Efecto de los TLC de nueva generación en la innovación de productos sostenibles: evidencia empírica de empresas textiles vietnamitas quecotizan en bolsa

Introduction: The covid-19 pandemic has significantly changed consumption habits, with by cutting unnecessary spending on fashion products, and focusing on sustainable products. Therefore, greener textile innovation is currently a rapidly growing trend, bringing new sales and flexible production capabilities. The article presents impact of new generation FTA like EVFTA, CPTPP on sustainable textile product innovation. Problem: Greener production is dominant in several export industries. After the Covid-19 pandemic shifting from fast fashion to sustainable fashion is more and more changing. Objective: The aim of this study is to examine impact directly as well as indirectly the relationship between FTA expectation on SPIC via 2 mediating variable such as environmental regulation and CEO’s perception. Methodology: The study is exploratory research, it was modeled using PLS-SEM to test the relationships in the model. Results: Both Environment Regulation and CEO\u27s perception play an important role as partial mediation in the relationship between FTA expectation and sustainable product innovation capability. Conclusion: This project seeks to generate a change in the behavior of the use towards efficiency and modification of user practices to favor the sustainability standard of the textile and garment firm. Originality: Through this research, integrated and sustainable textile and garment management strategies are formulated for green marketing strategies in Vietnam. Limitations: The lack of information provided by the municipality and access to the sampling points.Introducción: Este documento es el producto de la investigación “Efecto de los TLC de nueva generación en la innovación de productos sostenibles: evidencia empírica de empresas textiles cotizadas en Vietnam” desarrollada en la Universidad de Thuongmai (TMU) y la Universidad de Industria de Hanoi (HaUI) entre 2021 y 2023. La pandemia de COVID-19 ha cambiado significativamente los hábitos de consumo hacia la reducción de gastos innecesarios en productos de moda y centrándose en productos sostenibles. Por lo tanto, la innovación textil más ecológica es actualmente una tendencia de rápido crecimiento, que genera nuevas ventas y capacidades de producción flexibles. El artículo presenta los impactos de los acuerdos de libre comercio (TLC) de nueva generación como el Acuerdo de Libre Comercio entre la Unión Europea y Vietnam (EVFTA) y la Asociación Transpacífica Integral y Progresista (CPTPP) en la innovación de productos textiles sostenibles. Problema: La producción más ecológica es dominante en varias industrias de exportación. Después de la pandemia de COVID-19, el cambio de la moda rápida a la moda sostenible es cada vez más urgente. Objetivo: El objetivo de este estudio es examinar los impactos directos e indirectos de las expectativas del FTA en la capacidad de innovación de productos sostenibles (SPIC) a través de dos variables mediadoras, como las regulaciones ambientales y la percepción del CEO. Metodología: El estudio involucra una investigación exploratoria, utilizando PLS-SEM para probar las relaciones en el modelo. Resultados: Tanto la regulación ambiental como la percepción del CEO juegan un papel importante como mediación parcial en la relación entre la expectativa de TLC y la capacidad de innovación de productos sostenibles.  

MỘT MÔ HÌNH NHIỄU VÀ ỨNG DỤNG TRONG VIỆC PHÁT HIỆN CHẤT LIỆU

SUMMARYImages always have noises due to image acquisition processes. Noises are created by self of objects and environments. Each of materials has specific number of noises, which characterizes that material. Noise features of the material are called material noises. This paper deals with a technique for detecting image materials which base on noise analysis of images. By experiments, the technique exposed fairly accurate results for some natural materials at first, especially homogeneous materials about illuminates and extracted invariant features is sparse.Keywords. Noises, materials, invariant feature, reduce noise, wavelet, texture featureSUMMARYA NOISED MODEL AND ITS APPLICATION FOR DETECTING IMAGE MATERIALSImages always have noises due to image acquisition processes. Noises are created by self of objects and environments. Each of materials has specific number of noises, which characterizes that material. Noise features of the material are called material noises. This paper deals with a technique for detecting image materials which base on noise analysis of images. By experiments, the technique exposed fairly accurate results for some natural materials at first, especially homogeneous materials about illuminates and extracted invariant features is sparse.Keywords. Noises, materials, invariant feature, reduce noise, wavelet, texture featur