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The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency.

Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy.

The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited.

The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry.

This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.

Grassland degradation is a global ecological issue that inevitably leads to low livestock production efficiency (LPE). Adoption of appropriate technology is an effective way to improve productivity. However, the rate of technology adoption among herders in less developed pastoral areas is low. Therefore, it is critical to improve the level of technology adoption in order to increase LPE.

Based on remote sensing data and survey datasets of herder households in China’s Qinghai–Xizang Plateau, this paper innovatively constructs a stochastic production frontier model incorporating grassland productivity (i.e. grassland total net primary productivity) to accurately evaluate LPE and uses fractional regression models to determine the impact of technology adoption on LPE.

The results show that grassland productivity is essential to estimating LPE, and failing to account for it will result in overestimation. Technology adopters have a technical advantage with respect to average LPE (0.596) when compared with non-adopters (0.540), and technology adoption positively contributes to LPE. Furthermore, compared with profit-seeking technology, pro-environmental technology contributes more to improving LPE, and the combined adoption of both technologies leads to a markedly greater enhancement in LPE.

Few studies have empirically analyzed the economic benefits of technologies that most smallholders can afford, and few measure LPE considering grassland productivity. This study fills these gaps, and the findings are highly relevant for policies aimed at encouraging technology adoption and facilitating more efficient livestock production.

This paper aims to construct positivity-preserving finite volume schemes for the three-dimensional convection–diffusion equation that are applicable to arbitrary polyhedral grids.

The cell vertices are used to define the auxiliary unknowns, and the primary unknowns are defined at cell centers. The diffusion flux is discretized by the classical nonlinear two-point flux approximation. To ensure the fully discrete scheme has positivity-preserving property, an improved discretization method for the convection flux was presented. Besides, a new positivity-preserving vertex interpolation method is derived from the linear reconstruction in the discretization of convection flux. Moreover, the Picard iteration method may have slow convergence in solving the nonlinear system. Thus, the Anderson acceleration of Picard iteration method is used to solve the nonlinear system. A condition number monitor of matrix is employed in the Anderson acceleration method to achieve better robustness.

The new scheme is applicable to arbitrary polyhedral grids and has a second-order accuracy. The results of numerical experiments also confirm the positivity-preserving of the discretization scheme.

1. This article presents a new positivity-preserving finite volume scheme for the 3D convection–diffusion equation. 2. The new discretization scheme of convection flux is constructed. 3. A new second-order interpolation algorithm is given to eliminate the auxiliary unknowns in flux expressions. 4. An improved Anderson acceleration method is applied to accelerate the convergence of Picard iterations. 5. This scheme can solve the convection–diffusion equation on the distorted meshes with second-order accuracy.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

Low-carbon city policies (LCCP) are crucial environmental regulatory frameworks driving China’s transition toward a low-carbon economy. This study investigated the impact of LCCP on enterprise digital transformation (EDT).

This study employed a staggered difference-in-differences model for Chinese listed companies from 2007 to 2021. It also used a cross-sectional model for further analysis.

We found that the implementation of LCCP can promote EDT. This impact was more pronounced among enterprises with greater media attention in high-energy-consumption industries and well-developed economic areas.

This study has practical implications for the LCCP, as it evaluates the consequences of macro-level LCCP on micro-level corporate economic consequences. It provides an important reference for developing countries to implement LCCP and promote green industry upgrading.

This study broadens the impact of the LCCP, providing valuable insights into substantiating carbon neutrality goals and fostering the influencing factors of EDT.

The purpose of this paper is to embark on evaluating the role of Chat Generative-Trained Transformer (ChatGPT) in personal knowledge management (PKM) practices of individual knowledge workers across varied disciplines.

The methodology involves four steps, i.e. literature search, screening and selection of relevant data, data analysis and data synthesis related to KM, PKM and generative artificial intelligence (AI) with a focus on ChatGPT. The findings are then synthesized to develop a viewpoint on the challenges and opportunities brought by ChatGPT for individual knowledge workers in enhancing their PKM capability.

This work highlights the prevailing challenges and opportunities experienced by knowledge workers while leveraging PKM through implying ChatGPT. It also encapsulates how some management theories back the cruciality of generative AI (specifically ChatGPT) for PKM.

