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Long-term care (LTC) homes are highly regulated settings that provide care to people living with complex health conditions who are often at the end of their lives. Mental health and quality of life are important concepts in LTC given the inherent poor health and diminished autonomy of residents living in this setting. The COVID-19 pandemic had the potential to further compound these issues through lockdowns limiting movement within and outside of LTC homes, increased fear of severe COVID-19 infections, staff shortages, and impaired communication through personal protective equipment. However, the evidence describing the effect of the pandemic on mental health and quality of life is mixed, with some studies describing increased rates of mental health concerns and others presenting modest increases or decreases. Creative strategies to mitigate negative mental health consequences of lockdown included technology supported and window or outdoor visits, increased access to volunteers, and supports for families. However, the evidence in this area continues to evolve as subsequent waves of the pandemic progress. Future research may present new evidence about other strategies that became important in different stages of the pandemic.

Reynolds-averaged Navier–Stokes (RANS) models often perform poorly in shock/turbulence interaction regions, resulting in excessive wall heat load and incorrect representation of the separation length in shockwave/turbulent boundary layer interactions. The authors suggest that this can be traced back to inadequate numerical treatment of the inviscid fluxes. The purpose of this study is an extension to the well-known Harten, Lax, van Leer, Einfeldt (HLLE) Riemann solver to overcome this issue.

It explicitly takes into account the broadening of waves due to the averaging procedure, which adds numerical dissipation and reduces excessive turbulence production across shocks. The scheme is derived based on the HLLE equations, and it is tested against three numerical experiments.

Sod’s shock tube case shows that the scheme succeeds in reducing turbulence amplification across shocks. A shock-free turbulent flat plate boundary layer indicates that smooth flow at moderate turbulence intensity is largely unaffected by the scheme. A shock/turbulent boundary layer interaction case with higher turbulence intensity shows that the added numerical dissipation can, however, impair the wall heat flux distribution.

The proposed scheme is motivated by implicit large eddy simulations that use numerical dissipation as subgrid-scale model. Introducing physical aspects of turbulence into the numerical treatment for RANS simulations is a novel approach.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

Apparel manufacturers' achievement of green manufacturing (GM) goal remains low. This paper aims to identify and prioritise the barriers to GM implementation in apparel companies.

First, an extensive literature review is conducted to identify the key barriers to GM implementation. Second, 374 usable questionnaires are collected from apparel manufacturing companies to (a) examine the impact of and (b) rank the barriers. Third, interpretive structural modelling (ISM) is applied to test the relationships among barriers. Finally, structural equation modelling (SEM) is applied to improve the model derived from the ISM.

The results reveal that the independent barriers – lack of eco-literacy among upstream or downstream supply chain members, lack of specific company-level training and monitoring of the progress of GM implementation and inadequate support from regulatory authorities – are the root causes of all the barriers. These three barriers are also at a low level of the ISM model, indicating that they significantly affect the entire system and therefore should be accorded the highest priority in dealing with these barriers.

The results are useful for decision-makers and apparel companies to understand identified barriers, develop potential GM interventions and formulate appropriate strategies to overcome these barriers.

The listed barriers are yet to be comprehensively synthesised in a coherent model and empirically tested in the apparel sector using a combination of the ISM and SEM techniques. The empirically validated model presented in this study is an important step in that direction.

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand.

The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data.

Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility.

This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.

Companies are increasingly leveraging digital technologies toward innovation strategies that deliver novel features to customers sequentially through successive new product generations (i.e., successive innovation). Extant literature examining successive innovation is both limited and fragmented across marketing and management literatures. Our goal is to synthesize literature on concepts related to successive innovation (such as versioning and upgrades) to identify the core dimensions of successive innovation and provide a cohesive framework to guide future research in this domain.

Given the equivocality in understanding the conceptual domain of successive innovation, we review and synthesize literature across three disciplinary domains: marketing, management, and information and decision sciences. Based on the emerging patterns from the literature review, we develop a conceptual framework of successive innovation with the aim of moving the discussion toward greater theoretical clarity.

