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There is currently a gap in the research regarding the effect of corporate culture on corporate innovation capability. Based on cultural hierarchy theory, in this paper, we explore the interactions between cultural factors and innovation capability in emerging market firms (EMFs). We discuss the mechanisms by which incentive, institutional, and vibrant corporate cultures influence corporate innovation capability. Furthermore, we consider the transformation of artificial general intelligence (AGI) from a tool into a colleague and how this affects the relationship between corporate culture and innovation capability.

An online questionnaire was distributed to corporate employees to explore their attitudes towards AGI and corporate culture. In total, 523 valid questionnaires were empirically analysed using partial least squares structural equation modelling and multigroup analysis (MGA).

The results showed that incentive culture, institutional culture, and vibrant culture had a positive impact on corporate innovation capability. MGA revealed significant differences between employees who considered AGI a tool and those who considered it a colleague. Employees who treated AGI as a colleague were likely to be influenced by a vibrant culture, whereas employees who treated AGI as a tool were likely to be influenced by an incentive or institutional culture.

Building on cultural hierarchy theory, our study provides a new theoretical framework to enrich current research on the relationship between corporate culture and AGI. The study can help EMF managers adjust incentive and institutional cultures before AGI shifts from being a tool to a colleague and negatively impacts innovation capacity.

The purpose of this paper is to address two major challenges faced by robotic fish when operating in underwater environments: insufficient path planning capabilities and difficulties in avoiding dynamic obstacles. To achieve this, a method is proposed that combines the Improved Rapid Randomized Tree Star (IRRT*) with the dynamic window approach (DWA).

The RRT-connect algorithm is used to determine an initial feasible path quickly. The quality of sampling points is then improved by dividing the regions and selecting each region’s probability based on its fitness value. The fitness function and roulette wheel method are introduced for region selection. Subtarget points of the DWA algorithm are extracted from the IRRT* algorithm to achieve real-time dynamic path planning.

In various maps, the iteration count for the IRRT* algorithm decreased by 61%, 35% and 51% respectively, compared to the RRT* algorithm, whereas the iteration time was reduced by 75%, 34% and 57%, respectively. In addition, the IRRT*-DWA algorithm can successfully navigate through multiple dynamic obstacles, and the average time, path length, etc. do not change much when parameters change, and the stability is high.

A novel IRRT*-DWA algorithm is proposed, which, by refining the sampling strategy and updating sub-target points in real time, not only addresses the limitations of existing algorithms in terms of path planning efficiency in complex environments but also enhances their capability to avoid dynamic obstacles. Ultimately, experimental results indicate a high level of similarity between the actual and ideal paths.

This study examines the transformation of labour non-governmental organisations (NGOs) operating in Mainland China since the enactment of the 2017 Overseas NGO Management Law, which aims to regulate foreign concerns functioning outside the direct control of the state. It focuses on the extent to which these organisations have responded to the rapidly changing political and social environment by altering their goals and strategies in support of migrant workers. It also considers the relevance of Western social movement theories (SMTs) to China's grassroots labour movement in the 2020s. 

The research is based on case studies of ten labour NGOs operating in Beijing, Tianjin and Yunnan. It draws upon fifteen semi-structured interviews with the founders, leaders and activists affiliated with those organisations, as well as records and documented information of each of those organisations.

While the power and influence of labour NGOs markedly diminished, most have been able to adapt their goals and the strategies remain sustainable amidst both China's changing political and social climates and the global pandemic. It suggests that conventional SMTs can still offer valuable insights into understanding the development of labour NGOs in China, although they might not fully interpret the specific conditions and challenges faced by these organisations.

This study stands out as one of very few to offer empirical evidence on the inner workings of China's labour NGOs over the last six years. It also contributes to our understanding of social movements in a non-Western context.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

This paper aims to investigate the impact of digital inclusive finance on entrepreneurial activities in rural areas, as well as the underlying mechanisms and the variations of this impact across regions and household characteristics.

Utilizing the China Household Finance Survey Data, this paper applies the Two-Stage Least Squares with instrumental variables to assess the effect of digital inclusive finance on rural entrepreneurship.

The empirical findings indicate that digital inclusive finance significantly promotes entrepreneurial activities in rural areas by alleviating credit constraints, reducing financial information barriers, and altering risk attitudes for rural households. Additionally, this effect is more pronounced in the eastern region of China and for the “opportunity entrepreneurial activities.” Furthermore, the impact varies across rural households' income and consumption status, as well as the personal characteristics of household heads.

Firstly, this study broadens our understanding of the mechanisms through which digital inclusive finance influences entrepreneurial activities, thereby filling a gap in existing entrepreneurship research. Secondly, the study's findings affirm the inclusive nature of digital finance, contributing significantly to the literature on regional equality and illuminating potential pathways toward achieving “common prosperity.”

