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As a measure against plastic waste, Coca-Cola and Evian have begun introducing label-free plastic bottles. Food labels have long been recognized as an important marketing tool, but there is a lack of research on label-free products. To address this gap, this study examined the influence of label-free design on product attractiveness in the Japanese green tea market.

If existing products are used in an experiment, respondents would be subject to brand image bias. Hence, by mechanically combining the main design elements (cap shape, bottle style, decoration line, logo and label) with an orthogonal array, the conditions for bottles with and without labels are completely aligned. The authors conducted an online survey and applied the chi-square test to the attractiveness of 18 designs presented in random order.

Label-free designs were more attractive to consumers than labeled designs. The effect was higher among female, middle-aged and older adults; those with higher annual income and low-frequency purchasers.

Practitioners should adopt a label-free design that can satisfy both environmental considerations and customer value. It would be a formidable challenge to change the longstanding emphasis placed on label design, but this study demonstrates the value of doing so.

This is the first study in the package design literature on the advantages of label-free plastic bottles. The authors also applied an orthogonal array used for many years to optimize objective numerical values in marketing research.

Stainless-steel electromagnetic shielding (EMS) fabrics are widely applied as protective materials against electromagnetic interference (EMI). However, these fabrics primarily shield electromagnetic waves through reflection, which can lead to the formation of resonance effects that severely compromise their protective capabilities and potentially cause secondary electromagnetic pollution in the external environment.

In this paper, carbon nanotube fibers are added via spacing method to replace some stainless-steel fibers to impart absorbing properties to stainless-steel EMS fabric. The shielding effectiveness (SE) of the EMS fabrics across various polarization directions is analyzed. Additionally, a spacing arrangement for the carbon nanotube fibers is designed. The EMS fabric with carbon nanotube fibers is manufactured using a semi-automatic sample loom, and its SE is tested using a small window method test box in both vertical and horizontal polarization directions.

According to the experimental data and electromagnetic theory analysis, it is determined that when the spacing between the carbon nanotube fibers is less than a specific distance, the SE of the stainless-steel EMS fabric significantly improves. The fabric exhibits stable absorbing properties within the tested frequency range, effectively addressing the issue of secondary damage that arises from relying solely on reflective shielding. Conversely, as the spacing between the carbon nanotube fibers exceeds this distance, the SE diminishes. Notably, the SE in the vertical polarization direction is substantially higher than that in the horizontal polarization direction at the same frequency.

This study provides a new path for the development of high-performance EMS fabrics with good wave-absorption characteristics and SE.

Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data requirements, they are cost-prohibitive and underperforming for application scenarios with limited data. Therefore, it is essential to develop an advanced model with good applicability to small-sample problems for multiaxial fatigue life assessment.

Drawing inspiration from the modeling strategy of empirical multiaxial fatigue models, a modular neural network-based model is proposed with assembly of three sub-networks in series: the first two sub-networks undergo pretraining using uniaxial fatigue data and are then connected to a third sub-network trained on a few multiaxial fatigue data. Moreover, general material properties and necessary loading parameters are used as inputs in place of explicit damage parameters, ensuring the universality of the proposed model.

Based on extensive experimental evaluations, it is demonstrated that the proposed model outperforms empirical models and conventional data-driven models in terms of prediction accuracy and data demand. It also holds good transferability across various multiaxial loading cases.

The proposed model explores a new avenue to incorporate uniaxial fatigue data into the data-driven modeling of multiaxial fatigue life, which can reduce the data requirement under the promise of maintaining good prediction accuracy.

Smart community construction (SCC) and efficiency require resident participation. This paper aims to explore the determinants of residents’ participation intention (RPI) in the SCC.

Based on the theory of planned behavior (TPB), this study proposed an extended conceptual model to deeply analyze the RPI in the SCC. The relationship between all constructs was verified by processing and analyzing online survey data using confirmatory factor analysis (CFA), structural equation model (SEM), and bootstrapping method.

Participation attitude, perceived behavioral control, subjective norm, and perceived usefulness significantly and positively affected the RPI. Furthermore, intermediary effects in the extended conceptual model had been confirmed.

To fill the critical gap in the research on the determinants of the RPI in the SCC context, this study developed a novel conceptual model by extending the TPB to analyze the effects of self-driven and externally-driven factors on the RPI from the perspectives of residents’ psychology and external environment. The findings not only clarify the complex process of forming the RPI in the SCC but also provide a theoretical foundation for studying the RPI in similar community construction projects. Additionally, several strategies have been proposed to encourage residents’ participation in the SCC and promote the development of smart communities, such as clarifying residents’ participation obligations, improving the convenience services of smart communities, and diversifying residents’ participation approaches.

The purpose of the study is to investigate and analyze the dynamics of the government-enterprise grain joint storage mechanism, particularly, focusing on profit-driven speculative behaviors exhibited by enterprises within this context. The study aims to understand the various factors influencing the behavior of stakeholders involved in grain storage, including government storage departments, agent storage enterprises and quality inspection agencies.

The study employs a tripartite evolutionary game model to investigate profit-driven behaviors in government-enterprise grain joint storage. It analyzes strategies of government departments, storage enterprises and quality inspection agencies, considering factors like supervision costs and speculative risks. Simulation analysis examines tripartite payoffs, initial probabilities and the impact of digital governance levels to enhance emergency grain storage effectiveness.

