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The purpose of this paper is to examine the impact of residential and commercial loans on total real estate sector loans by using partial least square–structured equation modelling (PL–SEM) method. The residential loans as a mediator have been used to know the mediation effect between commercial and total real estate loans of banks in India. The residential loans as a mediator govern the relationship between commercial loans and total real estate loans in India. Real estate sector development is a lucrative opportunity for India. The real estate sector plays a major role in shaping economic conditions of the individuals, firms and family.

The research is descriptive in nature. The study on residential loans, commercial loans and total real estate loans has been taken into consideration, and on the other hand the measurement and structural model have been employed to the study the impact of residential loans and commercial loans on total real estate loans in India by using PL–SEM. The residential loans as a mediator have been taken to study the mediation effect of the relationship between commercial loans and total real estate loans in India.

The outcome of the structural model that is bootstrapping technique shows that there is an impact of residential and commercial loans by public and private sector banks on total real estate sector development in India. The residential loans show the full mediation effect between commercial loans and total real estate loans as the value of variation accounted for (VAF) is more than 1.93 which shows residential loans govern the nature of variable between commercial loans and total real estate loans.

The public and private sector banks are contributing to the real estate sector development in India which increases the economic growth of the country. The mediation analysis shows that residential loans are an important aspect between commercial and total real estate loans in India as the demand for residential housing is more in India. The increasing role of banks in the real estate sector strengthens the financial capability in the real estate sector market, and the property buyers will able to purchase more property which leads to increasing demand for real estate sector.

The research paper is original, and PL–SEM has been used to find the results.

Smart cities are an attempt to recognize the pioneering projects designed to make the cities livable, sustainable, functional and viable. The purpose of this paper is to evaluate funding released by the government city wise and sources available for finance for the development of the smart cities. The impact of fund released by the government for the development of smart cities (Chandigarh, Karnal, Faridabad, Pune, Chennai, Ahmedabad, Kanpur, Delhi, Lucknow and Agra) in India has been studied in detail. Urbanization is a continuous process, which is taking place throughout the globe, especially in developing countries like India.

The research is descriptive in nature. The sources of funding for smart cities in India have been taken into consideration, and χ² test of independence has been employed to study the impact of fund released by the government for smart city development in India by using IBM SPSS.

The total investment, area-based projects, pan-city initiatives and O&M costs for smart cities ranged between Rs 133,368 and Rs 203,979 lakh crores, Rs 105,621 and Rs 163,138 lakh crores, Rs 26,141 and Rs 38,840 lakh crores, and Rs 1,604 and Rs 1,999 lakh crores, respectively, in the year 2016 (for 60 smart cities) to 2017 (for 99 smart cities), which shows an increasing trend. The investment in retrofitting projects, redevelopment projects, greenfield projects and area-based projects ranged between Rs 94,419 and Rs 131,003 lakh crores, Rs 8,247 and Rs 23,119 lakh crores, Rs 2,955 and Rs 8,986 lakh crores, and Rs 105,621 and Rs 163,138 lakh crores, respectively, in the year 2016 (60 smart cities) to 2017 (99 smart cities), which shows the division of projects funding for smart city development in India. The funding released for smart city development such as other sources, loans from the financial institution, private investment, convergence, state government share funding and Central Government Funding ranged between Rs 14,828 and Rs 15,930 lakh crores, Rs 7,775 and Rs 9,795 lakh crores, Rs 30,858 and Rs 43,622 lakh crores, Rs 25,726 and Rs 43,088 lakh crores, Rs 27,260 and Rs 45,695 lakh crores, and Rs 29,207 and Rs 47,858 lakh crores, respectively, in the year 2016 (60 smart cities) to 2017 (99 smart cities), which reflects the different sources of funding for the development of smart cities in India. The χ² test of independence has been applied, which shows that there is no impact of fund released by the government on cities for smart city development in India as the p-values of Chandigarh (0.213), Karnal (0.199), Faridabad (0.213), Pune (0.199), Chennai (0.213), Ahmadabad (0.199), Kanpur (0.199), Delhi (0.199), Kolkata, Lucknow (0.213) and Agra (0.199) are greater than 0.05.

