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This paper aims to compare the differences between single- and multi-person interactions in virtual tourism, underpinned by the stimulus-organism-response (S-O-R) framework and media richness theory (MRT).

In this study, quantitative data gathered from questionnaires applied to 558 individuals was analyzed by using partial least squares structural equation modeling. The moderating role of interaction type was tested through multigroup analysis (MGA).

The results showed that vividness positively influenced telepresence, perceived attractiveness and authentic experiences; telepresence positively affected authentic experiences and perceived attractiveness; and authentic experiences and perceived attractiveness positively impacted willingness to visit in both interaction groups. A difference was detected between the two groups in that perceptions of media vividness were more easily transformed into a willingness to visit through telepresence in the multi-person interaction group. Interaction type moderated the effect of vividness on telepresence. The vividness of the media had a more significant effect on telepresence among those who participated in virtual tourism together.

In this study, a model was developed to explain how media vividness affected willingness to visit by considering the relationships between telepresence, authentic experiences and perceived attractiveness in virtual reality, as well as the social interaction aspect.

本研究旨在比较虚拟旅游中单人和多人互动的差异, 基于刺激-有机体-反应（S-O-R）框架和媒介丰富度理论（MRT）。

本研究对 558 名受试者的问卷调查数据进行了定量分析, 采用 PLS-SEM 模型分析, 并通过多群组分分析（MGA）测试了互动类型的调节作用。

研究结果显示, 生动性对临场感、感知吸引力和真实体验有正向影响; 临场感对真实体验和感知吸引力有正向影响; 真实体验和感知吸引力对参观意愿有正向影响。两组之间的差异在于, 在多人互动组中, 媒介生动性更容易通过临场感转化为参观意愿。互动类型调节了生动性对临场感的影响, 参与虚拟旅游的多人群体中, 媒介的生动性对临场感的影响更为显著。

本研究构建了一个模型, 解释了在虚拟现实中, 媒介生动性如何通过临场感、真实体验和感知吸引力的关系影响参观意愿, 同时考虑了社会互动的因素。

This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start.

For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease.

When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%.

The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications.

The purpose of this paper is to investigate the effects of surface texture with roughness orientation considered on tribological properties under a mixed lubrication state numerically and experimentally.

Based on the average Reynolds equation and asperity contact model, the impacts of surface texture parameters and roughness orientation on lubrication properties have been calculated using finite difference method. Tin–bronze samples with various prescribed surface texture geometric parameters and roughness orientation were fabricated by laser surface texturing technique, and the tribology performance of the textured surface was studied experimentally.

The effects of surface geometric parameters and roughness orientation parameters have been discerned. The experimental observations are in good agreement with the numerical prediction, which suggests that the numerical scheme adopted in this work is suitable in capturing the surface texture and roughness effect under mixed lubrication state.

By meticulously controlling the surface roughness and surface texture geometric characteristics based on the laser surface texturing process, samples with prescribed surface texture parameters and roughness orientation consistent with that in theoretical studies were fabricated and the theoretical model and results were verified experimentally.

During the forming process, aluminum alloy sheets develop various types of textures and are subjected to cyclic loading as structural components, resulting in fatigue damage. This study aims to develop polycrystalline models with different orientation distributions and incorporate suitable fatigue indicator parameters to investigate the effect of orientation distribution on the mechanical properties of Al-7.02Mg-1.78Zn alloys under cyclic loading.

In this study, a two-dimensional polycrystalline model with 150 equiaxed grains was constructed based on optical microscope images. Subsequently, six different orientation distributions were assigned to this model. The fatigue indicator parameter of strain energy dissipation is utilized to analyze the stress response and fatigue crack driving force in polycrystalline models with different orientation distributions subjected to cyclic loading.

The study found that orientation distribution significantly influences fatigue crack initiation. Orientation distributions with a larger average Schmid factor exhibit reduced stress response and lower fatigue indicator parameters. Locations with a larger average Schmid factor experience greater plastic deformation and present a higher risk for fatigue crack initiation. RVE with a single orientation undergoes more rotation to reach cyclic steady state under cyclic loading due to the ease of deformation transfer.

Currently, there are no reports in the literature on the calculation of fatigue crack initiation for Al-Mg-Zn alloys using the crystal plasticity finite element method. This study presents a novel strategy for simulating the response of Al-7.02Mg-1.78Zn materials with different orientation distributions under symmetric strain cyclic loading, providing valuable references for future research.

This study aims to explore the effect of chief executive officer education on firms’ action timing and acquisition performance in industry merger waves. In addition, this study investigated the moderating influence of CEO duality and firm cash flow on the relationship between education and entry timing.

Following the methodology for determining merger waves in previous studies, the authors identified 16 industry merger waves of Chinese listed firms from 2008 to 2019. Multiple linear regression was employed to examine the hypotheses.

