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Risks and assets: a qualitative study of a software ecosystem in the mining industry

Published: 12 August 2019 Publication History

Abstract

Digitalization and servitization are impacting many domains, including the mining industry. As the equipment becomes connected and technical infrastructure evolves, business models and risk management need to adapt. In this paper, we present a study on how changes in asset and risk distribution are evolving for the actors in a software ecosystem (SECO) and system-of-systems (SoS) around a mining operation. We have performed a survey to understand how Service Level Agreements (SLAs) -- a common mechanism for managing risk -- are used in other domains. Furthermore, we have performed a focus group study with companies. There is an overall trend in the mining industry to move the investment cost (CAPEX) from the mining operator to the vendors. Hence, the mining operator instead leases the equipment (as operational expense, OPEX) or even acquires a service. This change in business model impacts operation, as knowledge is moved from the mining operator to the suppliers. Furthermore, as the infrastructure becomes more complex, this implies that the mining operator is more and more reliant on the suppliers for the operation and maintenance. As this change is still in an early stage, there is no formalized risk management, e.g. through SLAs, in place. Rather, at present, the companies in the ecosystem rely more on trust and the incentives created by the promise of mutual future benefits of innovation activities. We believe there is a need to better understand how to manage risk in SECO as it is established and evolves. At the same time, in a SECO, the focus is on cooperation and innovation, the companies do not have incentives to address this unless there is an incident. Therefore, industry need, we believe, help in systematically understanding risk and defining quality aspects such as reliability and performance in the new business environment.

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  • (2024)5G goes underground: A Proof-of-Concept Using Digital Twin for Real-time Control and Monitoring2024 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)10.1109/EuCNC/6GSummit60053.2024.10597103(961-966)Online publication date: 3-Jun-2024
  • (2024)Multimodal data fusion for geo-hazard prediction in underground mining operationComputers and Industrial Engineering10.1016/j.cie.2024.110268193:COnline publication date: 1-Jul-2024
  • (2023)Navigating the Cyber-Security Risks and Economics of System-of-Systems2023 18th Annual System of Systems Engineering Conference (SoSe)10.1109/SoSE59841.2023.10178677(1-8)Online publication date: 14-Jun-2023
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cover image ACM Conferences
ESEC/FSE 2019: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
August 2019
1264 pages
ISBN:9781450355728
DOI:10.1145/3338906
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 12 August 2019

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Author Tags

  1. Case study
  2. Risk Management
  3. Service Level Agreement
  4. Software ecosystem
  5. Survey

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Overall Acceptance Rate 112 of 543 submissions, 21%

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Cited By

View all
  • (2024)5G goes underground: A Proof-of-Concept Using Digital Twin for Real-time Control and Monitoring2024 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)10.1109/EuCNC/6GSummit60053.2024.10597103(961-966)Online publication date: 3-Jun-2024
  • (2024)Multimodal data fusion for geo-hazard prediction in underground mining operationComputers and Industrial Engineering10.1016/j.cie.2024.110268193:COnline publication date: 1-Jul-2024
  • (2023)Navigating the Cyber-Security Risks and Economics of System-of-Systems2023 18th Annual System of Systems Engineering Conference (SoSe)10.1109/SoSE59841.2023.10178677(1-8)Online publication date: 14-Jun-2023
  • (2023)Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining DigitalizationIEEE Access10.1109/ACCESS.2023.326781311(40608-40628)Online publication date: 2023
  • (2020)IT service outage cost: case study and implications for cyber insuranceThe Geneva Papers on Risk and Insurance - Issues and Practice10.1057/s41288-020-00177-445:4(760-784)Online publication date: 16-Jul-2020
  • (2020)Enterprise IT service downtime cost and risk transfer in a supply chainOperations Management Research10.1007/s12063-020-00148-xOnline publication date: 21-Feb-2020

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