Search results

The purpose of the study is to investigate strategies for enhancing pollution oversight by local governments while reducing government-enterprise collusion (GEC) levels. Additionally, the factors influencing pollution control efforts at incineration plants are explored. Potential approaches to improving them and for effectively reducing waste incineration pollution are suggested.

The authors examined the most effective methods for mitigating incineration-related pollution and preventing collusion and developed a differential game model involving interactions between local governments and incineration plants. The findings of this work have significant policy implications for central governments worldwide seeking to regulate waste incineration practices.

The results indicate that, first, elevating environmental assessment standards can incentivize local governments to improve their oversight efforts. Second, collusion between incineration plants and local governments can be deterred by transferring benefits from the plants to the local government, while increased supervision by the central government and the enforcement of penalties for collusion can also mitigate collusion. Third, both central and local governments can bolster their supervisory and penalty mechanisms for instances of excessive pollution, encouraging incineration plants to invest more in pollution control. Finally, when the central government finds it challenging to detect excessive incineration-related pollution, enhancing rewards and penalties at the local government level can be a viable alternative.

This study stands out by considering the dynamic nature of pollutants. A differential game model is constructed which captures the evolving dynamics between local governments and incineration plants, offering insights regarding the prevention of collusion from a dynamic perspective. The findings may provide a valuable reference for governments as they develop and enforce regulations while motivating incineration plants to actively engage in reducing waste-incineration pollution.

Despite the potential of virtual fitting rooms (VFRs) to enhance the consumer experience, their adoption is in the preliminary stages. Little is known about inherent reasons why consumers would adopt VFRs. As consumers' attributional processes can be influenced by their enduring chronic traits, this study aims to investigate the influence of chronic regulatory focus on consumers' VFR adoptions via consumers' perceptions of value provided by VFRs. Additionally, the mediating effects of perceived functional and experiential values were examined. Further, the moderating effect of prior VFR experience was tested to allow for variations in consumer experiences.

Data were collected via an online survey of 480 consumers who have at least heard of VFRs via convenience sampling. Established measures were utilized to develop the survey questionnaire. Data were analysed using structural equation modelling to test the main model with mediation effects as well as multi-group comparisons to test the moderating effect.

Empirical results revealed that respective chronic regulatory foci, as preconceived factors that drive consumers' differences in processing, exerted significant influences on consumers' perceptions of VFRs, which, in turn, positively influenced their adoption intention. Also, perceived values mediated the relationship between regulatory foci and consumers' adoption intention. Further, prior VFR experience moderated the relationship between regulatory focus and perceived value.

The paper empirically tested the importance of chronic regulatory foci in understanding consumers' cognitive and affective attributional processes, explaining inherent psychological reasons why consumers would (not) adopt VFRs.

With the development trend of China’s service-oriented manufacturing moving toward intelligence and personalization, the deep integration of manufacturing and service has become a synergistic challenge for enterprises.

An improved migratory bird optimization (IMBO) algorithm is proposed to solve the multiobjective FJSP model. First, this paper designs an integer encoding method based on job-machine. The algorithm adopts the greedy decoding method to obtain the optimal scheduling solution. Second, this paper combines three initialization rules to enhance the quality of the initial population. Third, three neighborhood search strategies are combined to improve the search capability and convergence of the solution space. Furthermore, the IMBO algorithm introduces the concepts of nondominated ranking and crowding degree to update the population better. Finally, the optimal solution is obtained after multiple iterations.

Through the simulation of 15 benchmark studies and a production example of a furniture enterprise, the IMBO algorithm is compared with three other algorithms: the improved particle swarm optimization algorithm, the global and local search with reinitialization-based genetic algorithm and the hybrid grey wolf optimization algorithm. The experiment results show the effectiveness of the IMBO algorithm in solving the multiobjective FJSP.

The study does not consider the influence of disturbance factors, such as emergency interventions and equipment failures, on scheduling in actual production processing. It is necessary to further study the dynamic FJSP problem.

