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This study aimed to explore the spatial accessibility dynamics of urban parks and their driving forces from 1901 to 2010 in terms of the dynamic relationships between spatial morphology and road networks, taking Nanjing City as an example.

This study mapped and examined the spatiotemporal distribution of urban parks and road networks in four time points at Nanjing: the 1910s, 1930s, 1960s and 2010s, using the analysis methodology of spatial design network analysis, kernel density estimation and buffer analysis. Two approaches of spatial overlaying and data analysis were adopted to investigate the accessibility dynamics. The spatial overlaying compared the parks' layout and the road networks' core, subcore and noncore accessible areas; the data analysis clarified the average data on the city-wide and local scales of the road networks within the park buffer zone.

The analysis of the changing relationships between urban parks and the spatial morphology of road networks showed that the accessibility of urban parks has generally improved. This was influenced by six main factors: planning implementation, political policies, natural resources, historical heritage and cultural and economic levels.

The results provide a reference for achieving spatial equity, improving urban park accessibility and supporting sustainable urban park planning.

An increasing number of studies have explored the spatial accessibility of urban parks through the relationships between their spatial distribution and road networks. However, few studies have investigated the dynamic changes in accessibility over time. Discussing parks' accessibility over relatively long-time scales has practical, innovative and theoretical values; because it can reveal correlational laws and internal influences not apparent in short term and provide reference and implications for parks' spatial equity.

For start-ups or growing firms, to effectively navigate the unpredictable nature of digital development and achieve superior innovative performance, it is crucial to have a workforce comprised of creative and innovative employees. Drawing upon the principles of social information processing theory, this study aims to investigate whether specific combinations of organizational internal and external environments, as well as work characteristics in the digital age, can foster a high level of employee innovative behavior.

By collecting a multilevel and multisource data set comprising 693 employees and 88 CEOs from 88 start-ups or growing firms, this study used fuzzy-set qualitative comparative analysis to examine the distinctive configurations associated with achieving a high level of employee innovative behavior.

The study found that six solutions enabled employees to innovate more effectively, but six solutions led to the absence of employee innovative behavior.

The findings of this study offer important theoretical and practical implications to motivate employee innovative behavior in Chinese enterprises.

First, this study contributes to the literature on employee innovative behavior by addressing the need to explore the impact of the digital context on promoting innovation among employees. Second, this study adds to the existing literature on employee innovation and entrepreneurship by examining multiple organizational contexts and their influence on innovative behavior. Third, this study makes a significant contribution to the field of employee innovative behavior by examining the macroenvironment surrounding digital transformation within enterprises and integrating both internal and external organizational factors.

Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution.

First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model.

The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks.

This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

The embedding of digital technology and the fuzzy organizational boundary have changed the operation of platform innovation ecosystem (PIE). Specifically, as an important energy of PIE, the internal logic of knowledge flow needs to be reconsidered in the context of digital age, which will be helpful to select the cultivation and governance strategy of PIE.

A dual case-analysis is applied to open the “black box” of knowledge flow in the PIE from the perspective of enabled by digital technology, by taking the intellectual property (IP) operation platform as cases.

The research findings are as follow: (1) The knowledge flow mechanism of PIE is mainly demonstrated through the processes of knowledge acquisition, knowledge integration and knowledge spillover. During this process, connectivity empowerment and scenario empowerment realize the digital empowerment of the platform. (2) Connectivity empowerment provides a channel of knowledge acquisition for the digital connection between participants in PIE. In the process of knowledge integration, scenario empowerment improves the opportunities for accurate matching and collaborative innovation between knowledge supplier and demander, and enhance the value of knowledge. The dual effect of connectivity empowerment and scenario empowerment has accelerated the knowledge spillover in PIE. Particularly, connectivity empowerment expands the range of knowledge spillover, and scenario empowerment affects the generativity of the platform, resulting in the enhancement of platform’s capability to embed and expand its value network. (3) Participants have been benefitted from the PIE enabled by digital technology through three key modules (knowledge acquisition, knowledge integration and knowledge spillover), as the result of knowledge flow.

This study focuses on the knowledge flow mechanism of PIE enabled by digital technology, which enriches the PIE theory, and has enlightenments for the cultivation of digital platform ecosystem.

