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College of Business, Law and Governance Research Research Opportunities for prospective PhD students

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Research opportunities for prospective PhD students

Enterprise and sector transformation

Rather than just reacting to change, successful enterprises proactively drive strategic transformations setting new performance frontiers for themselves and, in most cases, the sectors in which they operate. Opportunities exist for doctoral candidates to become involved in developing frameworks to drive enterprise and sector transformation. Projects can focus on a variety of contexts such as SMEs and corporates, for-profit and non-for-profit entities, start-ups, and NGOs to name a few.

Advisor: Professor Siggi Gudergan


Complex systems thinking and modelling to navigate wicked business problems

Business challenges frequently surface as inadvertent byproducts of past actions. Businesses, and the ecosystems within which they operate, often grapple with policy resistance – the inclination for well-meant interventions to be thwarted by the system’s reaction to the very interventions themselves. Through capturing the numerous interlinked and interdependent components within the ecosystem, as well as dynamic and nonlinear interactions amongst them, complex systems modelling can unveil the many unforeseeable emergent behaviours and outcomes that prove arduous to manage.

Given the significance of navigating such complexities, senior management must cultivate proficiency in systems thinking. However, the precise impact of complex systems modelling on their decision-making process, which necessitates adaptability, remains unclear. Adaptive decision-making involves assimilating knowledge, enhancing understanding, and tailoring managerial decisions effectively, all aimed at adeptly managing uncertainties.

We invite expressions of interest from potential doctoral researchers to engage in projects aimed at unravelling how the structure and data generated by complex systems modelling influence the strategic decisions of senior management, especially when these decisions carry substantial consequences, such as those involving significant capital investments. Doctoral research projects will discern how such modelling facilitates adaptive decision-making in the face of uncertainty.

Advisors: Professor Nico AdamsProfessor Siggi Gudergan


Adaptive decision making to improve strategic resource allocation

Strategic decisions regarding the allocation of resources within the realm of business are inherently complex and imbued with uncertainty. The progression of modelling complex systems to furnish insights for these strategic decisions – such as those concerning substantial capital investments – not only offers a more nuanced comprehension but also holds significant potential for enhancing, or even revolutionizing, this decision-making process. Nonetheless, the precise manner in which senior management incorporates data from complex systems modelling into their decision-making that essentially is adaptive remains unclear. Adaptive decision-making denotes a process of assimilating knowledge, refining comprehension, and ultimately tailoring managerial decision making in an effective manner, directed at effectively managing uncertainties.

We welcome expressions of interest from prospective doctoral students for research projects that aim to elucidate how the adaptive decision-making of senior management functions, particularly in instances where they can harness the insights derived from complex systems modelling data.

Advisors: Professor Siggi Gudergan, Professor Nico Adams,


Foreign Direct Investment and Its Impacts on Domestic Firms

Foreign direct investment has played an important role in economic development, particularly for developing countries. The presence of foreign firms in the host economy is likely to affect domestic firms. For example, a number of existing studies have found FDI generates productivity spillovers to domestic firms. Researchers have summarized three channels that such spillovers can occur, namely the forward and backward linkages, worker mobility and competition and demonstration effects. Given the potential productivity spillovers from FDI, this project seeks to investigate how the presence of FDI affects domestic firms’ behaviour, such as innovation, advertising, and exporting, both theoretically and empirically in a host economy.

Advisor: A/Prof Sizhong Sun


Technology Adoption by Women in Agriculture

The adoption of rural technology is critical to increasing agricultural production.  Graziers, both men and women, need to be supported in their efforts to work smarter not harder.  Commonly graziers make decisions via direct observation of cattle management parameters  (e.g. water levels, rainfall, and distance to bores, National Livestock Identification Systems (NLIS) data recording), as well as visual cues from stock.  Adopting rural technologies can help reduce time and costs associated with direct observation and hands on farming.  Understanding user acceptance of rural technologies is critical because it will provide points of interest, which can be used to create favourable perceptions and thus foster user acceptance and usage.  Access to technology also allows the rural community to remain in contact with each other, whether by social media, email or through other smart technology, making farming less isolating and more enjoyable.  The social position of isolated rural women and men, who rely on technology for communication, business management and productivity related tasks, shapes the understanding of problems associated with innovation and the adoption of rural technology amongst beef producers in Queensland.

The research aims to further establish women’s role in the diffusion of digital technology to beef production and changes in technology adoption over time.  In addition, the research aims to explore and expand the notion that women using technology can reduce isolation within the farming partnership, particularly for men, reducing isolations effect on the well- being of the men, the women and the farming family and to explore the attractiveness of technological properties and technologies effect on staff retention and succession.

Advisor: Dr Rachel Hay