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Although it is acknowledged that entrepreneurial networks play a crucial role in fostering business model innovation (BMI) for start-ups, it is unclear how and when these networks affect BMI. This research developed a moderated mediation model to explore the impact of entrepreneurial networks on BMI in start-ups and examined the dual mediating effects of causation and effectuation, as well as the moderation of environmental dynamism.

The proposed framework was tested by hierarchical regression analyses and bootstrapping using samples of 248 start-ups in China.

The results showed that entrepreneurial networks significantly positively impacted start-up BMI. Causation and effectuation played dual mediating roles between entrepreneurial networks and BMI. Furthermore, the entrepreneurial networks-effectuation-BMI association was more substantial in highly dynamic environments, whereas the entrepreneurial networks-causation-BMI relationship was unaffected.

There are several theoretical contributions resulting from this research. The findings offer new insights for understanding the antecedents of start-up BMI from the network perspective. This research adds to the growing literature on resource orchestration (RO) by exploring the dual mediating influences of causation and effectuation in resource management. This investigation revealed the boundary condition between entrepreneurial networks and BMI by testing the moderating influence of environmental dynamism.

Start-ups must effectively use external resources embedded within networks to advance BMI. Start-up entrepreneurs should apply causation and effectuation to transform entrepreneurial network resources into BMI. Start-up entrepreneurs must dynamically manage resources in response to ever-changing environmental conditions. Resource acquisition and management of entrepreneurial networks can vary significantly in their influence on start-up BMI under different environmental contexts.

Unlike previous BMI research focused on internal organizational factors, this study highlighted the critical importance of entrepreneurial networks as a prerequisite for achieving start-up BMI, contributing to the literature on open innovation and resource-based view. Examining the dual mediating roles of causation and effectuation illustrated the bridging role of strategic decision-making logic in connecting resources to value creation, contributing to the developing RO literature. The moderating influence of environmental dynamism was explored, clarifying how start-up BMI benefits from entrepreneurial networks in differing situations. A framework for reconciling contradictory findings concerning the association between entrepreneurial networks and innovation is provided.

Drawing from resource orchestration theory, this research proposed an integrative model that leverages insights into counter resource constraints and uncertainty in start-up business model innovation (BMI). It investigated the influences of entrepreneurial networks and effectuation on BMI through bricolage in uncertain environments.

The research surveyed 481 start-ups in China. LISREL 8.80 and SPSS 22.0 were employed to test the validity and reliability of key variables, respectively. Additionally, hypotheses were examined through multiple linear regression.

First, entrepreneurial networks and effectuation were positively related to BMI, and combining these two factors improved BMI for start-ups. Second, bricolage contributed to BMI and played mediating roles in translating entrepreneurial networks and effectuation into BMI. Third, environmental uncertainty weakened the linkage between bricolage and BMI.

Future research should replicate the results in other countries because only start-ups in China were investigated in the study, and it is necessary to extend this research by gathering longitudinal data. This research emphasized the mediating effects of bricolage and the moderating influence of environmental uncertainty, and new potential mediating and moderating factors should be explored between resources and BMI.

There are three significant theoretical contributions. First, the findings enrich the literature on the complex antecedents of BMI by combining the impacts of entrepreneurial networks and effectuation. Second, an overarching framework is proposed explaining how bricolage (resource management) links entrepreneurial networks and effectuation and BMI. Third, it demonstrates the significance of environmental uncertainty in the bricolage–BMI linkage, deepening the understanding of the bricolage boundary condition.

The purpose of this paper is to present a novel assembly spring-back model which takes surface contact conditions between sheet metal parts into consideration so that the assembly dimensions and variations can be more precisely predicted than existing assembly simulation models.

Because an assembly process is composed of four essential steps, i.e. locating, clamping, joining and tool releasing, the mechanistic models associated with these steps are developed in the paper. In particular, the surface contact between the weld flanges (in folding joint configuration) and the overlapping surfaces (in lap joint configurations) is included in the models. Sensitivity models are developed.

Two cases studies are presented, i.e. the cantilever beams assembly and the Z-plates assembly. More precise prediction results are shown.