The study aims to address a critical gap in existing healthcare payment schemes and care service pricing by recognizing the influential role of patients' decisions on self-management efforts. These decisions not only impact health outcomes but also shape the demand for care, subsequently influencing care costs. Despite the significance of this interplay, current payment schemes often overlook these dynamics. The research focuses on investigating the implications of a novel behavior-based payment scheme, designed to align incentives and establish a direct connection between patients' decisions and care costs. The primary objective is to comprehensively understand whether and how this innovative payment scheme structure influences key stakeholders, including patients, care providers, insurers and overall social welfare.

In this paper, we propose a game-theoretical model to incorporate the performance of self-management with the demand for healthcare service, compare the patient's effort decision for self-management and provider's price decision for healthcare service under a behavior-based scheme with that under two implemented widely payment schemes, that is, co-payment scheme and co-insurance scheme.

Our findings confirm that the behavior-based scheme incentives patient self-management more than current schemes while reducing their possibility of seeking healthcare service, which indirectly induces the provider to lower the price of the service. The stakeholders' utility under various payment schemes is sensitive to the cost of treatment and the perceived health utility of patients. Especially, patient health awareness is not always benefited provider profit, as it motivates patient self-management while diminishing the demand for care.

We provide a novel framework for characterizing behavior-based payment schemes. Our results confirm the need for modification of the current payment scheme to incentivize patient self-management.

The intelligent connected vehicle (ICV) is an important trend in automobile development, but little research has been conducted on the technological differences in the ICV industry across countries. In this regard, the authors select China, the United States (US) and the European Union (EU) as countries with developed ICV industries to reveal these differences based on the perspective of subdivision technology.

The authors use logistic regression to fit lifecycles at technology level and country level based on ICV-related patents from China, the US and the EU, then use the Revealed Technological Advantage (RTA) index, Fast-Growing Specialization Index (FGSI) and International Patent Classification (IPC) numbers to conduct comparison of national technology advantages, finally use the social network analysis to investigate the evolution of characteristics and intermediate nodes of each technology innovation network.

Technology lifecycles vary according to the subdivision technology and country. The global development of the ICV industry has reached the mature stage, and 2030 may be a watershed moment, ushering in a wave of new technology iterations. In various subdivision technologies, China and the US have more leading RTAs, and China and the EU have more leading FGSIs. Innovation networks in different countries expand with technology lifecycles, with that in China being the fastest. China's Universities, the US's enterprises and the EU's research institutes are active in cooperative innovation as intermediaries.

This is the first study to compare the development of the ICV industry in major countries from the perspective of subdivision technology and reveal characteristics of innovation networks in each.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

Innovation is vital for sustainable regional development. Government is generally not a source of innovation per se, but the authors shows that by establishing and funding an industrial innovation ecosystem, it can create fertile conditions for research institutions to introduce innovative technologies into industry and for industry to introduce its gaps and needs to motivate and direct academic research. This paper aims to present a case study of the Jiangsu Industrial Technology Research Institute (JITRI) as a “triple helix” collaboration model engaging Industry-University-Research (IUR) institutions. The authors aim to provide a fresh perspective on constructing innovation ecosystems, promoting value creation and advancing the adoption of industrial technology.

Taking JITRI as a case study, this research examines its innovative approaches to interfacing with IUR organizations within China’s Yangtze Delta region. The authors propose a multilayered framework where JITRI serves as the core, facilitating the formation of a robust innovation ecosystem with diverse IUR entities.

This framework comprises three layers: core, platform and support. JITRI acts as the central nexus, binding these elements together and fostering a cohesive innovation ecosystem. By analyzing the operational mechanisms of the Jiangsu Provincial innovation system, the authors gain valuable insights into how JITRI bridges the gap between academia and industry. This facilitates the efficient commercialization of technologies. The success of the JITRI approach presents a compelling model for emulation by other provincial innovation ecosystems seeking to enhance their innovation capabilities.

This study enriches the ongoing conversation on innovation ecosystems, proposing novel avenues for further research. However, the field requires continuous monitoring through longitudinal studies. Given the long-term nature of such initiatives, the full impact of this approach might only be realized over several decades.

JITRI aims to create a robust and innovative provincial innovation ecosystem through its focus on IUR collaboration. This unique approach offers valuable insights and ideas for fostering the development of thriving innovation ecosystems in other provinces. These insights encompass new perspectives on innovation ecosystem development, value creation and industrial advancement.

This study pioneers the use of the JITRI system as a case study, offering valuable insights with potential application to innovation ecosystems across China and globally.