Brand image has been a crucial clue to making subjective judgment for consumers to determine the brand, which is critical to making a purchase decision. The influence mechanism from apparel brand images on consumers’ purchase intention was explored for theoretical and positive analysis based on the self-congruity theory. This research first constructed a hypothetical model of apparel brand images influencing consumers’ purchase intention with self-congruity and perceived quality as mediators, in which a questionnaire was designed and conducted to test the theoretical model. The research shows that apparel brand image and perceived quality can significantly influence consumers’ purchase intention. The consumer purchase intention is directly related to clothing brand image provided self-consistency and perceived quality play an intermediary with the regulatory effect of self-motivation and brand familiarity. A positive attitude toward apparel brand image will stimulate consumers to build cognitive clues and associations between the consumers and the brand and strengthen cognitive consistency with the apparel brand’s spirit. The research results are beneficial to textile fashion and clothing enterprises to improve brand building and marketing.

Posture monitoring and investigation in wearable technology play a significant role in the analysis of body postures. This study aims to develop a new flexible smart garment realized by stitching flex sensors at different joint positions for sensing flexion angles in static and kinematic motions. Calibration tests were conducted by systematically flexing wrist, elbow, and knee joints, respectively. A male subject then wore the developed flexible smart garment to sense different body postures. The measured data from flex sensors inside the smart garment exhibited immediate response after each joint movement of the male subject. The minimum measurement sensitivities of flex sensors mounted at the knee, elbow, and wrist was 0.94°, 0.8°, and 0.56°, respectively. Measured flexion angle changes were within 80°, 95°, and 140° ranges from knee, elbow, and wrist. Both stand and walk tests at a velocity of 4 km/h indicate that the flexion angles of three joint positions include wrist, elbow, and knee joints can be effectively monitored using the flex sensor–based smart garment. Flex sensor can be employed to monitor body joint movement and future to identify different postures of body joints in practice. The flexible smart garments cannot be washed.

Generally, comprehensive documents are needed to provide the research community with relevant details of any research direction. This study conducted the first descriptive bibliometric analysis to examine the most influential journals, institutions, and countries in the field of artificial intelligence in textiles. Furthermore, bibliometric mapping analysis was also used to examine diverse research topics of artificial intelligence in textiles. VOSviewer was used to process 996 articles retrieved from Web of Science—Core Collection from 2007 to 2020. The results show that China and the United States have the largest number of publications, while Donghua University and Jiangnan University have the highest output. These three themes have also appeared in textile artificial intelligence publications and played a significant role in the textile structure, textile inspection, and textile clothing production. The authors believe that this research will unfold new research domains for researchers in computer science, electronics, material science, imaging science, and optics and will benefit academic and industrial circles.

In view of the current lack of fashion brand competitiveness and innovation in China, this paper puts forward the concept of fashion brand image value creation and analyzes it from five dimensions: fashion brand image design, image publicity, brand aesthetics, brand charm, and brand function. This paper explores the relationship between fashion brand image value creation, customer participation behavior, experience value perception, intention, trust, and loyalty based on consumer value co-creation and experience value perception theories. On this basis, the structural equation model is used to test the research hypothesis empirically. An online survey questionnaire was subsequently developed and conducted to verify validity and reliability by statistical analysis. The results show that the value creation of fashion brand image will positively impact brand loyalty. Customer participation behavior and experience value perception play an intermediary and chain intermediary role, and customer participation willingness and fashion brand trust play a regulatory role. This study provides new ideas and references for the value creation of fashion brand image and provides quantitative scientific data for fashion enterprises to grasp the direction of brand image value creation and implement brand construction and marketing strategies.

While introducing new technology has completely transformed the textile production process, the rapid pace of massive industrialization has increased the volume of wastewater, which is highly hazardous. Even though the textile industry is essential to our economy, the textile industry is harmful to the environment because of the production of wastewater, solid wastes, air pollutants, noise, etc. Recycling textile wastewater is crucial, and oxidation, physical, biological, and physicochemical methods can be used to treat textile wastewater. Based on statistics and visualization tools, bibliometric analysis has evolved to demonstrate a given topic’s knowledge structures and developmental tendencies. Here we provide a bibliometric analysis focused on textile wastewater treatment from 1990 to 2022. Raw data was retrieved from the Web of Science (WoS) database and mapped using VOSviewer and biblioshiny. Textile, wastewater, and treatment were keywords. We retrieved 8,170 documents, 1,138 sources published these documents, a 22.7% annual increase, where 21458 authors published these documents with an average citation rate of 33.2%, and there were 6,680 research articles and 462 review articles. DESALINATION AND WATER TREATMENT stayed on top with 422 publications. We discovered that DONGHUA UNIVERSITY ranks first with 330 publications. Though China took first place with a total of 43961 citations, followed by India with a total of 33953 citations, from a total of 120 countries participating in this research, the research work of CRINI G and coworkers was most cited globally. The most common term was wastewater, which occurred 3,144 times, followed by textile, which appeared 2,669 times. We expect this research to be a significant resource for scholars by comprehensively describing the current state and future directions of textile wastewater treatment.