The study finds that leveraging digital governance tools in government-enterprise grain joint storage mechanisms can mitigate risks, enhance efficiency and ensure the security of grain storage. It highlights the significant impact of supervision costs, speculative risks and digital supervision levels on stakeholder strategies, offering guidance to improve the effectiveness of emergency grain storage systems.

The originality of this study lies in its integration of digital governance tools into the analysis of the government-enterprise grain joint storage mechanism, addressing profit-driven speculative behaviors. Through a tripartite evolutionary game model, it explores stakeholder strategies, emphasizing the impact of digital supervision levels on outcomes and offering insights crucial for enhancing emergency grain storage effectiveness.

This study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in achieving sustainability.

This study uses a quasinatural experiment design to combine difference-in-difference and propensity score matching methods for analysis. It examines 799 polluting and 1,130 nonpolluting firms from 2013 to 2020, enabling a comprehensive assessment of the GFS framework’s influence.

This study affirms a statistically significant positive influence of the GFS framework on escalating green investment levels in polluting firms. Robust sensitivity analyses, encompassing parallel trend assessment, entropy balancing test, and alternative proxies, corroborate these findings. A mediation analysis identifies the implementation of an environmental management system as the potential underlying mechanism. A cross-sectional analysis identifies high financial slack, high profitability, mandatory CSR regulations, and marketization level as the influencing factors.

The study’s findings have critical implications for policymakers, regulators, and companies. Demonstrating the effectiveness of the GFS framework in driving green investment underscores the importance of aligning financial systems with sustainability goals.

This study contributes novel empirical evidence on the positive effect of China’s GFS framework on corporate green development. The quasinatural experiment design, coupled with comprehensive sensitivity analyses, strengthens the robustness of the findings.

Highway traffic systems are complex and variable, and studying the bifurcation characteristics of traffic flow systems and designing control schemes for unstable bifurcation points can alleviate traffic congestion from a new perspective. Bifurcation analysis is used to explain the changes in system stability, identify the unstable bifurcation points of the system, and design feedback controllers to realize the control of the unstable bifurcation points of the traffic system. It helps to control the sudden changes in the stable behavior of the traffic system and helps to alleviate traffic congestion, which is of great practical significance.

In this paper, we improve the macroscopic traffic flow model by integrating severe weather factors such as rainfall, snowfall, and dust. We use traveling wave transform to convert it into a traffic flow stability model suitable for branching analysis, thus converting the traffic flow problem into a system stability analysis problem. First, this paper derives the existence conditions of the model Hopf bifurcation and saddle-node bifurcation for the improved macroscopic model, and finds the stability mutation point of the system. Secondly, the connection between the stability mutation points and bifurcation points of the traffic system is analyzed. Finally, for the unstable bifurcation point, a nonlinear system feedback controller is designed using Chebyshev polynomial approximation and stochastic feedback control method.

The Hopf bifurcation is delayed and completely eliminated without changing the equilibrium point of the system, thus controlling the abrupt behavior of the traffic system.

Currently there are fewer studies to explain the changes in the stability of the transportation system through bifurcation analysis, in this paper; we design a feedback controller for the unstable bifurcation point of the system to realize the control of the transportation system. It is a new research method that helps to control the sudden change of the stable behavior of the traffic system and helps to alleviate traffic congestion, which is of great practical significance.

The purpose of this study is to use the grounded theory to summarize the types of celebrity persona and to construct a theoretical model for celebrity persona on consumer purchase intention. Based on the study results, it provides better suggestions for merchants and live streamers and is an expansion of previous research on live-streaming e-commerce.

The grounded theory is recognized as the most scientific qualitative research method and is the ideal explorative method for generating theory. First, the participants were interviewed, and interview data were collected. Then the interview data were organized and analyzed. Finally, this paper summarizes the types of celebrity persona and constructes a theoretical model framework of celebrity persona on consumers' purchase intention.

The results show that the celebrity live streamer persona can be divided into two types: personalized persona and professional persona. Through emotional attachment, the celebrity's persona affects the consumer's purchase intentions. As well as, product type plays a moderating role between celebrity persona and consumer purchase intentions.

The contribution of this research is to start from the celebrity persona, link the celebrity persona with the consumer purchase intentions and expand the research scope of the celebrity persona. It opens the “black box” of the heterogeneity of celebrity live streamers' characteristics on consumer purchase intentions.

This study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this study argues that the aforementioned interaction negatively affects firm digitization. The moderating role of managerial discretion is also discussed in light of the principles of the awareness-motivation-capability (AMC) framework.

The proposed hypotheses are empirically tested using a negative binomial modeling approach. The data used are from A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2006 to 2020.

This study suggests that the interaction of independent innovation and cooperative innovation negatively impacts digitization. In addition, this study argues that environmental discretion and organizational discretion weaken the negative impact of the mentioned interaction on digitization. However, additional discretion in the Chinese context has no effect on above relationships.

This study explores the impact of the interaction of independent and cooperative innovation on digitization and incorporates managerial discretion into this framework based on the AMC framework.