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Titanium(IV) oxide nanoparticles (TiO₂ NP) were deposited to cotton denim fabrics using a self-crosslinking acrylate – a polymer dispersion to extend the lifetime of the products. This study aims to determine the optimum conditions to increase abrasion resistance, to provide self-cleaning properties of denim fabrics and to examine the effects of these applications on other physical properties.

The denim samples were first treated with nonionic surfactant to increase their wettability. Three different amounts of the polymer dispersion and two different pH levels were selected for the experimental design. The finishing process was applied to the fabrics with pad-dry-cure method.

The presence of the coatings and the adhesion of TiO₂ NPs to the surfaces were confirmed by scanning electron microscope and Fourier transform infrared spectroscopy analysis. It was ascertained that the most appropriate self-crosslinking acrylate amount and ambient pH level is 10 mL and “2”, respectively, for providing increased abrasion resistance (2,78%) and enhanced self-cleaning properties (363,4%) in the denim samples. The coating reduced the air permeability and softness of the denim samples. Differential scanning calorimetry and thermogravimetry analysis results showed that the treatments increased the crystallization temperatures and melting enthalpy values of the denim samples. Based on the thermal test results, it is clear that mass loss of the denim samples at 370°C decreased as the amount of self-crosslinking acrylate increased (at pH 3).

This study helped us to find out optimum amount of self-crosslinking acrylate and proper pH level for enhanced self-cleaning and abrasion strength on denim fabrics. With this finishing process, an environmentally friendly and long-life denim fabric was designed.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

Particles are of the controlled release delivery systems. Also, topically applied olive oil has a protective effect against ultraviolet B (UVB) exposure. Due to its sensitivity to oxidation, various studies have investigated the production of olive oil particles. The purpose of this study was to use chitosan and sodium alginate as the vehicle polymers for olive oil.

The gelation method used to prepare the sodium alginate miliparticles containing olive oil and particles were coated with chitosan. Morphology and size, zeta potential, infrared spectrum of olive oil miliparticles, encapsulation efficiency and oil release profile were investigated. Among 12 primary fabricated formulations, formulations F₅ (olive oil loaded alginate miliparticles) and F₁₁ (olive oil loaded alginate miliparticles + chitosan coat) were selected for further evaluations.

The size of the miliparticles was in the range of 1,100–1,600 µm. Particles had a spherical appearance, and chitosan coat made a smoother surface according to the scanning electron microscopy. The zeta potential of miliparticles were −30 mV for F₅ and +2.7 mV for F₁₁. Fourier transform infrared analysis showed that there was no interaction between olive oil and other excipients. Encapsulation efficiency showed the highest value of 85% in 1:4 (olive oil:alginate solution) miliparticles in F₁₁. Release study indicated a maximum release of 68.22% for F₅ and 60.68% for F₁₁ in 24 h (p-value < 0.016). Therefore, coating with chitosan had a marked effect on slowing the release of olive oil. These results indicated that olive oil in various amounts can be successfully encapsulated into the sodium-alginate capsules cross-linked with glutaraldehyde.

To the best of the authors’ knowledge, no study has used chitosan and sodium alginate as the vehicle polymers for microencapsulation of olive oil.

This case study outlines the strategic and organisational issues faced by an entrepreneurial firm operating in an emerging economy. This case study has been written to equip students with how entrepreneurs can overcome certain barriers and use technology to achieve product–market fit, taking the Indian laundry sector as an example. The following are the key learnings for the case: start-ups need to continuously assess the product–market fit to organise a highly unorganised sector; market entry and expansion modes require proper evaluation of available entry and expansion modes before pursual; franchising decisions require firm-specific and location-specific considerations; and careful consideration given to celebrity endorsement will result in increased sales.

The Indian laundry market was a highly unorganised market and presented an untapped opportunity. While the market opportunity was enormous, the existing solutions comprised local vendors that may not provide end-to-end services (washing, ironing, etc.). The case study described how a young entrepreneur, Arunabh Sinha, overcame certain challenges to achieve a product–market fit for metro cities and later expanded to Tier 2 and Tier 3 cities in India as well. However, the challenges remained, as the firm expanded by using a franchise model, and other modes of business were required to be evaluated as well.

