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bit more of this and that

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Daniel Rosel
2025-12-12 20:15:29 +01:00
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paper/src/chapters/03-methodology.tex
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@@ -15,9 +15,7 @@ Mathematical demonstration and validation of the COI and citation backed evidenc
\subsection{System Architecture} \subsection{System Architecture}
In order for our research to have grounding in interactions we built a robust e-commerce web-platform. We initially conducted a survey of the leading platforms of airlines and hotel booking sites to identify the specific interface patterns that effectively manage complex travel data. Our analysis revealed a clear industry standard: while both sectors rely on tabbed service selection and left-sidebar filtering to streamline navigation, they diverge in result presentation—airlines utilize visual date-price bars and multi-step wizards to optimize for logistical transparency, whereas hotel platforms leverage image-led cards and scarcity triggers to drive emotional engagement and urgency. Our web framework defines a highly agnostic boilerplane which can be seeded with any data-modality with an easy-to-tailor pattern, which we leverage to define a \texttt{hotel} and \texttt{airline} mode. Both modes are then individually deployed via an envrionment level argument which adjusts the proxy routing with a custom middleware inside next.js to render only the desired mode. The purpose of this was to create a baseline adaptable to any use-case or desired commercial application. In order for our research to have grounding in interactions we built a robust e-commerce web-platform. We initially conducted a survey of the leading platforms of airlines and hotel booking sites to identify the specific interface patterns that effectively manage complex travel data. Our analysis revealed a clear industry standard: while both sectors rely on tabbed service selection and left-sidebar filtering to streamline navigation, they diverge in result presentation: airlines utilize visual date-price bars and multi-step wizards to optimize for logistical transparency, whereas hotel platforms leverage image-led cards and scarcity triggers to drive emotional engagement and urgency. Our web framework defines a highly agnostic boilerplane which can be seeded with any data-modality with an easy-to-tailor pattern, which we leverage to define a \texttt{hotel} and \texttt{airline} mode. Both modes are then individually deployed via an envrionment level argument which adjusts the proxy routing with a custom middleware inside next.js to render only the desired mode. The purpose of this was to create a baseline adaptable to any use-case or desired commercial application.
\subsection{Experimental Design} \subsection{Experimental Design}
@@ -28,7 +26,9 @@ In order for our research to have grounding in interactions we built a robust e-
} }
\caption{Overview of the Dynamic Pricing Tasks.} \caption{Overview of the Dynamic Pricing Tasks.}
\end{figure} \end{figure}
Study methodology and approach. Data acquisition strategy. Defined objectives and success criteria. Observable metrics and KPIs
Study methodology and approach. Data acquisition strategy. Defined objectives and success criteria. Observable metrics and KPIs.
\subsection{Dynamic Pricing Algorithm Analysis} \subsection{Dynamic Pricing Algorithm Analysis}
Deep dive into how the algorithm works, different kinds and justification for chosen appraoches + agent impact modeling and quantification. Deep dive into how the algorithm works, different kinds and justification for chosen appraoches + agent impact modeling and quantification.