Call for Papers - Transforming Business Models Across Digital Platforms: Exploring the Role of Artificial Intelligence

Nowadays, more and more companies are adopting business models based on the use of two-sided platforms with the aim of connecting two different groups of customers. At the same time, there is, in several application fields, a growing introduction of AI elements in products and services. Both these topics have the potential to generate innovation. Platform Thinking refers to a market where platforms facilitate interactions between different user groups. These platforms leverage indirect network externalities to bring value. The classic illustration is the credit card market where both cardholders and merchants derive value from the platform's existence. This value arises from indirect or cross-side network externalities which associate the perceived value of one side (e.g., cardholders) with the availability of the other (e.g., merchants accepting cards). As the concept progressed, "two-sided markets" broadened to "two-sided platforms", indicating a shift from merely linking customers and suppliers to connecting two customer groups through specific network effects, easing interactions. These platforms, beyond just acting as connectors, offer services that benefit both sides. The emphasis in platform studies is the non-linear flow of value creation and capture. Over time, these platforms can evolve into multi-sided versions, expanding their ecosystem. Further advancements introduced non-transactional or orthogonal models, emphasizing data-driven value opportunities, especially with AI advancements. Often, platforms amalgamate transactional and orthogonal features, leading to Hybrid Platforms like Uber. Artificial Intelligence is transforming business, society, and stakeholder experiences. It's defined as a system's capability to interpret data, learn, and apply this learning flexibly for specific tasks. AI uses data from sources like IoT to identify patterns using machine learning and analytics, which enable computers to learn without specific programming. This evolution is evident in products and services across industries, from Apple's Siri to skin cancer detection systems and service robots. These robots utilize diverse data sources to offer tailored services. AI applications are broadening, impacting areas like agri-food traceability, supply chain management, and sustainability in operations. In marketing, AI aids in predicting consumer behaviors and generating tailored online recommendations. Furthermore, AI's influence in social media is growing. From an academic viewpoint, AI research spans ethical concerns, deep learning advancements, and its multifaceted impacts on an interconnected business landscape. This special issue invites scholars to reflect on the innovation opportunities deriving from the application of artificial intelligence to platform thinking in fields (e.g., health, manufacturing, agri-food, retailing).