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Facing the global public health emergency (GPHE), the conflict of cultural differences and the imbalance of vital resources such as knowledge among different organizations are becoming more severe, which affects the enthusiasm and sustainability of firms' innovation heavily. It is an urgent problem to be solved for firms how to make use of internal knowledge and external power to help firms' sustainable innovation (FSI). Thus, the purpose of this study is to deeply analyze how firms' internal knowledge diversity (KD) and external ego-network structures [ego-network density (ED) and honest brokers (HB)] affect FSI, as well as how the ego-network structures (ED and HB) moderate the relationship between KD and FSI based on the perspective of the ego network.

Based on the data of the alliance innovation networks of China's new energy industries in 2009–2019, this study uses the social network analysis method and negative binomial regression model to explore the effect of KD and ego-network structures (ED and HB) on FSI, as well as the moderating effects of ego-network structures (ED and HB) on the relationship between KD and FSI based on the perspective of ego network.

This study finds that KD, ED and HB can boost FSI. Moreover, ED plays a negative moderating role in the relationship between KD and FSI. However, the negative moderating effect of HB on the relationship between KD and FSI is not significant.

This study presents fresh empirical evidence and new insights for firms on how to make full use of firms' internal KD and external ego-network structures to facilitate FSI.

First, this study not only enriches the research on the consequences of KD but also expands our understanding of the knowledge-based view to some extent. Second, this study not only enriches the motivation research of the FSI based on the perspective of ego-network in the context of the GPHE but also expands the application scope of social network theory and sustainable innovation' theory in part. Third, this paper is a new attempt to apply social network theory and knowledge-based view at the same time.

This study aims to provide a nuanced understanding of the relationship between task-technology fit and employee innovative behavior, as well as the role of creative self-expectations.

Hierarchical regression analysis was used to test the proposed multilevel model on a sample of 407 employees working in Chinese companies.

Task-technology fit stimulates employee innovative behavior through the regulation of creative self-expectations and positive emotions. When creative self-expectations is low, the promoting effect of task-technology fit on innovative behavior is enhanced. However, when creative self-expectations is too high, this effect is reversed due to employees’ preference for challenging and complex work.

In the process of enterprise digital transformation, managers should not only focus on the alignment between employees' skills and individual task expectations, but also pay attention to employees' emotions and individual trait differences, to enhance the likelihood of innovative behavior occurrence and achieve successful enterprise digital transformation.

This study enriches the research on task-technology fit and provides recommendations for organizations to achieve digital transformation.

The purpose of this study is to investigate the corrosion resistance of superalloys subjected to ultrasonic impact treatment (UIT). The passive film growth on the superalloys’ surface is analyzed to illustrate the corrosion mechanism.

Electrochemical tests were used to investigated the corrosion resistance of GH4738 superalloys with different UIT densities. The microstructure was compared before and after the corrosion tests. The passive film characterization was described by electrochemical impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS) tests.

The compressive residual stress and corrosion resistance of the specimens significantly increased after UIT. The order of corrosion resistance is related to the UIT densities, i.e. 1.96 s/mm² > 1.71 s/mm² > 0.98 s/mm² > as-cast. The predominant constituents of the passive films are TiO₂, Cr₂O₃, MoO₃ and NiO. The passive film on the specimen with 1.96 s/mm² UIT density has the highest volume fraction of Cr₂O₃ and MoO₃, which is the main reason for its superior corrosion resistance.

This study provides quantitative corrosion data for GH4738 superalloys treated by ultrasonic impact. The corrosion mechanism is explained by the passive film’s characterization.

Crack damage detection for aluminum alloy materials using fiber Bragg Grating (FBG) sensor is a kind of structure health monitoring. In this paper, the damage index of full width at half maximum (FWHM) was extracted from the distorted reflection spectra caused by the crack-tip inhomogeneous strain field, so as to explain the crack propagation behaviors.

The FWHM variations were also investigated through combining the theoretical calculations with simulation and experimental analyses. The transfer matrix algorithm was developed to explore the mechanism by which FWHM changed with the linear and quadratic strain. Moreover, the crack-tip inhomogeneous strain field on the specimen surface was computed according to the digital image correlation measurement during the experiments.

The experimental results demonstrated that the saltation points in FWHM curve accorded with the moments of crack propagation to FBG sensors.

The interpretation of reflected spectrum deformation mechanism with crack propagation was analyzed based on both simulations and experiments, and then the performance of potential damage features – FWHM were proposed and evaluated. According to the correlation between the damage characteristic and the crack-tip location, the crack-tip of the specimen could be measured rapidly and accurately with this technique.

The whole garment technology offers a solution for the production efficiency by directly knitting a seamless tubular garment. Due to its complexity, high requirements and few references, the technology has not been widely applied in mass production. Therefore, the purpose of this paper is to show garment technology’s detailed design method, the technique calculation process and its merits compared than common technology.

This paper first analyzes the knitting principle of the four-bed computerized flat knitting machine from its configuration. After that, the design method is putted forward as well as the technique calculation process. To reveal the advantages of the whole garment technology, this paper builds a comprehensive evaluation system by comparing the knitting time, labor cost and the yarn consumption.

With the evaluation system, the whole garment technology is proved to be more productive, cost-saving and less materials-consuming. Moreover, this advantage stands more out when the machine gage is higher.

Due to limited research time and references, this paper only presents the whole garment technology for knitting common and traditional styles. More complicated and fashioned garments can be studied in the future research.

The design method and technology presented in this paper can be used as a reference for both the designers in the manufacture industry and the scholars for academic research works.

This paper has presented the whole garment technology and a specific method for technique calculation with consideration of garment structures. It also builds a evaluation system to show the advantages in terms of knitting efficiency, labor cost and yarn consumption.

A novel frequency domain approach, which combines the pseudo excitation method modified by the authors and multi-domain Fourier transform (PEM-FT), is proposed for analyzing nonstationary random vibration in this paper.

For a structure subjected to a nonstationary random excitation, the closed-form solution of evolutionary power spectral density of the response is derived in frequency domain.

The deterministic process and random process in an evolutionary spectrum are separated effectively using this method during the analysis of nonstationary random vibration of a linear damped system, only modulation function of the system needs to be estimated, which brings about a large saving in computational time.

The method is general and highly flexible as it can deal with various damping types and nonstationary random excitations with different modulation functions.

The increase in population in the world has brought an overpopulation in various parts of the world, with those cities where their countries are developing being most affected, mainly because these usually have corrupt governments that make urban planning difficult in an optimal way. The increase in the construction of urban areas generates problems in the environment due to the increase in carbon emissions, greenhouse gases, and the extraction of natural resources. Therefore, governments must promote urban innovation based on compliance with sustainable development that allows for preserving the ecosystem and the population's quality of life. Urban innovation must incorporate technologies that allow sustainable activities to be carried out efficiently and monitor the progress of environmental regulations.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.