Search results

This final chapter delves into the future of digital supply chain management (DSCM) amid today's dynamic business environment, shaped by technological advancements and factors like automation, artificial intelligence (AI), sustainability, and resilience. It emphasizes the crucial role of digital technologies (DTs) such as AI, the Internet of Things (IoT), Industrial IoT, and the Internet of Everything (IoET), along with blockchain, in revolutionizing supply chain operations. These technologies enable agility, flexibility, efficiency, and responsiveness, crucial for supply chains to proactively adapt to market changes. The chapter explores the trends in DSCs, focusing on real-time data analytics, end-to-end visibility, sustainability, and resilience. It highlights the growing importance of transparency in supply chains, driven by consumer demand for sustainable practices and product origins. DSCM is identified as pivotal for prioritizing sustainability, leading organizations toward green practices. Despite the opportunities in DSCM, challenges like cybersecurity, data management complexities, geopolitical uncertainties, and talent shortages are acknowledged. To overcome these, the chapter stresses strategic foresight in DSCM and the importance of robust process management, risk management, and talent development. The future-readiness of supply chain professionals is discussed, highlighting the need for change management, development of social and deep work skills, collaboration, and ethical practices. The chapter concludes by underscoring the transformative potential of DTs in the digital era, urging organizations to embrace innovation, transparency, and sustainability in their supply chains, recognizing that the future of DSC is an imminent reality.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

Due to the rapid increase in global warming and environmental disasters, destination management and tourists' environmental awareness have increased. This increase in environmental awareness has led destinations to prioritize green practices that reduce environmental pollution. Moreover, in recent years, with the rapid development of technology, artificial intelligence technology has also been used in applications that reduce environmental pollution in destinations. This is because environmentally friendly products and services offered by destinations have started to have an impact on tourists' travel choices. Additionally, tourists' awareness and loyalty towards environmentally friendly destinations have started to increase, resulting in the formation of brand value for destinations. Therefore, green practices and AI technologies play a role in the formation of consumer-based destination green brand value.

This chapter examines the effect of the Regenerative Tourism Movement on the global industry and the role of Artificial Intelligence (AI) in driving sustainability and innovation. The Regenerative Tourism Movement represents a paradigm shift in the tourism industry, focussing on the interconnectedness of economic, social, cultural, and environmental well-being. This approach aims to generate positive impacts on local systems by fostering partnerships, diversity in local economies, and transformative experiences for travelers. This chapter explores the key principles and nature-based solutions associated with regenerative tourism. Additionally, it delves into the role of AI in the tourism sector, highlighting its potential to enhance sustainability practices, deliver personalised experiences, and streamline operations. Various AI tools and technologies, such as data analytics, machine learning, natural language processing, computer vision, IoT integration, recommender systems, optimisation algorithms, blockchain technology, and AR/VR, are discussed in the context of regenerative tourism. This chapter concludes by outlining the benefits of AI in sustainable and regenerative tourism, emphasising reduced environmental impact, enhanced efficiency, and improved customer service. It also highlights the challenges and considerations associated with AI adoption in the tourism industry. Recommendations for the integration of AI-driven solutions and future directions for research in this field are provided, aiming to inspire further exploration and implementation of AI in regenerative tourism.

Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.