HU-Thesis | Survival Analysis for Management Support in E-Commerce
kandi X-RAY | HU-Thesis Summary
kandi X-RAY | HU-Thesis Summary
HU-Thesis is a Jupyter Notebook library. HU-Thesis has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
Survival Analysis for Management Support in E-Commerce
Survival Analysis for Management Support in E-Commerce
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HU-Thesis has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
HU-Thesis has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of HU-Thesis is current.
Quality
HU-Thesis has no bugs reported.
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HU-Thesis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
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HU-Thesis does not have a standard license declared.
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HU-Thesis releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
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Code Repository for M.Sc. Thesis in Economics and Management Science at Humboldt-Universität zu Berlin. In the past decade, we have seen the rise of numerous online marketplaces for used cars. This study explores the efficacy of combining survival analysis with model explanation frameworks to enhance the management system of online platforms. We extend the work done by Jerenz (2008) to estimate the demand function of used cars for a specific dealership using survival analysis. During the price and survival modelling stages, various models are evaluated to identify the key factors that impact demand. Finally, we apply the recently developed SurvSHAP(t) framework to derive key insights and recommendations for supporting online platforms. This study was done in collaboration with a private sector entity and the data used can not be shared.
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