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This concluding article summarizes the main findings in response to the theme issue strategic question: How are hospitality and tourism businesses in India responding to the COVID-19 pandemic?

The conclusion identifies some contemporary and relevant areas for development in the post-pandemic era. To summarize, this paper draws out the key findings of the theme issue articles and presents the main recommendations for industry action.

This conclusion highlights emerging issues for Indian hospitality and tourism businesses and includes specific recommendations for industry professionals, policymakers and other stakeholders in relation to strategies that could be adopted to mitigate the impact of the COVID-19 pandemic.

Given the wide impact of the pandemic across industries, this issue will be of interest to practitioners, higher education leaders, policymakers and other stakeholders as it draws on industry-focused research to explore the challenges and possible solutions to current and pending challenges. This issue also provides insights for further collaborative research.

This article provides insights from practitioners and academics relating to the current and on-going impact of the COVID-19 pandemic and developmental steps that the hospitality and tourism industry in India is taking in response.

The purpose of this paper is to electrically examine the quality of thin thermally grown SiO₂ with thickness variation, on Si‐face of 4H‐SiC <0001> (having 50 μm epitaxial layer) by current‐voltage (I‐V) and capacitance‐voltage (C‐V) methods.

Metal‐oxide‐silicon carbide (MOSiC) structures with varying oxide thickness have been fabricated on device grade 4H‐SiC substrate. Ni has been used for gate metal on thermally oxidized Si‐face and a composite layer of Ti‐Au has been used for Ohmic contact on the highly doped C‐face of the substrate. Each structure was diced and bonded on a TO‐8 header with a suitable wire bonding for further testing using in‐house developed LabVIEW‐based computer aided measurement setup.

The leakage current of fabricated structures shows an asymmetric behavior with the polarity of gate bias ( + V or −V at the anode). A strong relation of oxide thickness and temperature on effective barrier height at SiO₂/4H‐SiC interface as well as on oxide charges have been established and reported in this paper.

The paper focuses on the development of 4H‐SiC based device technology in the fabrication of MOSiC‐based integrated structures.

The purpose of this paper is to present a selective wet‐etching method of boron doped low‐pressure chemical vapour deposition (LPCVD) polysilicon film for the realization of piezoresistors over the bulk micromachined diaphragm of (100) silicon with improved yield and uniformity.

The method introduces discretization of the LPCVD polysilicon film using prior etching for the grid thus dividing each chip on the entire wafer. The selective etching of polysilicon for realizing of piezoresistors is limited to each chip area with individual boundaries.

The method provides a uniform etching on the entire silicon wafer irrespective of its size and leads to economize the fabrication process in a batch production environment with improved yield.

The method introduces one extra process step of photolithography and subsequent etching for discretizing the polysilicon film.

The method is useful to enhance yield while defining metal lines for contact purposes on fabricated electronic structures using microelectronics. Stress developed in LPCVD polysilicon can be removed using proposed approach of discretization of polysilicon film.

The work is an outcome of regular fabrication work using conventional approaches in an R&D environment. The proposed method replaces the costly reactive ion etching techniques with stable reproducibility and ease in its implementation.

Employment exchanges have been playing a significant role in the worldwide labor market for more than a hundred years now. In India, since 1946, millions of aspiring Indian youths have registered themselves with the government-run employment exchanges to find a job. About four million job seekers got registered at 1,000 employment exchanges in India, it is important to analyze the placement statistics of these exchanges. In recent years, new methods of job search have evolved. This study examines whether employment exchanges are effective in the changed scenario?

Using state-level employment exchange data for the period 2010–2011 to 2019–2020, this study analyzes the determinants of job placement at employment exchanges in India. A critical analysis of the functioning of employment exchanges along with recommendations to improve the job search ecosystem in India is also presented in the study.

This study found that increased share of service sector in the state economy negatively impacts placement at employment exchanges.

The absence of focus on the service sector requires policy intervention if Indian employment exchanges are to remain relavant.

The government administration should rethink that ignoring service sector employment potential is unaffordable for an emerging economy and employment exchanges should be aligned accordingly.

About 30 million people are unemployed in India. If employment exchanges are transformed, it can have far-reaching socio-economic advantages.

This study is the first sub-country level study on the institution of employment exchanges. This study comprehensively maps the landscape of career services in India. Empirically establishing the impact of sectoral structure of economy on efficacy of employment exchanges, and makes the case for policy intervention that is needed to keep the employment exchanges relevant in India.

Heightened public concerns for the global environment due to human overexploitation have given rise to many green product initiatives by businesses. Green cosmetics (GC) are products developed and marketed based on ecological sustainability and have shown increasing consumer appeal worldwide. The current research investigates the antecedents of green cosmetics consumption among Indian GC users, hitherto un-investigated comprehensively.

The study is a cross-sectional pairwise comparison of green evaluation criteria for cosmetics using an expert panel of thirty Indian cosmetic users using a fuzzy analytic hierarchy process (F-AHP) and investigate the impact of a comprehensive list of antecedents on the multi-criteria category consumption decision.

