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With the diversification of professional values, an increasing number of individuals voluntarily choose positions that demand less than their personal knowledge, skills and educational background, a phenomenon known as voluntary overqualification. This study aims to explore the reasons for discerning the motivations driving voluntary overqualification, define its conceptual content and develop the measurement scale for voluntary overqualification.

Through five phases, and using both qualitative and quantitative approaches, the authors constructed a scale comprising three dimensions: earnings-oriented, life-oriented and meaning-oriented to measure voluntary overqualification. Following the steps of scale development, the conceptual connotation and structural dimensions of voluntary overqualification were systematically coded and mined based on grounded theory. The scale’s reliability and validity were measured through exploratory and validation factor analyses. Finally, the validity of the voluntary overqualification scale was verified through the selection of professional identity and subjective well-being.

This study defined connotations and structural dimensions of voluntary overqualification based on grounded theory, resulting in a measurement scale with three dimensions and 13 items. These dimensions include earnings-, life- and meaning-oriented voluntary overqualification. Empirical testing of predictive validity used professional identity and subjective well-being as outcome variables.

This study provides a theoretical foundation and an effective measurement tool for subsequent research in voluntary overqualification by focusing on a new type of voluntary overqualification, defining its connotations and developing a complete set of scales.

Digital technologies over time are becoming increasingly pervasive and relatively affordable, finding a large diffusion in Small and Medium Enterprises (SMEs) also for internationalization purposes. However, less is known about the specific mechanisms by which this can be achieved. Specifically, we focus on how SMEs can face the international environment, leveraging digital technologies and thanks to their intellectual capital (IC).

We analyze the relationship between digital technologies and the internationalization of SMEs, exploring the mediating role of IC in its three dimensions: human, relational and innovation capital, and assessing the possible moderating effects posed by international institutional conditions, specifically the Sino-US trade frictions. The relationships are tested using a sample of companies listed on China’s A-share Growth Enterprise Market (GEM) from 2010 to 2021.

Digital technologies help to internationalize SMEs. However, this positive relationship is affected (mediated) by the presence of an already consolidated IC. In addition, the institutional conditions of the international market, such as the Sino-US trade friction, moderate the components of IC differently. Specifically, the overall mediating effect of human and relational capital is boosted, while this does not happen for innovation capital.

First, this study contributes to the literature on organizational resilience, especially digital resilience, confirming its validity in the context of internationalization and, in particular, those processes adopted by SMEs. Second, we clarify the mechanisms through which digital technologies exert their impact on the process of internationalization and in particular the prominent necessity of having IC. Third, our conclusions enrich the understanding of how IC components react to turbulence in international markets.

An inter-story isolation structure (IIS) for AP1000 nuclear power plants (NPPs) is provided to resolve the conflict of seismic safety and the optimal location of air intakes.

The effect of passive cooling system (PCS) is better with lower altitude of air intakes than that in the original design of AP1000 NPPs. Seismic performances of IIS NPPs, including the seismic responses, damping frequency bandwidth and seismic reduction robustness, are improved by combining the position of air intakes lower and the optimal design method.

Theoretical analysis and numerical simulation are illustrated that the seismic reduction failure of IIS NPPs is the lowest probability of occurrence when PCS has highest working efficiency.

The IIS NPPs can transfer the contradiction between PCS work efficiency and seismic safety of NPPs to the mutual promotion of them.

This paper investigates how a regulator pursuing social welfare maximization designs an optimal subsidy scheme to stimulate technology innovation in the presence of a consumer green premium. Specifically, the authors solve the following questions: (1) Does the consumers' green premium affect the design of the subsidy scheme? (2) How should the firm choose a green technology innovation strategy under the optimal subsidy scheme? (3) Does technology innovation bring higher social welfare and lower environmental impact?

The authors first develop a game model to explore the impact of subsidy schemes on social welfare without considering technology innovation. Then the authors investigate two innovation strategies, in-house innovation and external introduction, under the optimal subsidy scheme. Finally, they illustrate the optimal choices of innovation strategy for the firm, consumers and regulators.

The results reveal that the subsidy scheme will not always increase social welfare, which depends on the environmental improvement coefficient of the unit green level. The optimal subsidy level increases with the green premium, but it is not related to the size of the consumer green segment. Moreover, the success rate of in-house innovation will raise the optimal green level, but the company benefits from an increased success rate of in-house innovation only when the green segment is large enough. The green segment size and external green level jointly determine the choice of technology innovation strategy.

This research is the first to analyze this problem while considering the green demand and subsidy scheme simultaneously as drivers of a firm's technology innovation, thereby providing new managerial implications for decisions by the regulator and firms.

The purpose of this paper is to focus on the design of a dual-branch balance saliency model based on fully convolutional network (FCN) for automatic fabric defect detection, and improve quality control in textile manufacturing.

This paper proposed a dual-branch balance saliency model based on discriminative feature for fabric defect detection. A saliency branch is firstly designed to address the problems of scale variation and contextual information integration, which is realized through the cooperation of a multi-scale discriminative feature extraction module (MDFEM) and a bidirectional stage-wise integration module (BSIM). These modules are respectively adopted to extract multi-scale discriminative context information and enrich the contextual information of features at each stage. In addition, another branch is proposed to balance the network, in which a bootstrap refinement module (BRM) is trained to guide the restoration of feature details.

To evaluate the performance of the proposed network, we conduct extensive experiments, and the experimental results demonstrate that the proposed method outperforms state-of-the-art (SOTA) approaches on seven evaluation metrics. We also conduct adequate ablation analyses that provide a full understanding of the design principles of the proposed method.

The dual-branch balance saliency model was proposed and applied into the fabric defect detection. The qualitative and quantitative experimental results show the effectiveness of the detection method. Therefore, the proposed method can be used for accurate fabric defect detection and even surface defect detection of other industrial products.