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It is important to implement artificial intelligence (AI) because it can simplify and solve complex problems faster than humans. Because AI learns about people and their behavior from the first purchase, AI marketing can boost marketing efforts by leveraging data to target extremely precise consumer groups. There is a debate about the efficacy of AI marketing due to the constraints and limits imposed by the system's nature. This chapter presents insights from published studies regarding the relationship of AI with marketing and how AI can affect marketing. A real-world example of Netflix's usage of AI in marketing has been demonstrated. Then, consumer attitudes regarding AI were revealed. Then, several ethical considerations concerning AI were highlighted. Finally, the anticipated future of AI marketing was addressed. This chapter demonstrated the significance of firms implementing AI marketing to get a competitive advantage. Although some of the difficulties mentioned in this study need to be resolved, AI marketing has a bright future. There are ethical concerns about bias and privacy that should be addressed further. This chapter will encourage firms to use AI systems in marketing, and it will open the door to concerns that will need to be investigated academically in the future.

Digitalization and marketing technologies have made it possible to overcome some barriers to pricing – a multidisciplinary field between marketing, finance and IT – and have set the stage for a paradigm shift in the pricing profession. Value creation, the pricing process, and price communication have been transformed by innovative business models and advanced algorithmic and human–machine solutions. This chapter synthesizes the literature to date and provides a comprehensive framework for an all-encompassing 360° pricing approach that broadens the understanding of pricing in the context of digital business across all steps of the price management process. Starting from product attributes and motivational beliefs in consumers' value assessment and adoption of (technological or digital) products or services, new business models and pricing models emerge in the digital economy, human–machine solutions for price implementation and repricing are increasingly applied, and price search and communication take place through a variety of digital communication channels. Each stage of this framework discusses concrete examples, highlighting the freemium strategy, the subscription model, price tracking and repricing tools, and digital price information channels such as e-commerce, marketplace, or price comparison platforms. The implications for price management in a digital, technology-driven landscape are discussed from the executive level to the analyst level.

Adapting to external and internal transformations is a difficult task that managers and scholars must face while attempting to keep their organisations alive and well-established. This chapter explores the various decision-making tools that can assist practitioners and scholars to improve their understanding of the external scenario to determine the contemporary appropriateness of these approaches for analysing the environment and their implications for various types of organisations. The chapter investigates the barriers and drivers of these methods and proposes existing alternative paradigms created by academics and practitioners to analyse and comprehend the context. It demonstrates how these decision-making tools can be implemented by providing examples and case studies.

Purpose: The availability of resilient energy infrastructure and services is crucial to achieving sustainable development goals. However, defined and trustworthy definitions of resilience exist solely for engineering and energy systems, particularly in the industrialised world or metropolitan systems. However, no universally accepted definition considers the distinctive characteristics of rural regions in developing economies. To define resilience for rural power systems in developing countries, this chapter synthesises many perspectives on resilience, energy systems, and rural environments.

Methodology: It draws on extensive literature assessments on resilience, particularly concerning energy systems and rural areas, as well as other pre-existing frameworks.

Findings: To account for the unique challenges of electricity supply in rural developing nations, a comprehensive ‘Rural Power System Resilience Framework’ is introduced, including technical, economic, and social resilience.

Social implications: To better understand the elements contributing to the stability of electricity grids in developing nations and rural areas, this resilience framework may be utilised by global markets, system owners and operators, government officials, non-governmental organisations, and communities.

Originality: Through establishing this framework, this study sets the path for developing suitable and ‘effective resilience standards’ tailored for implementation in these rural areas, with the ultimate goal of facilitating the fulfilment of achieving domestic and worldwide sustainability objectives.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.