This study identifies the challenges and opportunities. from existing studies and does not imply empirical data/result. The authors believe that findings can be adjusted to diverse domains regarding knowledge workers’ PKM endeavors. This paper draws some conclusions and calls for further empirical research.

ChatGPT’s capability to accelerate organizational performance compelled scholars to focus in this domain. The linkage of ChatGPT to Knowledge Management is an under-explored area specifically the role of ChatGPT on PKM hasn't been given attention in the existing work. This is one of the earliest studies to explore this context.

Based on upper echelon theory and signaling theory, we aim to examine the impact of returnee executives on firms’ relative exploratory innovation focus and the moderating effect of economic policy uncertainty on this relationship.

Using panel data of Chinese listed companies from 2009 to 2020, we obtained empirical evidence to support our arguments.

Returnee executives positively influence firms’ relative exploratory innovation focus. This means that firms with returnee executives will shift the focus of their innovation activities toward exploratory innovation more than exploitative innovation. In addition, we find that economic policy uncertainty strengthens this relationship.

First, by showing how returnee executives positively influence firms’ shift in focus to exploratory rather than exploitative innovation, we expand our understanding of firms’ trade-offs between exploratory and exploitative innovation. Second, this study examines how returnee executives influence the relative importance that firms place on exploratory and exploitative innovation, allowing us to build a realistic and nuanced view of how returnee executives influence firms’ strategic choices. Finally, this study expands the strategic leadership literature and responds directly to the call for studies focusing on how institutional environmental conditions and executive characteristics work together to shape firm outcomes.

This study explores the spatial adaptive changes to different ancestral origins of Korean vernacular houses in Northeastern China and discusses the influence of changing family patterns on spatial capacity.

This study uses quantitative and comparative methods to explore changes to space arrangement, space area, and furniture forms in Korean vernacular houses. This study also explores the correlation between changes in family patterns and the changing characteristics of spatial capacity.

The results elucidate the changing characteristics of Korean houses' spatial capacity. While the changing individual needs of Korean family members have led to increased spatial accessibility, there is a weak correlation variability in remodelling outcomes and changes in individual needs. Moreover, the per capita living area of Korean vernacular houses has increased, and furniture forms tend to be simpler, smaller, and more integrated. These developments reflect the changes in the way of life, production, and family structure.

This study provides a unique perspective on the sociology and architecture of ethnic minority families in China. Its results can help architects and construction firms more intuitively understand Korean houses. This study also provides a reference for the future renewal of Korean houses in the region.

Although a growing number of studies have examined Korean vernacular houses and family patterns, none have explored the impact of changing family patterns on the spatial organisation of different ancestral origins of Korean vernacular houses. Therefore, this novel study addresses this gap, enriching the literature and providing practical insights.

This systematic literature review aims to investigate the application and integration of Industry 4.0 (I4.0) technologies in transportation infrastructure construction projects focusing on sustainability pillars.

The study employs a systematic literature review approach, combining qualitative review and quantitative analysis of 142 academic articles published between 2011 and March 2023.

The findings reveal the dominance of Building Information Modelling (BIM) as a central tool for sustainability assessment, while other technologies such as blockchain and autonomous robotics have received limited attention. The adoption of I4.0 technologies, including Internet of Things (IoT) sensors, Augmented Reality (AR), and Big Data, has been prevalent for data-driven analyses, while Unmanned Aerial Vehicle (UAVs) and 3D printing are mainly being integrated either with BIM or in synergy with Artificial Intelligence (AI). We pinpoint critical challenges including high adoption costs, technical barriers, lack of interoperability, and the absence of standardized sustainability benchmarks.

This research distinguishes itself by not only mapping the current integration of I4.0 technologies but also by advocating for standardization and a synergistic human-technology collaborative approach. It offers tailored strategic pathways for diverse types of transportation infrastructure and different project phases, aiming to significantly enhance operational efficiency and sustainability. The study sets a new agenda for leveraging cutting-edge technologies to meet ambitious future sustainability and efficiency goals, making a compelling case for rethinking how these technologies are applied in the construction sector.