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An increasing number of fashion firms face criticism for “greenwashing” due to the industry’s longstanding negative environmental and social impacts. This experimental study, in the fashion industry context, evaluated consumers’ perceptions of hypocrisy, demonstrated by false labeling, vague information and downsizing negative environmental impacts in corporate social responsibility initiatives. This study also investigated how these perceptions influence consumers’ evaluations of the firm’s moral inequity and their likelihood of engaging in complaint behaviors.

An online survey company recruited Chinese consumers to participate in a between-subjects experimental study. Three types of news articles were developed – false labeling, vague information and downsizing of negative aspects – reporting on a fictitious fashion firm’s greenwashing practices. Participants were randomly assigned to one of the stimuli and completed a corresponding survey.

Analysis of the 210 collected responses revealed that false labeling had the highest level of corporate hypocrisy perceptions, whereas the downsizing of negative aspects resulted in the lowest level. Moreover, perceived hypocrisy increased moral inequity, which subsequently influenced consumer complaint behaviors. Specifically, when consumers’ expectations toward a firm’s morality were violated – whether through false labeling, vague claims or selective omission – they felt deceived, leading to perceptions of moral hypocrisy. Upon detecting hypocritical behavior in corporate greenwashing, consumers felt moral inequity and took various complaint actions.

This study’s findings provide valuable insights into greenwashing within the fashion industry, addressing industry-specific issues. Academically, this study suggests new classifications of customer complaint behaviors by relating the current circumstances of customer complaints to previous classifications.

Providing quality emergency supplies is crucial to mitigate and respond to emergencies. However, despite government and consumer oversight of emergency supplies’ quality, a troubling trend persists among some enterprises to sacrifice product quality for financial gain. This paper examines the influence of strategy selections among governments, enterprises, and consumers to enhance the quality of emergency supplies.

We develop a tripartite evolutionary game model consisting of three stakeholders: government, enterprises, and consumers, considering factors including subsidies and penalties. After analysing three stakeholders’ strategic choices to ascertain system stability, parametric analyses were conducted.

Excessive or insufficient subsidies are not conducive to encouraging enterprises to adopt an authentic production strategy; excessive subsidies may result in consumers enduring counterfeiting. Furthermore, the government’s supervision strategy can stabilise the system quickly, suggesting that consumer reporting cannot replace government supervision. Additionally, incentivising enterprises to adopt an authentic production strategy can be achieved by increasing penalties and enhancing compensation while reducing consumer reporting, government supervision, and raw materials costs.

We present a preliminary exploration of how to promote the production of qualified emergency supplies in the early stages of an emergency event. The model and findings proposed in this paper can be generalised and applied to various emergency events, including epidemics and earthquakes.

The purpose of this paper is to investigate cutting-edge coagulant materials and procedures for the removal of harmful microplastics from the water.

Traditional methods of removing microplastics from water bodies, like filtration, face limitations due to the small sizes involved. Hence, coagulation and flocculation emerge as essential strategies to enhance filtration efficacy. This paper summarizes recent research on coagulant materials, including novel hybrids, for water purification. It also looks at the most recent improvements in coagulation and flocculation processes, as well as the factors that influence their efficiency.

This paper highlights recent research on coagulant materials, including novel hybrids, used in water purification. It also examines the most recent advancements in coagulation and flocculation procedures, as well as the elements influencing their effectiveness.

The environmental threat posed by plastics, especially in their non-naturally degradable forms, such as microplastics, has reached alarming proportions. These minute particles pervade our air, soil and water bodies, driven by various factors and sources. Their diminutive size, whether in micro or nano form, renders them ingestible by marine and freshwater organisms, as well as humans, posing significant health risks. Traditional methods of water cleaning are not effective in dealing with very small-sized plastics and hence this paper summarizes recent research on coagulant materials, including various novel hybrids, for water purification from tiny microplastics in detail.

The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined and analyzed.

The extracting process was optimized using the response surface methodology (RSM) approach. Material-liquid ratio, temperature and time were chosen as variables and the absorbance as a response. The stability of the tea stem pigment at the different conditions was tested and analyzed.

The optimized extraction technology was as follows: material-liquid ratio 1:20 g/ml, temperature 50°C and time 60 min. The stability test results showed that tea stem pigment was sensitive to oxidants, but the reducing agents did not affect it. The tea stem pigment was unstable under strong acid and strong alkali and was most stable at pH 6. The light stability was poor. Tea stem pigment would form flocculent precipitation under the action of Fe²⁺ or Fe³⁺ and be relatively stable in Cu²⁺ and Na²⁺ solutions. The tea stem pigment was relatively stable at 60°C and below.

No comprehensive and systematic study reports have been conducted on the extraction of pigment from discarded tea stem, and researchers have not used statistical analysis to optimize the process of tannase-assisted tea stem pigment extraction using RSM. Additionally, there is a lack of special reports on the systematic study of the stability of pigment extracted from tea stem.

The study aims to measure the contribution rate of scientific and technological progress of Shaanxi province and find out the main driving force of its economic development, which has important reference significance for formulating and implementing the economic and social development strategy of Shaanxi Province and other regions.

