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Customer experience (CE) has been of research interest especially with researchers in a Business-to-Consumer (B2C) context. Extensive research has identified the potential of similar studies in Business-to Business (B2B) contexts, yet we have little understanding of what influences a customer's experience in a B2B environment.

This chapter aims to capture the adequacy of efforts to capture the intricacies of CE in a B2B context using input–output measures both in the traditional and modern-day environment. The chapter would provide marketing managers with a clear understanding of how CE is affected in the B2B context. Essentially, it describes the importance of creating a positive CE through the direct interaction of various stakeholders with the company and its brand. This chapter advances the current state of knowledge by analysing the impact of CE on all dimensions of customer journey, creating a differential advantage over time.

The world is experiencing technological disruptions due to the dynamic business environment, technological advancements, customer preferences, increasing competitive pressure, globalization of supply chains, and environmental disruptions. Industry 4.0 technologies are paving the way for increased production efficiency and worker safety while optimizing resource utilization and improving sustainability. Industry 4.0 technologies find their applications in almost all sectors, but few studies explore industry 4.0 technologies in agriculture. The agri-food sector has experienced an upward trend in digitalization projects. The digital agri-food supply chains will help in the autonomous decision-making process, leading to enhanced visibility in the agri-food supply chains through real-time traceability solutions, thereby leading to improved food quality. It is anticipated that industry 4.0 technologies in the agri-food supply chains will impact climate change disruptions and improve the unequal distribution of resources in the agricultural sector. The present study highlights various industry 4.0 technologies and their applications in the agri-food supply chains. Based on the findings from a literature review, the study establishes 10 key performance indicators that will benefit decision-making in a digital, data-centered environment.

Purpose: This chapter attempts to apply Information Communication and Technology (ICT) to explain the increase in financial inclusion in the Indian financial system. The increasing use of facts and communication technology is integrating the arena. India’s information and conversation era is an industry that embodies globalization’s possibilities to develop low-profit economies.

Design/Methodology: The study is based on secondary data. The scope of the survey will only be confined to a financial institution in the economic systems of India. Various policy documents, lectures, reports, surveys, etc. of financial regulators and ministries are explored for analysis in the context of the objectives set. One of the largest challenges Indian banks will face in the next decade is banking operations, which is 50 per cent of India’s populace of around 1.2 billion (World bank, Overview 2021). The Reserve Bank of India encourages banks to use technology to maximize and attain growth profitability within the United States’ maximum faraway regions. For instance, ICT allows unknown clients to use biometrics to prompt their financial institution debts, disposing of the need for signatures.

Findings/Conclusion: The chapter concludes with numerous suggestions for expanding the manner of financial inclusion to reach the extremes of the Indian economy.

India's agri-food industry is rapidly expanding to keep up with the country's growing population. With the help of the fourth Industrial Revolution (Industry 4.0), modernization is creating a new revolution in the agri-food sector. Its applications in the food supply chain as a supply chain 4.0 (SC 4.0) have made it convenient to deliver products efficiently from farms to consumers. The various technologies such as the internet of things (IoT), artificial intelligence (AI), big data analytics and blockchain, etc., have impacted emerging supply chains. But many challenges are perceived by stakeholders toward the adoption of SC 4.0 technologies in India. The authors identified the challenges of adopting SC 4.0 for the agri-food sector and used the Total Interpretive Structural Modeling (TISM) tool to analyze those challenges. Based on literature research, nine major issues were diagnosed and then simulated using expert opinion. Primary data were also gathered with the help of a questionnaire to identify the status of acceptance level of these technologies. This study highlights the importance of government support, availability of sources of funds, customer orientation toward food safety, the commitment of management toward modernization, aware and well trained and motivated employees are a few of the major factors impacting the adoption of SC 4.0 technologies.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.