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Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

The purpose of this study is to (1) improve the spectral features of the second-order uniformly non-oscillatory (UNO) slope limiters, and (2) numerical simulation of the unified-form of generalized fully-coupled saturated thermo-poro-elastic systems in the axisymmetric cylindrical coordinate via cell-adaptive Kurganov-Tadmor (KT) central high-resolution scheme using the UNO limiters.

(1) The spectral features of the UNO limiter are improved by compression-adaptive MINMOD (MM) limiters, achieved by blending different types of MM limiters to achieve less numerical dissipation and dispersion. These blended MM limiters preserve the total variation diminishing (TVD) feature over non-uniform non-centered cells. Also, the spectral features of the central schemes using the UNO limiters are investigated. (2) For the thermo-poro-elastic problem, corresponding first-order hyperbolic system is provided, including flux, source, diffusion and nonlinear terms. Where, there are different interacting components in the source and flux terms. The nonlinear terms are also considered by the Picard-like linearization concept.

Compression-adaptive UNO limiters would be stable over adapted cells with centered and non-centered cells. The benchmarks confirm that both spectral features and numerical accuracy are improved. For the generalized thermo-poro-elastic problem, corresponding responses including the shock waves can properly be captured.

Studying heat effects (e.g. hot fluid or freezing) and explosions on tunnels. Also, the UNO limiters could be used for simulations of various systems of conservation laws.

The purpose of this study is to contribute to empirical research on individual ambidexterity drivers. This paper analyzes the relationships between inclusive leadership, team knowledge acquisition, team knowledge sharing, digital tools usage and individual ambidexterity.

This study conducted a questionnaire survey of high-tech and manufacturing enterprises in China and obtained 75 leader questionnaires and 365 employee questionnaires. The hypotheses were tested using hierarchical and cross-level regressions.

The research indicates that inclusive leadership improves team knowledge acquisition and sharing. However, only team knowledge sharing significantly boosts individual ambidexterity, and not team knowledge acquisition. Thus, inclusive leadership fosters individual ambidexterity primarily through team knowledge sharing. Digital tools usage strengthens the impact of inclusive leadership on team knowledge sharing, thereby intensifying its effect on individual ambidexterity. However, digital tools usage weakens the effect of inclusive leadership on team knowledge acquisition.

First, this study addresses the call for research on ambidexterity at different levels, revealing the heterogeneous impact of team knowledge acquisition and sharing on individual ambidexterity. Second, this study developed a theoretical model to explore how leadership affects individual ambidexterity. Third, this study responds to the question that digitalization has won, but has leadership lost by investigating the role of digital tools usage in the relationship between inclusive leadership and team knowledge integration.

Governments worldwide are placing a greater emphasis on enhancing ecology and the environment as a result of escalating ecological issues. One possible approach is sustainable governance. This chapter explores the interrelated roles of internal control, environmental accounting, and environmental auditing mechanisms in promoting sustainable governance and green transformation. By looking at these three aspects, the chapter illustrates how integrated approaches can promote sustainable practices and guarantee adherence to environmental standards. The objective of this chapter is to present a thorough knowledge of the ways in which these components work together to support sustainability as a whole.

Team-based work is increasing within organizations nowadays. Despite calls for differentiation between individual and team levels of analysis, research on leadership effects at multiple levels is still limited. By integrating the Conservation of Resources and Social Cognitive theories, this paper aims to analyze the relationships between coaching leadership, team collective efficacy and individual exhaustion via multilevel modeling.

This paper opted for an exploratory study testing a 2-2-1 multilevel mediational model, positing team collective efficacy as a key factor in mediating the relationship between coaching leadership at the team level and exhaustion at the individual level. The hypotheses were tested on a sample of 311 employees, nested in 72 teams (Msize = 5.70, SDsize = 2.82 team members) of a large Italian company that provides financial services.

Results supported the positive association between coaching leadership and team collective efficacy, which, in turn, was negatively associated with team members’ average score in exhaustion and fully mediated the effect of coaching leadership on exhaustion, even controlling for team design features (i.e. task interdependence and team virtuality). The association between coaching leadership and exhaustion was only indirect, explained by team collective efficacy.

