The growth of technology-rich data-driven decision environments is seen by some as a challenge to the future relevance of Operational Research. Extant research remains unspecific about the distinct contribution that Operational Research can make in environments that are influenced by big data, data science and analytics. This paper explores the possibility that these environments hold the potential for a new integrative Operational Research offering, which we conceptualise as Smart Operational Research. In developing this proposal, we combine automated co-occurrence analysis of a corpus of literature with human-driven data interpretation to identify instantiations of hybrid decision-making. We then bring theory and practice together to outline the Smart Operational Research framework with the overall aim to enhance actionable insight and positive results for Operational Research practitioners.

We develop a new constitutive definition of Community OR as a self-initiating, self-organising community actor network emerging spontaneously in response to a triggering event and showing evidence of non-codified OR behaviours leading to action to improve the problem situation. From this new definition we have re-conceptualised Community OR as a construct that can be empirically observed emerging from suitable behavioural data. Social media play an instrumental role, acting as both the source of data and the enabling mechanism through which this form of Community OR occurs. Social media afford new possibilities for community empowerment and participation, with consequences for social enterprise and citizenship. We use Actor Network Theory, and specifically the language of translations, hybrid forums, and Callon’s Co-production of Knowledge Model (CKM), as the methodological basis for our definition and analysis. The appearance of hybrid forums as a self-organising response to community needs after an event would seem to be a natural milieu for a range of OR competencies. However, unlike traditional practitioner-led engagements, here the OR practitioner’s competency enters in a supportive rather than leading role. We support our argument through the analysis of social media data arising from the community response to a devastating flooding event – the Carlisle floods of December 2015.

© 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved. This article argues that OR interventions, particularly problem structuring methods (PSM), are complex events that cannot be understood by conventional methods alone. In this paper an alternative approach is introduced, where the units of analysis are the activity systems constituted by and constitutive of PSM interventions. The paper outlines the main theoretical and methodological concerns that need to be appreciated in studying PSM interventions. The paper then explores activity theory as an approach to study them. A case study describing the use of this approach is provided.

When we use a PSM what is it we are actually doing? an answer to this question would enable the PSM community to considerably enlarge the available source of case studies by the inclusion of examples of non-codified PSM use. We start from Checkland's own proposal for a "constitutive definition" of SSM, which originated from trying to answer the question of knowing when a claim of SSM use was legitimate. By extending this idea to a generic constitutive definition for all PSMs leads us to propose a self-consistent labelling schema for observed phenomena arising from PSMs in action. This consists of a set of testable propositions, which, through observation of putative PSM use, can be used to assess validity of claims of PSM use. Such evidential support for the propositions as may be found in putative PSM use can then make it back into a broader axiomatic formulation of PSMs through the use of a set-Theoretic approach, which enables our method to scale to large data sets. The theoretical underpinning to our work is in causal realism and middle range theory. We illustrate our approach through the analysis of three case studies drawn from engineering organisations, a rich source of possible non-codified PSM use. The combination of a method for judging cases of non-codified PSM use, sound theoretical underpinning, and scalability to large data sets, we believe leads to a demystification of PSMs and should encourage their wider use. © 2014 Elsevier B.V. All rights reserved.