Liping Wu, Xingchen Yi, Kai Hu, Oleksii Lyulyov and Tetyana Pimonenko
The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and…
Abstract
Purpose
The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.
Design/methodology/approach
This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.
Findings
The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.
Research limitations/implications
Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).
Practical implications
According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.
Originality/value
This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.
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Shuxin Ding, Tao Zhang, Kai Sheng, Yuanyuan Chen and Zhiming Yuan
The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command…
Abstract
Purpose
The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.
Design/methodology/approach
This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.
Findings
The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.
Originality/value
This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.
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Kai Zhuang, Jieru Xiao and Xiaolong Yang
The purpose of this paper is to show that the droplet impact phenomenon is important for the advancement of industrial technologies in many fields such as spray cooling and ink…
Abstract
Purpose
The purpose of this paper is to show that the droplet impact phenomenon is important for the advancement of industrial technologies in many fields such as spray cooling and ink jet printing. Droplet bouncing on the nonwetting surfaces is a special phenomenon in the impact process which has attracted lots of attention.
Design/methodology/approach
In this work, the authors fabricated two kinds of representative nonwetting surfaces including superhydrophobic surfaces (SHS) and a slippery liquid-infused porous surface (SLIPS) with advanced UV laser processing.
Findings
The droplet bouncing behavior on the two kinds of nonwetting surfaces were compared in the experiments. The results indicate that the increasing Weber number enlarges the maximum droplet spreading diameter and raises the droplet bounce height but has no effect on contact time.
Originality/value
In addition, the authors find that the topological SHS and SLIPS with the laser-processed microwedge groove array produce asymmetric droplet bouncing with opposite offset direction. Microdroplets can be continuously transported without any additional driving force on such a topological SLIPS. The promising method for manipulating droplets has potential applications for the droplet-based microfluidic platforms.
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The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.
Abstract
Purpose
The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.
Design/methodology/approach
The author uses daily data from March 2, 2020, to July 23, 2021.
Findings
The author finds that policies interventions have a negative impact on Tunisia's stock market, particularly stock market returns due to stringency, confinement and health measures. Also, Government announcements regarding economic has a negative impact on Tunisia's stock market but this impact is insignificant. By conducting an additional analysis, the author shows that the government interventions policies amplify the negative effect of COVID-19 on stock returns.
Research limitations/implications
These results will be useful for policy authorities seeking to consider the advantages and drawbacks of government measures. Finally, a legislative proposal about the audit of public debt should be included in the Constitution to spur Tunisia's economic and social recovery.
Originality/value
This study contributes to the related literature in two ways: First, it is the first study to examine the impact of government actions on stock market performance. Second, it bridges a gap in the literature by investigating the case of Tunisia, because most studies focus on developed and emerging economies.
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Kai Hänninen, Jouni Juntunen and Harri Haapasalo
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive…
Abstract
Purpose
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.
Design/methodology/approach
Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.
Findings
Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.
Research limitations/implications
The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.
Practical implications
This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.
Originality/value
This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.
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Kai Zheng, Xianjun Yang, Yilei Wang, Yingjie Wu and Xianghan Zheng
The purpose of this paper is to alleviate the problem of poor robustness and over-fitting caused by large-scale data in collaborative filtering recommendation algorithms.
Abstract
Purpose
The purpose of this paper is to alleviate the problem of poor robustness and over-fitting caused by large-scale data in collaborative filtering recommendation algorithms.
Design/methodology/approach
Interpreting user behavior from the probabilistic perspective of hidden variables is helpful to improve robustness and over-fitting problems. Constructing a recommendation network by variational inference can effectively solve the complex distribution calculation in the probabilistic recommendation model. Based on the aforementioned analysis, this paper uses variational auto-encoder to construct a generating network, which can restore user-rating data to solve the problem of poor robustness and over-fitting caused by large-scale data. Meanwhile, for the existing KL-vanishing problem in the variational inference deep learning model, this paper optimizes the model by the KL annealing and Free Bits methods.
Findings
The effect of the basic model is considerably improved after using the KL annealing or Free Bits method to solve KL vanishing. The proposed models evidently perform worse than competitors on small data sets, such as MovieLens 1 M. By contrast, they have better effects on large data sets such as MovieLens 10 M and MovieLens 20 M.
