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The purpose of this paper is to develop a volatile organic component‐free water‐based binder with improved coating properties from urethane‐alkyd acrylate by emulsion polymerisation.

Alkyd resin based on interesterification of sardine fish and linseed oil (50:50 w/w) was synthesised and reacted with isophorone diisocyanate to form urethane alkyd. The resultant urethane alkyd and acrylic monomers in different ratios were polymerised by emulsion polymerisation to form air‐drying water‐based binders and studied for physicochemical and other coating properties.

Urethane alkyd, co‐polymerised with acrylates by emulsion polymerisation process, can be used to prepare water‐based air‐drying binders with excellent coating and application performance. The increase in acrylate component in the system resulted in improvement of performance properties.

In the present study, refined fish oil (FO) was obtained from sardine fish. Different FOs can be used to produce alkyd resin. Urethane alkyd and acrylic monomers in different ratios can be polymerised by emulsion polymerisation techniques.

The emulsion polymerisation is the most effective technique used to produce water‐based binders with excellent coating properties.

Water‐based binders can be widely used in exterior coatings and waterproofing of cement and roofs.

The purpose of this paper is to develop an inorganic-organic hybrid emulsion polymer using grafted hyperbranched alkyd modified with nanometal oxide and to study the performance of the developed hybrid emulsion in paint formulation with respect to antimicrobial and other properties.

A novel hybrid emulsion polymer was synthesized by grafting of vinyl acetate (VAM), vinyl ester of versatic acid (VeoVa 10) monomers onto hyperbranched alkyd resin and incorporation of nano magnesium oxide (MgO) into the hybrid resin matrix during dispersion of resin in water. Subsequently, paint was prepared by using this hybrid emulsion followed by a performance study.

The performance of nano MgO modified into VAM and VeoVa 10 grafted hyperbranched alkyd resulted in unique properties of coating especially antimicrobial activity.

In the present study, soya fatty acid, polyol and di basic acid have been used to prepare hyperbranched alkyd by condensation polymerization. Monomers like VAM and VeoVa 10 used for grafting onto hyperbranched alkyd and nano MgO have been incorporated into hybrid resin matrix during emulsification of hybrid resin in water.

Grafting of VAM and VeoVa 10 onto hyperbranched alkyd along with in situ incorporation of nano MgO in resin matrix is an effective technique to achieve excellent coating properties.

Nano MgO modified VAM and VeoVa 10 grafted hyperbranched alkyd-based hybrid emulsion can be used as binder in water-based metal primer, direct to metal (DTM) coating as well as topcoat application. The developed system has antimicrobial properties as well as superior mechanical properties.

The primary purpose of this work is to prepare the renewable source-based polyurethanes coatings which can be used to substitute petroleum-based materials. In the secondary purpose, the paper included improvement in the properties of said PU coatings using modified nano TiO₂ for industrial PU coatings.

The authors have synthesised low molecular weight polyols (monoglycerides) based on vegetable oils such as castor, linseed, coconut, mustard, sunflower and rice bran oils. These monoglycerides were successfully utilised in the preparation of polyurethane coatings. In order to improve the performance of these coatings, modified nano TiO₂ was incorporated into them. The particle size of TiO₂ was determined by transmission electron microscopy. Coatings prepared were characterised for their properties such as gloss, scratch resistance, impact resistance, flexibility, cross cut adhesion and chemical resistance. The thermal stability of coatings was also studied by thermo gravimetric analyzer.

The polyurethane coatings prepared from six monoglycerides of different oils with polymeric diphenyl methane diisocyanate showed good chemical resistance and thermal stability. Coating properties like impact resistance, flexibility and adhesion were excellent for all of the prepared samples of PU coatings. PU coatings with excellent hardness up to 5B were found with the modification of nano TiO₂ by silane coupling agent. The authors successfully prepared the renewable source-based (monoglycerides of oil) PU coatings.

Practically the authors are able to convert renewable source that is vegetable oils into polyurethane coatings which may have strong potential to be used as industrial surface coating. The properties of the PU coatings were evaluated before and after the incorporation of different concentration of surface-modified nano TiO₂ which revealed that the presence of 1 percent nano TiO₂ showed significant enhancement in coating properties.