By comparing and referring to the advantages and disadvantages of existing research methods, this paper combined C-D production function and Solow residual method to calculate the elastic coefficient through neural network algorithm, and then calculated the contribution rate of technological innovation to economic growth in Shaanxi province as a whole and in various regions, analyzed and put forward reasonable suggestions.

The results show that the economic growth is mainly depends on capital investment, and the contribution rate of technological innovation to economic growth is low and fluctuates greatly. In the future, each region of Shaanxi should improve the ability of technological innovation to speed up the economic transformation to the intensive type.

To make the technological innovation in Shaanxi province and other regions play a more significant role in promoting economic growth and accelerate the productivity and economic transformation of Shaanxi Province, the following suggestions are put forward, strengthen the coordinated development of innovation and economy in all regions of Shaanxi. Second, this paper need to give full play to the role of policy support and incentives. Third, this paper need to improve the market system and vigorously support enterprise innovation. Fourth, use new and high technology to transform and upgrade industrial technology. Fifth, this paper need to speed up the development of high-quality personnel.

Innovation quality is a critical component of enterprise innovation. Prior research primarily focuses on company-level and external policy-level factors that affect innovation quality, while ignoring social-level factors. Based on institutional isomorphism theory, this study examines how the innovation quality of three-dimensional institutional equivalence, which is an important and unique reference group for firms to follow the “law of imitation of close preference”, affects the likelihood of firms' innovation quality.

This study conducts firm random effects and industry/year fixed effects models using China's listed companies from 2002 to 2021.

This study finds that compared with the innovation quality of its other industry, community, or network peers, the innovation quality of three-dimensional institutional equivalence has a greater impact on firm innovation quality. Furthermore, technological intensity significantly increases the effect of three-dimensional institutional equivalence on focal company innovation quality, while financing constraints significantly attenuate this effect. Additionally, when there is no institutional equivalent, the innovation quality of network, industry, and community peers has significant positive effects on enterprise innovation quality. Heterogeneity analysis also indicates that, under the conditions of non-state-owned enterprises, a low regional legal environment, or low regional factor market development, three-dimensional institutional equivalence contributes significantly to firm innovation quality.

This study focuses on the effect of three-dimensional institutional equivalence on Chinese enterprises' innovation quality. Nonetheless, research samples from other countries are not considered in this study.

This study explores the impact of three-dimensional institutional equivalence on firm innovation quality within a systematic theoretical framework and incorporates firm attributes into this framework.

This paper aims to examine the level of awareness and determinants of the actual adoption of fintech services. This paper further focuses on how usages of different kind of fintech services fulfills the business needs of the micro-entrepreneurs of urban slum dwellers of Uttarakhand.

The research investigated the predictive significance of actual adoption of fintech services using the unified theory of acceptance and use of technology (UTAUT) and prospect theory framework. Data was collected from 80 micro-entrepreneurs of urban slum areas of Uttarakhand, using an adapted semi-structured questionnaire. For analysis of data partial least square structural equal modeling has been used.

This paper finds that different fintech services have different levels of awareness whereas payment, regulation and market provision-related fintech services have high awareness. The main drivers for adopting fintech are services trust (ST) and behavioral intention (BI). BI significantly influences fintech adoption, while ST positively impacts BI, actual usage and facilitating conditions; perceived risk, however, negatively affects ST. The widely used fintech services are payment-based fintech (unified payments interface), followed by regulatory fintech (Khatabook app). Fintech effectively serves the business needs of micro-entrepreneurs in the urban slums of Uttarakhand with innovative product solutions.

The findings of this study are valuable for various fintech providers. These results can serve as a roadmap to strengthen fintech services in the broader population, including niche market segments.

This study uniquely contributes to the literature that addresses the issues of entrepreneurs of the lower strata of society through the use of fintech services.

The problem of fabric defect detection is a particularly challenging task, as the fabric defects occupy only a small portion of the image pixels and it is difficult to collect sufficient samples for training deep learning-based models. The purpose of this work is to present a novel self-supervised learning method to address this problem.

In order to solve the problem of lack of defect samples, based on the fabric-specific degree of texture regularity, we propose an anomaly generation method to create synthetic fabric defects by destroying the normal fabric texture. To improve the detection of defects of different sizes, a global–local parallel detection mechanism is proposed. A self-supervised model including an anomaly generation module, a reconstruction subnetwork and a discriminative subnetwork is established to achieve model training without prior anomaly information.

The proposed method features self-supervised training, does not require no labelled anomaly data and detects anomalies by distinguishing their distance from normal samples at both global and local levels. When tested on four fabric datasets, our approach outperforms state-of-the-art unsupervised and self-supervised methods and achieves significantly higher localization accuracy.

A high-fidelity fabric defects synthesis method is presented to alleviate the problem of collecting numerous fabric defects, providing a reference for other surface anomaly detection problems. The proposed global–local parallel detection mechanism can serve as a reference for other methods dedicated to detecting particular anomalies. The proposed self-supervised network model can effectively locate fabric anomalies without prior labelling information, which could be used as a framework for other model designs.

Natural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. Resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC context.

The quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and functions.

The results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC network.

The study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.