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The purpose of this paper is to investigate the unsteady aerodynamic characteristics in the deflection process of a morphing wing with flexible trailing edge, which is based on time-accurate solutions. The dynamic effect of deflection process on the aerodynamics of morphing wing was studied.

The computational fluid dynamic method and dynamic mesh combined with user-defined functions were used to simulate the continuous morphing of the flexible trailing edge. The steady aerodynamic characteristics of the morphing deflection and the conventional deflection were studied first. Then, the unsteady aerodynamic characteristics of the morphing wing were investigated as the trailing edge deflects at different rates.

The numerical results show that the transient lift coefficient in the deflection process is higher than that of the static case one in large angle of attack. The larger the deflection frequency is, the higher the transient lift coefficient will become. However, the situations are contrary in a small angle of attack. The periodic morphing of the trailing edge with small amplitude and high frequency can increase the lift coefficient after the stall angle.

The investigation can afford accurate aerodynamic information for the design of aircraft with the morphing wing technology, which has significant advantages in aerodynamic efficiency and control performance.

The dynamic effects of the deflection process of the morphing trailing edge on aerodynamics were studied. Furthermore, time-accurate solutions can fully explore the unsteady aerodynamics and pressure distribution of the morphing wing.

Evaluating mechanical properties of simply made samples by 3D printing technology at nanoscale provides a clear path to better understand larger-scale responses of complex natural rocks. Therefore, to realize the similarity between synthetically manufactured materials and natural geomaterials, this study focused on nanoscale mechanical characterization of a 3D printed object with only two constituent components (gypsum powder and infiltrant).

The study method includes nanoindentation technique combined with numerical simulation via discrete element method (DEM).

Four typical load-displacement curves were identified from nanoindentation of total test points indicating a typical elastic-plastic behavior of the 3D printed gypsum rock sample. Mechanical parameters such as Young’s modulus and hardness were calculated by energy-based methods and a positive correlation was observed. The infiltrant was found to considerably be responsible for the majority of the sample nano-mechanical behavior rather than the gypsum particles, thus expected to control macroscale properties. This was decided from deconvolution and clustering of elastic modulus data. Particle flow modeling in DEM was used to simulate the nanoindentation process in a porous media yielding rock-alike mechanical behavior.

The results show a matching load-displacement response between experimental and simulation results, which verified the credibility of simulation modeling for mechanical behavior of 3D printed gypsum rock at nanoscale. Finally, differential effective medium theory was used to upscale the nanoindentation results to the macroscale mechanical properties, which provided an insight into the geomechanical modeling at multiscale.

This study aims to propose a new airport gate assignment method to effectively improve the comprehensive operation capacity and efficiency of hub airport. Gate assignment is one of the most important tasks for airport ground operations, which assigns appropriate airport gates with high efficiency reasonable arrangement.

In this paper, on the basis of analyzing the characteristics of airport gates and flights, an efficient multi-objective optimization model of airport gate assignment based on the objectives of the most balanced idle time, the shortest walking distances of passengers and the least number of flights at apron is constructed. Then an improved ant colony optimization (ICQACO) algorithm based on the ant colony collaborative strategy and pheromone update strategy is designed to solve the constructed model to fast realize the gate assignment and obtain a rational and effective gate assignment result for all flights in the different period.

In the designed ICQACO algorithm, the ant colony collaborative strategy is used to avoid the rapid convergence to the local optimal solution, and the pheromone update strategy is used to quickly increase the pheromone amount, eliminate the interference of the poor path and greatly accelerate the convergence speed.

The actual flight data from Guangzhou Baiyun airport of China is selected to verify the feasibility and effectiveness of the constructed multi-objective optimization model and the designed ICQACO algorithm. The experimental results show that the designed ICQACO algorithm can increase the pheromone amount, accelerate the convergence speed and avoid to fall into the local optimal solution. The constructed multi-objective optimization model can effectively improve the comprehensive operation capacity and efficiency. This study is a very meaningful work for airport gate assignment.

An efficient multi-objective optimization model for hub airport gate assignment problem is proposed in this paper. An improved ant colony optimization algorithm based on ant colony collaborative strategy and the pheromone update strategy is deeply studied to speed up the convergence and avoid to fall into the local optimal solution.

Although microblogs have become an important information source, the credibility of their postings is still a critical concern due to the open and unregulated nature. To understand the antecedents of microblog information credibility, the purpose of this paper is to investigate the dual-role of cognitive heuristics (i.e. the additivity and bias roles) and the effect of gender differences.

This study collected data via an online field survey of active microblog users, and a total of 204 valid responses was received.

This study demonstrates the dual-role of source credibility and vividness, the additivity role of microblog platform credibility, and the bias role of social endorsement. Furthermore, this study also found out gender difference that the additivity role of cognitive heuristics was stronger for men while bias role was stronger for women.

This research enriches the microblog literature by examining the cognitive heuristic determinants as key predictors of microblog information credibility, and contributes to the information credibility literature by identifying and analyzing the dual-role effect of cognitive heuristics and corresponding gender differences.

This study can help organizations better manage their reputation, especially during the reputation crises, and also serves as a reminder to microblog platform operators of the importance of their microblog platform credibility.

This study can help organizations better manage their reputation, especially during the reputation crises, and serves as a reminder to the microblog platform operators of the importance of their microblog platform credibility.

This study investigates the dual-role effect of cognitive heuristics (i.e. the additivity role and bias role) and corresponding gender differences that are less touched on before, and thus provides a more nuanced understanding of the more complex effects of cognitive heuristics.

This study aims to investigate consumer ethnocentrism and determine its impact on actual purchasing behavior in relation to six product categories. It also examines the role of demographic variables as moderators in the relationship between ethnocentric tendencies and purchasing behavior.

A total of 467 completed questionnaires were obtained through convenience and snowball sampling. Data were analyzed using SPSS-24 and AMOS-23 software: SPSS to conduct the exploratory factor analysis and AMOS for the confirmatory factor analysis. Regression analysis was performed to determine the effect of ethnocentrism on purchasing behaviors; the SPSS process was used to test the moderating effects.

The consumer ethnocentric tendencies scale was collected in two dimensions: hard ethnocentrism, which influences actual purchasing behavior in five product categories; and soft ethnocentrism, which influences actual purchasing behavior in only two product categories. The results show that the effect of consumer ethnocentrism on purchasing behavior differs across product categories. Further, gender, marital status and personal income moderate this relationship.

Few studies investigate purchasing behavior across several product categories and the literature on consumer ethnocentrism does not address the impact of demographic variables as moderators in consumer behavior. This study contributes to the existing literature in four ways. First, it was conducted in Azerbaijan, a country with specific characteristics. Second, it examines the impact of ethnocentric tendencies on actual purchasing behavior. Third, it examines purchasing behavior in relation to six different product categories. Fourth, the moderating effect of demographic variables was tested.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.