This research study aims to achieve a developing country’s sustainable development in the clothing industry by exploring consumer behavior to a willingness to purchase organic cotton clothing (OCC) and apparel retailers’ responsibilities. Organic cotton clothing development in the fashion industry could play an important role in textile and environmental pollution and create new business opportunities for green clothes. Survey data was collected from top cities in Bangladesh, and 303 useable responses were collected (81.5% male and 18.5% female). In our survey, 60.7% of the participant was employed. This research model was inspired by the Theory of Reasoned Action (TRA) and added some new variable that influences purchase willingness under OCC fashion in developing countries like Bangladesh. The findings of this study stated that consumer environmental concerns and consumer attitudes positively impact the OCC purchase willingness of Bangladeshi consumers. Also, the authenticity and fashionable of OCC products have a significant impact on Bangladeshi consumer purchase intention. Product Performance found an indirect effect on Bangladeshi consumers’ intention. Furthermore, this study will find that the Bangladeshi market is already very aware of the sustainability movement and concerned about environmental issues. Retailers should focus more on environmental awareness of OCC textile and authentic OCC items. Also, this study will update previous research findings on consumer attitudes toward OCC fashion in the Bangladesh market.

The fast fashion industry has been widely criticized for its substantial consumption of resources and significant environmental pollution. In contrast, virtual fashion clothes are attracting attention from consumers and academics for their notable sustainability benefits and potential for fashion innovation. However, research on consumer acceptance of virtual clothes and the role of sustainability remains limited. This study aims to fill this gap by applying the Emotional Three-Level Theory to identify key virtual fashion attributes, including aesthetic, reality, personalization, presentation, sustainability, and inclusivity features, and evaluating their impact on acceptance using the Technology Acceptance Model (TAM). A survey of 503 Generation Z consumers in China, analyzed through structural equation modeling, reveals that perceived enjoyment, usefulness, and ease of use significantly influence the intention to adopt virtual fashion clothes. Aesthetic and realistic features enhance enjoyment, while personalization and presentation improve usefulness and ease of use. Sustainability features positively impact all three factors, promoting consumer acceptance. These findings offer theoretical insights for virtual fashion research and practical guidance for the fashion industry to leverage virtual technologies for environmental sustainability. Notably, the study emphasizes the potential of virtual clothes in promoting sustainable development in the fashion industry.

Due to environmental concerns, an increasing number of Chinese consumers have begun to resist fast fashion, promoting cheap and lower quality materials with a short lifetime. A shift from a linear economic model to a circular fashion has become an urgent issue for the industry. To examine how brand stereotype affects consumers’ purchasing intention toward upcycled fabric clothing, this study adopted a grounded theory approach to develop the dimensions of brand stereotypes, including product, manufacturing process, service, and communication. Furthermore, a theoretical model was constructed incorporating brand stereotypes, brand green trust, fashion consciousness, and green consciousness. Results from structural equation model analysis indicated that (1) each dimension of brand stereotypes had a significantly positive impact on behavior intention, and especially product and service image have the most influence; (2) brand green trust mediated the relationship between brand stereotypes and buying intention, and (3) green consciousness positively moderated the relationship between brand stereotype and trust, whereas brand warmth in communication and trust was moderated negatively by fashion consciousness. The findings offer implications for the implementation of the green branding strategy, brand positioning, and cultivating consumers’ green awareness to improve market acceptance of upcycled fabric clothing.

Purpose: Drawing on social cognitive theory, this study aims to examine the relationship between supervisor developmental feedback and employee innovative behavior, incorporating with the mediating role of psychological safety and the moderating role of face orientation.Design/methodology/approach: A survey was conducted in 15 manufacturing companies in China. The participants comprised 302 employees. Hierarchical regression analysis was used to test the hypotheses. The mediating effects and the moderated mediating effects are further examined with bias-corrected bootstrapping method.Findings: Supervisor developmental feedback has a positive effect on employee innovative behavior through psychological safety, and this mediating effect is weakened by protective face orientation (fear of losing face), while the moderating effect of acquisitive face orientation (desire to gain face) is not significant.Practical implications: Organizations should create a development-oriented and safe innovation atmosphere for employees. In addition, leaders should adopt differentiated feedback and communication methods according to subordinates' face orientation.Originality/value: The study has demonstrated the positive effect of supervisor developmental feedback on employee innovative behavior, which is different from previous studies on performance feedback and leadership types. Meanwhile, this study has also explored the mediating effect of psychological safety and the moderating effect of face orientation, which provides more insights on the mechanism and boundary conditions of the effect of supervisor developmental feedback.

Standard time is a key indicator to measure the production efficiency of the sewing department, and it plays a vital role in the production forecast for the apparel industry. In this article, the grey correlation analysis was adopted to identify seven sources as the main influencing factors for determination of the standard time in the sewing process, which are sewing length, stitch density, bending stiffness, fabric weight, production quantity, drape coefficient, and length of service. A novel forecasting model based on support-vector machine (SVM) with particle swarm optimization (PSO) is then proposed to predict the standard time of the sewing process. On the ground of real data from a clothing company, the proposed forecasting model is verified by evaluating the performance with the squared correlation coefficient (R²) and mean square error (MSE). Using the PSO-SVM method, the R² and MSE are found to be 0.917 and 0.0211, respectively. In conclusion, the high accuracy of the PSO-SVM method presented in this experiment states that the proposed model is a reliable forecasting tool for determination of standard time and can achieve good predicted results in the sewing process.

More and more garment enterprises begin to pay attention to the importance of recycling, take the corresponding recycling strategy to recycle garment products and remanufacture, forming a closed-loop supply chain (CLSC). In reality, recycling is a complex system, the recycling strategy of clothing brands will not only affect the reverse channel of closed-loop supply chain, but also affect the consumer demand of forward channel, and then affect the profit of supply chain. In order to solve this problem, we propose a CLSC composed of a manufacturer, a retailer and a collector, establish three different Stackelberg leadership models, and derive the optimal recycling strategy. Our results show that consumers' sensitivity to the recycling price will affect the optimal decision of supply chain members. The increase of the recycling market is not always beneficial to the profits of supply chain members. By comparing the profits of the three models, it is found that the retailer leadership model is the most effective scenario of CLCS. The results of this paper provide a reference for garment enterprises to formulate recycling strategies.