Risks and Assets: A Qualitative Study of a Software Ecosystem in the Mining Industry

Thomas Olsson; Ulrik Franke

arxiv: 1907.08412 · v1 · pith:52PL4BYNnew · submitted 2019-07-19 · 💻 cs.SE

Risks and Assets: A Qualitative Study of a Software Ecosystem in the Mining Industry

Thomas Olsson , Ulrik Franke This is my paper

Pith reviewed 2026-05-24 19:16 UTC · model grok-4.3

classification 💻 cs.SE

keywords software ecosystemmining industryrisk managementservitizationdigitalizationservice level agreementsCAPEXOPEX

0 comments

The pith

Mining operators shift capital costs to vendors via leasing but manage risks through trust rather than contracts.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper studies how digitalization and servitization are changing asset ownership and risk allocation in a mining software ecosystem. It identifies a shift where mining operators move investment costs from capital expenses to operational expenses or full services provided by vendors. This transfers operational knowledge to suppliers and increases the operator's dependence on them for maintenance as systems grow more complex. Because the transition remains early, companies have not yet adopted formal risk tools such as service level agreements and instead depend on mutual trust and expectations of shared future innovation gains.

Core claim

The mining industry is moving investment costs from the operator to vendors through equipment leasing or service acquisition, which relocates knowledge and increases operator reliance on suppliers for operation and maintenance; in this early stage, risk management stays informal and rests on trust plus incentives from promised mutual innovation benefits rather than formalized agreements such as SLAs.

What carries the argument

The CAPEX-to-OPEX or service model transition in mining software ecosystems, which redistributes assets, knowledge, and operational responsibility from operators to vendors.

If this is right

Mining operators lose direct knowledge of infrastructure and become increasingly dependent on vendors for ongoing operation and maintenance.
Risks remain unaddressed through contracts because the ecosystem is still forming and participants lack immediate incentives to formalize them.
Cooperation in innovation activities substitutes for explicit risk allocation until an incident forces change.
System complexity grows without corresponding formal mechanisms to allocate responsibility for reliability or performance.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Other industrial domains undergoing similar servitization may face parallel gaps in risk allocation until incidents occur.
Developing ecosystem-specific quality definitions for reliability and performance could help companies move beyond informal trust.
The absence of incentives to address risk proactively suggests that external standards or regulatory pressure might accelerate formalization.

Load-bearing premise

The survey responses and focus group discussions accurately capture the distribution of assets, risks, and practices across the wider mining software ecosystem rather than only the participating companies.

What would settle it

A larger-scale survey or multiple case studies across mining operations that document widespread adoption of SLAs or other formal risk contracts would falsify the claim that companies currently rely primarily on trust.

read the original 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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper supplies a few new observations on CAPEX-to-OPEX shifts and informal risk handling in one mining SECO, but the lack of any methodological detail undercuts the broader claims.

read the letter

The main takeaway is that this paper records focus-group discussions showing mining operators shifting capital costs to vendors, leasing equipment as OPEX, and becoming more dependent on suppliers for maintenance and knowledge as systems grow complex. It also notes that SLAs are absent and companies instead rely on trust plus expected future gains from joint innovation. Those specifics are new data points for the SECO literature in this narrow domain. The survey of SLAs in other fields is a straightforward way to highlight the contrast. The work does a reasonable job of connecting the business-model change to operational consequences and flagging the missing formalized risk tools as a practical issue that may only get attention after an incident. That framing is clear and stays grounded in the conversations described. The soft spot is exactly what the stress-test note flags: the abstract and summary give no sample sizes, selection rules, interview guides, or analysis steps for either the survey or the focus groups. Without those, the leap to an “overall trend” across the mining ecosystem cannot be checked for selection bias or social-desirability effects, so the generalizability claim stays unsupported. The paper is otherwise coherent and does not invent entities or hide circular logic. It is aimed at readers who already work on software ecosystems in traditional heavy industries or on servitization cases. Someone looking for a quick industrial example might find the concrete descriptions useful, but the contribution is incremental and the evidence base is thin. I would bring it to a reading group only if the group has a specific interest in mining or IoT business models. I would not cite it myself because the scope is narrow and the documentation too light to build on. It still deserves a serious referee: the observations are worth recording if the methods section is expanded, and the topic is timely enough that review could strengthen the write-up without requiring a complete redo.

Referee Report

2 major / 2 minor

Summary. The paper presents a qualitative study of risks and asset distribution in a software ecosystem (SECO) and system-of-systems around mining operations. It reports results from a survey examining Service Level Agreements (SLAs) in other domains and from focus-group discussions with companies. The central claim is that the mining industry is shifting capital expenditure (CAPEX) from operators to vendors, causing operators to lease equipment or purchase services (OPEX), which moves knowledge and increases reliance on suppliers for operation and maintenance; because the shift is early-stage, formalized risk management via SLAs is absent and companies instead rely on trust and mutual innovation benefits.

