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The purpose for writing this article is derived from the misery and chaos prevalent in the world due to the coronavirus pandemic – since late 2019 and still continuing as of December 2020.

A blockchain-based solution to verify the country visit trail and disease and treatment history of the passengers who arrive at the immigration counters located at various national borders and entry points is proposed. A fuzzy inference based suspect identifier system is also presented in this article that could be utilized to make further decisions based on the degree of suspicion observed on a particular passenger.

This paper attempted to put forth a blockchain-based system which consumes the healthcare and visit trail summary of a passenger (appearing for an interview before an immigration officer) and forwards it to a fuzzy inference system to reach to a conclusion that the passenger should be advised to self-quarantine, detained, or should be allowed to enter. Such a system would help to make correct decisions at the immigration counters to check pandemic diseases, like COVID-19, right at the entry points.

The implications of this work are manifold. First, the proposed framework works independent of the type of pandemic and is a readymade tool to check the spread of disease through infected human carriers. Second, the proposed framework will keep the mortality rates under check, which would give ample time for the authorities to save the lives of the people with co-morbidities and age vulnerabilities (Vichitvanichphong et al., 2018). Third, it is a general phenomenon to restrict the flights from the country where the first few cases of infection are discovered; however, the infected person, at the same time, might travel through alternative routes. The blockchain-enabled proposed framework ensures the detection of such cases at no other cost. Finally, the solution may appear costly in the first place, but it has the potential to hold back the revenue of the countries that would otherwise be spent on reactive measures.

As of now no other study or research article provides the solution to the biggest problem persists in the world in this way. The contribution is original and worth applying.

The purpose of this paper is to develop chicken cutlets enrobed with bread crumbs vis-à-vis dried carrot pomace and to assess its effect on physico-chemical properties, sensory attributes and texture profile analysis.

Three experimental groups were made: control group chicken cutlets (C), chicken cutlets enrobed with bread crumbs group (T_b) and chicken cutlets enrobed with dried carrot pomace group (T_c). All the procedures used in the study for estimation of various physico-chemical properties, sensory evaluation and texture profile analysis were standard protocols.

There was a significant (p < 0.05) increase in water holding capacity, crude fibre content and ash content of enrobed chicken cutlets, whereas moisture, fat content and shrinkage of product were significantly (p < 0.05) decreased. The results for sensory evaluation and texture profile analysis of enrobed chicken cutlets were better than control group. Overall acceptability score of chicken cutlets enrobed with dried carrot pomace was revealed to be highest (7.5 ± 0.29) and that of control group was found to be lowest (6.4 ± 0.22). Hardness (N/cm²) value found for control group chicken cutlets, chicken cutlets enrobed with bread crumbs group and chicken cutlets enrobed with dried carrot pomace group were 2.2 ± 0.17, 3.1 ± 0.29 and 4.3 ± 0.27, respectively.

Future research may benefit to assess the effect of enrobing with bread crumbs and dried carrot pomace on mineral and vitamin content and lipid profile of meat products.

Enrobing of chicken cutlets with bread crumbs and dried carrot pomace improved the sensory attributes along with texture profile analysis. Hence, enrobing with bread crumbs and dried carrot pomace could be used as processing technology to improve sensory appeal, especially crispiness of meat products.

This study aims to develop and demonstrate a deposition framework for the implementation of a region-based adaptive slicing strategy for the Tungsten Inert Gas (TIG) welding-based additive manufacturing system. The present study demonstrates a deposition framework for implementing a novel region-based adaptive slicing strategy termed as Fast Interior and Accurate Exterior with Constant Layer Height (FIAECLH).

The mentioned framework has been developed by performing experiments using the design of experiments and analyzing the experimental data. Analysis results have been used to obtain the mathematical function to integrate customization in the process. The paper, in the end, demonstrates the FIAECLH framework for implementing region-based adaptive slicing strategy on the hardware level.

The study showcase a new way of implementing the region-based adaptive slicing strategy to arc-based metal additive manufacturing. The study articulating a new strategy for its implementation in all types of wire and arc additive manufacturing processes.

Wire-arc-based technology has the potential to deliver cost-effective solutions for metal additive manufacturing. The research on arc welding-based processes is being carried out in different dimensions. To deposit parts with complex geometry and better dimensional accuracy implementation of a novel region-based adaptive slicing strategy for the arc-based additive manufacturing process is an essential task. The successful implementation of an adaptive slicing strategy would ease the fabrication of complex geometry in less time. This paper accomplishes this need of implementing a region-based adaptive slicing strategy as no experimental investigation has been reported for the TIG-based additive manufacturing process.

The volatile nature of foreign portfolio flows, especially flows into debt market, has large implications on financial and macroeconomic stability in recipient countries. It is necessary to identify the main drivers of portfolio investments in bond market of developing economies to design effective policies to enhance resilience of the economy and help in managing capital flow volatility. The determinants of foreign portfolio investment to Indian equity market have been examined in literature, but flows to bond market remain unexplored. Thus, the purpose of this paper is to identify the possible determinants of foreign portfolio flows to Indian bond market both in the short and in the long run.

