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- All Subjects: Economics
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The questionnaire was then used in conjunction with two interviews of small business owners. The interviews covered both the overall financial status of their business and their business’ pre-existing accounting system. The feedback received during these interviews was subsequently used to provide the business owners with eleven recommendations ranging from the implementation of new policies to verification of existing internal controls.
Finally, I summarize my findings, both academic and real-world, conveying that many small business owners do not implement formal internal control systems. I also discuss why the business owners, in this specific circumstance, did not yet implement the aforementioned eleven suggestions.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
In the 21st century economy, life moves pretty fast, and change is happening all around us. For example, it was common to drive to shopping malls with your friends or family and spend the whole afternoon browsing through hundreds of items until you found the perfect purchase. Or, only a few months ago, the entire world was put on lockdown to stop the spread of COVID-19, which caused a recession when consumers stopped spending as much to start saving. Americans also used to enjoy their loud, gas-guzzling cars and trucks to get them from place to place. Now what changed, and why? The study of economics justifies how we, as human, fundamentally live and make choices every day. As we notice the results of our choices, we may continue to do the same the next day, temporarily go another route, or alter our behavior permanently. This framework presents the concept of innovation. By applying this logic to the business world, I will attempt to analyze and defend why the innovations of e-commerce, COVID-19 vaccines, and electric vehicles were the natural cause of society changing perspective to move forward toward a better tomorrow.