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The Foundation of Dissertation Proposal Elements
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The Foundation of Dissertation Proposal Elements
Introduction
Developing a dissertation proposal necessitates establishing a robust theoretical
framework that fundamentally grounds the envisaged research from the outset of the process.
Grant & Osanloo (2014) emphasize that theory-driven thinking is at the core of selecting a
research topic, formulating research questions, and creating a well-structured proposal. In this
discussion, we will delve into three essential elements of a dissertation proposal – the research
topic, the research gap, and the research design. Each of these indispensable components holds
significant influence over the course and caliber of the research by virtue of their respective
functions. A doctoral-level dissertation will only achieve success if its fundamental parts are
distinctly expressed, and its arguments are backed thoroughly by previous scholarly works.
The Research Topic:
The research topic is the foundation upon which the entire dissertation proposal rests.
Choosing the proper subject matter is a pivotal choice as it delineates the range and path of the
investigation. A well-defined research topic should be of scholarly interest, relevant to the field
of study, and offer opportunities for original contributions. The topic I have selected for my
proposed research, examining the effect that artificial intelligence has on maintaining business
viability within the evolving commercial environment, holds considerable significance as
technological progress continues transforming industries and economies at large (Grant &
Osanloo, 2014). This research topic was ultimately selected owing to a thorough analysis of the
breadth of literature that served to inform and substantiate the choice fully. There has been
significant discussion among experts regarding the possibility of artificial intelligence radically
changing various domains, such as commerce and environmental protection, through novel
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applications and innovations. Scholars like Brynjolfsson and Rubeis (2020) underscored the
disruptive power of AI technologies, suggesting these innovations carry the potential to
meaningfully reshape customary models of commerce by significantly altering traditional
business approaches. Additionally, researchers such as Strydom & Buckley (2018) have pointed
out the importance of sustainability in the context of contemporary business practices. Despite
extensive research exploring AI's influence on organizational productivity and endurance
individually, comprehensive evaluations integrating these two viewpoints simultaneously still
need to be made available. Most existing studies tend to focus on AI's implications for business
operations or its contribution to sustainability, but rarely do they explore the interplay between
these two aspects. My investigation seeks to close this divide by exploring how artificial
intelligence can boost sustainable business operations and, reciprocally, how applying
sustainability can encourage innovative practices powered by advanced technologies.
The Research Gap:
Identifying a research gap is a pivotal step in the dissertation proposal process, as it
demonstrates that the proposed study adds value to the existing body of knowledge. A research
gap is an area within the literature where there is a lack of sufficient or conclusive research,
creating an opportunity for further investigation. As mentioned earlier, my research topic, "The
Impact of Artificial Intelligence on Business Sustainability," is underpinned by a specific
research gap that demands exploration. The existing literature on AI and business sustainability
primarily focuses on the isolated effects of AI on business efficiency, cost reduction, and
innovation or sustainability practices such as green supply chain management, corporate social
responsibility, and environmental regulations. While these individual aspects are important, there
is limited research that connects these two domains to understand how AI adoption can enhance
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sustainability practices in a broader sense. This gap is evident in the study by Strydom &
Buckley (2020), who examined the effect of AI on business performance but needed to explore
its implications for sustainability extensively.
The Research Design:
The research design is a critical aspect of any dissertation proposal, as it outlines the
methodology and approach that will be used to address the research questions and bridge the
identified research gap. In the context of this research, the research design is a key component. It
guarantees the validity and reliability of the study. To address the research questions and bridge
the research gap, it is viable to adopt a mixed-method research design. This design will allow for
a comprehensive and multifaceted exploration of the research topic. The quantitative component
will involve the collection and analysis of data from a large sample of businesses to understand
the extent of AI adoption and its impact on business sustainability metrics. This quantitative
phase will draw upon existing surveys and datasets to provide a wide-ranging perspective. The
qualitative aspect of the research design will involve in-depth interviews and case studies with
select organizations that have successfully integrated AI into their sustainability initiatives. This
qualitative phase will provide insights into the strategies and best practices adopted by these
organizations, offering a deeper understanding of the mechanisms by which AI can enhance
sustainability. By combining quantitative and qualitative methods, this research design aligns
with Grant & Osanloo's (2014) emphasis on selecting and integrating a theoretical framework in
dissertation research.
Conclusion
It is conclusive that a winning dissertation proposal rests on solid grounds of defined
subject matter, evident research hole, and substantial research model. The selection of this
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research topic, "The effect of AI on business sustainability," is based on a literature review that
reflects its importance and scientific significance. Thus, this suggests a research gap, evidenced
by the limited holistic work conducted on AI and business sustainability, which offers additional
scope for investigation and a potential contribution to the area. This is a mixed method involving
a design for the research that focuses on bridging the research gap through a blend of quantitative
and qualitative approaches in addressing the research questions.
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References
Grant, C., & Osanloo, A. (2014). Understanding, selecting, and integrating a theoretical
framework in dissertation research: Creating the blueprint for your ‘house.’
Administrative Issues Journal Education Practice and Research, 4(2).
https://doi.org/10.5929/2014.4.2.9
Rubeis, G. (2020). The disruptive power of artificial intelligence. Ethical aspects of
gerontechnology in elderly care. Archives of Gerontology and Geriatrics, 91, 104186.
https://www.sciencedirect.com/science/article/abs/pii/S0167494320301801
Strydom, M., & Buckley, S. (Eds.). (2019). AI and big data’s potential for disruptive innovation.
IGI Global.
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