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This paper aims to control the deformation of a thin wall CrZrCu cylinder components (wall thickness 5 mm, diameter 400 mm) during thermal spray alumina-titania (AT13) coating by adjusting the spray parameters without deteriorating its quality evidently.

The deformation was controlled by lowering the temperature of the component in the way of adjusting the spray parameters. The main parameters adjust included extending the spraying distance, from normally 120 mm to 140 mm, decreasing plasma power from 50to 42 kW. An alumina-titanium (AT13) ceramic coating was chosen for protecting the substrate from corrosion. Microscopic morphology and phase analysis, insulation resistance testing, neutral salt test and electrochemical method were used to analyze the anti-corrosion and insulation performances of the coating.

The results indicate that, after adjusting the spraying parameters, the coating has a relatively high porosity, with an average value of 8.96 ± 0.77%. The bonding strength of the coating is relatively low, with an average value of 17.69 ± 0.85 MPa. However, after sealing, the polarization resistance of the coating in seawater can be maintained above 6.25 × 10⁶ Ω.cm² for an extended period. The coating has a high resistance (=1.1 M Ω), and there is no apparent galvanic corrosion when contacted with TC4 alloy. Additionally, analysis of corrosion products on the sample surface reveals that the samples with sprayed alumina-titanium ceramic show no copper corrosion products on the surface, and the coating remains intact, effectively isolating the corrosive medium.

By adjusting the spraying parameters, the deformation of the cylinder thin-walled component can be effectively controlled, making the φ 400 × 392 mm (thickness 5 mm) CrZrCu cylinder com-ponent with a maximum diameter deformation of only 0.14 mm. The satisfactory corrosion performances can be achieved under adjusting spraying parameters, which can guarantee the application of ceramic coating for weapon launching system of naval ships.

This study aims to examine how fairness concerns and power structure in dyadic green supply chains impact retail price, supply chain profits and greening level decisions.

This study develops game-theoretic models considering fairness concerns and asymmetric power structures under an iso-elastic demand setting. The research paper employs the Stackelberg game approach, taking into consideration the fairness concern of the channel leader.

The findings indicate that under fairness, there is an increase in both wholesale and retail prices, as well as greening expenditures. Notably, when comparing the two models (manufacturer Stackelberg and retailer Stackelberg), double marginalization is more pronounced in the retailer Stackelberg setup than in the manufacturer Stackelberg setup. In a traditional supply chain with iso-elastic demand, the follower typically extracts higher profit compared to the leader; however, our results show that, under fairness conditions, the leader achieves higher profit than the follower. Additionally, our study suggests that supply chain coordination is unattainable in a fairness setup. This paper provides insights for managers on the optimal supply chain structure and the level of fairness to maximize profit.

This paper investigates the impact of a leader's fairness on the optimal decisions within a green supply chain, an area that has received limited attention previously. Additionally, the study investigates how fairness concerns manifest in distinct power dynamics, specifically, in the contexts of manufacturer Stackelberg and retailer Stackelberg.

Existing research on innovation has mainly focused on how to promote technological innovation in megaprojects and management innovation (MI) in megaprojects is still an unknown research field. The purposes of this study are to examine the effect of MI on megaproject performance and how the top management team (TMT) regulatory focus affects the use of MI in projects. At the same time, the moderating effects of project uncertainties are also tested.

On the basis of an explorative/exploitative ambidextrous analysis framework, this study divides MI into two dimensions: explorative and exploitative MI, and integrates the theoretical perspectives of the TMT regulatory focus and project uncertainties into a research model. Taking 314 responses from megaprojects’ TMTs in China as research data, this study empirically tests the above model.

Results show that exploratory MI has a U-shaped relationship with megaproject performance; whereas exploitative MI has an inverted U-shaped relationship with megaproject performance. The TMT promotion focus has a positive effect on exploratory and exploitative MI; and the TMT prevention focus has a negative effect on exploratory MI but has a positive effect on exploitative MI. Project uncertainties have a positive moderating effect on the positive relationship between TMT promotion focus and exploratory MI, whereas it has a negative moderating effect on the negative relationship between the TMT prevention focus and exploratory MI.

By empirically measuring the relationship between two types of MIs and megaproject performance, this study clarifies the differential mechanism of the effect of different MIs on megaproject performance. This study also examines the MI of megaprojects from the perspective of the TMT regulatory focus and expounds how changes in uncertainties affect the relationship between the TMT regulatory focus and MI.

We analyzed the effects of different combinations of organic soil amendments (OSAs) and chemical fertilizers on agrifood production, focusing on banana yields in China, the second-largest producer of bananas globally.