Because of the self-report nature of the measures and the cross-sectional nature of the data, this research results might raise problems of variance in common methods and not allow causal conclusions to be drawn. Therefore, researchers are encouraged to test the proposed propositions further.

This paper includes several practical implications for enhancing group efficacy beliefs, which have an impact on individual well-being within the team.

This paper addresses the lack of empirical findings on the multilevel nature of the relationship between coaching-based leadership, collective team effectiveness and individual exhaustion.

This study aims to assess how envy, both directly and indirectly, through negative behaviors such as ostracism, negative word-of-mouth and alignment with the negative behaviors of superiors, influences innovative behavior based on the cultural dimension of individualism versus collectivism.

The data was collected using a survey applied to 305 individuals between October 2022 and June 2023. The model developed was analyzed and validated using partial least squares estimation with structural equation modeling (PLS-SEM) and PLS-SEM multigroup analysis techniques.

The results suggest that for individualistic individuals, negative word-of-mouth exerts a greater positive mediating influence on the relationship between envy and ostracism, and that envy exerts a greater positive influence on both alignment with the negative behaviors of superiors and on ostracism. In addition, the results indicate that negative word-of-mouth and ostracism together negatively influence the relationship between envy and innovative behavior.

This research provides empirical evidence that envy triggers negative behavior in both individualistic and collectivist individuals. Thus, in practical terms, envy can be considered as something more primitive that goes beyond the accepted values of sociability, especially in the organizational environment.

The main contribution of this research is to understand the effects of envy on innovative behavior, based on a conceptual model that considers the mental programs that differentiate one group of individuals from another. In addition, it presents theoretical and empirical implications that provide descriptive evidence of behaviors, making it possible to broaden the psychological understanding of them. In this specific sense, this research differs from other organizational studies, whose objectives are to standardize behavior.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

This study aims to investigate an adaptive notch filtering approach to suppress the effects of elastic vibration on the attitude control of flexible launch vehicles.

First, the dynamics model of the flexible launch vehicle and baseline PID controller are presented. Furthermore, the frequency identification algorithm based on a second-order notch filter is developed to identify the elastic vibration frequency. Finally, a frequency holder is developed to update the notch frequency of the adaptive notch filter.

The proposed adaptive notch filter with a frequency holder can identify the vibration frequency accurately, update the notch frequency appropriately and suppress the effects of the elastic vibration on the attitude control of flexible launch vehicles effectively.

A novel adaptive notch filter with a frequency holder is proposed to address the adaptive filtering problem of elastic vibrations under nonelastic interference and elastic frequency uncertainty. Compared with the conventional filter for attitude control of flexible launch vehicles, an adaptive filter with a proposed frequency holder is developed to solve the problem of the frequency real-time update during the vibration suppression and frequency keeping after the vibration suppression.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

As an ancient art form, embroidery has strong practicality and artistic value. However, current embroidery style migration models produce images with unclear textures and a lack of stitch detail. So, in this paper, we propose a cyclic consistent embroidery style migration network with texture constraints, which is called Texture Cycle GAN (TCGAN).

The model is based on the existing Cycle GAN network with an additional texture module. This texture module is implemented using a pre-trained Markovian adversarial network to synthesize embroidery texture features. The overall algorithm consists of two generative adversarial networks (for style migration) and the Markovian adversarial network (for texture synthesis).

Qualitative and quantitative experiments show that, compared with the existing convolutional neural network style transfer algorithm, the introduction of the texture-constrained embroidery style transfer model TCGAN can effectively learn the characteristics of style images, generate digital embroidery works with clear texture and natural stitches and achieve more realistic embroidery simulation effects.

By improving the algorithm for image style migration and designing a reasonable loss function, the generated embroidery patterns are made more detailed, which shows that the model can improve the realism of embroidery style simulation and help to improve the standard of embroidery craftsmanship, thus promoting the development of the embroidery industry.