The beauty of this work includes synthesis of polyurethanes coatings from renewable source material (monoglycerides of vegetable oils) to substitute petroleum-based materials. The incorporation of silane-modified TiO₂ nanoparticles in renewable source-based PU coatings is another originality of the work. This article is also representing comparative study of various vegetable oils on PU coatings.

This chapter proposes a test for a parametric specification of the autoregressive function of a given stationary autoregressive time series. This test is based on the integrated square difference between the empirical distribution function estimate and a convolution-type distribution function estimate of the stationary distribution function obtained from the autoregressive residuals. Some asymptotic properties of the proposed convolution-type distribution function estimate are studied when the model’s innovation density is unknown. These properties are in turn used to derive the asymptotic null distribution of the proposed test statistic. We also discuss some finite sample properties of the test statistic based on the block bootstrap methodology. A simulation study shows that the proposed test competes favorably with some existing tests in terms of the empirical level and power.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.

The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability.

Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions.

The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance.

Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories.

Compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

An investor is expected to analyze the market risk while investing in equity stocks. This is because the investor has to choose a portfolio which maximizes the return with a minimum risk. The mean-variance approach by Markowitz (1952) is a dominant method of portfolio optimization, which uses variance as a risk measure. The purpose of this paper is to replace this risk measure with modified expected shortfall, defined by Jadhav et al. (2013).

Modified expected shortfall introduced by Jadhav et al. (2013) is found to be a coherent risk measure under univariate and multivariate elliptical distributions. This paper presents an approach of portfolio optimization based on mean-modified expected shortfall for the elliptical family of distributions.

It is proved that the modified expected shortfall of a portfolio can be represented in the form of expected return and standard deviation of the portfolio return and modified expected shortfall of standard elliptical distribution. The authors also establish that the optimum portfolio through mean-modified expected shortfall approach exists and is located within the efficient frontier of the mean-variance portfolio. The results have been empirically illustrated using returns from stocks listed in National Stock Exchange of India, Shanghai Stock Exchange of China, London Stock Exchange of the UK and New York Stock Exchange of the USA for the period February 2005-June 2018. The results are found to be consistent across all the four stock markets.

The mean-modified expected shortfall portfolio approach presented in this paper is new and is a natural extension of the Markowitz’s mean-variance and mean-expected shortfall portfolio optimization discussed by Deng et al. (2009).

The study aims to evaluate the financial distress position of selected sample banks in India. The top 10 banks with the highest levels of gross non-performing assets (NPA) under both public and private sector ownerships have been chosen for the study. Application of the Altman Z-score model has been used to compare both ownership banks’ financial distress for five years from 2017 to 2021. Based on the study’s findings, it was found that private sector banks demonstrated better financial stability than their public sector counterparts. Specifically, the average Z-score of the selected sample banks was higher than the safe zone threshold of 2.9 during the study period.

The circular economy (CE) has become increasingly popular in recent years due to its potential in combining the economic growth positively with businesses, society and the environment simultaneously. The purpose of this review is to provide a concise summary of the existing literature regarding how CE strategies can help mitigate climate change.

A comprehensive review of extant literature is undertaken on the topic of CE and climate change. Six sectors are explored in this chapter; although these sectors are different, but still, they are interdependent and are not completely separate.

Thorough study of literature reveals that the energy, transport and manufacturing sectors have the greatest potential for reducing greenhouse gas emissions, while the waste and building sector have a moderate potential for savings. The agriculture sector, on the other hand, is predicted to have the lowest potential for savings.

This chapter provides implications for achieving a sustainable future in terms of economic growth, social harmony and environment conditions by developing efficient and affordable methods to achieve the goal of CE.

This chapter is a unique endeavour to explore the intricate relationship between CE and climate change. Although both concepts have been explored individually by various studies, but our study is one of the few attempts made to emphasise the crucial role of CE to mitigate the climate change.

Mobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.

The app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.

The high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.

The findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.

The previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.