Originality/value
This paper presents the usage of the variational inference model for collaborative filtering recommendation and introduces the KL annealing and Free Bits methods to improve the basic model effect. Because the variational inference training denotes the probability distribution of the hidden vector, the problem of poor robustness and overfitting is alleviated. When the amount of data is relatively large in the actual application scenario, the probability distribution of the fitted actual data can better represent the user and the item. Therefore, using variational inference for collaborative filtering recommendation is of practical value.
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Kai Foerstl, Anni-Kaisa Kähkönen, Constantin Blome and Matthias Goellner
This paper aims to conceptualize supply market orientation (SMO) for the purchasing and supply chain management function and discusses how SMO capabilities are developed and how…
Abstract
Purpose
This paper aims to conceptualize supply market orientation (SMO) for the purchasing and supply chain management function and discusses how SMO capabilities are developed and how their application differs within and across firms. This research can thus be used as a blueprint for the development of a SMO capability that accommodates a firm’s unique contextual antecedents’ profile.
Design/methodology/approach
The qualitative research design comprises five in-depth case studies with 43 semi-structured interviews with large manufacturing and service firms.
Findings
SMO is defined as the capability to exploit market intelligence to assess, integrate and reconfigure the heterogeneously dispersed resources in purchasing and supply chain management in a way that best reflects the peculiarities of a firm’s supply environment. The empirical analysis shows that although SMO capabilities are configured similarly, their application varies across and within firms depending on the characteristics of a firm’s purchasing categories and tasks. Hence, reactive versus proactive SMO application is contingent upon firm-level and purchasing category–level characteristics.
Originality/value
The study uses the dynamic capabilities view as a theoretical background and provides empirical evidence and theoretical reasoning to elaborate and endorse SMO as a dynamic capability that firms need to have to compete in a complex and dynamic environment. The study provides guidance for supply chain managers on how to successfully develop and deploy a SMO capability.
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Kai Yu, Liqun Peng, Xue Ding, Fan Zhang and Minrui Chen
Basic safety message (BSM) is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle (V2V) and…
Abstract
Purpose
Basic safety message (BSM) is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Although some safety prototypes of connected vehicle have been proposed with effective strategies, few of them are fully evaluated in terms of the significance of BSM messages on performance of safety applications when in emergency.
Design/methodology/approach
To address this problem, a data fusion method is proposed to capture the vehicle crash risk by extracting critical information from raw BSMs data, such as driver volition, vehicle speed, hard accelerations and braking. Thereafter, a classification model based on information-entropy and variable precision rough set (VPRS) is used for assessing the instantaneous driving safety by fusing the BSMs data from field test, and predicting the vehicle crash risk level with the driver emergency maneuvers in the next short term.
Findings
The findings and implications are discussed for developing an improved warning and driving assistant system by using BSMs messages.
Originality/value
The findings of this study are relevant to incorporation of alerts, warnings and control assists in V2V applications of connected vehicles. Such applications can help drivers identify situations where surrounding drivers are volatile, and they may avoid dangers by taking defensive actions.
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Anja Wittmers, Kai N. Klasmeier, Birgit Thomson and Günter W. Maier
Drawing on COR theory and based on a person-centered approach, this study aims to explore profiles of both leadership behavior (transformational leadership, abusive supervision…
Abstract
Purpose
Drawing on COR theory and based on a person-centered approach, this study aims to explore profiles of both leadership behavior (transformational leadership, abusive supervision) and well-being indicators (cognitive irritation, emotional exhaustion). Additionally, we consider whether certain resource-draining (work intensification) and resource-creating factors (leader autonomy, psychological contract fulfillment) from the leaders' work context are related to profile membership.
Design/methodology/approach
The profiles are built using LPA on data from 153 leaders and their 1,077 followers. The relationship between profile membership and correlates from the leaders' work context is examined using multinomial logistic regression analyses.
Findings
LPA results in an interpretable four-profile solution with the profiles named (1) Good health – constructive leading, (2) Average health – inconsistent leading, (3) Impaired health – constructive leading and (4) Impaired health – destructive leading. The two groups with the highest sample share – Profiles 1 and 3 – both show highly constructive leadership behavior but differ significantly in their well-being indicators. The regression analyses show that work intensification and psychological contract fulfillment are significantly related to profile membership.
Originality/value
The person-centered approach provides a more nuanced view of the leadership behavior – leader well-being relationship, which can address inconsistencies in previous research. In terms of practical relevance, the person-centered approach allows for the identification of risk groups among leaders for whom organizations can provide additional resources and health-promoting interventions.