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Digital-only fashion represents an ideal fusion of sustainability and fashionability, garnering growing interest among fashion professionals. However, there is a noticeable gap in research focusing on digital-only fashion acceptance among consumers. Hence, this study aims to empirically examine consumers’ motivations, evaluations and acceptance of digital-only fashion based on the Functional Theory of Attitudes.

A US-based research agency was hired to collect data, resulting in 247 completed survey responses. Data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach.

Testing results highlight that consumer acceptance of digital-only fashion is directly influenced by both overall attitude and self-expressive attitude. Self-expression is particularly pivotal in digital-only fashion acceptance. Adorning avatars and dressing realistic on-screen bodies are distinct yet complementary aspects of using digital-only fashion. Consumers with positive environmental beliefs about digital-only fashion are concerned about how well digital-only fashion items allow them to express such beliefs.

This study innovatively applied the functional theory of attitudes to the emerging domain of digital-only fashion and identified consumers’ four functional attitudes toward digital-only fashion, along with the underlying motivations served by each functional attitude. Furthermore, this study provides valuable practical insights across the digital-only fashion value chain.

The absence of government intervention and market supervision cannot effectively promote green process innovation in manufacturing industries. As a new government regulation approach, environmental taxes provide a platform to internalize the externality of environmental pollution. This paper empirically investigates the impact of environmental taxes on green process innovation and the moderating effects of industry pollution heterogeneity and green credit.

This research collects manufacturing industry data ranging from 2008 to 2020, resulting in a total of 351 observations. Time-individual, two-way fixed effect models are constructed to examine the hypotheses.

The results indicate environmental taxes have an inverted-U effect on green process innovation in manufacturing industries. Implementation intensity of the current environmental taxes on China's manufacturing industries does not reach an inflection point. Further analysis suggests that environmental taxes exert influence on the inverted-U relationship with low-pollution industries displaying a steeper curvilinear pattern than high-pollution industries. Moreover, the analysis shows that green credit plays a moderating role in the inverted-U relationship, as low green credit provides more limited stimulus than high green credit in terms of the effect of environmental taxes on green process innovation.

This study offers empirical evidence to accommodate negative externalities of corporate production and provides new perspectives in nudging corporate green-process innovation.

This paper verifies the effect of environmental taxes on green process innovation amid industry pollution heterogeneity by introducing an industrial-level analysis unit. This study improves the means by which environmental taxes are measured. Existing literature has narrowly used pollution discharge fees as a proxy for environmental taxes. The authors have summed up the taxes on vehicle and vessels, urban land use, urban maintenance and construction, vehicle purchases, waste gas, wastewater and solid waste to measure the effect of environmental taxes in this study.

Concerns over environmental degradation, alongside the global legalization of hemp cultivation, have prompted applications of hemp-derived textile products. However, research examining consumers’ acceptance of such products is lacking. It is critical to understand how young consumers adopt these products as they prioritize sustainability and lead the future purchasing power. Thus, this study aims to investigate young consumers’ perceptions, attitudes, and purchase intentions regarding hemp fiber textiles and clothing based on the Theory of Consumption Value and the Spiral of Silence Theory.

A US-based research company was hired to recruit survey participants, yielding 314 valid data. Data analysis, including Exploratory Factor Analysis and Partial Least Squares Structural Equation Modeling, was conducted using the R programming language and RStudio software.

Purchase intentions of hemp-based clothing and textiles among young consumers are influenced by attitude, perceived social value and future trend perception. Perceived social value also impacts attitude and future trend perception. High environmental involvement correlates with positive attitudes. Consumers’ subjective knowledge of hemp and objective knowledge regarding hemp fiber impact their perceptions of future trends in such products.

This research represents a seminal consumer study focusing on the resurgence of industrial hemp fiber textiles and clothing. This study empirically validates the significant role of social factors in young consumer acceptance of such products at both personal and societal levels. This study expands current knowledge and provides actionable insights for practitioners.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

This paper aims to report on the China‐North America Library Conference held in Beijing, China. The conference theme is Sharing Digital Resources: Challenges and Opportunities. Six sub‐themes are also intertwined with the conference theme: Resource sharing policies and perspectives; Digital infrastructure and repository technology; Research data sharing; Sharing digital preservation methods; and Shared digital access, retrieval and use.

The paper summarizes several important presentations at the conference.

The shared projects in this report include: National Cultural Information Resource Sharing Project; Multicultural Canada Project; Data Conservancy; National Library Digital Exchange Services; and Digital Museum Platform.

This is an original conference report which would help those who are interested in sharing digital resources on a global scale to understand the challenges, issues, and opportunities on that aspect.

Aqueous zinc-ion battery has broad application prospects in smart grid energy storage, power tools and other fields. Co₃O₄ is one of the ideal cathode materials for water zinc-ion batteries due to their high theoretical capacity, simple synthesis, low cost and environmental friendliness. Many studies were concentrated on the synthesis, design and doping of cathodes, but the effect of process parameters on morphology and performance was rarely reported.

Herein, Co₃O₄ cathode material based on carbon cloth (Co₃O₄/CC) was prepared by different temperatures hydrothermal synthesis method. The temperatures of hydrothermal reaction are 100°C, 120°C, 130°C and 140°C, respectively. The influence of temperatures on the microstructures of the cathodes and electrochemical performance of zinc ion batteries were investigated by X-ray diffraction analysis, scanning electron microscopy, cyclic voltammetry curve, electrochemical charging and discharging behavior and electrochemical impedance spectroscopy test.

