Doctoral research

The Work and Organisation group brings together academics from a number of different disciplines to conduct research and contribute to practice across diverse issues in the management of people and the social and psychological relations of work and organisations.

Members of the group carry out distinctive work across many contemporary topics of importance to work, employment, organisations and society. These include:

  • organisational psychology
  • working identities and workplace equalities
  • career management
  • work-related health and wellbeing
  • the sociology of work, technology and organisations
  • issues in international HRM, labour and employment.

Applications are invited from prospective PhD students interested in working with well-established researchers in the School. Colleagues are available to supervise PhD research in a wide range of topics. If you're interested in joining a dynamic community of talented researchers from around the world to explore research questions that matter, we would like to hear from you.

Please feel free to browse our group members to identify a potential supervisor(s), develop your research proposal, share this with the identified supervisor(s) and confirm they are willing to be named in support of your application. You are encouraged to ask for feedback from them to develop your research proposal. Then you should be ready to formally apply.

Our research topics

Within the Work and Organisation group we are especially keen to receive PhD research proposals in the following areas:

Technology and organisations

  • Exploring the positive and negative features of digital technology at work; including innovation in personnel selection, changing employment relationship, algorithmic management.

Changing practices of work

  • The expansion of atypical work: issues of precarious jobs, identity, meanings of work, changes in career patterns, changing professional occupations.
  • Employee health and wellbeing; improving gender equalities, preventing bullying and enhancing dignity and respect, quality of work life.

Societal and environmental issues

  • Citizenship, responsibility and sustainability: implications for organisations, management, employment practices, industry.
  • Employee voice and participation in MNCs: advancement of mutual benefits and joint responsibilities for sustainable business and fair labour practices.

Proposed PhD projects

Reconceptualising abusive leadership behaviours, and their impact on employee wellbeing: A novel measurement approach

Project reference

LB24-NB (please quote this in your application).


Project description

Abusive leadership is a prevalent issue in organisational settings, posing significant threats to employee wellbeing and overall workplace dynamics. However, currently the research on abusive leadership lacks accurate measurement tools to capture the true nature of these behaviours, as experienced by employees in the workplace. This research therefore aims to develop a new measurement instrument, which will address previous major shortcomings such as the conflation of behaviours with their effects on outcomes (Fisher & Sitkin, 2023). After validating this tool, the project will investigate the antecedents and consequences of abusive leadership, using an experience sampling study (Gabriel et al., 2019).

This research aims to contribute to the understanding of abusive leadership and its impact on employee wellbeing. The development of a comprehensive measurement tool will not only advance academic research but also provide practical tools for organizations to identify and address abusive leadership behaviours, fostering healthier and more productive workplaces. The ideal candidate should have undergraduate and postgraduate degrees in business studies, psychology, social psychology or other relevant studies. The candidate should also have a good knowledge of quantitative research methods, and statistical analysis skills using specific software packages (eg Mplus, R).

Progress or regress? Using AI enabled decision-making to evaluate leadership potential in diverse work groups

Project reference

LB24-IC (please quote this in your application).


Project description

The use of algorithms to enable and enhance HRM decision-making has advanced at such a speed that business and academics are only beginning to understand its potential for identifying leaders at work, and for improving workplace diversity and inclusion (EDI).

This PhD studentship will add to current knowledge and practice by investigating (1) how employers are using AI and integrated digital systems to identify individuals with leadership potential, and (2) potential consequences of such systems for workplace inclusion and differential progression to leadership roles.

We therefore invite proposals focusing any of the following areas:

  • The impact of integrated AI and digital platforms on the advancement of women and minority candidates to leadership roles.
  • Employer engagement with digital and AI-driven decision-making for assessing leadership potential.
  • Employee trust and engagement with digital and AI-driven leadership evaluation.
  • The contribution of AI-driven assessment of leadership potential to counterproductive and unethical leader behaviour.

Artificial intelligence and creative work performance – threat or opportunity?

Project reference

LB24-OK/ED (please quote this in your application).


Project description

New technology is offering tremendous potential to organisations, eg to increase creative work performance. Research on creativity has advanced our knowledge about factors that contribute to the creative idea generation, stemming from the belief that creativity leads to higher organisational performance. Empirical studies however indicate that idea generation does not always relate to better performance. Thus, it is crucial for organisations and the scientific community to get an understanding of personal and situational factors influencing both the generative (van Knippenberg & Hirst, 2020, JAP) and the receiving side (Zhou et al., 2019, JOM) of creativity which includes perception, evaluation and adoption of creative ideas.

The present PhD project addresses this gap by drawing on recent theoretical advances in the creativity domain to investigate how Artificial Intelligence (AI, eg ChatGPT) use relates to creative performance among others as evaluated by others. This project will enhance our understanding of AI use and individual creative performance.

The ideal candidate has an MSc in (Work) Psychology or similar, a quantitative research focus and motivation to conduct experimental and experience sampling studies (Gabriel et al., 2019, ORM). We encourage and support the publication of this research project at international conferences and in excellent journals.

Exploring AI implications on employee experience and wellbeing: a longitudinal study

Project reference

LB24-OK/AP (please quote this in your application).


Project description

Research studies have shown that AI application in HRM influence streamline processes, enhance decision-making and improve overall organisational efficiency. However, there is limited research that systematically explores the impact of AI on employee experience and wellbeing over an extended period. Existing studies often focus on short-term outcomes, neglecting the evolving nature of employee perceptions and wellbeing over time.

In this respect, this PhD thesis, by building upon existing literature, aims to provide a longitudinal perspective on the implications of AI in HRM for employees' experiences and wellbeing. It aligns with the growing recognition of the importance of employee wellbeing in organisational success. This study will be using longitudinal research design based on three waves of data collection. Specific data collection instrument will be developed based on validated measures.

The ideal candidate should have an undergraduate and postgraduate degree in business studies, work psychology or other relevant studies. The candidate should also have a good knowledge of statistical analyses using specific software like SPSS, MPlus, Stata or relevant. Experience in conducting surveys will be also considered.