Giulio Toscani
Biographic Data
| ID | 4424977 |
|---|---|
| NAME | Giulio Toscani |
| GIVEN NAMES | Giulio |
| FAMILY NAME | Toscani |
| SIGNATURE | TOSCANI G |
| AFFILIATIONS | Barcelona School of Economics |
| ORCID | 0000-0002-1289-4510 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Chaos as incompetence
Purpose This paper aims to examine how disruptive presidential leadership reshapes the business–government nexus by analyzing the Trump administration as a critical case of political and economic transformation. It explores how unilateral governance, policy volatility and weaponized interdependence compelled firms to adopt short-term, defensive and state-contingent innovation strategies. Through a comparative analysis of the Obama, Trump and Bide…
Garbage in, garbage forever
Purpose This paper aims to address the systemic issue of data deterioration caused by fragmented corporate data practices. It introduces the “data cold chain” as a novel regulatory framework for government-led standardization, designed to ensure data integrity and usability as information traverses organizational and sectoral boundaries. Design/methodology/approach This study uses a qualitative approach, drawing on semistructured interviews with …
The unknown-known trap
Hyperspecialization in machine learning creates blind spots: deep technical skill without contextual awareness. Drawing on a Grounded Theory design, data were gathered through semi-structured interviews with 153 practitioners across 50 countries. This research identifies three operational modes: Known-Unknowns (specialized focus), Unknown-Unknowns (integrated collaboration), and Crisis (forced integration). Effective performance depends on “toggl…
Future proofing expertise
No prominent works on this page.
Future proofing expertise
Chaos as incompetence
Purpose This paper aims to examine how disruptive presidential leadership reshapes the business–government nexus by analyzing the Trump administration as a critical case of political and economic transformation. It explores how unilateral governance, policy volatility and weaponized interdependence compelled firms to adopt short-term, defensive and state-contingent innovation strategies. Through a comparative analysis of the Obama, Trump and Bide…
Garbage in, garbage forever
Purpose This paper aims to address the systemic issue of data deterioration caused by fragmented corporate data practices. It introduces the “data cold chain” as a novel regulatory framework for government-led standardization, designed to ensure data integrity and usability as information traverses organizational and sectoral boundaries. Design/methodology/approach This study uses a qualitative approach, drawing on semistructured interviews with …
The unknown-known trap
Hyperspecialization in machine learning creates blind spots: deep technical skill without contextual awareness. Drawing on a Grounded Theory design, data were gathered through semi-structured interviews with 153 practitioners across 50 countries. This research identifies three operational modes: Known-Unknowns (specialized focus), Unknown-Unknowns (integrated collaboration), and Crisis (forced integration). Effective performance depends on “toggl…
Ethics and Social Impacts of AI (3 works) · Artificial Intelligence in Healthcare and Education (2 works) · Corporate governance (2 works) · Accountability (1 work) · Cognition (1 work) · Cognitive Load (1 work) · Data governance (1 work) · Data integrity (1 work) · Data quality (1 work) · Data Quality and Management (1 work)