Based on the literature review and synthesis, we identify three core-dimensions that define successive innovation and compare these across digital and physical product realms: coexistence, embeddedness, and adoption controllability.

Our proposed conceptual dimensions of successive innovation, and discussion of differences across physical and digital product domains, offer important directions for future research and a common vocabulary.

As physical and digital successive innovations can differ in coexistence, embeddedness, and adoption controllability, firms need to consider relevant barriers to adoption of successive product generations and select appropriate strategies to promote and communicate successive innovation. Our proposed successive innovation conceptual dimensions help managers comprehend the complexity of arranging such innovation in business and consumer segments.

Our contribution to the emerging literature on successive innovation is threefold. First, by conducting a comprehensive literature review, we integrate insights from different fields of inquiry (i.e., marketing, management, and information and decision sciences). Second, based on the synthesis of the literature, we offer a conceptual framework of successive innovation, which aims to move the discussion toward greater theoretical clarity. Third, based on our review and conceptual framework, we discuss a set of future research directions to guide academic research efforts.

This paper aims to investigate the feasibility of developing an eco-friendly dyeing process for a regenerated polyester fiber (polytrimethylene terephthalate) using a natural dye (Lac) and bio-mordant.

The effects of temperature, time, initial pH of dye bath, material to liquor ratio and mordant concentration on color strength of polytrimethylene terephthalate fiber dyed with Lac were examined. The results were compared using three bio-mordant (catechu, myrobalan and pomegranate) and three inorganic mordant (alum, ferrous sulfate and stannous chloride). Single replicate of 25-design methodology was used to identify three significant factors affecting color strength, and optimization was done using response surface methodology based on 2³-central composite rotatable design.

Color strength achieved using catechu as a bio-mordant was close to that with ferrous sulfate and higher than with stannous chloride. Temperature, initial pH and mordant concentration were identified as significant factors affecting color strength of dyed fiber with catechu. Optimization revealed temperature of 133OC, initial pH of 6 and bio-mordant (Catechu) concentration of 10 per cent to be the optimal conditions for dyeing, with K/S value of 4.55.

The study revealed the possibility of satisfactory dyeing of regenerated polyester fibers with natural dyes, replacing disperse dyes. The comparison of color strength achieved indicated the possibility of replacing inorganic mordant with bio-mordant in such dyeing process. The dyeing process could thus be made more eco-friendly by removal of toxic chemicals from effluents.

World over organizations are focusing on sustainable goals, where along with economic success their role in protecting the planet and people are becoming important. Whilst transforming the supply chain into a sustainable one, there would be some barriers which might hinder this process. This paper aims to study these barriers in the context of the electronics industry so that organizations can better implement sustainable supply chain programs.

In this research, barriers affecting sustainability implementation in the electronics supply chain are shortlisted from literature review and experts’ opinion. Using the combined methodology of Grey DEMATEL, the causal factors, the effect factors and degree of prominence of barriers is found out. The overall relationship among barriers is established by a diagraph. Sensitivity analysis is performed to check the robustness of the results.

It is found that lack of regulation and guidance from authorities is the primary causal barrier affecting operations of sustainable supply chain management. There are five barriers which fall in the influenced group and among them, complexity in measuring and monitoring sustainability practices has the largest net effect value on the implementation of a sustainable supply chain. The barrier having the highest correlation with other barriers is the high cost for disposal of hazardous wastes. The implications of these findings on managers and academicians is explored in the study.

In this research, the number of barriers shortlisted is limited to 11 in the context of the electronics supply chain. More factors could be added in future research based on the industry being studied.

The research analyses 11 barriers under categories of policy, technology, financial and human resources in the Indian electronics industry by evaluating the cause and effect group of barriers. These results can guide policymakers of the electronic sector and industry for mitigating barriers during the implementation of sustainable programs.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.