The results showed that higher CEO education was associated with early participation in merger waves. CEO duality negatively moderated the education-entry timing relation. The effect of CEO education on entry timing was more pronounced when firms had higher cash flow. Moreover, more educated CEOs materially enhanced acquisition performance in merger waves.

Entry timing in industry merger waves has important implications, as early movers establish competitive advantages and achieve higher acquisition performance. However, the managerial characteristics determining entry timing have not received adequate attention. Meanwhile, studies examining the effect of CEO education on acquisitions are limited. This study explored the effect of CEO education on firms’ entry timing and acquisition performance in merger waves, thereby contributing to the literature on merger waves and managerial characteristics. This study’s findings regarding the moderators of the education-entry timing relation enrich the literature on corporate governance and agency theory.

Globally, co-production is of great significance in promoting neighborhood regeneration. However, in the Chinese context, characterized by a governance system with strong government discourse power and a tradition of passive public participation, co-production has faced significant challenges. To address issues, this paper aims to deeply understand the co-production behaviors and strategy choices of local governments and residents in the co-produced neighborhood regeneration.

An evolutionary game approach was utilized as the research method to analyze the interest interactions between the two parties, the differences and similarities in strategy choices and the influencing factors in government and resident-initiated project types, respectively. Chongqing was selected as the case area for empirical analysis, with data derived from project materials and in-depth interviews.

This study revealed dynamic interactions between local governments and residents, significant differences between the two project types regarding co-production levels, the positive role of residents' perceived loss and the effect of marginal benefits on critical influencing factors.

Drawing upon co-production theory, this paper elucidates how different levels of co-production are implemented and highlights the differences between the two types of neighborhood regeneration projects within governance systems characterized by strong state discourse power and a lack of public participation tradition. It addresses current issues and provides critical references for government policymakers and urban planners to make informed decisions and promote co-produced neighborhood rehabilitation projects.

This paper aims to critically evaluate the role of advanced artificial intelligence (AI)-enhanced image fusion techniques in lung cancer diagnostics within the context of AI-driven precision medicine.

We conducted a systematic review of various studies to assess the impact of AI-based methodologies on the accuracy and efficiency of lung cancer diagnosis. The focus was on the integration of AI in image fusion techniques and their application in personalized treatment strategies.

The review reveals significant improvements in diagnostic precision, a crucial aspect of the evolution of AI in healthcare. These AI-driven techniques substantially enhance the accuracy of lung cancer diagnosis, thereby influencing personalized treatment approaches. The study also explores the broader implications of these methodologies on healthcare resource allocation, policy formation, and epidemiological trends.

This study is notable for both emphasizing the clinical importance of AI-integrated image fusion in lung cancer treatment and illuminating the profound influence these technologies have in the future AI-driven healthcare systems.

Industrialized construction has brought about expectations of improved productivity in the construction industry. However, the lack of a commonly accepted definition has created confusion regarding the types of development covered by the industrialized construction umbrella. These inconsistent definitions convoluted the discussion on this phenomenon. This study aims to clarify the definition of industrialized construction through a systematic literature review.

This systematic literature review was conducted according to PRISMA principles. Records were gathered from Scopus and Web of Science. Following the scientometric analysis, content analysis was conducted according to the template analysis approach.

The analysis of 121 articles revealed four main themes related to industrialized construction: 1) the construction concept, 2) construction methodologies, 3) systematization, rationalization and automatization and 4) societal and industrial change processes. Definitions of industrialized construction can be analyzed with seven clusters: 1) prefabrication, 2) standardization, 3) sector, 4) integration, 5) manufacturing practices, 6) technological investment and 7) none. Based on the content analysis, the proposed definition is: industrialized construction is the adoption of practices that minimize project-specific work in construction from the start of the design to the end of the building’s life cycle.

This study proposes a definition for industrialized construction following content analysis of broadly sampled literature. The proposed definition can provide a basis on which developments in the construction industry can be reflected.

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.

This paper aims to address the issue of designing aerodynamically robust empennage. Aircraft design optimization often narrowed to analysis of cruise conditions does not take into account other flight phases (manoeuvres). These, especially in unmanned air vehicle sector, can be significant part of the whole flight. Empennage is a part of the aircraft, with crucial function for manoeuvres. It is important to consider robustness for highest performance.

Methodology for robust wing design is presented. Surrogate modelling using kriging is used to reduce the optimization cost for high-fidelity aerodynamic calculations. Analysis of varying flight conditions, angle of attack, is made to assess robustness of design for particular mission. Two cases are compared: global optimization of 11 parameters and optimization divided into two consecutive sub-optimizations.

Surrogate modelling proves its usefulness for cutting computational time. Optimum design found by splitting problem into sub-optimizations finds better design at lower computational cost.

It is demonstrated, how surrogate modelling can be used for analysis of robustness, and why it is important to consider it. Intuitive split of wing design into airfoil and planform sub-optimizations brings promising savings in the optimization cost.

Methodology presented in this paper can be used in various optimization problems, especially those involving expensive computations and requiring top quality design.