Significance. If the descriptive claims hold, the work supplies primary empirical observations on how servitization and digitalization are reshaping business models and risk allocation inside a real-world SECO. This is useful for software-engineering research on ecosystems, as it identifies a concrete domain where cooperation incentives currently substitute for contractual risk controls and flags the resulting need for systematic quality and reliability definitions. The study also supplies a baseline against which future work on SLA design or incident-driven risk formalization in SECOs can be compared.

major comments (2)

[Abstract / Empirical study description] Abstract and the description of the empirical work: the paper states that a survey on SLAs and focus groups were conducted yet supplies no information on sample size, participant selection criteria, interview protocol, or thematic analysis procedure. Because the headline claim asserts an 'overall trend' across the mining software ecosystem, the absence of these details leaves the mapping from raw responses to the reported distribution of assets, risks, and risk-management practices unexamined and therefore load-bearing for the generalizability assertion.
[Results / Discussion of trends] Presentation of results on industry trends: the statements that 'there is an overall trend' of CAPEX-to-OPEX shift, increased operator reliance, and absence of SLAs rest on data from the participating companies without reported safeguards against selection bias or social-desirability effects. If the firms are atypical or their answers shaped by the research setting, the claimed ecosystem-wide patterns do not follow; this is the weakest link in moving from local observations to the central descriptive claim.

minor comments (2)

[Methods / Results] The survey on SLAs in other domains is mentioned but its specific findings are not contrasted with the mining focus-group data; a short table or paragraph separating the two data sources would improve traceability of which observations come from which instrument.
[Abstract] The abstract is unusually long and already contains the full set of conclusions; shortening it to the study design and key observations while moving interpretive claims to the discussion would improve conventional abstract structure.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for these detailed comments on our empirical methods and the presentation of results. We address each point below.

read point-by-point responses

Referee: [Abstract / Empirical study description] Abstract and the description of the empirical work: the paper states that a survey on SLAs and focus groups were conducted yet supplies no information on sample size, participant selection criteria, interview protocol, or thematic analysis procedure. Because the headline claim asserts an 'overall trend' across the mining software ecosystem, the absence of these details leaves the mapping from raw responses to the reported distribution of assets, risks, and risk-management practices unexamined and therefore load-bearing for the generalizability assertion.

Authors: We agree that the current manuscript lacks sufficient detail on the empirical procedures. In the revised version, we will add a dedicated Methods section describing the survey sample size and how participants were selected, the focus group composition and selection criteria, the protocol used to guide discussions, and the thematic analysis process. This will strengthen the transparency of how the data led to the reported findings on asset and risk distribution. revision: yes
Referee: [Results / Discussion of trends] Presentation of results on industry trends: the statements that 'there is an overall trend' of CAPEX-to-OPEX shift, increased operator reliance, and absence of SLAs rest on data from the participating companies without reported safeguards against selection bias or social-desirability effects. If the firms are atypical or their answers shaped by the research setting, the claimed ecosystem-wide patterns do not follow; this is the weakest link in moving from local observations to the central descriptive claim.

Authors: The study is explicitly qualitative and exploratory, as indicated in the title and abstract. We will revise the manuscript to include a Limitations section that discusses potential selection bias (companies were chosen for their active role in the ecosystem) and social-desirability effects, noting that focus groups were facilitated to encourage open discussion. We will also temper the language around 'overall trend' to reflect that these are observations from the studied participants rather than a claim of industry-wide statistical prevalence. The survey on SLAs in other domains serves as a point of comparison but is not used for generalization within mining. We believe these changes will address the concern without altering the core contribution. revision: partial

Circularity Check

0 steps flagged

No circularity: empirical qualitative study with no derivations or self-referential logic

full rationale

The paper reports primary data from a survey on SLAs in other domains and focus-group discussions with companies in the mining software ecosystem. All claims about CAPEX/OPEX shifts, knowledge transfer, reliance on suppliers, and absence of formalized SLAs are presented as direct observations from these data sources. No equations, fitted parameters, uniqueness theorems, ansatzes, or self-citation chains exist that could reduce any result to its inputs by construction. The derivation chain is therefore self-contained and consists solely of empirical reporting.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper introduces no free parameters, mathematical axioms, or invented entities. It rests on the standard domain assumption of qualitative research that focus-group and survey data can be treated as informative about real-world practices.

axioms (1)

domain assumption Focus group and survey responses provide reliable insights into industry practices
The study treats participant statements as representative of ecosystem-level changes without independent verification of response accuracy.

pith-pipeline@v0.9.0 · 5856 in / 1430 out tokens · 35948 ms · 2026-05-24T19:16:33.200059+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