For the Smart Cities Mission to be financially sustainable, the right policy and institutional framework should be implemented for modernization and aggregation of government landholding. Consolidation of all the landholdings under the smart city project should be properly implemented, and the role of private sectors should be encouraged for public‒private partnership projects to make Smart City Mission more successful.

The benefits of smart cities development will help provide affordable, cleaner and greener housing infrastructure for all, especially the inclusive group of developers belonging to the lower middle-income strata of India, and the benefits will be replicated when adopted on a smaller scale in the rural part of the country.

The research paper is original and χ² test has been used to study the impact of fund released by the government for smart city development in India.

Modern thermal and non-thermal pretreatment techniques, namely, enzymatic treatment, gas phase plasma treatment and ohmic heating have become more pronounced over conventional techniques for enhanced coloured phytochemicals (pigments) extraction. Presently, numbers of pretreatment techniques are available with some unique feature. It is difficult to choose best pretreatment method to be employed for phytochemicals extraction from different sources. Therefore, this paper aims to discuss different modern pretreatment techniques for extraction with their potential results over conventional techniques.

Research and review articles targeting to the thermal and non-thermal pretreatment techniques were collected from Google Scholar. The required information has been tabulated and discussed which included qualities of modern pretreatment techniques over conventional techniques, phytochemical extraction and best pretreatment methods for optimized results.

Every pre-treatment has its own advantages and disadvantages for a particular phytochemical and its extraction from various sources. Enzymes can be used in combinations to enhance final yield like extraction of carotenoids (pectinase, cellulase and hemicellulase) from chillies and lycopene (pectinase and cellulase) from tomato. Utilization of each method depends upon many factors such as source of pigment, cost and energy consumption. CO₂ pretreatment gives good results for carotenoid extraction from algae sources. Ohmic heating can yield high anthocyanin content. Modifications in conventional blanching has reduced final waste and improvised the properties of pigment.

This study comprises collective information regarding modern pre-treatment for extraction over conventional pre-treatments. The study also covers future trends and certain new hybrid approaches which are still less flourished.

The outbreak of COVID-19 saw a robust increase in viewership of over-the-top (OTT) media platforms. This study aims to investigate the impact of COVID-19 on OTT platforms in India, as it has led to reshaping consumer content preferences.

The authors have conducted primary research by doing a survey and focus group discussion. The first study has focused on the impact of various factors such as time, content, convenience, satisfaction and work from home (WFH) on OTT platforms during the COVID-19 crisis and the second study has focused on change in behavior of people before and during lockdown using visual representation.

The findings of this study show that lockdown has played a major role in the increase in viewership of OTT platforms, as people working from home are also using OTT platforms more. The average hours spent on OTT have increased from 0–2 to 2–5 h and average spending that users are willing to make on OTT platforms is Rs 100–300 (per month). The satisfaction level of customers is directly related to space to watch with family, time to use OTT platforms, the quality of content on OTT platforms and preference of OTT platform over television. Also, factors such as age group, occupation, city and income groups also determine the usage of the OTT platform.

The main contribution of this paper is to analyze the customer needs that impact their satisfaction level.

This study aims to analyze the perceptions of smallholder farmers on climate change and events and further explores climate change adaptation strategies and associated challenges. The findings provide useful information for enhancing the adaptive capacity of smallholder farmers to adjust to climate-related hazards and improve their resilience and disaster preparedness in northern Ghana.

This study uses a multistage sampling procedure and sample size of 150 farmers, the Binary Probit Model (BPM), to identify and examine the determinants of climate change adaptation strategies adopted by smallholder farmers. Also, the constraints of adaptation were analyzed using Kendall’s coefficient of concordance.

The results from the BPM and statistics of Kendall’s coefficient revealed that the farm risk level, ability to adapt, farmer’s income, age, farming experience, climate change awareness and extension visits were factors that significantly influenced the adaptation strategies of smallholder farmers (in order of importance). The majority (60%) of the farmers ranked farm risk level as the major constraint to adopting climate change strategies.

The findings of this study enhance understanding on access to relevant and timely climate change adaptation information such as an early warning to farmers during the start of the farming/rainy season to support their adaptive responses to climate change.