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This study aims to apply for the first time in literature a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm and test the sensors' configuration found in a delamination identification case study.

This work aims to study the damage identification in an aircraft wing using the Lichtenberg and multi-objective Lichtenberg algorithms. The former is used to identify damages, while the last is associated with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time.

The proposed method was not only able to find a sensor configuration for each sensor number and modal metric but also found one that had full accuracy in identifying delamination location and severity considering triaxial modal displacements and minimal sensor number for all wing sections.

This study demonstrates for the first time in the literature how the most used modal metrics vary with the sensor number for an aircraft wing using a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm.

Traceability is an increasingly important tool for reducing food safety risks and managing supply logistics. Given the costs of implementing and maintaining traceability systems, it is crucial to understand consumer willingness to pay (WTP) for traceable products.

The authors conducted a scoping review to collate the existing literature on consumer WTP for traceability in food products to determine the nature of the evidence base and to identify research gaps.

A total of 77 articles were included in the review. The number of studies published per year generally increased over the review period, and China and the United States were the most common countries in which studies were conducted (43.6 and 14.1% of total studies, respectively). All but one of the studies investigated at least one factor that might influence consumer WTP for traceability, the most common of which was socio-demographic characteristics (72.7%). Three-quarters of studies used hypothetical methods to elicit WTP values (75.3%), whereas one-quarter used non-hypothetical methods (24.7%). Most studies included some measure of preference heterogeneity (83.1%).

There is some potential for systematic bias in the evidence due to the predominance of studies from only a few countries and the possible presence of hypothetical bias. These potential biases could be corrected through future research.

To the authors’ knowledge, no previous study systematically and comprehensively identifies and summarizes the evidence base on consumer WTP for traceable food products.

The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses.

The multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model.

It was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively.

There is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses.

Numerical literature shows that agricultural insurance can affect pesticide investments, but few of them are devoted to explain how agricultural insurance affects farmers’ selection on green or traditional pesticides. This paper aims to develop a theoretical model about how agricultural insurance influences on green pesticides selections and tests our conclusions by using the data from China land economic survey (CLES) from 2020 to 2021.

We employ probit model to capture the effects of agricultural insurance on green pesticides adoption.

We indicate that green pesticides have a stronger effect on stabilizing yield and increasing income than traditional pesticides, but there are still risks disturbing farmers’ decisions on green pesticides usage. By providing premium subsidies after the farmers are affected by natural risk, agricultural insurance improves the farmers’ expected income and encourages farmers to use green pesticides. Further, we further confirm these conclusions by considering different scenarios such as climate risks, farmers’ entrepreneurship and credit constraints. We find that the effects are more salient if croplands are under higher natural risks and, farmers are equipped with entrepreneurship and formal credit. This paper implies that the agricultural insurance decoupled with green technologies also have salient positive effects on agricultural pollution control.

The potential contributions of this paper can be outlined in three aspects in detail. Firstly, this paper aims to revel the effects of agricultural insurance on pesticide selection by structuring a general theoretical model. By using the CLES data from 2020 to 2021, we confirm that agricultural insurance increases the probability for adopting green pesticides. Secondly, this paper discusses the effects of farmers’ characteristics on the results and finds that if farmers have entrepreneurship, the effects of agricultural insurance on green pesticide usage will be more salient. Thirdly, it uncovers some practices in China, which will supply experiences for other developing countries. For example, this paper further demonstrates that “insurance + credit” plan the present Chinese government carried out will be an important measure for strengthening effects of agricultural insurance on green pesticides usage. Moreover, it shows that decouple agricultural policies will also guide farmers to use green technologies eventually if the technologies are reliable and farmers can afford.

Previous studies have reached inconsistent conclusions on foreign direct investment (FDI) technology spillovers and corporate innovation. The main purpose of this paper is to explore the technological spillover effects of FDI from the microperspective of firm linkages induced by geographic distance. Further analysis is conducted on the impact and mechanism of this spillover on the innovation quality of Chinese enterprises. The conclusions drawn from this paper can guide Chinese enterprises' foreign capital utilization and innovation strategy choices.

Using the data of China's A-share listed companies from 2009 to 2019, this paper explores the role of FDI technology spillover in enterprise innovation quality through a two-way fixed-effect model. The robustness of the results is proven by substituting variables, adding industry fixed effects and excluding high-profit groups, and further using the two-stage least squares (2SLS) method to alleviate the empirical endogeneity problem.

These findings indicate that FDI technology spillover based on geographic proximity has a positive impact on the innovation quality of Chinese enterprises. However, there are different impacts for different types of enterprises. FDI technology spillover has a positive impact on the innovation quality of non-state-owned enterprises (non-SOEs) and small- and medium-sized enterprises (SMEs), while it has no effect on state-owned enterprises (SOEs) and large enterprises. The authors also find that the degree of financing constraints and R&D investment are important transmission mechanisms between FDI technology spillover and enterprise innovation quality.

This study ignores industry characteristics when considering foreign enterprises around Chinese enterprises. In fact, technology spillover effects differ across industries. When the authors matched microdata to regions, only the provincial level was considered. Therefore, there is still room for further research. In future research, the authors should consider industry characteristics and group foreign enterprises and Chinese enterprises in the same industry and in different industries to explore industry differences in technology spillover. In addition, when matching corporate data to regions, the authors can match to the city level and draw city-level conclusions.

This study is different from previous studies that focus on the quantity of enterprise innovation or innovation output. The authors focus on the role of technological spillovers in the quality of Chinese enterprise innovation, enriching research in the field of enterprise innovation quality. In addition, the current FDI technology spillover indicators are technically difficult to measure at the micro level. The authors draw inspiration from the theory of the geographical structure of financial supply and combine the creation methods of macro and micro indicators in existing articles in other fields. The authors ingeniously construct a new FDI technical spillover indicator. This indicator combines the commonly used regional FDI technology spillover with the geographic proximity of enterprises at the microlevel by constructing an interaction term between the two. This indicator not only alleviates the endogeneity problem to a certain extent but also has implications for future research in the field of FDI technology spillovers at the micro level.