The study results indicate that perceived consumer effectiveness is the most critical factor for green cosmetics consumption in India, followed by brand trust, behavioural control, and environmental effectiveness. The least important factors are price and social norms.

As the GC category is at nascent stage in India the investigation is limited to the GC category innovators – a set of people high in intellectual and financial resources. The study is also limited to women users as the male cosmetic market in the country is still very small.

The study results can help marketers in designing and implementing GC related marketing strategies to deliver higher customer value to the target segment. Academicians can use the study results for better prediction of category related behaviour of consumers.

The study results will help promote GC category adoption and usage which can benefit the environment and consumer health.

The study contributes to literature and practice by assessing a comprehensive set of critical antecedents to GC adoption using a novel approach of F-AHP and an expert user panel. The study results offer insights to marketers that can be used to develop suitable strategies to convert non-GC users into GCs in India and similar markets, improving category penetration and benefitting marketers, retailers, users, and the environment.

COVID-19 disrupted the lives of consumers across the globe, and the retail sector has been one of the hardest hits. The impact of COVID-19 on consumers' retail choice behaviour and retailers' responses has been studied in detail through multiple lenses. Now that the effect of COVID-19 is abating, there is a need to consolidate the learnings during the lifecycle of COVID-19 and set the agenda for research post-COVID-19.

Scopus database was searched to cull out academic papers published between March 2020 and June 6, 2022, using keywords; shopping behaviour, retailing, consumer behaviour, and retail channel choice along with COVID-19 (171 journals, 357 articles). Bibliometric analysis followed by selective content analysis was conducted.

COVID-19 was a black swan event that impacted consumers' psychology, leading to reversible and irreversible changes in retail consumer behaviour worldwide. Research on changes in consumer behaviour and consumption patterns has been mapped to the different stages of the COVID-19 lifecycle. Relevant research questions and potential theoretical lenses have been proposed for further studies.

This paper collates, classifies and organizes the extant research in retail from the onset of the COVID-19 pandemic. It identifies three retail consumption themes: short-term, long-term reversible and long-term irreversible changes. Research agenda related to the retailer and consumer behaviour is identified; for each of the three categories, facilitating the extraction of pertinent research questions for post-COVID-19 studies.

The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

The purpose of the article is to construct a new class of higher-order iterative techniques for solving scalar nonlinear problems.

The scheme is generalized by using the power-mean notion. By applying Neville's interpolating technique, the methods are formulated into the derivative-free approaches. Further, to enhance the computational efficiency, the developed iterative methods have been extended to the methods with memory, with the aid of the self-accelerating parameter.

It is found that the presented family is optimal in terms of Kung and Traub conjecture as it evaluates only five functions in each iteration and attains convergence order sixteen. The proposed family is examined on some practical problems by modeling into nonlinear equations, such as chemical equilibrium problems, beam positioning problems, eigenvalue problems and fractional conversion in a chemical reactor. The obtained results confirm that the developed scheme works more adequately as compared to the existing methods from the literature. Furthermore, the basins of attraction of the different methods have been included to check the convergence in the complex plane.

The presented experiments show that the developed schemes are of great benefit to implement on real-life problems.

This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security).

The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t-tests.

The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences.

Previous studies have looked into impulse buying in its generic sense and not through the “types” of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour.

The Quadrilateral Group for Security Dialogues (QUAD), comprising Japan, Australia, India, and the USA, has experienced a noteworthy escalation in both environmental depletion and economic performance over the preceding 2 decades. Consequently, it becomes crucial to outline strategies through which the QUAD can attain a harmonious equilibrium between sustainable economic growth and ecological well-being. This research endeavors to dissect the intricate relationships among trade globalization, regulatory quality, and environmental sustainability within the QUAD for the period 1990–2021. The study checks for the Pollution Haven Hypothesis (PHH), and Pollution Halo Effect Hypothesis (PHEH).

The long-run association is based on the autoregressive distributed lag (ARDL) model and bounds test approach to cointegration while divergence or convergence is studied with the help of decoupling index (DI). Results have been verified by applying serial correlation LM test, autoregressive conditional heteroskedasticity (ARCH), and cumulative sum of recursive residuals (CUSUM) tests to ensure the robustness and stability of the model.

The empirical results of this study affirm the applicability of the PHEH in the contexts of India, Japan, and the USA, whereas the PHH is validated in the case of Australia. Furthermore, the analysis reveals the existence of relative decoupling solely in the case of India. This testifies that the rate of growth of the Indian economy surpasses the rate of growth in ecological footprint (EF), indicating a relative reduction in the intensity of environmental impact per unit of economic growth.

The empirical findings of our study suggest that countries with effective regulatory systems are better positioned to control and mitigate the potential adverse environmental effects resulting from increased global trade. Thus, policymakers are prompted to reassess the development policies for sustainable economic growth that will minimize adverse environmental repercussions. The implication of the negative relation between urbanization and EF is paramount for policymakers in developing countries seeking strategies for balanced urban development that aligns with environmental sustainability.

The present study is a unique exploration of the impact of trade globalization and regulatory quality on EF, specifically on PHH/PHEH in the context of QUAD.