Observed and Potential Conflicts in Management of Interdependent Infrastructure Systems
Publication: Journal of Management in Engineering
Volume 40, Issue 4
Abstract
In recent decades, there has been considerable research into how infrastructure systems and sectors mutually rely upon each other, how a single failure in one system can cascade and affect numerous systems, and how collective restoration sequences should be conceived. However, lacking in these discussions are how individual decision-making heuristics, intraorganizational structure and priorities, and interorganizational conflict influence infrastructure operator decisions, and how this, in turn, influences the collective performance and reliability of coupled infrastructure. Building upon literature on intra- and interorganizational conflict and governance, we develop a conceptual framework for contextualizing the operational and strategic decision patterns of operators of complex interdependent systems during situations of high uncertainty. This enables us to pinpoint (some) sources of conflict that, if addressed and resolved, could induce multiple beneficial collective outcomes. These benefits, in principle, include faster outage recoveries and better reliability. The framework is demonstrated in proof-of-concept case study of outages of an interdependent infrastructure system (electrical power, steam, water, and information technology) at a large university campus in the US. Using cognitive task analysis, system operators were interviewed about their experiences with outage events. The resulting qualitative data were assessed for patterns using the framework. We find that (1) improved communication to reduce ambiguity, (2) stronger relational norms, and (3) alternative contractual incentives and penalties may induce better coordinated maintenance and operations across the systems. Because interdependent infrastructure modeling often examines only incentives and penalties, our results highlight how qualitative analysis of individual and organizational conflict and governance can provide complementary insights.
Practical Applications
Interdependent infrastructure systems, which are coupled via physical, geographic, institutional, and cyber linkages, are becoming increasingly critical to modern society while at the same time being exposed to greater threats, such as climate change. Thus, understanding their resilience to hazards is of great importance to the continuation of the reliable services they provide. Much of the scientific work in the area of interdependent infrastructure resilience has focused on creating optimal system configuration and response strategies, which provides useful guidance, but often neglects that such configurations and strategies will have to be operated and implemented by managers and operators, who by nature of being human, do not always act optimally. Thus, a gap in understanding of how managers and operators might behave when given the opportunity to act only in their personal or their system’s interest potentially leaves optimal plans vulnerable. This study outlines a framework for identifying ways in which noncooperative behavior among managers and operators might lead to interdependent infrastructure systems deviating from optimal behavior. Furthermore, the framework links these potential areas of conflict with management and governance responses that can be implemented to foster resilience across systems.
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Data Availability Statement
No data, models, or code were generated or used during the study.
Acknowledgments
This work is funded by grants from the National Science Foundation (NSF), Grant No. 1832642, “CRISP 2.0 Type 1: Accelerating restoration through information-sharing: Understanding operator behavior for improved management of interdependent infrastructure.” The support of the sponsor is gratefully acknowledged. Any opinions, findings, conclusions or recommendations presented in this paper are those of the authors and do not necessarily reflect the view of the National Science Foundation.
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Received: Sep 5, 2023
Accepted: Jan 5, 2024
Published online: Mar 30, 2024
Published in print: Jul 1, 2024
Discussion open until: Aug 30, 2024
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