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Issam Aib and Raouf Boutaba. 2007. On leveraging policy-based management for maximizing business profit. Network and Service Management, IEEE Transactions on 4, 3 (2007), 25–39

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Jakob Axelsson, Efi Papatheocharous, and Jesper Andersson. 2014. Character- istics of software ecosystems for Federated Embedded Systems: A case study. Information and Software Technology 56, 11 (2014), 1457–1475

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Markus Borg, Thomas Olsson, and John Svensson. 2017. Piggybacking on an Autonomous Hauler: Business Models Enabling a System-of-Systems Approach to Mapping an Underground Mine. In International Requirements Engineering Conference (RE). IEEE, 372–381. https://doi.org/10.1109/RE.2017.55

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Funmilade Faniyi and Rami Bahsoon. 2015. A Systematic Review of Service Level Management in the Cloud. ACM Comput. Surv. 48, 3, Article 43 (Dec. 2015), 27 pages. https://doi.org/10.1145/2843890

work page doi:10.1145/2843890 2015

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Bent Flyvbjerg. 2006. Five Misunderstandings About Case-Study Research. Qual- itative Inquiry 12 (2006), 219–45. https://doi.org/doi:10.1177/1077800405284363

work page doi:10.1177/1077800405284363 2006

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Ulrik Franke. 2012. Optimal IT Service Availability: Shorter Outages, or Fewer? Network and Service Management, IEEE Transactions on 9, 1 (2012), 22–33

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Ulrik Franke and Markus Buschle. 2016. Experimental Evidence on Decision- Making in Availability Service Level Agreements. IEEE Transactions on Network and Service Management 13, 1 (2016), 58–70. https://doi.org/10.1109/TNSM.2015. 2510080

work page doi:10.1109/tnsm.2015 2016

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Axel Kieninger, Detlef Straeten, Steven Orla Kimbrough, Björn Schmitz, and Gerhard Satzger. 2013. Leveraging Service Incident Analytics to Determine Cost- Optimal Service Offers. In 11th International Conference on Wirtschaftsinformatik . 1015–1029

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Bill Malik and Donna Scott. 2010. How to Calculate the Cost of Continuously A vailable IT Services. Technical Report. Gartner, Inc

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Messerschmitt and Clemens Szyperski

David G. Messerschmitt and Clemens Szyperski. 2003. Software Ecosystem: Un- derstanding an Indispensable Technology and Industry (1 ed.). Vol. 1. MIT Press

work page 2003

[17] [17]

Nguyen, L

T. Nguyen, L. Le, K. Nguyen-An, and T. Truong. 2017. Aligning Service Level Agreements with Service-Oriented Enterprise Architecture. In 2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW), Vol. 00. 8–14. https://doi.org/10.1109/EDOCW.2017.11

work page doi:10.1109/edocw.2017.11 2017

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2010.Critical Elements of Cloud-Based Con- tact Center Services: Pricing, Service-Level Agreements and Service Integration

Daniel O’Connell and Drew Kraus. 2010.Critical Elements of Cloud-Based Con- tact Center Services: Pricing, Service-Level Agreements and Service Integration . Technical Report. Gartner, Inc

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[19] [19]

Neil Rickard and Danellie Young. 2013. Bandwidth Doesn’t Matter; A vailability Drives Enterprise Network Costs . Technical Report. Gartner, Inc

work page 2013

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Colin Robson. 2011. Real World Research (3rd ed ed.). Wiley

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Per Runeson, Martin Höst, Austin Rainer, and Björn Regnell. 2012. Case Study Research in Software Engineering: Guidelines and Examples . John Wiley & Sons, Inc. https://doi.org/10.1002/9781118181034

work page doi:10.1002/9781118181034 2012

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Carolyn B Seaman. 2008. Qualitative methods. In Guide to advanced empirical software engineering. Springer, 35–62

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Gheorghe Cosmin Silaghi, Liviu Dan Şerban, and Cristian Marius Litan. 2010. A framework for building intelligent SLA negotiation strategies under time constraints. In Economics of Grids, Clouds, Systems, and Services . Springer, 48–61. Pre-print Risks and Assets: A Qualitative Study ESEC/FSE ’19, August 26–30, 2019, Tallinn, Estonia Table 3: SLA survey re...

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Sharon Taylor, Vernon Lloyd, and Colin Rudd. 2007. Service Design (ITIL) . The Stationery Office, TSO. See Appendix F

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Edwin Yaqub, Ramin Yahyapour, Philipp Wieder, Constantinos Kotsokalis, Kuan Lu, and Ali Imran Jehangiri. 2014. Optimal Negotiation of Service Level Agree- ments for Cloud-Based Services through Autonomous Agents. In Services Com- puting (SCC), 2014 IEEE International Conference on . IEEE, 59–66

work page 2014