The results show that the Co₃O₄/CC material synthesized at 120°C has good performance. Co₃O₄/CC nanowire has a uniform distribution, regular surface and small size on carbon cloth. The zinc-ion battery has excellent rate performance and low reaction resistance. In the voltage range of 0.01–2.2 V, when the current density is 1 A/g, the specific capacity of the battery is 108.2 mAh/g for the first discharge and the specific capacity of the battery is 142.6 mAh/g after 60 charge and discharge cycles.

The study aims to investigate the effect of process parameters on the performance of zinc-ion batteries systematically and optimized applicable reaction temperature.

The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

This study aims to investigate the effect of coatings prepared by the addition of copper-aluminum alloy powder on the corrosion behavior of 90/10 copper-nickel alloy.

Coatings of copper-aluminum alloy powder at different contents (Wt.% = 50%, 60%, 70% and 80%) were prepared by the high-temperature heat treatment process. The microstructure and component of the coatings were characterized by scanning electron microscope, X-ray diffraction, energy dispersive spectrometer and X-ray photoelectron spectroscopy. The electrochemical properties of the coating were explored by electrochemical impedance spectroscopy.

The results show that the aluminized layer was successfully constructed on the surface of 90/10 copper-nickel alloy, the composition of the coating was composed of copper-aluminum phase and aluminum-nickel phase, the existence of the aluminum-nickel phase was formed by the diffusion of Ni elements within the substrate and because of the diffusion, the Al-Ni phase was distributed in the middle and bottom of the coating more. The Al-Ni phase is considered to be the enhanced phase for corrosion resistance. When the copper-aluminum alloy powder content is 70 Wt.%, the corrosion resistance is the best.

The enhancement of corrosion resistance of 90/10 copper-nickel alloy by the copper-aluminum alloy powder was revealed, the composition of the aluminized layer and the mechanism of corrosion resistance were discussed.

This study aims to investigate the effect of changes in iron content in 70/30 copper–nickel alloy on the corrosion process.

70Copper–30Nickel-xFe-1Mn (x = 0.4,0.6,0.8,1.0 Wt.%) alloy were prepared by the high frequency induction melting furnace. The scanning electron microscope, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy were used to analyze the morphology and component of the corrosion product film.

The results show that the corrosion resistance of 70/30 copper–nickel alloy added with 1.0%Fe is the best, and the film is divided into inner dense Cu2O composite film and outer hydration loose layer; XRD showed that after adding 1.0% Fe, the content of Cu2(OH)3Cl in the corrosion product film was significantly reduced, while the content of Cu2O remained unchanged; XPS showed that nickel accumulates in the inner layer of corrosion product film; the stage growth mode of the film, the role of nickel in it and the enrichment mechanism of iron in the inner film were summarized and discussed.

The changes in the composition and structure of the corrosion product film caused by the iron content are revealed, and the mechanism of the difference in corrosion resistance is discussed.

This paper aims to study the impact of individual relationships on tacit knowledge sharing in the company setting of compulsory bond, expressive bond, instrumental bond and self-monitoring by empirical explorations.

The paper raises seven hypotheses that focus on the impact of employees’ relationship with tacit knowledge sharing in knowledge-intensive industries and positions based on relationship theory. Before distributing the formal questionnaires, a pre-research was done in a college by collecting comments and suggestions so as to correct and modify the questionnaires. A four-page questionnaire based on the Likert scale with 45 questions was used for data collection, and 210 valid questionnaires were collected from a research institute, a software company and an educational institute. Finally, SPSS17.0 was used to analyze these data, including reliability analysis, validity analysis, correlation analysis and regression analysis, etc.

The findings include: there is a positive correlation between employees’ compulsory bond and the efficiency of tacit knowledge sharing; there is a positive correlation between employees’ expressive bond and the efficiency of tacit knowledge sharing; there is a negative correlation between employees’ instrumental bond and the efficiency of tacit knowledge sharing; the more apt employees are at self-monitoring, the more effectively they will share tacit knowledge; the interaction between compulsory bonds and self-monitoring has a positive and stimulating impact on tacit knowledge sharing; the interaction between expressive bonds and self-monitoring has a positive and stimulating impact on tacit knowledge sharing; and the interaction between instrumental bonds and self-monitoring has a certain impact on tacit knowledge sharing.

However, the efficiency of tacit knowledge sharing cannot be measured easily and how to share the tacit knowledge based on employees’ relationships should be further concerned by knowledge industries.

This paper illustrates multiple, in-depth approaches to research on knowledge sharing. It shows why it is important to pay attention to employees’ relationships during the process of tacit knowledge sharing. The author argued some key factors such as compulsory bond, emotional bond and self-monitoring that may have a certain impact on the tacit knowledge sharing. The paper also further discussed the influence on the sharing of tacit knowledge as for the interaction between different relationship types and self-monitoring.

The knowledge is critical to enhance enterprises’ performance, and it will become more useful when the new knowledge is shared with others. However, tacit knowledge cannot be measured easily, and how to share the tacit knowledge based on employees’ relationships should be further concerned by knowledge industries. A series of findings are proposed in this paper.

Integrating the knowledge of different individuals, of which 90 per cent is tacit knowledge, in an organization that engages in producing products and providing service is instrumental to the sustainability and productivity of that organization. This study addressed the factors and dynamics of tacit knowledge sharing that can be used in knowledge management to effectively capture, store and disseminate tacit knowledge across an organization.