(1) FDI technology spillovers are an effective way to improve the innovation quality of local enterprises, especially for non-SOEs and SMEs. Therefore, The authors suggest that in the context of dual circulation, the Chinese government should continue to open wider to the outside world and encourage foreign enterprises to invest in China. (2) In future development, managers of SOEs and large enterprises should create an innovation incentive mechanism. Moreover, they should change their vertical management structure and make full use of their policy advantages and budget advantages to increase innovation activities. In the process of acquiring technology spillovers, enterprises need to solve their own financing constraints.

First, this study solves a technical problem. It is technically difficult to measure the current FDI technical spillover indicators at the micro level. This study innovatively constructs a new FDI technology spillover indicator that combines regional FDI technology spillovers with the microperspective of the geographical proximity of enterprises. This approach not only alleviates certain endogeneity problems in the empirical evidence but also enriches relevant research in the field of technology spillover. In addition, this study focuses on the impact and mechanism of this spillover, which addresses the current research gap among previous studies that mainly focus on innovation quantity and ignore innovation quality.

This study investigates the convergence-of-interest and entrenchment effects on the relationship between managerial ownership and financial distress using evidence from the Chinese stock market. It also analyzes whether the relationship is mediated by research and development (R&D) investment.

Using a dataset consisting of 19,059 firm-year observations of Chinese listed companies in the Shanghai and Shenzhen Stock Exchanges between 2010 and 2020, this study employs both piecewise and curvilinear models.

The results indicate that managerial ownership has a negative association with firm financial distress in both the low (below 12%) and high (above 18%) convergence-of-interest regions of managerial ownership, suggesting that managerial ownership in this region may contribute to improve firm financial status. Meanwhile, managerial ownership has a positive association with firm financial distress in the entrenchment region (12–18%), implying that managerial ownership in the entrenchment region may contribute to impair firm financial status. Furthermore, the results show that R&D investment mediates the association between managerial ownership and financial distress.

This study is the first to provide evidence of a nonlinear relationship between managerial ownership and financial distress, and identify the entrenchment region in the Chinese setting.

This chapter deals with the issue of the role of imitation and innovation in explaining economic growth in the context of the Polish economy, taking the endogenous growth theory and the technology catch-up theory as guidelines. This issue is extremely important as Poland faces the urgent need to reduce productivity gap through investments in R&D and/or the absorption of foreign technologies.

The aim of this chapter is to find the effects of innovation and imitation on economic performance of Poland and shed light on possible outcome differences between these two kinds of activities.

The empirical analysis uses data on innovation, imitation and Gross Domestic Product (GDP) of the Polish economy between 2005 and 2021, collected from a few statistical sources. We apply the autoregressive distributed lag (ARDL) model to find the impact of innovation and imitation on economic growth.

The results suggest that R&D investments positively affect economic performance of the Polish economy, whereas the impact of imitation activities on GDP appears to be insignificant.

The European Union’s Digital Markets Act (DMA) calls for far-reaching changes to the way economic activity will occur in EU digital markets. Before its remedies are imposed, it is critical to assess their impacts on individual markets, the digital sector, and the overall European economy. The European Commission (EC) released an Impact Assessment in support of the DMA that purports to evaluate it using cost/benefit analysis.

An economic evaluation of the DMA should consider its full impacts on dynamic competition. The Impact Assessment neither assesses the DMA's impact on dynamic competition in the digital economy nor evaluates the impacts of specific DMA prohibitions and obligations. Instead, it considers benefits in general and largely ignores costs. We study its benefit assessments and find they are based on highly inappropriate methodologies and assumptions. A cost/benefit study using inappropriate methodologies and largely ignoring costs cannot provide a sound policy assessment.

Instead of promoting dynamic competition between platforms, the DMA will likely reinforce existing market structures, ossify market boundaries, and stunt European innovation. The DMA is likely to chill R&D by encouraging free riding on the investments of others, which discourages making those investments. Avoiding harm to innovation is critical because innovation delivers large, positive spillover benefits, driving increases in productivity, employment, wages, and prosperity.

The DMA prioritizes static over dynamic competition, with the potential to harm the European economy. Given this, the Impact Assessment does not demonstrate that the DMA will be beneficial overall, and its implementation must be carefully tailored to alleviate or lessen its potential to harm Europe’s economic performance.

The purpose of this paper is to study the impact of government supervision and market environment on farmers' pesticide application behavior, as well as the intermediary effect of farmers' literacy, and investigate the substitution effect between government supervision and market environment.

In this paper, logit and Poisson regression models were used to investigate the comprehensive impact of government supervision and market environment on farmers' pesticide application behavior, and the intermediary effect model is used to examine the intermediary effect of farmers' literacy.

Government supervision is an important constraint for the formation of individual behavior paradigm, but it has both positive and negative effects, depending on different instruments. The market subject constraint and market incentive are two important ways that the market environment affects Chinese farmers' pesticide application behavior. Farmers' literacy plays a partial mediating role in the influencing mechanism of government and market factors. The government supervision and market environment, two different constraint forces, have substitution effects in the process of regulating farmers' pesticide application behavior.

In the influence mechanism, farmers' literacy, such as values, responsibilities and skill requirement related to scientific pesticide use, was included into the analysis framework as intermediary variables. The authors found that government supervision and market environment not only directly affect farmers' pesticide application behavior but also indirectly affect farmers' pesticide application behavior through farmers' literacy.