Reserve–Interruption Management: An Epistemological Framework for Operational Diagnosis and Continuity Preservation
Main Article Content
Abstract
Livestock systems increasingly operate under conditions of recurring disasters, climate variability, market instability, and logistical disruption, where maintaining operational continuity depends not only on resource availability but also on the timely diagnosis of operational conditions. Existing continuity-oriented approaches have advanced preparedness, recovery planning, and resilience; however, they generally emphasize hazards, resources, or post-disruption recovery rather than the diagnostic reasoning through which operational interventions are formulated under temporal constraint.
This study proposes Reserve–Interruption Management (RIM) as a field-embedded diagnostic methodology for preserving operational continuity in livestock systems. Using a qualitative conceptual methodology integrating strategic discourse analysis, epistemological analysis, and systems interpretation, the study develops a continuity-oriented diagnostic framework in which diagnosis begins with the first diagnostic question, which determines the object of preservation before empirical evidence is interpreted. The methodology subsequently identifies the operational object, diagnoses its conditions of existence, determines its operational position, and guides configuration adjustment and operational synchronization within the remaining temporal window.
The study introduces several interrelated concepts, including conditions of existence, operational position, configuration adjustment, operational synchronization, and the first diagnostic question as the epistemological foundation of diagnosis. Within this framework, empirical evidence does not constitute diagnosis itself; rather, evidence acquires diagnostic meaning only after the operational object and its operational context have been identified. Diagnosis therefore functions not merely as an assessment of existing conditions, but as a mechanism for preserving meaningful intervention capability before critical temporal windows close.
By repositioning diagnosis as the primary mechanism of continuity management, RIM shifts analytical attention from resource preservation toward diagnostic intervention. Operational continuity is consequently understood as the capability of operational systems to sustain intended developmental trajectories across successive production cycles through timely diagnosis, configuration adjustment, and operational synchronization. The proposed methodology integrates epistemological reasoning, operational interpretation, and field-based decision-making into a coherent framework for preserving operational continuity.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Thai Journal of National Interest Academic Journal under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License The journal allows access or distribution of academic work without charge or registration. To support the exchange of knowledge Scope covers academic work in geopolitics. Geoeconomics and Innovation
Users can share, copy and distribute all information published in National Interest Academic Journal in any form or medium subject to the following conditions:
Citation — Permission to use, reproduce, distribute, or modify the work. But credit must be given to the owner of the work. If the work is used without credit, the name of the owner of the work will be Must obtain permission from the owner of the work first.
Noncommercial — The work may be used, reproduced, distributed, or modified. However, the work or article may not be used for commercial purposes.
Cannot be modified — The work may be used, reproduced, and distributed. But do not modify the work. unless permission is received from the owner of the work first
References
Bhaskar, R. (1975). A realist theory of science. Routledge.
Boin, A., & van Eeten, M. J. G. (2013). The resilient organization. Public Management Review, 15(3), 429–445. https://doi.org/10.1080/14719037.2013.769856
Checkland, P. (1999). Systems thinking, systems practice. In W. L. Currie & B. Galliers (Eds.), Rethinking management information systems (pp. 45–56). Oxford University Press.
Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1–14. https://doi.org/10.1108/09574090410700275
Food and Agriculture Organization of the United Nations. (2025). The state of food and agriculture 2025: Addressing land degradation across landholding scales. FAO. https://doi.org/10.4060/cd7067en
Folke, C. (2006). Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change, 16(3), 253–267. https://doi.org/10.1016/j.gloenvcha.2006.04.002
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4, 1–23. https://doi.org/10.1146/annurev.es.04.110173.000245
Intergovernmental Panel on Climate Change. (2023). Climate change 2023: Synthesis report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Core Writing Team, H. Lee, & J. Romero, Eds.). IPCC. https://doi.org/10.59327/IPCC/AR6-9789291691647
International Organization for Standardization. (2019). ISO 22301:2019 Security and resilience—Business continuity management systems—Requirements. https://www.iso.org/standard/75106.html
Klein, G. A. (1998). Sources of power: How people make decisions. MIT Press.
Kuhn, T. S. (2012). The structure of scientific revolutions (4th ed.). University of Chicago Press. (Original work published 1962)
Malone, T. W., & Crowston, K. (1994). The interdisciplinary study of coordination. ACM Computing Surveys, 26(1), 87–119. https://doi.org/10.1145/174666.174668
Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124–143. https://doi.org/10.1108/09574090910954873
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
Sheffi, Y., & Rice, J. B., Jr. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 46(4), 41–48.
Simon, H. A. (1996). The sciences of the artificial (3rd ed.). MIT Press.
United Nations Office for Disaster Risk Reduction. (2015). Global assessment report on disaster risk reduction 2015. https://www.undrr.org/publication/global-assessment-report-disaster-risk-reduction-2015
United Nations Office for Disaster Risk Reduction. (2023). Annual report 2023: Accelerating resilience for all. https://www.undrr.org/annual-report/2023
Walker, B., Holling, C. S., Carpenter, S. R., & Kinzig, A. (2004). Resilience, adaptability and transformability in social–ecological systems. Ecology and Society, 9(2), Article 5. http://www.ecologyandsociety.org/vol9/iss2/art5/