Aaqib Danish

Email: malikdanish9288@gmail.com


Aaqib DanishAaqib Danish (Prof.) is an Assistant Professor of Human Resource Management and Organisational Behaviour at the New Delhi Institute of Management (NDIM), New Delhi. He is doing a PhD in Management (Human Resource Management) at Guru Nanak Dev University, Amritsar, and holds an M.Phil. in Human Resource Management (Gold Medallist), an MBA, and a B.Com (Honours).and Human Resource Management Course from Brentwood Open Learning College, LE3 1HR, United Kingdom Prof. Danish’s research interests span Electronic and Sustainable Human Resource Management (e-HRM & s-HRM), organisational sustainability, HR analytics, digital workforce and future of work, employee wellbeing, organisational behaviour, and technology-enabled HR practices. He has published extensively in Scopus-indexed, ABDC-listed, and UGC-CARE journals, with research focusing on HRM effectiveness, organizational performance, and sustainability across sectors such as education, banking, IT, and textiles. He has previously served as Assistant Professor at Amity Business School, Research Associate at Great Lakes Institute of Management, and Consultant with institutions including IRMA and the Indian Institute of Corporate Affairs (Ministry of Corporate Affairs). Dr Danish has also presented papers at reputed national and international conferences, including IIM-hosted conferences, and actively contributes to academia as a reviewer for leading journals, including Sage publications and the Academy of Management Annual Meetings.




Papers Published in World Economics:


Reassessing Global GDP Data Accuracy in the Digital Era

GDP’s reliability as a measure of economic performance has been increasingly undermined by rapid digitalisation of production and consumption between 2010 and 2024, particularly through the under-capture of intangible assets and cross-border digital value flows. Using secondary data from the IMF, OECD, and World Bank alongside simulated datasets, the study identifies structural biases in traditional national accounting frameworks and substantial cross-country differences in the extent of digital undercounting. A mixed-methods approach combining statistical trend analysis with qualitative interpretation quantifies the scale of this under-representation and highlights the resulting distortions in official GDP figures.

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