This study carries out a time series analysis by deploying autoregressive distributed lag (ARDL) approach to cointegration of monthly data of the period from January 2002 to December 2016 for the Indian economy. A mix of pull and push factors has been analysed in this study. Domestic growth, domestic stock market performance, interest rate differential, exchange rate, volatility in exchange rate, stock market returns in other emerging economies, foreign output growth and dummy variables to trace the external developments such as global financial crisis and unconventional monetary policies of advanced economies have been used as explanatory variables.

The dominant pull factor such as interest rate differential explains the dynamics of flows in Indian bond market. The relationship between capital movements and interest rate differentials is the most accepted paradigm in international finance (Haynes, 1988). Among other domestic factors are stock market performance, volatility in exchange rates and domestic growth rates which are found to be significant drivers of foreign portfolio bond flows to India. The study also confirmed that global conditions could induce a fast outflow of capital from India.

The study concludes that both domestic factors and external factors are equally important in determining the foreign portfolio investments in the Indian debt market.

The empirical analysis conducted in this study suggests that direct and indirect measures can be taken to increase and stabilise foreign investments in the Indian bond market. Direct policy measures refer to those tools which are under the ambit of policymakers. Indirect measures comprise those tools that are not under the direct control of the fiscal and monetary authorities but require coordinated efforts of the government and private sector. In this context, strengthening of not only financial and economic but also administrative institutions will be necessary. Creditworthiness and policy credibility should be improved to address erratic foreign portfolio investment in debt market of India.

This study is an original research study. This study adds to the existing literature and is expected to guide policymakers on the specific aspect of the management of capital flows as it gets affected by changes in monetary and fiscal policies.

The purpose of this paper is to propose a conceptual framework for the application of blockchain in the Public Distribution System (PDS) in India to manage the supply of food grains to the targeted beneficiaries. The framework will help prevent diversions and leakages of grains at the warehouse and Fair Price Shop (FPS) level. The paper also identifies the enablers and disablers in the context of the framework.

This paper will firstly review the previous literature in PDS and blockchain-enabled agricultural and food supply chains. The study then proposes a framework that could be implemented in the PDS in India using blockchain technology.

The proposed framework provides an effective way to combat corruption, exclusion errors of targeted beneficiaries, leakage of PDS food grains and is cost-effective. The identified enablers and disablers give an insight into the application of blockchain in PDS in India.

The research work may have implications for the Ministry of Food and PDS (Central Government), Food Corporation of India and State Governments to manage the supply of the grains more efficiently and effectively.

The current study caters to the implementation of blockchain technology starting from the warehouse level to the FPSs and consumers and simultaneously connecting them to concerned authorities to ensure transparency and accountability.

After working through the case, the students should be able to understand Indian political economy and the brand building process of NaMo; identify the media mix strategies used to build the brand NaMo in India; evaluate possible future growth strategies for brand NaMo; and compare and contrast brand NaMo with business brands.

Narendra Modi popularly called as NaMo was the current Prime Minister of India. He belonged to Bhartiya Janata Party (BJP) which won India’s general elections in two consecutive terms 2014 and 2019. NaMo was recognised worldwide for his prudence in leading the country to greater heights of achievement. NaMo started his political journey as the worker of BJP at a tender age. His rise in political career was akin to flagship brand overtaking the parent brand. All the steps taken in the past to position himself as a cult brand, will it fortify to NaMo’s victory in 2024 general elections? Business firms may follow NaMo’s strategies. What can the business brands emulate from NaMo to market and position themselves? Can political success be transpired to business success?

This case is designed for use in a graduate-/postgraduate-level marketing course in segments on brand management, brand expansion and the marketing strategies of a market leader. The case can also be used in a brand management course to discuss brand management models (e.g. Keller’s brand resonance pyramid and brand value chain). This case has particular application for classes that focus on brand equity, STP for any brand (segmentation, targeting and positioning) and brand value chain. The case looks in detail at the Indian political market and brand building process of NaMo and examines competitive moves since its inception. This case can be used in brand management, media management courses. The dilemma can be explained as part of a marketing course for postgraduate and executive programmes.

Teaching notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes.

CSS 8: Marketing.

The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).

The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.

The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.

By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.

The purpose of this paper is to investigate the relationship between dividend policy and the life cycle of firms in India. In addition, this study intends to examine the variation in dividend behaviour over the life cycle of a firm. The study anticipates that a firm's dividend behaviour varies over its life cycle.

To scrutinize the validity of the proposition, the authors classify 1968 non-financial industrial firms listed at Bombay Stock Exchange (BSE) into growth, mature and stagnant firms over the period 2000–20. Additionally, to check the robustness of the results, they use an array of techniques such as analysis of variance, pooled ordinary least squares, fixed effects models and random effects models.

The empirical findings suggest that dividend behaviour varies over a firm's life cycle. Specifically, stagnant firms are paying significantly higher dividends than growth firms. Mature firms are paying significantly higher dividends than growth firms. The results are consistent after controlling the effects of firm's size, profitability, leverage, operating risk, systematic risk and growth opportunities.

The findings are useful for corporate decision makers in establishing an appropriate dividend policy conditional on firms' life cycle stage and for shareholders in making investment decisions.

The relation between dividend policy and firm life cycle has not been examined before in the context of Indian stock market. Thus, this research bridges this gap in the literature.

This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.

This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.

The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.

To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.