The model developed in this paper is based upon analytical elastic beam theories. Therefore, the results and case studies are limited only to workpieces that can be approximately represented by beam geometries. However, the methods can be broadened to generic workpiece geometries by using finite element methods; thus, the developed method is highly valuable to a broad range of applications such as automotive body assembly and aerospace industries.

The novelty of this research lies in its inclusion of surface contact conditions in an assembly simulation model by using analytical beam mechanistic models to achieve more accurate assembly variation predictions.

This study aims to examine the role of authenticity in tourists’ destination selection, analyze the factors that influence tourists to form their initial opinions and explore how tourists construct the authenticity of traditional villages. The authors selected Chengkan village in Huizhou district, Huangshan city, as a case. In the study, the authors constructed an attribute-hardware-software research framework and analyzed tourists’ authentic emic experiences from the perspective of constructivism. The findings of this study suggest that tourists’ destination selection is influenced by authenticity. The destination culture brokers who interact with tourists play an essential role in forming authentic experiences. According to differences in how tourists construct authenticity, the study divided tourists into three types: primitive imagination, aesthetic reality and rational cognition. The results of this study provide a deeper understanding of various viewpoints about authenticity research and contribute to the academic discussion on how to understand the authenticity of unique cultural heritage sites such as traditional villages in the context of tourism development.

The microseismic monitoring technique has great advantages on identifying the location, extent and the mechanism of damage process occurring in rock mass. This study aims to analyze distribution characteristics and the evolution law of excavation damage zone of surrounding rock based on microseismic monitoring data.

In situ test using microseismic monitoring technique is carried out in the large-span transition tunnel of Badaling Great Wall Station of Beijing-Zhangjiakou high-speed railway. An intelligent microseismic monitoring system is built with symmetry monitoring point layout both on the mountain surface and inside the tunnel to achieve three-dimensional and all-round monitoring results.

Microseismic events can be divided into high density area, medium density area and low density area according to the density distribution of microseismic events. The positions where the cumulative distribution frequencies of microseismic events are 60 and 80% are identified as the boundaries between high and medium density areas and between medium and low density areas, respectively. The high density area of microseismic events is regarded as the high excavation damage zone of surrounding rock, which is affected by the grade of surrounding rock and the span of tunnel. The prediction formulas for the depth of high excavation damage zone of surrounding rock at different tunnel positions are given considering these two parameters. The scale of the average moment magnitude parameters of microseismic events is adopted to describe the damage degree of surrounding rock. The strong positive correlation and multistage characteristics between the depth of excavation damage zone and deformation of surrounding rock are revealed. Based on the depth of high excavation damage zone of surrounding rock, the prestressed anchor cable (rod) is designed, and the safety of anchor cable (rod) design parameters is verified by the deformation results of surrounding rock.

The research provides a new method to predict the surrounding rock damage zone of large-span tunnel and also provides a reference basis for design parameters of prestressed anchor cable (rod).

The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings.

A feature selection scheme and stacking ensemble model to fulfill cooling load prediction task was proposed. Firstly, the abnormal data were identified by the data density estimation algorithm. Secondly, the crucial input features were clarified from three aspects (i.e. historical load information, time information and meteorological information). Thirdly, the stacking ensemble model combined long short-term memory network and light gradient boosting machine was utilized to predict the cooling load. Finally, the proposed framework performances by predicting cooling load of office buildings were verified with indicators.

The identified input features can improve the prediction performance. The prediction accuracy of the proposed model is preferable to the existing ones. The stacking ensemble model is robust to weather forecasting errors.

The stacking ensemble model was used to fulfill cooling load prediction task which can overcome the shortcomings of deep learning models. The input features of the model, which are less focused on in most studies, are taken as an important step in this paper.

The properties of materials under impact load are introduced in terms of metal, nonmetallic materials and composite materials. And the application of impact load research in biological fields is also mentioned. The current hot research topics and achievements in this field are summarized. In addition, some problems in theoretical modeling and testing of the mechanical properties of materials are discussed.

The situation of materials under impact load is of great significance to show the mechanical performance. The performance of various materials under impact load is different, and there are many research methods. It is affected by some kinds of factors, such as the temperature, the gap and the speed of load.

The research on mechanical properties of materials under impact load has the characteristics as fellow. It is difficult to build the theoretical model, verify by experiment and analyze the data accumulation.

This review provides a reference for further study of material properties.

