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Dr Mohammad Islam, PhD, FHEA, CMBE


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Lecturer in Business and Management

I joined the University as a Lecturer in Business and Management (HRM) in January 2024. My role includes teaching and learning, supervision, personal academic tutoring, subject development, assessment, research, and other administrative tasks for various undergraduate and postgraduate business courses.

Before joining the University of Sunderland, I was a sessional lecturer at Newcastle University. I taught a range of undergraduate and postgraduate business courses, including HRM and the Future of Work, Corporate Communications and Social Media, Managing Change in Organisations and Advanced Global Strategy. I worked on-campus (Cambridge Education Group) and taught several business and management modules for undergraduate and master’s foundation courses. These include Organisational Behaviour, Academic and Professional Skills for Business (APSB) and Principles of Management. I also worked as a Business Tutor and a Module Leader at Teesside International Study Centre. I taught several business and management modules at levels 4, 5 and 6. These include Business Enterprises, Business and Economics, Understanding Organisations, Business Enterprise, Human Resource Management (Future of HR) and Research Methods.

I graduated with a first-class honours degree in Business Studies from the University of Wales and gained my MSc in Human Resource Management from King’s College London. I hold a postgraduate research training (PgCert) certificate and a PhD in management studies from Newcastle University.

My teaching interests include HRM, digitalisation, change management, strategic management, ethics and sustainability, cross-cultural management, research methods, organisational behaviour and leadership, and information systems.

My research interests include Artificial Intelligence (AI), big data analytics, industry 4.0, smart HR, Brexit, equality and diversity, and industrial relations. My recent research, titled “AI-Augmented HRM: Literature Review and a Proposed Multilevel Framework for Future Research,” is available in the Technological Forecasting and Social Change Journal, a highly ranked academic journal rated A on ABDC and 3 on CABS.

I am a UK Higher Education Academy Fellow and a CMBE from the Chartered Association of Business Schools.



Teaching and supervision

I primarily teach the following HRM modules:

  • MGTM20: Organisational Development and Digital Practices
  • MGTM26: Developing Research Practitioners and
  • MGT201: Managing Self and Others
  • MGTM15: HRM in International and Digital Context
  • MGTM09: Managing the Employment Relationship

I supervise management reports on MGTM26: Developing Researching Practitioners (MSc HRM).

Research interests for potential research students

  • Human resource management
  • Leadership
  • Ethics and Corporate Social Responsibility (CSR)
  • Employment relations
  • Technology adoption (Digitalisation)
  • Fourth Industrial Revolution (I4.0)
  • Artificial Intelligence
  • Smart HR
  • Automated supply chain system
  • Performativity
  • Retail 4.0

Research

My research interests are the fourth industrial revolution, artificial intelligence (AI), big data analytics, smart HR, and employment relations. I am particularly interested in how AI impacts employment relations and the core HR functions of an organisation.  More precisely, I am interested in employee upskilling and the role of smart HR in managing the fourth industrial revolution.

My recent research entitled: ‘AI-Augmented HRM: Literature Review and a Proposed Multilevel Framework for Future Research’’ is available in the Technological Forecasting and Social Change Journal. A highly ranked academic journal rated A on the Australian Business Deans Council (ABDC) and 3 on the Chartered Association Business Council journal list (CABS).

Publications

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Number of items: 1.

Article

Verma, Prikshat, Islam, Mohammad, Patel, Parth, Malik, Ashish, Budwar, Professor Pawan and Gupta, Suraksha (2023) AI-Augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting & Social Change, 193. p. 122645. ISSN 0040-1625

This list was generated on Wed Dec 18 05:43:35 2024 GMT.

Last updated 04 July 2024