Decision Making in Service Shops Supported by Mining Enterprise Resource Planning Data Article Swipe
Shaun West
,
Daryl Powell
,
Fabian Ille
,
Stefan Behringer
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/sci6020027
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/sci6020027
This research examines the application of Enterprise Resource Planning (ERP) systems in service shops, focusing on the specific challenges unique to these environments compared to those in the manufacturing sector. Service shops, distinguished by their smaller scale and variable demands, often need different functionalities in ERP systems compared to manufacturing facilities. Our analysis is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers. This study analyses ERP data from 27 service shops over 35 months. It is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers that support managerial decision making. Our findings emphasise the importance of incorporating additional contextual information to augment the effectiveness of ERP systems in service contexts. Our analysis shows that simple, standardised data mining methods can significantly enhance operational management decision making when supported with visuals to support understanding and interpretation of the data. Moreover, this study suggests potential directions for future research aimed at improving business analytics and intelligence practices to optimise the use of ERP systems in service industries. This research contributes to the academic discourse by providing empirical evidence on utilising ERP data in service shops and offers practical recommendations for ongoing operational improvements.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/sci6020027
- https://www.mdpi.com/2413-4155/6/2/27/pdf?version=1714900671
- OA Status
- gold
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All OpenAlex metadata
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https://doi.org/10.3390/sci6020027Digital Object Identifier
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Decision Making in Service Shops Supported by Mining Enterprise Resource Planning DataWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-05-05Full publication date if available
- Authors
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Shaun West, Daryl Powell, Fabian Ille, Stefan BehringerList of authors in order
- Landing page
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https://doi.org/10.3390/sci6020027Publisher landing page
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https://www.mdpi.com/2413-4155/6/2/27/pdf?version=1714900671Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2413-4155/6/2/27/pdf?version=1714900671Direct OA link when available
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Enterprise resource planning, Business, Service (business), Resource planning, Resource (disambiguation), Process management, Knowledge management, Computer science, Marketing, Environmental resource management, Environmental science, Computer networkTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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