Asad Noor
Biographic Data
| ID | 4462984 |
|---|---|
| NAME | Asad Noor |
| GIVEN NAMES | Asad |
| FAMILY NAME | Noor |
| SIGNATURE | NOOR A |
| AFFILIATIONS | Green University of Bangladesh |
| ORCID | 0000-0002-9744-5019 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Earnings volatility and worker well-being in Dhaka’s gig economy
This study examines earnings volatility and worker well-being among ride-hailing and delivery workers in Dhaka, Bangladesh. Drawing on a survey of 512 workers, earnings diaries, and qualitative interviews, the article conceptualizes platform work as digitally reorganized informality. Quantile regression and SEM-based association analysis show that multi-homing and tenure are associated with lower earnings volatility, whereas payment frictions, lo…
Can supply chains decarbonize? Exploring the potential of scope 3 emission reduction for sustainable transformation
Scope 3 emissions are the largest and most complex component of corporate carbon footprints, presenting major challenges for decarbonization. This study analyzes a panel dataset of publicly listed European companies (2002–2023) using advanced econometric methods to assess how Scope 3 emission reduction strategies affect Environmental, Social, and Governance (ESG) performance. We employ Panel Autoregressive Distributed Lag (ARDL) models to capture…
No prominent works on this page.
Can supply chains decarbonize? Exploring the potential of scope 3 emission reduction for sustainable transformation
Scope 3 emissions are the largest and most complex component of corporate carbon footprints, presenting major challenges for decarbonization. This study analyzes a panel dataset of publicly listed European companies (2002–2023) using advanced econometric methods to assess how Scope 3 emission reduction strategies affect Environmental, Social, and Governance (ESG) performance. We employ Panel Autoregressive Distributed Lag (ARDL) models to capture…
Earnings volatility and worker well-being in Dhaka’s gig economy
This study examines earnings volatility and worker well-being among ride-hailing and delivery workers in Dhaka, Bangladesh. Drawing on a survey of 512 workers, earnings diaries, and qualitative interviews, the article conceptualizes platform work as digitally reorganized informality. Quantile regression and SEM-based association analysis show that multi-homing and tenure are associated with lower earnings volatility, whereas payment frictions, lo…
Corporate governance (2 works) · Digital Economy and Work Transformation (1 works) · Earnings (1 works) · Empirical evidence (1 works) · Environmental Impact and Sustainability (1 works) · Greenhouse gas (1 works) · Investment (military (1 works) · Livelihood (1 works) · Payment (1 works) · Quantile regression (1 works)