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In this paper, life cycle economic analysis (LCEA) of stand-alone solar photovoltaic (PV) modules is performed. It is tested for their commercial prospects in remote regions of India, which do not have a direct access of grid supply. Availability of grid supply depends on the population density. Solar PV technology is one of the first among several renewable energy technologies that have been adopted worldwide for meeting the basic needs of generation of electricity particularly in remote areas. Overall lifetime expenditures related to the power projects are analyzed and compared with the help of net present worth (NPW) theory. In the context of a developing country like India, it is found that the cost effectiveness of conventional or ‘green’ power driven sources depends on kW rating of generators and daily demand of consumers. The demand coverage, which would determine the commercial viability of renewable and non-renewable sources is calculated considering the practical power rating of generators available in the local market. This study is intended to assist planning of financial matters with regard to installing small to medium scale electric power generation using solar PV module in remote areas of India.

This paper investigates the selection of semiconductor switches used in contactless power transfer (CPT) system. In the present paper a single phase high frequency full bridge inverter using different semiconductor switches like IGBT, MPOSFET and GTO has been considered. Harmonic injection in input current of the inverter for different semiconductor switches has been analyzed using PSIM software. The THD of input current of the inverter for the particular switching device has been determined by using Fourier Transforms. It has been observed that THD in case of the IGBT is minimised.

Rising crude oil prices are likely to have an asymmetric and nonlinear negative impact on GDP growth. The purpose of this paper is to ask the following questions: Does the effect of a crude price shock depend on the position of crude price cycle, i.e. is the effect of price shock larger/smaller in periods of already elevated crude price? And, does the effect of crude price shock depend on the position of the economy in the business cycle, i.e. does the crude price shock affect growth differentially in periods of low/high growth?

The authors use a local linear projection (LLP) model to examine the asymmetric impact of crude price on GDP growth in an environment of high crude price. Next, a quantile regression model is used to account for differential impact on growth around high and low growth periods.

Results from the LLP model show that when oil price is above $70, each additional percentage point of increase in oil price results in a 20 basis point (bps) drop in quarterly GDP growth rate on average. The impact is felt between the third and sixth quarters. When oil prices rise above $80, the impact is similar, with a sharper drop in growth (30 bps). The exercise with quantile regression shows that the impact of an increase in crude prices on growth is almost double at lowest quantiles of growth compared with the median.

There is a growing literature that evaluates the impact of oil price in developing economies. However, nonlinearities in crude price-GDP growth dynamics have not received enough attention, especially during phases of elevated crude price or a growth downcycle. The authors believe that accounting for such effects is especially relevant in the present economic scenario of high oil prices because of geopolitical crises and a period of vulnerable growth because of supply chain issues arising out of the pandemic. Using recent data from oil-importing emerging market economies such as India, this paper fills a crucial gap in the literature.

Sultanate of Oman witness a long summer with mostly clear blue skies and typically higher ambient temperatures as seen in other GCC countries. This type of environment warrants the use of high capacity and reliable air conditioning systems, both at resident buildings and vehicles. During summer, cars parked directly under the sun, experience a very high temperature rise inside its cabin in the range of near to 50 °C. This high cabin air temperature often causes thermal discomfort to passengers entering the parked car and also has a serious impact on the cars air-conditioning systems, as it takes longer time to bring back the thermal comfort inside the cabin. The studies also revealed that the high cabin temperature often causes health hazards to occupants, especially to infants. Current research paper, reports an experimental study carried out on a parked car, with instrumentation to identify the various the temperature zones inside the car cabin. This experiential study is aimed to improve the thermal comfort inside the cabin through solar powered cabin air ventilator for effective management of cabin air temperature. The study was carried on a chosen vehicle parked at a set direction and location exposed to day long sunlight at Muscat for considerable period of time. Firstly, the study identified the various temperature zones inside the car cabin and ventilation driven with a 10 Wp solar panel was developed to accomplish the required air exchange inside the cabin, along with continues instantaneous heat rejection through steady air exchange between inside and outside environment. A simple ventilator was developed by means of two fans which drove out the hot trapped air and a secondary fan to cool down the temperature inside the car by providing fresh air for limited time. The experimental investigation showed that the vehicle cabin temperature was typically 10 °C lower when ventilator was turned on. On a typical day on month of May, the cabin air temperatures was approximately 21 °C higher than the ambient air temperature, while with the developed ventilator the difference between the cabin and outside air temperature was reduced by 50% approximately. With the ventilator in operation, it was observed that time taken to reduce the cabin air temperature through vehicle air conditioning system to a satisfactory level was much quicker; typically it took less than the half of the time compared to those values tested without ventilator. Thus indicating, the power saving potential of the developed system as the desired level of thermal comfort can be achieved within the shorter period of time. The reduction in time taken to cool down the cabin temperature to the acceptable limits has direct two fold effects; firstly, the fuel consumption for cooling purpose is reduced and secondly, increased thermal comfort level inside the cars cabin. However, the temperature drop pattern was not similar all around the cabin, due to the varied level of cabin sunlight exposure. Temperature drop at the front of the car was lower than in middle and rear of the car. From the study it can be concluded that, with solar powered ventilator, the temperature inside the car was nearly 10 °C lesser compared to cabin without ventilator and it also helps in to bring back the thermal comfort inside the cabin nearly within half time vis-à-vis cabin without ventilation.

Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.

The purpose of this paper is to examine the causal relationship between economic development and financial sector development for 28 countries at different stages of their development. The authors specifically focus on the nature of causality during economic boom and tranquil cycles.

The study uses quarterly time series panels of 17 developed and 11 emerging countries, during 1993Q1-2014Q4 with each having three sub-panels – full sample, a period of the economic uptrend (UP), and period of the economic downtrend. The authors use a univariate analysis for initial screening followed by panel unit root test, panel co-integration and causality test proposed by Toda–Yamamoto to examine the causal relationship.

The principal results suggest that for developed economies, there is a causal flow from financial sector to real sector in line with the “supply-leading” hypothesis, whereas for emerging economies, it is from real sector to financial sector, in line with the “demand-following” hypothesis. This overall relationship is strong for both emerging and developed economies during economic boom or UP cycles, but becomes weak during economic downturns or tranquil periods.

This study is different from previous studies on this issue and contributes to the existing literature in a number of ways. First, the focus of this paper revolves around identification of differential patterns in causal flows between real and financial sectors for different economies, across different economic cycles. Second, to present a robust representation of financial sector, the authors consider both banking sector and stock market parameters as the proxy for financial sector development. Third, the authors address the “stock-flow problem” in the measurement of financial variables a typical criticism of some of the previous studies. Finally, the authors use a rich sample size comprising of about 2,500 quarterly observations for each variable, with about 1,500 observations from developed and 1,000 from emerging economies.

Corporate social responsibility (CSR) was mandated and institutionalised in India through the Companies Act (2013), a decade ago. It is critical to understand the priorities of the models used by the companies to effectuate their CSR policy. This paper aims to understand the skewing of interest towards Education and Health interventions. The paper then proposes a framework to cross-level and effectuate CSR programme implementation.

The qualitative study conducted in-depth interviews of the stakeholders from the CSR environment. The findings are used to derive a model to effectuate CSR in India.

The findings may be divided into two sub-themes – (a) observations from the field study and (b) integrated solution ecosystem (ISE) framework. The qualitative study and the insights form the first component. The proposed framework which can enhance the efficiency of CSR practices may be found in the second sub-theme.

Operationalisation of the proposed model, if adopted would require integrated efforts from multiple functional departments which could lead to an extended timeframe for implementation. This may eventually lead to a need to revise the model in the making. The research could also include perspectives from governmental stakeholders which is missing here.

The emerging model can present an opportunity for corporates and policymakers to revisit the CSR structure and frameworks. It can also be used to evaluate and audit the CSR practices of companies.

The ISE posits a bunch of actionable themes which can deliver an impactful transition from the existing approach to CSR to a more far reaching one. While the ground rules are revisited, the approach also allows a critical departure from a corporate-driven model of engagement with the community. The modifications or corrections in this model would also mean a more inclusive layering of developmental interventions. The diversity which could potentially be brought in to designing interventions can be another key impact.

This paper presents insights for some of the pivotal stakeholders of CSR in countries like India. It presents a possible model of effective and optimal utilisation of CSR spending.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

This study aims to examine the association between risk tolerance and risky investment intention with financial literacy as a moderating variable. The proposed relationship was explored specifically for millennials.

The questionnaire was divided into three segments to assess millennials' financial literacy, risk tolerance and risky investment intention. This study uses survey data from 402 millennial investors residing in Delhi-NCR region. The authors exploited PLS-SEM for the analysis because the model involved higher-order constructs.

The findings revealed that financial literacy has a negative impact on risky investment intention. Further, risk tolerance had a positive and significant influence on risky investment intention; however, when financial literacy was added as a moderating variable in this relationship, it had a negative impact on risky investment intention.

Every generation has its quirks, and millennials are no exception. Given their age and sheer number, leading to their dominance in the global workforce, millennials will bring about a generational shift. Awareness of Gen Y's financial literacy and risk behavior enhances their ability to make informed financial decisions, thus proving beneficial not only to them, but also to the whole economy. This will also help policymakers and institutions to introduce financial literacy programs and financial products in alignment with their needs and preferences.