Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data

Samaneh Beheshti-Kashi; Aseem Kinra; Jürgen Pannek

doi:10.1016/j.ifacol.2019.11.449

Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data

Samaneh Beheshti-Kashi, Aseem Kinra, Jürgen Pannek

School of Energy, Geoscience, Infrastructure and Society

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

Within this paper, we aim to highlight the potential of unstructured data sources such as blogs to complement and improve data triangulation and to support supply chain decision making. To this end, we combine the fields of supply chain management and control theory to provide a proof of concept for the utilization of unstructured data. An in-depth application example for the monitoring of trends on product features in fashion supply chains is developed using blog based textual data. The application example demonstrates predictive validity and forecasting risks of expert opinions found in textual data.

Original language	English
Pages (from-to)	1721-1726
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	52
Issue number	13
DOIs	https://doi.org/10.1016/j.ifacol.2019.11.449
Publication status	Published - 25 Dec 2019
Event	9th IFAC Conference on Manufacturing Modelling Management and Control 2019 - Berlin, Germany Duration: 28 Aug 2019 → 30 Aug 2019

Keywords

decision support systems
data processing
production
identification
estimation

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10.1016/j.ifacol.2019.11.449

Cite this

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title = "Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data",

abstract = "Within this paper, we aim to highlight the potential of unstructured data sources such as blogs to complement and improve data triangulation and to support supply chain decision making. To this end, we combine the fields of supply chain management and control theory to provide a proof of concept for the utilization of unstructured data. An in-depth application example for the monitoring of trends on product features in fashion supply chains is developed using blog based textual data. The application example demonstrates predictive validity and forecasting risks of expert opinions found in textual data.",

keywords = "decision support systems, data processing, production, identification, estimation",

author = "Samaneh Beheshti-Kashi and Aseem Kinra and J{\"u}rgen Pannek",

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T1 - Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data

AU - Beheshti-Kashi, Samaneh

AU - Kinra, Aseem

AU - Pannek, Jürgen

PY - 2019/12/25

Y1 - 2019/12/25

N2 - Within this paper, we aim to highlight the potential of unstructured data sources such as blogs to complement and improve data triangulation and to support supply chain decision making. To this end, we combine the fields of supply chain management and control theory to provide a proof of concept for the utilization of unstructured data. An in-depth application example for the monitoring of trends on product features in fashion supply chains is developed using blog based textual data. The application example demonstrates predictive validity and forecasting risks of expert opinions found in textual data.

AB - Within this paper, we aim to highlight the potential of unstructured data sources such as blogs to complement and improve data triangulation and to support supply chain decision making. To this end, we combine the fields of supply chain management and control theory to provide a proof of concept for the utilization of unstructured data. An in-depth application example for the monitoring of trends on product features in fashion supply chains is developed using blog based textual data. The application example demonstrates predictive validity and forecasting risks of expert opinions found in textual data.

KW - decision support systems

KW - data processing

KW - production

KW - identification

KW - estimation

U2 - 10.1016/j.ifacol.2019.11.449

DO - 10.1016/j.ifacol.2019.11.449

M3 - Conference article

SN - 2405-8963

VL - 52

SP - 1721

EP - 1726

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 13

T2 - 9th IFAC Conference on Manufacturing Modelling Management and Control 2019

Y2 - 28 August 2019 through 30 August 2019

ER -

Complementing Decision Support and Forecasting Risk in Supply Chain with Unstructured Data

Abstract

Keywords

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