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With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

Smart community construction (SCC) and efficiency require resident participation. This paper aims to explore the determinants of residents’ participation intention (RPI) in the SCC.

Based on the theory of planned behavior (TPB), this study proposed an extended conceptual model to deeply analyze the RPI in the SCC. The relationship between all constructs was verified by processing and analyzing online survey data using confirmatory factor analysis (CFA), structural equation model (SEM), and bootstrapping method.

Participation attitude, perceived behavioral control, subjective norm, and perceived usefulness significantly and positively affected the RPI. Furthermore, intermediary effects in the extended conceptual model had been confirmed.

To fill the critical gap in the research on the determinants of the RPI in the SCC context, this study developed a novel conceptual model by extending the TPB to analyze the effects of self-driven and externally-driven factors on the RPI from the perspectives of residents’ psychology and external environment. The findings not only clarify the complex process of forming the RPI in the SCC but also provide a theoretical foundation for studying the RPI in similar community construction projects. Additionally, several strategies have been proposed to encourage residents’ participation in the SCC and promote the development of smart communities, such as clarifying residents’ participation obligations, improving the convenience services of smart communities, and diversifying residents’ participation approaches.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

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.

Outstanding unexercised stock options can motivate managers to engage in actions that increase the value of their company’s stock, including buying back their firm’s stock. The objective of granting stock options to managers is to align their interests with stockholders by tying a portion of their compensation to the company’s stock performance. However, unexercised stock options may have unintended consequences by providing managers with a vested interest in artificially boosting stock prices via stock buybacks. The primary objective of this research is to study the main factors that influence firms' buyback decisions amongst hospitality firms at a time when these firms were clamoring for taxpayer bailouts. Results from logistic regression seem to suggest that outstanding executive stock options are a major contributory factor in a firm’s buyback decision. Estimates also indicate that larger, more profitable firms will likely engage in stock buybacks. These findings survive a battery of tests.

The authors use logistic regression to predict the probability of a firm’s buyback decision based on a given set of exogenous explanatory variables.

The paper supports the hypothesis that buyback decisions are guided by the motive to prop support stock prices in the presence of outstanding restricted stock options/warrants granted to firms' executives.

The paper focuses on the buyback decision of U.S. hospitality firms. The results, therefore, might not be generalizable to firms in other industries or countries.

U.S. share repurchase corporate policy and government regulation needs to be revisited given the economic imperative for firms to invest in activities to restore employment and put them in a position for economic recovery.

Public criticism of the size, structure and form (i.e. loan vs grant) of COVID-19 bailouts warrants an examination of whether the factors that drive hospitality and tourism firms to repurchase shares support economic recovery.

Consistent with agency theory, the authors find a significant positive association between outstanding restricted stocks and a firm’s decision to support the stock prices by buying back shares.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

Based on the perspective of knowledge management, this study aims to discuss how to build cross-city emergency management collaboration mechanism in major emergencies and explore the important role of knowledge management in emergency management collaboration.

Based on the theoretical analysis of knowledge management and the typical case study of cross-city emergency management collaborative rescue, this study provides an in-depth analysis of how these cities achieve high emergency management performance through multidimensional and multilevel knowledge collaboration, thus revealing the mechanism of knowledge transfer, integration and sharing in achieving high emergency management performance.

Through analyzing typical cases, this study finds that building a smooth mechanism for multichannel emergency rescue information can promote the diversification of knowledge transfer methods, building a platform-based integration mechanism for emergency rescue information can enhance knowledge integration capabilities and building a linkage mechanism for emergency rescue materials between cities can promote knowledge-sharing level, thereby improving emergency management performance level.

This study has great significance for how to build cross-city emergency management collaboration mechanism in the digital era. In the future, the authors need to further discuss the following two aspects in depth: research on the impact of cross-city emergency management collaboration mechanism on improving the knowledge management capabilities of government emergency management departments; and research on the impact mechanism of knowledge management capabilities on city resilience.

Through case analysis of cross-city emergency management collaborative rescue for major emergencies in China in recent years, this study proposes three specific strategies for cross-city emergency management (smooth, integration and linkage mechanisms) and reveals that these three strategies are essentially aimed at improving the government’s knowledge management level.

Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.

The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.

This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.

This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.

While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.

To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.

The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.

In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

How does the regional institutional environment of China’s transitional economy influence the relationship between a firm’s R&D investment intensity and innovation performance? Based on the resource-based view and institution-based view, an empirical study was executed to identify the moderating effects of institutional environment variables from the Marketization Index of China’s Provinces: National Economic Research Institute (NERI) Report on the relationship between a firm’s R&D investment intensity and innovation performance. This paper aims to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment.

Against the background of China’s transitional economy, the authors present empirical evidence from panel data covering 374 Chinese A-share listed high-tech manufacturing firms on the Shanghai and Shenzhen Stock Exchange to examine the relationship between R&D investment intensity and innovation performance.

Empirical results illustrate the following: The R&D investment intensity and innovation performance displayed an inverse U-shaped relationship, and R&D investment intensity had a lagged effect on R&D output according to the uncertainty and industrialization period of R&D activities. The level of financial market development can intensify the effects of R&D investment intensity on innovation performance. The degree of government intervention weakens the effect of R&D investment intensity on innovation performance.

Based on the background of China’s institutional environment during the transition period, combined with previous research and the Marketization Index of China’s Provinces: NERI Report, selecting financial market development, government intervention level and legalization level as moderating variables to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment. Due to the different ownership of firms during the transition period, the appropriate impact of the institutional environment on the relationship between R&D investment intensity and innovation performance will vary. Moreover, the level of legalization would impact on innovation insignificantly.