DSM02 - Rethinking sustainability strategies for resilience in supply chain systems: addressing food sector challenges in the VUCA (vulnerability, uncertainty, complexity, and ambiguity) reality

Supervisors: Dr Anna John (Department of Strategy and Marketing, The Open University Business School, Faculty of Business and Law) and Dr Nicoleta Tipi (Department of People and Organisations, The Open University Business School, Faculty of Business and Law).

Problem, Focus and Aims

Recently, many modern societies and organisations have been relentless in developing sustainable food supply systems - those which meet the national and global food security objectives while maintaining the delicate 3P (people-planet-profit) balance - in the face of the VUCA (vulnerability, uncertainty, complexity, and ambiguity) reality (John et al., 2022). Indeed, food supply systems in the UK and abroad have experienced difficulties in attaining sustainability and resilience following such VUCA-driven challenges as the cost-of-living crisis, health crises (e. g. global pandemic Covid-19, an outbreak of Ebola Virus Disease in West Africa in 2014-2016), devastating wars (e. g. Russia-Ukraine war, Palestine-Israel war), political and military crises (e.g. coups in Niger and Gabon 2023; Nagorno-Karabakh in 2023), riots and protests (e.g. anti-immigration riots and counter-protests in England in July-August 2024) and natural disasters (e.g. Turkey-Syria earthquake in 2023, fires in Hawaii in 2023, cyclone Idai in Mozambique in 2019).

In this context, it becomes critical to rethink sustainability strategies for resilience in supply chain systems. Therefore, we invite proposals addressing the following research question:

How can sustainability strategies be made resilient to ensure security and growth in food supply systems in the face of modern challenges (e.g. VUCA reality)?

Possible Research Angles

A list of possible research angles to finding new ways of working with models may include but is not limited to:

Growth and survival strategies (John et al., 2022),
Supply Chain Modelling (Tipi, 2021),
Meta-modelling (Jahangiri et al., 2023),
Systems thinking (Driscol et al., 2022; Hamzah et al., 2022; Esfandabadi et al., 2022; Johnson, 2013),
Open systems (Grewatsch et al., 2023),
Heuristic approaches and biases (Ahmad et al., 2022),
Hypernetworks (Johnson, 2014),
Liminality (John and Lawton, 2021),
Wicked problems (Lonngren and Van Peck, 2021; Coyne, 2005).

Empirical Scope

Geographically, proposals may focus on:

UK food supply,
International and global food chains,
Food supply in emerging economies,
Food supply chains in advanced economies.

In terms of the strategic scope, proposals may include but should not necessarily be limited to:

Survival strategies, or strategies for security of food supply systems (e.g., looking into foods (i.e., potatoes and rice) which are essential for survival of a nation in the conditions of large-scale disruptions);
Growth strategies, or strategies for developing leadership in food supply systems (e.g., looking into foods (i.e., fruit linked to a particular climate zone) which help a nation to create a competitive advantage on the global market).

Theoretical Perspective and Field

The future proposals may build an argument by using such theories as institutional theory (John and Vicente, 2020), dynamic based view (DBV), especially a simple rules view of dynamic capabilities (Eisenhardt and Martin, 2000), and resource dependency theory (Pfeffer and Salancik, 2003; John and Lawton, 2018). We also welcome new creative ways of combining theories and developing new theories.

Potential for Theoretical Contribution

The theoretical value of this research will come from addressing the following emerging paradigmatic shifts:

A shift in the supply chain strategy paradigm from centring on some incremental or partial disruptions to considering larger scale disruptions with a greater magnitude of effects;
A shift in the supply chain strategy paradigm from seeing sustainability and resilience as two independent or, in the best case, loosely related phenomena to considering potential synergies between sustainability and resilience;
A shift in the supply chain strategy paradigm from considering an organisation level decision in isolation from the national security and development priorities to integrating organisational and national decision-making objectives.

Impact

The research is expected to generate insights which will have short-term, mid-term and long-term implications for the socio-economic development, policy making activity, socio-technical innovations, and sustainability synergies. Additionally, the research will contribute to its doctoral author’s professional development and employability.

Proposed Methodology

We invite proposals which will use quantitative methods. Where possible and appropriate, researchers may also use approaches assuming linearity. For example, they can make use of structural equation modelling and statistical analysis with the use of multivariate techniques. Mixed methodologies combining quantitative and qualitative approaches are also possible. In all the cases, the candidates are expected to justify their choices of specific methods and techniques by explaining their appropriateness for addressing the key research question.

