Modeling Loss Aversion in High-Stakes Game Scenarios
Michael Davis 2025-02-09

Modeling Loss Aversion in High-Stakes Game Scenarios

Thanks to Michael Davis for contributing the article "Modeling Loss Aversion in High-Stakes Game Scenarios".

Modeling Loss Aversion in High-Stakes Game Scenarios

This paper applies systems thinking to the design and analysis of mobile games, focusing on how game ecosystems evolve and function within the broader network of players, developers, and platforms. The study examines the interdependence of game mechanics, player interactions, and market dynamics in the creation of digital ecosystems within mobile games. By analyzing the emergent properties of these ecosystems, such as in-game economies, social hierarchies, and community-driven content, the paper highlights the role of mobile games in shaping complex digital networks. The research proposes a systems thinking framework for understanding the dynamics of mobile game design and its long-term effects on player behavior, game longevity, and developer innovation.

This paper explores the application of artificial intelligence (AI) and machine learning algorithms in predicting player behavior and personalizing mobile game experiences. The research investigates how AI techniques such as collaborative filtering, reinforcement learning, and predictive analytics can be used to adapt game difficulty, narrative progression, and in-game rewards based on individual player preferences and past behavior. By drawing on concepts from behavioral science and AI, the study evaluates the effectiveness of AI-powered personalization in enhancing player engagement, retention, and monetization. The paper also considers the ethical challenges of AI-driven personalization, including the potential for manipulation and algorithmic bias.

This research explores the role of big data and analytics in shaping mobile game development, particularly in optimizing player experience, game mechanics, and monetization strategies. The study examines how game developers collect and analyze data from players, including gameplay behavior, in-app purchases, and social interactions, to make data-driven decisions that improve game design and player engagement. Drawing on data science and game analytics, the paper investigates the ethical considerations of data collection, privacy issues, and the use of player data in decision-making. The research also discusses the potential risks of over-reliance on data-driven design, such as homogenization of game experiences and neglect of creative innovation.

A Comparative Analysis This paper provides a comprehensive analysis of various monetization models in mobile gaming, including in-app purchases, advertisements, and subscription services. It compares the effectiveness and ethical considerations of each model, offering recommendations for developers and policymakers.

This research explores the integration of ethical decision-making frameworks into the design of mobile games, focusing on how developers can incorporate ethical principles into game mechanics and player interactions. The study examines the role of moral choices, consequences, and ethical dilemmas in games, analyzing how these elements influence player decision-making, empathy, and social responsibility. Drawing on ethical philosophy, game theory, and human-computer interaction, the paper investigates how ethical game design can foster awareness of societal issues, promote ethical behavior, and encourage critical thinking. The research also addresses the challenges of balancing ethical considerations with commercial success and player enjoyment.

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