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Maintenance processes are vital for safe and continuous availability of rail assets and services. These processes are increasingly embracing the \u2018Intelligent Infrastructure\u2019 paradigm, which uses automated analysis to predict asset state and potential failure. Understanding the cognitive processes of maintenance operators is critical to underpin design and acceptance of Intelligent Infrastructure. A combination of methods, including observation, interview and an adaptation of critical decision method, was employed to elicit the decision-making strategies of operators in three different types of maintenance control centre, with three configurations of pre-existing technology. The output is a model of decision-making, based on Rasmussen\u2019s decision ladder, that reflects the varying role of automation depending on technology configurations. The analysis also identifies which types of fault were most challenging for operators and identifies the strategies used by operators to manage the concurrent challenges of information deficiencies (both underload and overload). Implications for design are discussed.<\/jats:p>","DOI":"10.1007\/s10111-020-00636-x","type":"journal-article","created":{"date-parts":[[2020,6,20]],"date-time":"2020-06-20T16:12:39Z","timestamp":1592669559000},"page":"255-271","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Modelling decision-making within rail maintenance control rooms"],"prefix":"10.1007","volume":"23","author":[{"given":"Nastaran","family":"Dadashi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Golightly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah","family":"Sharples","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,6,20]]},"reference":[{"issue":"5","key":"636_CR1","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1016\/j.ijinfomgt.2014.05.002","volume":"34","author":"MG Aboelmaged","year":"2014","unstructured":"Aboelmaged MG (2014) Predicting e-readiness at firm-level: an analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. 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