Sep 2026· Foundations and Trends® in Marketing· Vol 20, pp. 1-70· 102 references
Abstract
The 21st-century entertainment landscape has undergone a radical transformation driven by the internet, smartphones and the emergence of artificial intelligence (AI). As entertainment becomes deeply integrated into everyday life, marketing has evolved from a supporting function to a vital strategic pillar necessary for navigating a hyper-competitive attention economy. This monograph provides a comprehensive, integrative scholarly review of entertainment marketing, specifically addressing the radical demand uncertainty inherent in experiential goods. A central contribution of this work lies in its synthesis of two frequently competing viewpoints: the consumer perspective, which frames entertainment as a hedonic pursuit of emotion and narrative, and the business perspective, which conceptualizes it as a high-stakes commercial endeavor requiring advanced analytics and global distribution strategies. By identifying points of convergence, including content quality, personalization and community building, this monograph illustrates how firms can create a virtuous cycle in which individual gratification and commercial performance mutually reinforce each other. The scope of this research encompasses the major pillars of the entertainment world: movies, video games, music, books, tourism, gambling, social media and sports. Beyond the consumer–business dyad, the review also incorporates the perspective of artists and content creators, including the well-documented concentration of rewards among a small set of superstars, and critically examines industry consolidation, privacy and related public-policy concerns that complicate optimistic accounts of consumer welfare. Finally, this work evaluates emerging trends, with a particular focus on the AI revolution, exploring the impact of generative AI and virtual influencers on the authenticity paradox of contemporary branding. This monograph serves as both a theoretical foundation for academic researchers and a practical roadmap for industry leaders operating within the shifting boundaries of the global entertainment ecosystem.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.