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Observes a number of human-resource management problems in the Indian hand-loom industry.

Considers what gave rise to the problems and considers how they may be solved.

Highlights the need to: attract talented designers with the right values and alignment to the company vision; refine training strategies to make them need-based and relevant; attract the right artisans; enhance productivity levels; standardize pricing and quality of products; and preserve art and craft to sustain the business.

Presents a number of review questions. In what way can a firm like Paradise differ from other retailers? Define some realistic strategies to combat the problems of Paradise Retail. Which will be cost-effective? What can be gauged about the organizational culture of Paradise Retail? What are its values?

Deals with some of the problems of poorly paid workers in a traditional industry in a developing country.

Introduction: Big data in the insurance industry can be defined as structured or unstructured data that can affect the rating, marketing, pricing, or underwriting. The five Vs of big data provide insurers with a valuable framework for converting their raw data into actionable information. These five Vs are specifically: (1) Volume: The need to look at the type of data and the internal systems; (2) Velocity: The speed at which big data is generated, collected, and refreshed; (3) Variety: Refers to both the structured and unstructured data; (4) Veracity: Refers to trustworthiness and confidence in data; and (5) Value: Refers to whether the data collected are good or bad.

Purpose: Insurance companies face many data challenges. However, the administration of big data has allowed insurers to acknowledge the demand of their customers and develop more personalised products. In addition, it can be used to make correct decisions about insurance operations such as risk selection and pricing.

Methodology: We do this by conducting a systematic literature review on big data. Our emphasis is on gathering information on the five Vs of the big data and the insurance market. Specifically, how big data can help in data-driven decisions.

Findings: Big data technology has created an endless series of opportunities, which have ensured a surge in its usage. It has helped businesses make the process more systematic, cost-effective, and helped in the reduction in fraud and risk prediction.

This study aims to understand the influence of lone wolf tendencies, technology ease of use and team collaboration on the development of transactive memory systems (TMSs) and, consequently, their impact on the performance of supply chain and operations teams.

By using a comprehensive operations management simulation involving 160 business student teams, this research tests five hypothesized relationships using structural equation modeling.

Lone wolf tendencies, technology ease of use and team collaboration contribute positively to an efficient TMS. This group cognitive system, in turn, strengthens a team’s competitive position and operational efficiency. This study highlights the need to reevaluate traditional management practices that discourage candidates with lone wolf characteristics. In addition, it shows that technology ease of use not only affects individual productivity as highlighted by the technology acceptance model but also influences the team knowledge system.

This study deepens understanding of the antecedents and consequences of TMSs in supply chain management. Lone wolf tendencies, characterized by independent work proclivity, are common in supply chain teams due to task complexities. Prior research on the impact of lone wolf behavior has yielded mixed results. Furthermore, although Industry 4.0 technologies are widely adopted in supply chain operations, it remains unclear how ease of using these complex technologies affects TMSs and team performance. To the best of the authors’ knowledge, this research is among the first to investigate the influence of lone wolf tendencies and technology ease of use on group cognitive systems.

The durability of antimicrobial agents and its effectiveness is the most important factor for consumer usage. One important class of antimicrobial agents are inorganic metals and their metal oxides which can be prepared into nanoparticles and can be imparted to enhance the antimicrobial properties. The purpose of this paper is to investigate the effect of three different polymeric binders during the application of zinc oxide (ZnO) nanoparticles on the antimicrobial and performance properties of the finished fabric.

In this study, ZnO nanoparticles were prepared by a wet chemical method. The nano-particles size distributions was determined using Nanoplus Dynamic Light Scattering particle size distribution analyzer and concentration of nano ZnO 0.1% (w/v) was applied with 2% (w/v) polymeric binders, namely, polyvinyl alcohol (PVA), polyurethane (PU) and butyl acrylic (BA) on cotton fabric by pad dry cure method. The treated samples were tested for physical properties such as tearing strength, tensile strength, crease recovery and air permeability and antimicrobial properties using test method American Association of Textile Chemists and Colorists (AATCC) 100. Further, the content of zinc in the treated samples was determined by the atomic absorption method. The treated fabric was analyzed using fourier transform infrared spectroscopy and scanning electron microscopic and also tested for cytotoxicity as per International Organization for Standardization 10993.

