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The aspect of economic contrast seen in developing countries shoots primarily from the structure of loan allocation to the micro, small and medium enterprises (MSME) sector, which is essential for job creation and understanding the role of microfinance institutions (MFIs) in meeting the credit demands of the vulnerable but vital sector of less developed economies. The study demonstrates the impact of MSME protection in terms of both fixed and adjustable factor coefficient settings, creating a model of a small open economy with three sectors: a skill-intensive export sector; a capital-intensive import competing sector; and a labour-intensive import competing and intermediate products producing sector. It analyzes the types of protection that aid in the expansion of credit and the alleviation of capital constraints, which further highlights the insufficiencies of tariff protection for the organized sector and simple credit guarantee policies to provide adequate credit flow and thus continued MSME growth. Finally, it considers the importance of priority sector lending policies in ensuring adequate credit distribution to this sector. The results show that protection helps in enhancing flow of credit and thereby works to relax the capital constraint. However, the tariff protection for organized sector may positively or negatively affect the non-traded unorganized sector.

Purpose: The concept of sustainability in the livelihood of rural people is the central point for the discussion for policymakers. Different policies for poverty reduction, developing economies, and environment management are not capable of using multimedia technology for rural entrepreneurial development.

Need of the Study: The study analyses the impact of multi-media and tries to understand its significance for rural enterprises to contribute to developing entrepreneurship in rural areas to minimise poverty.

Methodology: This research analysed a framework that highlights that multi-media technology offers different ways to earn a sustainable livelihood by enhancing the range of advanced technology, access to information assets, increased social networks, information transfer system, and modernisation of traditional working. A total of 450 rural entrepreneurs were contacted to collect the data from 6 different divisions of Haryana through a questionnaire on 5-point scale. A purposive sampling technique was used for primary data collection.

Findings: The multi-media technology influences rural entrepreneurial development through certain organisational factors, new products and services, improved customer service, generation of employment opportunities over time, increased loyalty, and novel combination of resources within the specific context.

Practical Implications: The study concludes the capabilities may be utilised up to maximum advantages that increase with the use of multi-media technology in the rural framework.

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.