We computed these combinations by dividing the expenditures on OSAs by those on chemical fertilizers and called them OSA-CF ratios. First, we classified farmers based on quintiles of expenditures on chemical fertilizers. Then, we studied the association between OSA-CF ratios and banana yields for each quintile. We also considered an alternate specification in which farmers were grouped along the OSA-CF ratio continuum. The first group comprised farmers not using OSAs. Their OSA-CF ratio was zero. Farmers applying low, medium, and high OSA-CF ratios constituted groups two, three, and four; the groups were delineated based on the OSA-CF ratio tertiles, and the associations between tertiles of OSA-CF ratios and banana yields for each quintile were analyzed. The data used in this study were collected by surveying 616 households in three major banana-producing provinces (Guangdong, Hainan, and Yunnan) of China. Standard linear regressions and the two-stage predictor substitution method were employed to complete the analysis.

There were variations in the effects of OSA-CF ratios on banana yields obtained by farmers iifferent quintiles. For the first and second quintiles, low, medium, and high OSA-CF ratios improved banana yields relative to not using OSAs. For farmers in the first quintile using only chemical fertilizers, applying a low OSA-CF ratio was associated with an improvement of 792 kg/mu in banana yields. For their counterparts in the second quintile, the same transition was associated with a gain of 534 kg/mu. For the fifth quintile, comprising farmers spending 320 yuan/mu or more on chemical fertilizers, applying a high OSA-CF ratio instead of using only chemical fertilizers was associated with a 401 kg/mu decline in banana yields. Even so, for this group, no differences were observed between the yields of farmers not applying OSAs and those using low and medium OSA-CF ratios.

Banana farmers in southern China, using only chemical fertilizers, can improve yields by combining them with OSAs if their chemical fertilizer expenditures are less than 66.67 yuan/mu. Those using only chemical fertilizers and spending between 68 yuan/mu and 300 yuan/mu on them can maintain yields by applying OSAs in conjunction with chemical fertilizers. However, yields may decline for farmers using only chemical fertilizers and spending 320 yuan/mu or more on them if they incorporate OSAs such that the OSA-CF ratio reaches 0.78 or higher. Overall, combining OSAs with chemical fertilizers can improve yields while attenuating the adverse effects of chemical fertilizers on the environment. Policymakers should inform farmers of these benefits and accelerate the transition to sustainable agriculture through educational and awareness programs.

Farmers apply OSAs such as organic fertilizers and farmyard manure to adjust and remedy soil nutrition to improve farm productivity. However, little is known about how combining OSAs with chemical fertilizers affects banana yields. This study provided the first attempt to explore the associations between OSA-CF ratios and banana yields using cross-sectional data on farming households.

A public–private partnership (PPP) is an agreement between the government and private investors to deliver long-term public services. The efficiency of PPP projects depends on PPP contracts stipulating contractual parties' corresponding responsibilities and rights to deal with relational and performance risks. Although more complex contracts provide more remedies for mitigating ex-post transaction costs, they also result in the increased ex ante transaction costs associated with contract writing. Thus, contractual complexity is a design choice that can reduce the overall contract transaction costs.

Using 365 transportation PPP projects in China from 2010 to 2019, this study applies the Poisson regression model to examine the effects of payment mechanisms, ownership by investors and equity structure on contractual complexity.

PPP contracts have control and coordination functions with unique determinants. Parties in the government-pay mechanism are more likely to negotiate coordination provisions, which results in greater contractual complexity. PPP projects with state-owned enterprises (SOEs) have less contractual complexity in terms of both two functions of provisions, whereas the equity structure has no impact on contractual complexity.

These findings provide a nuanced understanding of how various contractual provisions are combined to perform control or coordination functions and make managerial recommendations to parties involved in PPP projects.

The paper covers mega infrastructure construction supply chain (MICSC) in Engineering-Procurement-Construction (EPC) projects, where the frequent occurrence of risk incidents has greatly affected human life. The research aims to establish a risk evaluation index system for MICSC in EPC projects, exploring what risk factors lead to risk incidents and measure the importance and causality of all these risk factors.

The research applies a combination of quantitative and qualitative analysis methodology to process data sequentially. In the first place, risk factors for MICSC in EPC projects are extracted and identified from literature survey and expert interviews. In the second place, an integration model fuzzy Analytic Hierarchy Process (f-AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (f-DEMATEL) is constructed to comprehensively analyze all these risk factors.

12 primary risk factors and 36 secondary risk factors comprise the risk evaluation index system for MICSC in EPC projects from 178 literature and 5 professionals. The results indicate that Political Situation (F1), Social Security (F2) and Management Mode (F8) are critical risk factors, where F1 and F2 are cause factors and F8 is an effect factor.

There are three main contributions of this paper. First and foremost, from the perspective of the research content, no other study has been able to assess risk factors for MICSC in EPC projects, while embedding nine phases of the whole project life cycle and six subjects of stakeholders into a risk evaluation index system. Additionally, from the perspective of research method, a combined model incorporating f-AHP and f-DEMATEL is constructed to avoid the one-sidedness of a single model. Last but not least, from the perspective of practical significance, focusing on the critical risk factors, a series of effective measures are formulated to make appropriate management decisions for nodal enterprises of MICSC, which can improve their risk management capabilities.

