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With the continuous improvement of public–private partnership (PPP) projects, the participants' value creation goals are not only limited to achieving the basic performance objectives but also to realising value added. However, the effect of traditional contract management on realising the value creation objectives of PPP projects is limited. According to the view of multifunctional contract, joint-contract functions that integrate contract control and flexibility are likely to be effective in enhancing the value creation of PPP projects. This study aims to explore the effects of joint-contract functions on PPP project value creation and relevant influencing mechanism by investigating the mediating effect of in-role behaviour and extra-role behaviour.

After collecting 258 valid questionnaires from PPP professionals in China, this study used structural equation modelling to validate the hypotheses.

Contract control and flexibility can improve PPP project value creation. Specifically, contract control improves the achievement of the basic contract objectives of PPP projects, whereas contract flexibility enhances the achievement of the value-added of PPP projects. Moreover, only in-role behaviour mediates the effect of contract control on value creation. In addition, the mediating effect of extra-role behaviour on the impact of contract flexibility on value creation is stronger than that of in-role behaviour. The mediating effect of in- and extra-role behaviour is mainly reflected in the realisation of basic and value-added performance, respectively.

The findings of this study can help realise value creation in three ways. Firstly, new perspectives for PPP project value creation should be proposed by combining the improvement of contract objectives and the realisation of the participants' implicit demands. Secondly, the effects of different contract functions on value creation should be analysed instead of a single dimension of contractual governance. Thirdly, the mediating effects of different types of cooperation behaviour that may influence the relationship between contractual governance and value creation should be evaluated.

This study verifies the impacts of different contract functions on PPP project value creation. In addition, cooperative behaviour is embedded as a mediating variable, and the mediated transmission path from contract function to cooperative behaviour and further to PPP project value creation is systematically analysed.

This paper aims to conduct work to obtain high-quality brazed joint of YAG ceramic and kovar alloy.

Wetting and spreading behavior of AgCuTi filler alloy on YAG ceramic and kovar alloy under vacuum (2∼3 × 10–4 Pa) and argon conditions was investigated and compared. Then, YAG ceramic was brazed to kovar alloy under a high vacuum of 2∼3 × 10–4 Pa; the influence of holding time on the interface structure of the joint was investigated.

The wettability of AgCuTi on YAG is poor in the argon atmosphere, the high oxygen content in the reaction layer hinders the formation of the TiY2O5 reaction layer, thereby impeding the wetting of AgCuTi on YAG; in the vacuum, a contact angle (?=16.6°) is obtained by wetting AgCuTi filler alloy on the YAG substrate; the microstructure of the YAG/AgCuTi/kovar brazed joint is characterized to be YAG/Y2O3/(Fe, Ni)Ti/Ag(s, s) + Cu(s, s)/Fe2Ti + Ni3Ti/Fe2Ti/kovar; at 870 °C for the holding time of 10 min, a (Fe, Ni) Ti layer of approximately 1.8 µm is formed on the YAG side.

Wetting and spreading behavior of the brazing filler alloy under different conditions and the influence of the holding time on the interface microstructure of the joint were studied to provide references for obtaining high-quality brazed joints.

The commercial sharing service (CSS) represents an emerging business model in which users pay a minor fee to rent a product for a short period of time. Fashion CSSs enable individuals to rent various garments and accessories with the goal of enhancing one’s public image while saving money. Marketers have strived to popularize fashion CSSs, but concerns related to contamination have thwarted their efforts. Based on face consciousness theory, this research examines how consumers’ desire to enhance their public image (i.e. to “gain face”) can attenuate the negative impacts of contamination concerns and thus facilitate fashion CSS usage.

Two scenario-based studies were conducted to collect data. Participants were recruited via online survey platforms in mainland China. The hypotheses were tested by partial least squares (PLS) path modeling and linear regression analysis.

The analysis results revealed a two-stage mediation model. Contamination concerns were found to inhibit consumers’ participation in fashion-sharing by increasing their perceived risk, which further decreased the perceived value of the CSS. However, consumers’ desire to gain face can mitigate the negative (direct and indirect) effects of contamination concerns on CSS usage, facilitating CSS adoption.

Our findings suggest that eliciting consumers’ desire to gain face can promote fashion CSS usage and attenuate the negative impacts of contamination concerns. Moreover, consumers are less risk-averse and less concerned about shared pieces being contaminated when they seek to enhance their face through fashion products. Practical implications for fashion marketers are discussed.

This study provides a bibliometric analysis of business literature on the interlinks of fintech, climate risks, and sustainable finance. Fintech growth promotes national environmental efficiency and green finance by decreasing carbon intensity toward the net-zero target. National fintech growth moderates the impact of environmental, social, and governance investment on bank efficiency. Fintech mitigates the loan bankruptcy risk imposed by climate risks with strict mortgage lending decisions due to climate concerns. Fintech applications in banking systems optimize financing costs and increase the accessibility of money for firms, decreasing corporate greenwashing behaviors and promoting green innovation. The existing literature leaves room for future studies on fintech to promote climate finance with important policies for climate action toward Sustainable Development Goals.

To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.

The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.

Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.

The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.

The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.

We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

This study aims to introduce a method for predicting the remaining useful life (RUL) of bearings based on parallel feature extraction. The proposed model provides prior knowledge and removes redundant handcrafted feature information, additionally, which focuses on the important features at different time scales.

Distinct from traditional parallel feature extraction methods, which can lead to information redundancy, a one-dimensional convolutional autoencoder is introduced to process selected indicators to remove redundancy and retain useful feature information. To fully capture the important degradation information within different stages in the feature sequences, a novel multi-scale attention feature fusion module is proposed to extract degradation features at different time scales. Considering the impact of degradation modes on RUL prediction, a dual-task prediction module based on no degradation mode labels is designed to obtain accurate RUL.

Comparative experiments and ablation studies on the PHM2012 bearing dataset verified the effectiveness of the proposed method. Furthermore, the rationality of the selected parameters is confirmed through model parameter analysis.

The novelty of the proposed method is that it not only provides prior knowledge but also further removes redundant information from prior knowledge. In addition, the distribution differences between the original features and their multi-scale convolution results are measured through Kullback–Leibler divergence as the attention scores, which allows the proposed method to focus on important information at different time scales.

This research focuses on analyzing the impact of Green Supply Chain Management (GSCM) on the Sustainable Performance (SP) of Spanish wineries, as well as the mediating effect of Green Ambidexterity Innovation (GAI) and the moderating role of Top Management Environmental Awareness (TMEA) on the main relationship posited (GSCM-SP). In addition, age, size and membership in a Protected Designation of Origin (PDO) were used to increase the precision of the cause-effect relationships examined.

The study proposes a conceptual model based on previous studies, which is tested using structural equations (PLS-SEM) with data collected from 196 Spanish wineries between September 2022 and January 2023.

The results of the research reveal the existence of a positive and significant relationship between the development of GSCM and SP of Spanish wineries, as well as the partial mediation of GAI and the positive moderation of TMEA in this linkage.

The novelty of this study lies in its exploratory approach, as it ventures into new research territory by examining the mediating effect of GAI and the moderating influence of TMEA on the relationship between GSCM and SP, being, to the authors' knowledge, the first research to investigate these specific dynamics.

A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.

This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.

The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.

Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.

This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.