Stefano Bresciani – författare

Digital Transformation Management for Agile Organizations highlights and explores new dynamics regarding current digital developments globally scale, by examining the threats, as well as the opportunities these innovations offer to organizations of all kinds. Digital transformation is addressed from an organizational standpoint and is examined in relation to differing management theories in the work.This ground-breaking study discusses how digital transformation can and is being embraced by a range of companies, as well as demonstrating how digital expansion is resulting in specific economic and social consequences. The authors present chapters providing wide-ranging coverage of digital transformation, with exploration of digital transformation as a process for business model innovation, digital marketing, leadership and establishing new business ecosystems.Digital Transformation Management for Agile Organizations is essential reading for all academic researchers with a focus on innovation management, technology management, human resource management, and strategy and leadership.

This book is a concise and integrative synthesis of the rapidly expanding literature on dynamic pricing in e‑commerce. Algorithmic dynamic pricing has become a central strategic tool for brand manufacturers and retailers operating in e‑commerce and platform‑mediated markets. Prices are no longer static decisions but are continuously updated by algorithms that learn from demand, inventory, competition, and consumer behavior—while operating under governance, fairness, and operational constraints.Based on a systematic literature review of 101 high‑quality journal articles and supported by bibliometric mapping, the book organizes existing research into four coherent streams: operational and algorithmic pricing, consumer perceptions and fairness, platform governance and ecosystems, and revenue management in services and hospitality. Beyond summarizing prior work, the book proposes a contemporary definition of dynamic pricing as an algorithmic, learning‑based policy and outlines 17 research propositions that structure future inquiry. These propositions connect methodological challenges—such as learning under competition and non‑stationarity—with actionable managerial levers for pricing design. Designed for researchers, (pre)doctoral students, and practitioners, the book provides a clear entry point into a fragmented field and offers practical insights for firms navigating pricing decisions in data‑driven, policy‑constrained online markets.