The study proposes an IMBO algorithm to solve the multiobjective FJSP problem. It also uses three initialization rules to broaden the range of the solution space. The study applies multiple crossover strategies to avoid the algorithm falling into local optimality.

To solve the problems of annotation noise, ambiguity recognition and nested entity recognition in the field of Chinese furniture, this paper aims to design a new recognition model ALE-BiLSTM-CRF.

This paper addresses the relative independence of text characters in the Chinese furniture domain named entity recognition (NER) task. It also considers the limited information provided by these text characters in this task. Therefore, a model named ALE-BiLSTM-CRF for Chinese furniture domain NER is proposed. First, the ERNIE pre-trained model is used to transform text into a dynamic vector that integrates contextual information. And adversarial learning is combined to generate adversarial samples to enhance the robustness of the model. Next, the BiLSTM module captures the temporal information of the context, and the multi-head attention mechanism integrates long-distance semantic features into the character vectors. Finally, a CRF layer is used to learn the constraints between labels, enabling the model to generate more reasonable and semantically consistent label sequences. This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.

This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.

This paper demonstrates its universality and generalization by conducting comparative experiments with mainstream models on the Weibo data set. It also conducts comparative experiments with representative pre-trained models on the furniture data set and conducts ablation experiments on the model itself, further demonstrating the superiority and effectiveness of the model.

In the furniture domain, NER aims to use various methods, including rule templates, machine learning and deep learning techniques, to extract structured information related to furniture from unstructured text. These pieces of information may include the name, material, brand, style and function of the furniture. By extracting and identifying these named entities, this paper can provide more accurate data support for furniture design, manufacturing and marketing, thereby promoting further development and innovation in the furniture industry.

In the furniture field, NER faces some special challenges, which are different from entity recognition in general fields. Furniture terminology is often highly specialized and complex in structure. At the same time, there may be a large number of nested entities in the text of the furniture field. For example, the furniture name “sofa bed” contains two entities “sofa” and “bed.” Current sequence labeling methods often find it difficult to recognize such nested entity structures simultaneously. Additionally, because furniture terminology and descriptions may change with trends and design styles, the model also needs to have a certain degree of adaptability and update capabilities. These reasons make it more difficult to extract information in the furniture field, and NER in the furniture field faces huge challenges.

This paper conducts comparative experiments with mainstream models on the Weibo data set, achieving an F1 score of 75.52%, demonstrating its generality and robustness. Additionally, comparative and ablation experiments are conducted on a self-constructed furniture data set in the Chinese furniture field, achieving an F1 score of 89.62%, verifying the model’s superiority and effectiveness.

Innovation resilience, which refers to firms’ ability to consistently innovate and recover from disruptions, has recently gained increasing attention. Digital transformation plays a crucial role in the innovation of manufacturing firms. This paper aims to investigate the impact mechanisms of manufacturing firms’ innovation resilience in the context of digital transformation.

Using panel data from Chinese A-share listed manufacturing firms spanning from 2017 to 2022 as an example, this research examines the impact of digital transformation on innovation resilience. It also tests the moderating effect of innovation network embeddedness and the mediation effect of absorptive capacity.

It is found that digital transformation can enhance the innovation resilience of manufacturing firms. Furthermore, the structural embeddedness and relational embeddedness of manufacturing firms within innovation networks moderate the relationship between digital transformation and innovation resilience. The absorptive capacity of manufacturing firms acts as a mediator in the relationship between digital transformation and innovation resilience.

This paper is one of the first studies that investigates the impact mechanisms of digital transformation on the innovation resilience of manufacturing firms based on network embeddedness theory and dynamic capability theory.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

In the context of innovation-driven development strategy, open innovation has become an important way for enterprises to gain competitive advantages on the path of innovation and development. However, with the increasing competition, enterprises' open innovation is restricted by some constraints. How to promote open innovation in the restricted situations has become an existing research gap. Based on the perspective of digital transformation, this paper discusses how to promote the open innovation of enterprises under the restricted situations and find its breakthrough path, and analyzes the moderating effect of innovation persistence and political relevance.