The case study is suitable for students pursuing MBA courses in marketing, service marketing and entrepreneurship development.

Teaching notes are available for educators only.

CSS3: Entrepreneurship.

The purpose of this study is to use liposome technology in the treatment of fabrics textiles because of its efficient energy saving, reducing time and temperature.

The newly prepared lecithin liposome was used to encapsulate dyes for the purpose of increasing dyeing affinity. Different ratios of commercially available lecithin liposomes (1%, 3%, 5% and 7%) were used simultaneously in the dyeing of cotton and wool fabrics. The treated fabrics (cotton and wool fabrics) were confirmed using different analytical procedures such as scanning electron microscope (SEM), Fourier-transition infrared spectroscopy, ultraviolet protection factor, colour strength (K|S) measurements and fastness measurements.

The results show that increasing liposome ratios in dyeing baths leads to increased dyeing affinity for cotton and wool fabrics compared with conventional dyeing without using liposomes. In addition to that, the colour strength values, infrared spectra, SEM and fastness properties of non-liposome-dyed fabrics and liposome-dyed fabrics were investigated.

The research paper provides broad spectrum of green encapsulation fabrics using liposome technology to perform the dye stability, dye strength and fastness.

The present study identifies the factors that impact behavioral intentions to adopt solar water heaters (SWHs) and examines their relationship with behavioral intentions using an extended “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.

The study used a primary survey to collect data from 423 respondents across seven Indian states selected through purposive sampling. The collected data was analyzed using IBM SPSS software and “Structural Equation Modeling” (SEM) was performed using SmartPLS 3.5.5.

The results suggest that social influence is the most significant factor affecting SWH adoption, followed by effort, performance expectancy and facilitating conditions. The perceived cost negatively affects behavioral intentions and social influence on behavioral intentions is partially mediated by facilitating conditions. People prefer SWHs if they are easy to install and compatible with other home appliances. Positive perception of friends and family, easy access and government incentives contribute to SWH adoption.

SWH adoption can be promoted by designing sector-specific programs and improving ease of installation, operation, maintenance and after-sale services.

This study explores the behavioral intentions of individuals in India to adopt SWHs. India is a developing tropical country with a high potential for SWH adoption but has not received much attention. Further, the research integrates the perceived cost construct in the UTAUT model and examines the partial mediation impact of facilitating conditions to improve the model’s comprehensibility.

This paper aims to synthesize new screen-printing ink formula based on new derivatives of azo thiadiazol disperse dyes and evaluate their characteristics after being printed on polyester fabric substrates.

New dispersed dyes based on 1, 3, 4-Thiadiazole derivatives (dyes 1 and 2) were prepared and confirmed by different analyses, infrared (IR), mass and nuclear magnetic resonance (NMR) spectroscopy, and then formulated as colored materials in the screen-printing ink formulations. Printing pastes containing the prepared dyestuffs and other ingredients were used for printing polyester using screen-printing or traditional printing. The characteristics of printed polyester fabric substrates were measured by color measurements such as a*, b*, L*, C*, E, Ho, R% and color strength, as well as light, washing, crock and alkali perspiration fastness, and finally, the depth of penetration was evaluated.

The prepared 1, 3, 4-Thiadiazole derivatives (dyes 1 and 2) were obtained from the reaction of 5,5’-(1,4-phenylene)bis(1,3,4-Thiadiazole-2-amine) with resorcinol and m-toluidine as a coupling component. The suitability of the prepared dyestuffs for silk screen-printing on polyester fabrics has been investigated. The prints obtained from a formulation containing dye 1 possess high color strength as well as good overall fastness properties if compared to those obtained using dye 2.

The method of synthesis of the new dyestuffs and screen-printing ink provides a simple and practical solution to prepare some new heterocyclic disperse azo dyes, and they are formulated in the screen-printing inks for printing on a polyester fabric substrate.

The prepared disperse dyes based on 1,3,4-Thiadiazole derivatives (dyes 1 and 2) could be used in textile printing of polyester on an industrial scale.

The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.