Towards an Algorithm-Based Automatic Differentiation of Liability Cases by Analyzing Complaint Texts

Insa Lemke, Nadine Schlüter

2024

Abstract

Effective complaints management is important to maintain customer loyalty and offers the opportunity to feed knowledge back into product development and production. However, with products and supply chains becoming increasingly complex, the picture is often unclear when it comes to handling complaints. This applies in particular to the handling of legal liability issues. The challenge arises from the correct classification of the various legal bases in connection with the receipt of a customer complaint. To this end, we introduce the concept of an algorithm that uses automatic text recognition to analyze the text of a complaint and determine whether a liability case may exist under German law. This paper presents the different development steps and phase components of the algorithm as well as the current implementation status.

Paper Citation

in Harvard Style

Lemke I. and Schlüter N. (2024). Towards an Algorithm-Based Automatic Differentiation of Liability Cases by Analyzing Complaint Texts. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 603-611. DOI: 10.5220/0012569100003690

in Bibtex Style

@conference{iceis24,
author={Insa Lemke and Nadine Schlüter},
title={Towards an Algorithm-Based Automatic Differentiation of Liability Cases by Analyzing Complaint Texts},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={603-611},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012569100003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Towards an Algorithm-Based Automatic Differentiation of Liability Cases by Analyzing Complaint Texts
SN - 978-989-758-692-7
AU - Lemke I.
AU - Schlüter N.
PY - 2024
SP - 603
EP - 611
DO - 10.5220/0012569100003690
PB - SciTePress