The manufacturing industry has recently faced many environmental issues and pressures due to increased environmental awareness. Business leaders identified that green innovation (GI) is a crucial aspect of sustainable development (SD) and can provide a competitive edge. On the other hand, boosting SD through GI is a complicated network activity involving various partners, and there is a need to transmit or share knowledge equitably and acceptably. Following the natural resource-based view (NRBV), this research presents a novel framework for investigating how green knowledge sharing (GKS) and green dynamic capabilities (GDC) affect green creativity (GC) and GI directly and through GC. Besides, the moderation of mimetic pressure (MP) was also evaluated in these targeted relations, as it is a critical element for enhancing GI in the context of SD.

Data consisted 232 respondents from Pakistani manufacturing industries, and seven substantial hypotheses were verified regarding the direct, mediating and moderating effect of targeted variables in confounding ways using partial least squares structural equation modeling (PLS-SEM).

According to the empirical findings, GKS and GDC positively correlate with GC and GI. Moreover, GKS and GDC significantly and positively impact GI both directly and indirectly. Furthermore, GC partially mediates GI, whereas MP has a significant moderating effect in these relationships.

A significant correlation among these constructs was observed, demonstrating the conceptual framework for this study. These findings can assist practitioners and academics gain a better understanding of how to manage and evaluate GI in manufacturing projects at both the project and firm levels. Therefore, policymakers and project managers can enhance GI by focusing more on GKS, GDC, MP and GC.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

The purpose of this study is to explore how government subsidies influence technology innovation in new-energy enterprises in the new era of Industry 4.0. Specifically, this study investigates the mediating effect of digital transformation and the moderating effect of a top management team (TMT) with digital experience.

Using a sample of 225 listed new-energy companies, with annual information, patent data, and financial data for the years 2010–2020, this study employs panel fixed effect regression models to obtain the results.

This study finds strong evidence that government subsidies promote the technology innovation of new-energy enterprises, and digital transformation partially mediates the effect of government subsidies on technology innovation. In addition, a TMT's digital experience moderates the effect of government subsidies on digital transformation, but has no significant moderating effect on the relationship between digital transformation and technology innovation. Further analysis shows that subsidies make a sustained contribution to both digital transformation and technological innovation over the next two years. The digital subsidies have a stronger role in promoting digital transformation and further technological innovation through digital transformation.

The Chinese government needs to continue to intermittently increase subsidies for new-energy enterprises, and focus on guiding enterprises' digital transformation. Chinese new-energy enterprises should pay attention to the importance of having TMTs with digital experience, make full use of government subsidies, actively implement digital transformation, and improve their innovation levels.

A new conceptual framework is proposed to examine the relationships between government subsidies, digital transformation, a TMT's digital experience, and technology innovation. This paper provides an important theoretical basis and practical reference for improving the technology innovation ability of Chinese new-energy enterprises, and the high-quality development of renewable energy in the context of Industry 4.0.

This study investigates the causal relationship and mechanisms between the development of digital finance and household carbon emissions. Its objective is to explore how digital finance can influence the carbon footprint at the household level, aiming to contribute to the broader understanding of financial innovations' environmental impacts.

The research combines macro and micro data, employing input-output analysis to utilize data from the China Household Finance Survey (CHFS) for the years 2013, 2015, 2017, and 2019, national input-output tables, and Energy Statistical Yearbooks. This approach calculated CO2 emissions at the household level, including the growth rate of household carbon emissions and per capita emissions. It further integrates the Peking University Digital Financial Inclusion Index of China (PKU-DFIIC) for 2012–2018 and corresponding urban economic data, resulting in panel data for 7,191 households across 151 cities over four years. A fixed effects model was employed to examine the impact of digital finance development on household carbon emissions.

The findings reveal that digital finance significantly lowers household carbon emissions. Further investigation shows that digital transformation, consumption structure upgrades, and improved household financial literacy enhance the restraining effect of digital finance on carbon emissions. Heterogeneity analysis indicates that this mitigating effect is more pronounced in households during the nurturing phase, those using convenient payment methods, small-scale, and urban households. Sub-index tests suggest that the broadening coverage and deepening usage of digital finance primarily drive its impact on reducing household carbon emissions.

The paper recommends that China should continue to strengthen the layout of digital infrastructure, leverage the advantages of digital finance, promote digital financial education, and facilitate household-level carbon emission management to support the achievement of China's dual carbon goals.

The originality of this paper lies in its detailed examination of the carbon reduction effects of digital finance at the micro (household) level. Unlike previous studies on carbon emissions that focused on absolute emissions, this research investigates the marginal impact of digital finance on relative increases in emissions. This method provides a robust assessment of the net effects of digital finance and offers a novel perspective for examining household carbon reduction measures. The study underscores the importance of considering heterogeneity when formulating targeted policies for households with different characteristics.