The purpose of this paper is to investigate the structural, electronic and optical properties of pure zinc oxide (ZnO) and transition metal (Tm)-doped ZnO using Tm elements from silver (Ag) and copper (Cu) by a first-principles study based on density functional theory (DFT) as implemented in the pseudo-potential plane wave in CASTEP computer code.

The calculations based on the generalized gradient approximation for Perdew-Burke-Ernzerhof for solids with Hubbard U (GGA-PBEsol+U) were performed by applying Hubbard corrections U_d = 5 eV for Zn 3d state, U_p = 9 eV for O 2p state, U_d = 6 eV for Ag 4d state and U_d = 9.5 eV for Cu 3d state. The crystal structure used in this calculation was hexagonal wurtzite ZnO with a space group of P63mc and supercell 2 × 2 × 2.

The total energy was calculated to determine the best position for Ag and Cu dopants. The band structures and density of states show that Tm-doped ZnO has a lower bandgaps value than pure ZnO because of impurity energy levels from Ag 4d and Cu 3d states. In addition, Ag-doped ZnO exhibits a remarkable enhancement in visible light absorption over pure ZnO and Cu-doped ZnO because of its lower energy region and extended wavelength spectrum.

The results of this paper are important for the basic understanding of the 3d and 4d Tm doping effect ZnO and have a wide range of applications in designing high-efficiency energy harvesting solar cells.

In today’s Taiwan, sha-cha sauce is an indispensable ingredient for beef hot pot and stir-fried dishes. The purpose of this paper contextualizes the history of sha-cha sauce in Tainan, the oldest city in Taiwan, and argues that sha-cha sauce, introduced by Chaoshan immigrants, has contributed to new styles and habits of beef consumption tastes and habits in the post-1949 Tainan and beyond.

This paper uses documentary materials, oral interviews and diaries to explore the relationship between beef consumption and sha-cha sauce. It begins with an historical overview of Taiwan’s beef consumption during the Japanese colonial era (1895-1945). Then, it focuses on two Chaoshan business enterprises: the Bull-Head, which makes the world’s largest “canned sha-cha sauce,” and the Xiao Haozhou, a Tainan restaurant specializing in sha-cha beef hot pot. Finally, this study analyzes Xinrong Wu, a Tainan gentry whose diary entries from 1933 to 1967 documented the changing dietary habits of beef consumption among Taiwanese.

The Chaoshan migrants played an important role in introducing the sha-cha sauce to postcolonial Tainan, and this input bolstered the beef consumption among Taiwanese. The production of sha-cha provided a reliable source of income for these migrants in Tainan, and major businesses like the Bull-Head became the international brands of Taiwanese food products.

The study, though limited to Tainan, reveals the symbiosis between popularization of sha-cha sauce and widespread beef consumption in Taiwan.

This study helps researchers examine the connection between Chinese migrations and food culture.

This paper is an original scholarly investigation of the relationship between food diet and Chaoshan migration in postcolonial Tainan.

This study aims to accurately calculate the magnetic field distribution, which is a prerequisite for pre-design and optimization of electromagnetic performance. Accurate calculation of magnetic field distribution is a prerequisite for pre-design and optimization.

This paper proposes an analytical model of permanent magnet machines with segmented Halbach array (SHA-PMMs) to predict the magnetic field distribution and electromagnetic performance. The field problem is divided into four subdomains, i.e. permanent magnet, air-gap, stator slot and slot opening. The Poisson’s equation or Laplace’s equation of magnetic vector potential for each subdomain is solved. The field’s solution is obtained by applying the boundary conditions. The electromagnetic performances, such as magnetic flux density, unbalanced magnetic force, cogging torque and electromagnetic torque, are analytically predicted. Then, the influence of design parameters on the torque is explored by using the analytical model.

The finite element analysis and prototype experiments verify the analytical model’s accuracy. Adjusting the design parameters, e.g. segments per pole and air-gap length, can effectively increase the electromagnetic torque and simultaneously reduce the torque ripple.

The main contribution of this paper is to develop an accurate magnetic field analytical model of the SHA-PMMs. It can precisely describe complex topology, e.g. arbitrary segmented Halbach array and semi-closed slots, etc., and can quickly predict the magnetic field distribution and electromagnetic performance simultaneously.