A broad range of approaches may be used for performing a project’s literature review. Both qualitative (John et al, 2022) and quantitative (Møller and Myles, 2016) systematic reviews may be used for integrating prior research and theorising from it.

References

Ahmad, M., Wu, Q., Naveed, M., and Ali, S. (2022). Probing the impact of cognitive heuristics on strategic decision-making during the COVID-19 pandemic: evidence from an emerging economy. International Journal of Social Economics, 49(10), 1532-1550.

Coyne, R. (2005). Wicked Problems revisited. Design Studies 26 (1), 5-17.

Di Guilmi, C. (2023). Agent-based modelling. In Elgar Encyclopedia of Post-Keynesian Economics (pp. 4-6). Edward Elgar Publishing Limited.

Driscoll, P. J., Parnell, G. S., and Henderson, D. L. (Eds.). (2022). Decision making in systems engineering and management. John Wiley & Sons.

Eisenhardt, K. and Martin, J. (2000). Dynamic capabilities: what are they? Strategic Management Journal, Vol. 21, Issue 10-11, pp. 1105-1121.

Esfandabadi, Z. S., Ranjbari, M., and Scagnelli, S. D. (2022). The imbalance of food and biofuel markets amid Ukraine-Russia crisis: A systems thinking perspective, 1640-1651.

Grewatsch, S., Kennedy, S., and Bansal, P. (2023). Tackling wicked problems in strategic management with systems thinking. Strategic Organization, 21(3), 721-732.

Hamzah, H., Hamzah, M. I., and Zulkifli, H. (2022). Systematic Literature review on the elements of metacognition-based Higher Order Thinking Skills (HOTS) teaching and learning modules. Sustainability, 14(2), 813.

Jahangiri, S., Abolghasemian, M., Ghasemi, P., and Chobar, A. P. (2023). Simulation-based optimisation: analysis of the emergency department resources under COVID-19 conditions. International Journal of Industrial and Systems Engineering, 43(1), 1-19.

John, A. and Lawton, T. (2018). International Political Risk Management: Perspectives, Approaches and Emerging Agendas. International Journal of Management Reviews, 20(4), pp. 847-879.

John, A. and Lawton, T. (2021) Political Risk Management in Bailey, K., & Breslin, D. (2021). The COVID‐19 pandemic: what can we learn from past research in organizations and management? International Journal of Management Reviews, 23(1), 3-6.

John, A. and Vicente, G. J. (2020) Institutional foundations of management of natural disasters: Lessons from the recent cyclones in Mozambique. In Leite da Silva, Oliveiro da Silva, Eduardo Sol and Vilar Lopes, Gills eds. Questões humanitrias e poder aeroespacial. Comunicação, Arte & Cultura (pp. 63-86).

John, A., Coetsee, J. and Flood, P. (2022). Understanding the mechanisms of sustainable capitalism: the 4S model, The Business Ethics, the Environment & Responsibility (early access).

Johnson, J. (2013). Hypernetworks in the Science of Complex Systems (Vol. 3). World Scientific.

Johnson, Jeffrey; Denning, Peter; Delic, Kemal and Bromley, Jane (2020). COVID-19 and computation for policy. Ubiquity, 2020 (October) pp. 1-14.

Lonngren, J. and Van Peck, K. (2021). Wicked problems: A mapping view of the literature. International Journal of Sustainable Development and World Ecology, 28(6), 481-502.

Møller, A. M., and Myles, P. S. (2016). What makes a good systematic review and meta-analysis? BJA: British Journal of Anaesthesia, 117(4), 428-430.

Pfeffer, J., and Salancik, G. R. (2003). The external control of organizations: A resource dependence perspective. Stanford University Press.

Tipi, Nicoleta (2021) Supply Chain Analytics and Modelling: Quantitative Tools and Applications, Kogan Page, ISBN: 9780749498627, UK.

Yang, Y., Bremner, S., Menictas, C., and Kay, M. (2022). Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review. Renewable and Sustainable Energy Reviews, 167, 112-671.

Zha, D., Bhat, Z. P., Lai, K. H., Yang, F., and Hu, X. (2023). Data-centric ai: Perspectives and challenges. In Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) (pp. 945-948). Society for Industrial and Applied Mathematics.