The DOI matches its Crossref record; 92 of the 95 references it cites were found in a registry or an index.
Controlling Technical Debt Remediation in Outsourced Enterprise Systems Maintenance: An Empirical Analysis
Abstract
Technical debt refers to maintenance obligations that stem from violations of established standards during the development and subsequent maintenance of enterprise systems. Technical debt remediation is particularly challenging in the outsourcing context due to information asymmetry between client and vendor teams. Control balancing—the periodic adjustments to the control configurations of outsourced projects—has been proposed as a process to help mitigate these information asymmetry challenges. Using data collected from 1,824 real-world projects, we tested to what extent control balancing improves the remediation of technical debt. After controlling for a number of technical and environmental factors, including system size, system lifespan, and contract parameters, we find that control balancing can benefit technical debt remediation, but primarily when processes for migrating technical debt-laden systems to new technological platforms have been identified. We highlight the role of technical debt in influencing the effects of relational flexibility in inter-firm engagements.
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In the citing paper
“In our context, we contend that the growing reliance on AI-assisted development may accelerate the accumulation of technical debt, as design shortcuts taken to expedite system deployment become embedded in software systems (Ramasubbu and Kemerer 2016, 2021).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Ramasubbu and Kemerer 2021
In the citing paper
“While GenAI promises to enhance development speed and broaden participation, it may simultaneously intensify the very technical debt that constrains system reliability, scalability, and long-run performance (Ramasubbu and Kemerer 2021).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Ramasubbu and Kemerer 2021
In the citing paper
“we measured technical debt at the project level using PR rework, which reflects the extent to which initially submitted contributions require modification before being integrated into the codebase (Ramasubbu and Kemerer 2016, 2021).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Ramasubbu and Kemerer 2021
In the citing paper
“Specifically, Banker et al. (2021), Ramasubbu and Kemerer (2021) measure technical debt as the proportion of customized code in customer relationship management (CRM) systems that does not adhere to vendor-prescribed standards.”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Ramasubbu and Kemerer 2021
In the citing paper
“In this study, we operationalize technical debt through process and outcome indicators, using rework rates, and maintenance effort, thereby connecting debt to developer behavior and organizational performance (Banker et al. 2021, Ramasubbu and Kemerer 2021).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Ramasubbu and Kemerer 2021
Citations
Cites
(2014) · Palgrave Macmillan eBooks · doi:10.1057/9781137399595.0007 · Cited by 8,312
Testing for Weak Instruments in Linear IV Regression
Stock, J. H., & Yogo, M. (2005) · Identification and Inference for Econometric Models · doi:10.1017/cbo9780511614491.006 · Cited by 7,211
Fama, E., & French, K. (1997) · Journal of Financial Economics · doi:10.1016/s0304-405x(96)00896-3 · Cited by 5,776
A Conceptual Framework for the Design of Organizational Control Mechanisms
Ouchi, W. G. (1979) · Management Science · doi:10.1287/mnsc.25.9.833 · Cited by 3,707
Control: Organizational and Economic Approaches
Eisenhardt, K. M. (1985) · Management Science · doi:10.1287/mnsc.31.2.134 · Cited by 2,065
Steps toward a science of service systems
Spohrer, J., Maglio, P. P., Bailey, J., & Gruhl, D. (2007) · Computer · doi:10.1109/mc.2007.33 · Cited by 1,264
An Empirical Investigation of Information Technology Sourcing Practices: Lessons from Experience1
Lacity, M. C., & Willcocks, L. P. (1998) · MIS Quarterly · doi:10.2307/249670 · Cited by 1,005
Papell, C. P., & Skolnik, L. R. (1992) · Journal of Social Work Education · doi:10.1080/10437797.1992.10778754 · Cited by 1,000
Antecedents of Knowledge Transfer from Consultants to Clients in Enterprise System Implementations
Ko, D., Kirsch, L. J., & King, W. R. (2005) · Journal of the Association for Information Systems · Cited by 978
Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams
Hinds, P. J., & Bailey, D. E. (2003) · Organization Science · doi:10.1287/orsc.14.6.615.24872 · Cited by 974
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Metadata
- Authors
- Ramasubbu, N., & Kemerer, C. F.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Kemerer, Chris F.
- Venue
- Journal of Management Information Systems
- Publisher
- Informa UK Limited
- Published
- 2021-01-02
- Volume
- 38
- Issue
- 1
- Pages
- 4-28
- ISSN
- 0742-1222 (ISSN-L)
- 1557-928X
- OpenAlex
- W3151948865
- Cited by
- 17
- References
- 95
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 2 · 2023: 3 · 2022: 1 · 2021: 2
- FWCI
- 1.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Management Information Systems (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Outsourcing and Supply Chain Management
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Keywords
- technical debt, software maintenance, software outsourcing, information asymmetry, enterprise systems, inter-firm relationships
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
