Data ecosystem business models: Value propositions and value capture with Artificial Intelligence of Things

In today's rapidly evolving global economy, cultivating a thriving innovation ecosystem is essential for achieving sustainable commercial success. This chapter explores the fundamental elements necessary for such ecosystems, including the pivotal roles of government policies, financial institutions, entrepreneurs, academic institutions, and established businesses. There is a systematic discussion of methods for cultivating a collaborative culture, building infrastructure that supports it, guaranteeing financial availability, and encouraging talent development. The chapter also examines successful case studies, highlighting diverse approaches to innovation. Moreover, it tackles notable obstacles like regulatory barriers, financial shortfalls, cultural opposition, and the intricacies of ecosystem administration. Additionally, the chapter explains the critical role of AI in enhancing these ecosystems by enabling more efficient processes, predictive analytics, and data-driven decision-making.

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Exploring Untapped Market Niches With Deep Learning Models

Yadav,

Mittal,

Jayarathne

2024

Advances in Business Strategy and Competitive Advantage

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The paper looks at how deep learning models work, analyse emerging and hidden markets, and apply the information to discuss how to develop business development strategies. Applying deep learning in market research involves demonstrating methodologies such as Systematic Literature Review (SLR) and PRISMA. By going over how neural networks compute, determining which business sectors to target, and illustrating how deep learning can help in market analysis, this paper shows businesses how these will be able to discover and thus dominate specific niches. Therefore, the summative integration of artificial intelligence and comprehensive data analysis methods offers an initial prototype design of the reference architecture to be used by organisations to improve strategic market designs and optimise incremental modifications necessary to build markets. The optimistic trend regarding DL in the market analysis is connected to the new prospects and potentialities that can offer new opportunities for deepening the learning process to cover the market and create enhanced models.

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Data ecosystem business models: Value propositions and value capture with Artificial Intelligence of Things

Cited by 3 publications

References 110 publications

Digital transition, data-and-tasks crowd-based economy, and the shared social progress: unveiling a new political economy from a European perspective

Digital transition, data-and-tasks crowd-based economy, and the shared social progress: unveiling a new political economy from a European perspective

Innovation Ecosystem Cultivating Environment for Sustainable Commercial Success

Exploring Untapped Market Niches With Deep Learning Models

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