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Big Data is disrupting the fashion retail industry and revolutionising the traditional fashion business models. Nowadays, leading fashion brands and new start-ups are actively engaging with Big Data analytics to enhance their operations and maximise on profitability. In hope of motivating and providing direction to fashion retail managers, industry experts, and academics alike, the purpose of this paper is to consider the most recent and trending applications of Big Data in fashion retailing with the aim of concisely summarising the industry’s current position and status.

This conceptual paper provides a brief introduction to the emerging topic of Big Data in fashion retailing by briefly synthesising findings from industry, market and academic research.

Most existing fashion brands are yet to fully engage with Big Data. The authors find that the main reasons underlying the application of Big Data analytics in fashion are trend prediction, waste reduction, consumer experience, consumer engagement and marketing, better quality control, less counterfeits and shortening of supply chains. The authors also identify key challenges which must be overcome for the most fashionable industry to be able to capitalize on Big Data to understand and predict fashion consumer behaviour.

The brief synthesis provides a foundation for future investigations into the use of Big Data in fashion retailing.

This paper serves as an up-to-date introduction to how Big Data can transform fashion retailing and can act as a sound reference guide for fashion industry managers and professionals grappling with Big Data-related issues.

In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy environment. Assessment of electronic service quality (ESQ) of libraries is significantly important according to their major roles. It should be noted that the ESQ has a significant impact on customer satisfaction, which improves organizational performance. Accordingly, low ESQ means waste of organizational resources and poor user satisfaction. So, there is a dire need to reflect reasons inducing failure modes in academic library ESQ. Thus, investigation of failure modes affecting academic library ESQ is highly important. One solution in this area is utilization of the intuitionistic fuzzy (IF) failure mode and effects analysis (FMEA) as one of the widely used methods for prediction and identification of failure modes.

The present study in terms of objective is applied and in terms of the type of method is descriptive-analytical. The research sample included four experts of Yazd academic Libraries (Iran). To collect data, three types of questionnaires were distributed among experts. The purpose of the first questionnaire was to identify and reach an agreement on e-library failure modes. Type II questionnaire was used to determine the importance of identified risk factors and Type III questionnaire was used to prioritize the factors.

Results indicate that the difficulty of using websites, lack of provided information feedback to users and lack of links on the website to users' are the main priorities for improving ESQ in the studied academic libraries.

In this approach, the Intuitionistic fuzzy Elimination Et Choix Traduisant la REalité and technique for order of preference by similarity to ideal solution method were used to rank failure modes in academic library ESQ within the FMEA framework.]

With respect to two new subjects, i.e. nanofluids and microchannels, in heat transfer systems and modern techniques used for building them, this paper aims to study on effect of using aluminum oxide nanoparticles in non-Newtonian fluid of aqueous solution of carboxy-methyl cellulose in microtube and through application of different slip coefficients to achieve various qualities on surface of microtube.

Simultaneously, the effect of presence of nanoparticles and phenomenon of slip and temperature jump has been explored in non-Newtonian nanofluid in this essay. The assumption of homogeneity of nanofluid and fixed temperature of wall in microtube has been used in modeling processes.

The results have been presented as diagrams of velocity, temperature and Nusselt Number and the investigations have indicated that addition of nanoparticles to the base fluid and increase in microtube slip coefficient might improve rate of heat transfer in microtube.

The flow of non-Newtonian nanofluid of aqueous solution of carboxy methyl cellulose-aluminum oxide has been determined in a microtube for the first time.

The purpose of this paper is to optimize the frictional input parameters related to the yarn and woven fabric samples. Indeed, using metaheuristic techniques for optimization, it helps to attempt the best quality appearance of garment, by analysing their effects and relationships with the bagging behaviour of tested fabrics before and after bagging test. Using metaheuristic techniques allows us to select widely the minimal residual bagging properties and the optimized inputs to adjust them for this goal.

The metaheuristic methods were applied and discussed. Hence, the genetic algorithms (GA) and ant colony optimization (ACO) technique results are compared to select the best residual bagging behaviour and their correspondent parameters. The statistical analysis steps were implemented using Taguchi experimental design thanks to Minitab 14 software. The modelling methodology analysed in this paper deals with the linear regression method application and analysis to prepare to the optimization steps.

The regression results are essential for evaluate the effectiveness of the relationships founded between inputs and outputs parameters and for their optimizations in the design of interest.

This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to optimize the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behaviour due to bagging phenomenon can be analysed and optimized accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones can fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help to understand why residual bagging behaviour remained after garment uses due to the internal stress and excessive extensions.

Until now, there is no work dealing with the optimization of bagging behaviour using metaheuristic techniques. Indeed, all investigations are focused on the evaluation and theoretical modelling based on the multi linear regression analysis. It is notable that the metaheuristic techniques such as ACO and GA are used to optimize some difficult problems but not yet in the textile field excepting some studies using the GA. Besides, there is no sufficiently information to evaluate, predict and optimize the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behaviour. Several and different denim fabrics within their different characteristics are investigated to widen the experimental analysis and thus to generalize the results in the experimental design of interest.

In this paper, the forced convection heat transfer of the nanofluid composed of water and AL2O3 nanoparticles is simulated in a two-dimensional horizontal microchannel by injecting the lower wall. The upper wall of the microchannel is 303 K at temperature TH. On the lower wall of the microchannel, there are three holes for flow injection. Other parts of the wall are insulated. In this paper, the effect of parameters such as Reynolds number, slip coefficient and volume fraction of nanoparticles is investigated.

The boundary condition of the slip velocity is considered on the upper and lower walls of the microchannel. In this work, the flow of nanofluid in the microchannel is considered to be slow, permanent and Newtonian. In the present study, the effect of injection through the microchannel wall on the slip velocity is examined for the first time.

The results are also presented as velocity profiles and Nusselt number diagrams. It was found that the Nusselt number increases with increasing the amount of slip coefficient of velocity and the weight percentage of solid nanoparticles. The rate of this increase is higher in the high values of the Reynolds number.

A novel paper concerned the simulation of cross-flow injection effects on the slip velocity and temperature domain of a nanofluid flow inside a microchannel.

The purpose of this study is to evaluate the impact of psychological entitlement and perceived organizational justice on cyberloafing.

In this study, a cross-sectional research design based on a questionnaire method was used to collect the required data from a sample of 226 employees working at selected universities in the city of Isfahan, Iran. To test the research hypotheses, structural equation modeling was used.

According to the findings, psychological entitlement could have a significant impact on perceived organizational justice and consequently perceived organizational justice could significantly influence cyberloafing. Moreover, psychological entitlement could significantly influence cyberloafing and finally, psychological entitlement could have a significant effect on cyberloafing through perceived organizational justice.

This research provides valuable insight for studying the relationship among psychological entitlement, perceived organizational justice and cyberloafing.