Due to the complexity and confidentiality of military–civilian integration enterprises, they have become typical innovation-restricted enterprises. In this study, it selects a-share listed companies in the field of military–civilian integration in China in 2016–2020 as the research sample, and uses the two-way fixed-effect model to analyze the proposed variables. Finally, the robustness of the results in this paper is verified by a series of robustness tests and endogeneity tests.

The results show that digital transformation facilitates open innovation in military–civil integration enterprises, and that innovation persistence and political relevance positively moderate the relationship between the two. Further, digital transformation can promote open innovation in military–civil integration enterprises by easing the financing constraints and reducing information asymmetry. Innovation persistence has a more pronounced positive moderating effect among civilian-to-military and SMEs, and digital transformation of firms in the South has a negative effect on open innovation, but innovation persistence and political relevance dampen this negative effect.

Previous studies on the restrictions of open innovation or its dark side are mostly case studies and qualitative research. In contrast, the superiority and novelty of this study is in the form of a typical innovation-restricted enterprises “civil-military integration enterprise” as the research sample, based on the perspective of digital transformation, through empirical analysis method to explore how to better implementation of open innovation in the restricted situations. The findings of the study can not only enrich the application of digital transformation and open innovation theory, but also provide practical guidance for military–civil integration innovation in restricted situations.

The consideration of the substitution phenomenon in the project portfolio selection problem can improve the robustness of project portfolio selection and help enterprises better achieve their strategic objectives. However, the existence of inter-project risk propagation will have a negative impact on project substitution. This paper proposes a new framework for project portfolio selection and constructs a risk propagation model based on strategic objectives to study the impact of risk propagation on substitution in the project portfolio.

The authors first construct a risk propagation model based on strategic objectives to describe the risk propagation between projects. Then the project substitution phenomenon based on risk propagation is put forward, and the calculation method of substitution loss is given. Finally, a robust project portfolio selection framework based on strategic objectives considering risk propagation is constructed.

The analysis of a case study demonstrates that (1) With the increase of risk intensity, the strategic loss of the same project portfolio increases linearly, and under the same risk intensity, the more projects in the portfolio, the stronger the robustness. (2) Considering risk propagation, the effect of project substitution is significantly weakened, and the strategic loss rate of the project portfolio is significantly increased compared with that of a direct attack.

This study is the first to take the project substitution into account in the project portfolio selection process. Moreover, the authors describe inter-project risk propagation and analyze the impact of risk propagation on the project substitution phenomenon. Finally, the authors extend the evaluation index of robustness. This paper puts forward a new way to solve the problem of project portfolio selection.

This study explores whether and how financial agglomeration affects enterprise specialization, and whether it weakens the division effects of logistics accessibility.

Using the panel data of A-share listed companies in the Chinese manufacturing industry from 2010 to 2018, the authors test the hypotheses of the research framework by constructing a double fixed effect model.

First, for every 1% increase in financial agglomeration and logistics accessibility, enterprise specialization will increase by 1.8% and 5.6%. Meanwhile, financial agglomeration weakens the division effects of logistics accessibility. After a multiple robustness test, the above conclusions still hold. Second, the mechanism test shows that financial agglomeration can promote enterprise specialization through cost saving effect, scale expansion effect and technological progress effect. Third, financial agglomeration has a stronger positive impact and negative moderating effect on enterprise specialization in periphery areas and small-scale enterprises, but logistics accessibility is more likely to increase enterprise specialization in core regions and small-scale firms.

In the context of the global value chain (GVC) reshaping caused by the transformation of the international situation, exploring the relationship among financial agglomeration, logistics accessibility and enterprise specialization based on China’s experience can be an important insight for other emerging economies to enhance their position in the GVC.

The above findings enrich the literature on the division of labor among firms and contribute to the further improvement of GVC theory and division theory.