Newcastle University Business School

Staff Profile

Harsh Jha

Lecturer Quantitative Methods Management


Harsh joined the Newcastle University Business School in 2016 as a lecturer in the Leadership, Work & Organisation (LWO) group. He received his PhD in Management (Concentration - Organization & Management) from the Paul Merage School of Business, University of California, Irvine, USA.

Prior to the PhD program, he completed a BA in Sociology, PGDM (equivalent to MBA) and an MSc in Management Research. Dr. Jha also holds more than six years of managerial experience of sales, marketing and product management functions in telecommunication, consumer products and social care industries.


My research interests primarily include temporal analysis of big field level changes and meaning construction process, especially how actors use discourse to make legitimacy, identity and status claims. I am also interested in socio-political aspects of market construction.

Methodologically, I use both qualitative and quantitative methods. Among qualitative methods, I draw extensively on traditional qualitative and archival research, focusing on grounded theory driven analyses of archival data and intensive interviews. Among quantitative methods I specialize in probability based modeling tools for large data content analysis, such as correspondence analysis, topic modeling and MDS.

My current research looks at various empirical contexts, including professional services (e.g. English legal services), education (e.g. charter schools in USA) and early stage technology entrepreneurship.



BUS3057     International Business Diplomacy (Module Leader)

BUS2031     Managing Change (Module Leader)

BUS3035    Contemporary Issues in International and Comparative Business (2016-2017)

MGMT 5      Managing Contemporary Organizations (University of California, Irvine, USA)


NBS8265     Managing Change in Organisations (Module Leader)

NBS 8061   Managing across Cultures (Module Leader)

NBS 8284   Research Methods in HRM 

NBS 8327   Research Methods in IBM