The results indicated that the type of polymeric binders did not show any influence on the uptake of the zinc content. All treated samples showed positive results >99% with regard to antibacterial property. However, the polymeric treated samples showed a difference in physical properties. The ZnO nano-finish reduced the tensile strength and tearing strength of the fabrics. The difference in crease recovery for samples ZnO/PVA and ZnO/PU was not much except for ZnO/BA where it increased by 38%. The air permeability decreased after application for all treated samples, the lowest among treated samples was in ZnO/PU fabric. Further, ZnO/PVA finished fabric was found to retain antibacterial property up to 50 washes and was effective against MS2 Bacteriophage as a surrogate virus when analyzed as per AATCC 100–2012 test method, and therefore can be potentially used as health-care apparel such as doctors coat and scrub suits.

The outcome of this research is in its contribution to the field of reusable textiles. It highlights the use of nanotechnology to design and develop cotton fabrics for antimicrobial properties which has the potential of preventing the growth of harmful bacteria. The study brings forth the use of ZnO nanoparticles mixed with PVA binder on 100% cotton fabrics which exhibits antibacterial and antiviral properties with adequate wash durability. Currently, there is a high demand of effective durable textiles with barrier properties and the present study provides a promising solution to provide reusable textiles with a greater level of protection.

This study aims to study the simultaneous treatment of polyethylene terephthalate (PET) fabric with sodium hydroxide (NaOH) and TiO₂ nanoparticles (NPs).

PET fabrics loaded by TiO₂ NPs were investigated by the use of scanning electron microscopy (SEM), energy dispersive X-ray (EDX) and Fourier transformed infrared spectroscopy (FT-IR). Factors affecting the finishing process such as NaOH and TiO₂ NPs concentrations, finishing duration and temperature were discussed.

The finished PET fabrics imparted new properties such as antimicrobial and ultraviolet protection factor protection, what is undoubtedly will increase the spread of this type of fabric and its use in new areas.

The method used mainly depends on activating the surface of PET fabrics by a chemical method, specifically NaOH to cause partial decomposition, which may lead to an environmental impact.

The obtained results revealed that the simultaneous treatment of PET fabric with NaOH and TiO₂ NPs showed antimicrobial and UV protection properties. They exhibited a strong antimicrobial activity and UV protection efficiency even after five washing cycles, indicating excellent laundering durability.

The approach has simplicity and implementability on an industrial scale without cost investment.

The purpose of this paper is to provide a functional framework encapsulating a wide range of contributions to the ongoing debate on virtue as a critical dimension of contemporary organizations. In so doing, the authors elaborate and develop an encompassing framework that is in a position to capture the diversity of research in this very field.

Extant literature on virtue in organizational settings is properly categorized through a taxonomy articulated around the potential foci, as well as loci of virtuous behavior. Virtuousness denotes an ethical attribute of managers, leaders or employees and as such, it may be situated at the micro-individual, meso-organizational or macro-societal level, respectively.

Based on the potential foci and loci of virtuous behavior, the paper differentiates between virtuous managerial, leaders’ and employees’ attitudes on one hand, and virtuous management and leadership development, as well as virtuous employee training on the other. Furthermore, ethically grounded managerial initiatives and leaders’ responsibilities to further the common good are entwined with endeavors to transform employees into virtuous corporate citizens affirming organizational ethicality.

By identifying both targeted group and level of analysis, organizations can effectively design and implement interventions promoting virtuousness as a valued end in itself.

The paper introduces a framework that can help integrate varying trends on organizational virtuousness that substantially differ in terms of both scope and perspective. In addition, the taxonomy will facilitate both researchers and practitioners to better navigate into the dispersed, and ultimately fragmented streams of literature on the role of virtue in business environments.

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.

The reliability prediction is among the most important objectives for achieving overall system performance, and this prediction carried out by anticipating system performance degradation. In this context, the purpose of this research paper is to development of methodology for the photovoltaic (PV) modules' reliability prediction taking into account their future operating context.

The proposed methodology is framed by dependability methods, in this regard, two methods of dysfunctional analysis were used, the Failure Mode and Effects Criticality Analysis (FMECA) method is carried out for identification of the degradation modes, and the Fault Tree Analysis (FTA) method is used for identification the causes of PV modules degradation and the parameters influencing its degradation. Then, based on these parameters, accelerated tests have been used to predict the reliability of PV modules.

The application of the proposed methodology on PWX 500 PV modules' in different regions of Algeria makes it possible to predict its reliability, taking into account the future constraints on its operation. In this case, the temperature and relative humidity vary from one region to another was chosen as constraints. The results obtained from the different regions confirms the reliability provided by the designer of the Saharan cities Biskra, In Salah, Tamanraset, and affirms this value for the two Mediterranean cities of Oran and Algiers.

The proposed methodology is developed for the reliability prediction of the PV modules taking into account their future operating context and, the choice of different regions confirms or disproves the reliability provided by the designer of the PV modules studied. This application confirms their performance within the framework of the reliability prediction.