فصلنامه علوم و فناوری نساجی
سال دوازدهم شماره 4 (زمستان 1402)

Nowadays, due to the reduction of fresh water resources and the increase in demand in the world, the removal of various pollutants, such as dyes, from industrial wastewaters to reuse them has received much attention. In this research, activated carbon (AC) was synthesized by the chemical activation of apricot kernel shell, and then, this adsorbent was modified by iron-containing functional groups (Fe-AC) and used as an adsorbent to remove reactive red dye 198 from the aqueous medium. The properties of these adsorbents were identified using BET, EDX-SEM, and FT-IR analyses. The results of equilibrium data showed that the adsorption process is single-layer and the maximum adsorption capacity of AC and Fe-AC absorbents is equal to 192.6 mg/g and 277 mg/g, respectively. The increase in adsorption capacity after modification is due to the positive adsorption sites of iron (O-Fe+) on the surface of the modified adsorbent, which adsorb the reactive dye red 198 by electrostatic mechanism. Also, the physical adsorption due to the porous structure of the adsorbent is effective in the adsorption of reactive red dye on the Fe-AC adsorbent. The analysis of kinetic data with different kinetic models showed that the pseudo-second-order kinetic model is consistent with the experimental result. The spontaneity and exothermic nature of the adsorption process were determined by determining the thermodynamic parameters. The successive cycles of adsorption and desorption indicate the ability to regenerate and reuse the synthesized adsorbent, which can be a suitable option for use in industrial dimensions.

The purpose of this research is to investigate the factors influencing the adoption of Internet of Things (IOT) in the digital clothing supply chain using FUZZY AHP and WASPAS techniques. This research has a mixed approach, in terms of descriptive-survey method. The statistical population includes Mazandaran textile employees and managers. The research tool is a pairwise comparison questionnaire. In the first stage, the components of the study were collected from the research literature and screened by experts using the Delphi technique in 3 rounds. In order to prioritize the levels of Mazandaran textile clothing supply chain, Fuzzy Hierarchy Analysis (FUZZY AHP) technique was used and in order to prioritize the factors of Internet of Things acceptance, WASPAS technique was used. The results of the research indicate that, in the first stage, the level of customer demand with a weight of 0.499 has been prioritized. In the second step in adopting the Internet of Things in the digital clothing supply chain, system integration is the first priority, the infrastructure of the Internet of Things is the second priority, the flexibility of the supply chain is the third priority, human capital is the fourth priority, and organizational culture is the fifth priority. Considering the first priority of system integration in the implementation of Internet of Things in Mazandaran Textile, it is suggested that regulatory organizations act more agile and active in setting the standards of Internet of Things.

In the modern world, to remain competitive, the use of digital marketing tools in various industries is of high importance. Since the Textile and clothing industry is considered one of the priority industries of the country and the startups in this industry have encountered competition challenges, the current research aims to identify and localize digital marketing components in Iranian fashion and clothing industry startups. The method of this research is applied-developmental in terms of its purpose and exploratory in nature. The research strategy consists of qualitative content analysis in the first stage and phenomenological qualitative method in the second stage. For this purpose, scientific documents related to the topic were selected purposefully and the digital marketing components were identified and analyzed using NVIVO software. Then, the results obtained were localized through interviews with 12 Iranian fashion and clothing industry. The research results showed that in order to properly implement digital marketing in Iranian fashion and clothing industry startups and achieve their success, organizational factors, innovation-competitive advantage, business-profitability factors and also 12 extracted components are of high importance.

The purpose of the current research is to identify and analyze marketing performance measures in the fashion and clothing industry. This research was conducted with the developmental research design and a mixed qualitative/quantitative approach in two steps. In the first step, the marketing performance measures of companies operating in the fashion and clothing industry were identified using the content analysis method in MaxQDA software in a library environment using a systematic review of selected articles indexed in the Web of Science database over the period 1970-2023. The second step involved a field study on 400 experts of the fashion and clothing industry using a questionnaire derived from the results of the first step conducted in the form of exploratory factor analysis. This study identifies market and innovation, customer behavior, product management, customer profitability, distribution channel management, price, and financial and internal performance measures within a comprehensive framework as the most important marketing performance metrics for the companies operating in the fashion and clothing industry, being derived from the study of scientific articles published at the national and international levels and approved by experts in this field. Hence, the current research invites the operators and decision makers of this important industry, as one of the country's strategic industries, to rethink the isolated approaches which are sometimes solely focused on financial aspects of performance in assessing the marketing performance of these companies. The comprehensive approach derived from the results of this study can help gain a competitive advantage for this promising industry in the country, which is also adorned with an original and rich cultural past.

The purpose of this research is to provide a scale of customer delight in textiles and clothing with a qualitative and quantitative approach. A semi-structured interview and the opinions of 18 experts in the field of carpet marketing were used to collect data. Thematic analysis approach and MAXQDA software were used to analyze qualitative data. The main finding of the current research is the constituent indicators of the customer delight scale in textiles and clothing. Cohen's kappa index was used to validate the coding and quality control process in the qualitative part, the dimensions, and components of the customer delight scale in textile and clothing.The main finding of the current research is the indicators of customer delight scale in textile and clothing with a qualitative and quantitative approach. Based on experts' opinions, customer delight indicators in textiles were classified into 4 dimensions and 9 components. Based on this, the main themes include 4 overarching themes and 9 sub-themes and 44 basic themes. According to the obtained results, the value of the Kappa index was calculated as 0.901, which is at the level of excellent agreement. According to the presented model, recognizing emotions and classifying customers towards emotions can be a suitable model for a correct understanding of customer delight. In order to increase customer delight, managers should create surprise and happiness in textile and clothing customers, and this can be done by strengthening distinct ideas to increase satisfaction and desire for customer delight.

The progress and improvement of human societies caused extensive changes and transformations in materials and their artifacts and led to the emergence of smart materials as a turning point in the course of developments. The range of use of smart materials in the textile industry is very noticeable and extensive research has been done in this field, which finally led to the introduction of smart textiles to the consumer market. The main purpose of this research is the Introduction and classification of smart materials applied in textiles. In this regard, first The theoretical foundations of smart materials are presented, and then their classification from different points of view. These materials are divided into three categories in common models such as the biological model(sensors/nerves and afferent neurons), operators (muscles) and processors (brain), or the structural model (sensory or passive, pragmatic or active, and intelligent or adaptive). But in the present research, in order to be more consistent with textiles a practical model was introduced, which divides smart materials into two categories: practical responders or energy converters, and all smart materials were categorized under them. For each material, a practical example or one related to textiles was given. It was concluded that the applied model is more convergent than the existing models with textiles. On the other hand, it was found that the growth of smart textiles continues at an increasing pace, although in some areas, there is still a need for more research and experience.