Purpose: The purpose of this text is to provide an overview of digital marketing and its significance in today's world. It touches upon the evolving landscape of marketing and the challenges marketers face in adapting to new technologies and consumer behaviors. Design/methodology/approach: This section discusses the approach taken in the text. It outlines the content's structure and how it presents information about digital marketing, including its focus on communication, customer engagement, and ethical considerations. Findings: The findings section summarizes key points about digital marketing, emphasizing the increasing importance of mobile devices and the uncertainty surrounding the impact of the Internet of Things (IoT). It also highlights the challenges marketers face in measuring the effectiveness of traditional advertising. Research, Practical & Social implications: Here, we delve into the implications of digital marketing from three perspectives: research, practical application, and social impact. It explores the need for research agendas related to ethics, privacy, and bias in marketing, as well as how marketing strategies and consumer behavior may evolve. Originality/value: This section underscores the originality and value of the text by emphasizing the unique insights it offers into the future of marketing, including the intersection of technology, economics, and geopolitics. It suggests that the text provides valuable insights into ethical considerations and potential changes in marketing practices.

Digital marketing is an integrated term used for marketing of products or services with the help of internet so marketers can reach the customers and sale their products. The basic motto of the manufacturer is make a brand image of their enterprises, enhance more prospective customers & the sale of products & services by utilizing the digital marketing techniques. Indian market is today changing at faster pace day by day and with the help of Internet marketers are making communication with the consumers. These days marketers are aware that people are spending more time online in India every day, they are now spending more time on WhatsApp, facebook and on other social media. Therefore the companies are selling their products online and also their products are available on the various social media websites, this way they are making their market digital market rather than going for the traditional markets. Digital marketing growth comes from social media, people nowadays spend their time on social media and that is a plus point for marketers. Digital Marketing in India is growing day by day at higher speed.

This chapter examines the evolving concept of corporate digital sovereignty within the context of global geopolitical dynamics and technological transformation. It highlights how organizations increasingly navigate complex regulatory environments, data localization policies, and geopolitical tensions while maintaining operational efficiency and strategic autonomy. The discussion integrates key dimensions such as digital infrastructure control, data governance, AI sovereignty, and cybersecurity frameworks to explain how firms adapt to fragmented digital ecosystems. Furthermore, the chapter explores the role of sovereign cloud strategies, digital supply chain resilience, and cross-border governance in shaping corporate competitiveness. By linking geopolitical forces with corporate digital capabilities, the study provides a comprehensive framework for understanding how businesses achieve sustainable advantage in a multipolar digital economy.

Environmental policy affects economic growth, incentives, and the structural composition of economies, functioning not merely as a regulatory instrument but as a transformative macroeconomic force. By generating price, risk, and behavioral signals, environmental policies influence firms, households, and financial markets through multiple transmission channels, including productivity, innovation, capital allocation, and social distribution. While transition costs may temporarily reduce output in carbon-intensive sectors, long-term productivity gains can emerge through improved energy efficiency, process innovation, and shifts toward higher-value activities. Stringent environmental regulations often stimulate research and development in low-carbon, energy-efficient, and circular-economy technologies, thereby mitigating abatement costs and supporting sustainable growth. Financial markets respond through changes in asset valuation, credit availability, risk premia, and portfolio composition as sustainability standards and disclosure mandates reshape investor expectations.

The transition toward a circular economy requires intelligent systems capable of redesigning traditional linear supply chains into regenerative value networks. This chapter explores AI-enabled circular economy models that integrate advanced analytics, machine learning, IoT, and predictive optimization to enhance resource efficiency, waste minimization, and sustainable value creation. By embedding artificial intelligence across procurement, production, distribution, consumption, and reverse logistics, organizations can achieve real-time visibility, predictive maintenance, demand forecasting, and automated material recovery. The study develops a conceptual framework linking AI capabilities with circular business strategies, sustainable supply chain performance, and long-term competitive advantage. It also examines governance, ethical, and technological challenges associated with AI-driven sustainability transformation.

Autonomous Business Process Management (ABPM) represents an emerging paradigm that integrates artificial intelligence with traditional Business Process Management to enable self-optimizing and intelligent organizational workflows. This chapter explores the foundational theories and conceptual frameworks underlying ABPM, emphasizing how AI-driven process modeling, machine learning, and advanced analytics transform conventional workflow design into adaptive and autonomous systems. It examines the evolution of BPM toward intelligent automation, highlighting technologies such as predictive analytics, process mining, and intelligent decision-support mechanisms that allow processes to monitor, analyze, and optimize themselves in real time. The chapter also discusses theoretical perspectives that support autonomous process orchestration, including systems theory, digital transformation frameworks, and intelligent workflow architectures.