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  4. Turning Big Data Into Value: A Literature Review On Business Value Realization From Process Mining Research Paper
 
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Turning Big Data Into Value: A Literature Review On Business Value Realization From Process Mining Research Paper

Type
conference paper
Date Issued
2020
Author(s)
Eggers, Julia
Hein, Andreas  
Abstract
In recent years, process mining has emerged as the leading Big Data technology for business process analysis. By extracting knowledge from event logs readily available in information systems, process mining provides new ways to discover, monitor, and improve processes while being agnostic to the source system. Despite its undisputed practical relevance, we have a limited understanding of how organizations realize value potentials from applying process mining in different organizational contexts. Addressing this gap, we conduct an assessing literature review by analyzing 58 papers from the literature on process mining to synthesize the existing knowledge on business value realization from process mining. Our analysis is guided by adopting the perspective of process mining embedded within its organizational context. By analyzing the dimensions of the nomological net around process mining, we contribute to the broader research field of Big Data value realization twofold. First, we uncover which benefits organizations gain by applying process mining. Second, we analyze the organizational capabilities and practices that influence how organizations use and implement process mining. In addition, we reveal how process mining leads to business value realization. Based on these results, we suggest directions for future research on process mining in the organizational context.
Language
English (United States)
Keywords
Big Data Analytics
Process Mining
IS Value Realization
Antecedents
HSG Classification
contribution to scientific community
Refereed
Yes
Event Title
European Conference on Information Systems
Event Location
Virtual Conference
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/119383
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

File(s)
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Thumbnail Image

open.access

Name

Eggers & Hein_2020 ECIS.pdf

Size

673.01 KB

Format

Adobe PDF

Checksum (MD5)

c6b8c74d8e2d1fbb851255bce56b55c8

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