The paper aims to reveal the relationship among energy efficiency, thermal comfort and thermal regulation of electrically heated footwear and to investigate influencing factors on the energy efficiency and thermal comfort.

A finite volume model was proposed to simulate the two-dimensional heat transfer in electrically heated footwear (EHF) under an extremely cold condition. The model domain consists of three-layer footwear materials, a heating pad, a sock material, an air gap and skin tissues. Model predictions were verified by experimental data from cold-contact exposure. Then the influencing factors on the energy efficiency and thermal comfort were investigated through parametric analysis.

The paper demonstrated that the skin temperature control (STC) mode provided superior thermal comfort compared to the heating pad temperature control (HPTC) mode. However, the energy efficiency for the HPTC mode with a heating temperature of 38 °C was 18% higher than the STC mode. The energy efficiency of EHF while reaching the state of thermal comfort was strongly determined by the arrangement and connection of heating elements, heating temperature, thickness and thermal conductivity of footwear materials.

The findings obtained in this paper can be used to engineer the EHF that provides optimal thermal comfort and energy efficiency in cold environments.

This study aims to explore the relationship between house prices and time-on-market (TOM) in Silicon Valley. Previous findings have been inconclusive due to variations in property characteristics. This paper highlights the discrepancy between listing and selling prices and identifies differences among housing types such as condominiums, detached houses and townhouses based on housing orientations and customer groups. Additionally, this study considers the impact of the COVID-19 pandemic and the Fed’s interest rate policies on the housing market.

The authors analyze 63,853 transactions from the Bay East Board of Realtors’ Multiple Listing Service during 2018 to 2022. The study uses a multiple-stage methodology, including a nonlinear hedonic pricing model, search theory and two-stage least squares method to address concerns relating to endogeneity.

The Silicon Valley housing market shows resilience, with low-end properties giving buyers more bargaining power without significant price drops. High-end properties, on the other hand, attract more attention over time, leading to aggressive bidding and higher final sale prices. The pandemic, despite reducing housing supply, did not dampen demand, leading to price surges. Post-COVID, price correlations with TOM changed, indicating a more cautious buyer approach toward high premiums. The Fed’s stringent monetary policies post-2022 intensified these effects, with longer listing times leading to greater price disparities due to financial pressures on buyers and shifting dynamics in buyer interest.

Results reveal a nonlinear positive correlation between TOM and the price formation process, indicating that the longer a listed property is on the market, the greater the price changes. For low-end properties, TOM becomes significantly negative, while for high-end properties, the coefficient becomes significantly positive, with effects and magnitudes varying by type of dwelling. Moreover, external environmental factors, especially those leading to financial strain, can significantly impact the housing market.

The experience of Silicon Valley is valuable for cities using it as a development model. The demand for talent in the tech industry will stimulate the housing market, especially as the housing supply will not improve in the short term. It is important for government entities to plan for this proactively.

Despite the increasing interest in the role of supply chain concentration (SCC) in improving performance, its influence on firms' sustainability performance remains unexplored, as do the underlying mechanisms of this relationship. Drawing on resource dependence theory, the authors investigate the relationship between SCC and manufacturing firms' sustainability performance and the moderating roles of operational slack and information transparency.

The authors use secondary data from 3,581 manufacturing firms listed on the Shanghai and Shenzhen A-share stock markets from 2006 to 2020 to conduct an empirical analysis using panel data regression models.

Manufacturing firms' SCC is negatively related to sustainability performance until it reaches a certain point, where SCC positively affects sustainability performance, presenting a U-shaped relationship. In addition, operational slack represented by a quick ratio moderates the relationship between SCC and sustainability performance by flattening the curve. Operational slack represented by receivable turnover ratio moderates the relationship between SCC and sustainability performance by steepening the curve and shifting the turning point left. Information transparency strengthens the effect of SCC on the sustainability performance by steepening the curve.

This investigation provides a comprehensive view of the SCC– sustainability performance relationship.

Metaverse is going to change the landscape in every field, sector, and business. This chapter aims to explore the role of marketing in the metaverse focusing on each sector and business. This chapter has adopted bibliometrics analysis to explore the importance of metaverse marketing. The results suggest that the publication and citation of articles have seen a huge jump from 2022 onwards. Keyword co-occurrence analysis shows that metaverse with blockchain, marketing, education, and virtual reality (VR) are hot words in the upcoming time. Metaverse marketing shows that innovation, mixed reality, and extended reality will change the landscape of marketing. Analysis suggests that China, the United States, South Korea, and India are the top contributing countries in the research of metaverse. By understanding the implications of the metaverse on purchaser conduct and promoting systems, organizations can draw in the main interest group and gain esteem in this new advanced scene.