast reaction speed, high recovery rate of enzyme activity and good reusability through corresponding theoretical guidance and experimental exploration.
Design methodology approach
A diblock resin was synthesized by reversible addition-fragmentation chain transfer polymerization method using N, N-diethylacrylamide (DEA) and β-hydroxyethyl methacrylate (HEMA) as functional monomers poly(N, N-diethylacrylamide)-b-poly(β-hydroxyethyl methacrylate) (PDEA-b-PHEMA) was obtained, and the effect of the ratio of DEA and HEMA on the activity of PGA was investigated, and the appropriate block ratio of DEA and HEMA was obtained. After that, the competitive rate of HEMA and glycidyl methacrylate (GMA) under the carrier preparation conditions was investigated. Based on the above work, a thermosensitive resin carrier PDEA-b-PHEMA-b-P(HEMA-co-GMA) with different target distances was synthesized, and the chemical structures and molecular weight of copolymers were investigated by hydrogen NMR (1H NMR).
Findings
The lower critical solution temperature of the resin support decreases with the increase of the monomer HEMA in the random copolymerization; the catalytic performance study indicated that the response rate of the immobilized PGA is fast, and the recovery rate of the enzyme activity of the immobilized PGA varies with the distance between the targets. When the molar ratio of HEMA to GMA in the resin block is 8.15:1 [i.e. resin PDEA100-b-PHEMA10-b-P(HEMA65-co-GMA8)], the activity recovery rate of immobilized PGA can reach 50.51%, which was 15.49% higher than that of pure GMA immobilized PGA.
Originality value
This contribution provides a novel carrier for immobilizing PGA. Under the optimal molar ratio, the enzyme activity recovery could be up to 50.51%, which was 15.49% higher than that of PGA immobilized on the carrier with nonregulated distance between two immobilization sites.
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Yanhong Gan, Xingyu Gao, Wenhui Zhou, Siyuan Ke, Yangguang Lu and Song Zhang
The advanced technology enables retailers to develop customer profile analysis (CPA) to implement personalized pricing. However, considering the efficiency of developing CPA, the…
Abstract
Purpose
The advanced technology enables retailers to develop customer profile analysis (CPA) to implement personalized pricing. However, considering the efficiency of developing CPA, the benefit to different retailers of implementing more precise personalized pricing remains unclear. Thus, this essay aimed to investigate the impact of efficiency on participants’ strategies and profits in the supply chain.
Design/methodology/approach
A two-stage game model was introduced in the presence of a manufacturer who sets his wholesale price and a retailer that decides her CPA strategy. The equilibrium results were generated by backward induction.
Findings
Most retailers are willing to develop the highest CPA to implement perfect personalized pricing, but those inefficient retailers with high production costs would like to determine a middle CPA to implement bounded personalized pricing. The retailers’ profits may decrease with the efficiency of developing CPA when the efficiency is middle. In this case, as the efficiency improves, the manufacturer increases the wholesale price, resulting in lower demand and thus lower profits. Moreover, define a Pareto Improvement (PI) strategy as one that benefits both manufacturers and retailers. Therefore, uniform pricing is a PI when the unit cost is high and the efficiency is low; personalized pricing is a PI when the unit cost is low and the efficiency is low or high; otherwise, there is no PI.
Originality/value
This study is the first that investigates how the retailer develops CPA to implement personalized pricing on a comprehensive spectrum, which can provide practical insights for retailers with different efficiencies.
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Keywords
Zhouyang Gu, Fanchen Meng and Siyuan Wang
Recent years have seen a substantial increase in academic interest in social capital and innovation. Nonetheless, the bibliometric and visualization study on this subject is…
Abstract
Purpose
Recent years have seen a substantial increase in academic interest in social capital and innovation. Nonetheless, the bibliometric and visualization study on this subject is inadequate. This study aims to analyse the leading trends in literature that have connected social capital with innovation over the past few decades.
Design/methodology/approach
This study attempts to provide an overview utilizing various bibliometric techniques combined with assorted themes and data extracted from the Scopus database. Results based on 716 documents reveal not only the principal modern trends but also the evolution of these scientific production developments.
Findings
Results based on 716 Scopus indexed documents reveal the trends and trajectories as well as specific topics, journals and countries of social capital and innovation research Furthermore, this study offers an overview of trends and trajectories, as well as a visual and schematic framework for further research on this subject.
Originality/value
Since there is lack of analyses the bibliographic data on social capital-related innovation, so this study is a unique contribution to the literature as complement. This may benefit researchers in identifying current trends and prospective study areas, as well as assisting future authors in conducting more efficient studies.
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Siyuan Huang, Limin Liu, Xiongjun Fu, Jian Dong, Fuyu Huang and Ping Lang
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In…
Abstract
Purpose
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.
Design/methodology/approach
Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.
Findings
Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.
Originality/value
This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.
Details
Keywords
Using the multifunctional friction and wear testing machine independently developed by the research group, the friction and wear tests of different friction conditions (contact…
Abstract
Purpose
Using the multifunctional friction and wear testing machine independently developed by the research group, the friction and wear tests of different friction conditions (contact pressure and sliding speed) are conducted on the brake materials of high-speed trains with the ambient humidity of 95% and the initial temperature of the disk of 200°C.
Design/methodology/approach
Friction and wear.
Findings
The test results show that changing the friction conditions has a significant effect on the braking performance of high-speed trains.
Originality/value
YES.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0171/
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Rong Huang, Xinyue Zhou, Weiling Ye and Siyuan Guo
This paper aims to clarify an important nuance by proposing that people attribute human mind to brands on two distinct dimensions: think and feel.
Abstract
Purpose
This paper aims to clarify an important nuance by proposing that people attribute human mind to brands on two distinct dimensions: think and feel.
Design/methodology/approach
Eight studies were conducted to first develop and validate the 14-item Brand Anthropomorphism Questionnaire, and then to investigate how the two subscales, think or feel dimensions, influence consumer moral judgment of brands.
Findings
This research developed a 14-item Brand Anthropomorphism Questionnaire with two subscales, which are psychometrically sound and show discriminant validity with regard to existing brand constructs. Furthermore, think or feel brand anthropomorphism dimensions can predict consumers’ moral judgment of brands.
Research limitations/implications
The present research offers preliminary evidence about the value of distinguishing between think brand and feel brand in consumer moral judgment. Further research could investigate other potential impact of the two dimensions, and possible antecedents of think/feel dimensions.
Practical implications
Managers can use the scale for assessment, planning, decision-making and tracking purposes. In addition, in the event of brand scandal or brand social responsibility activities, public-relations efforts can use the findings to earn or regain the trust of consumers, as this research demonstrates that marketers can shape (tailor) the feel or think dimensions of brand perception to change consumers’ moral judgment of the brands.
Originality/value
This research makes theoretical contribution to the brand anthropomorphism literature by differentiating the two dimensions and exploring the influence of anthropomorphism of consumer moral judgment.