Policy Effectiveness through Configurational and Mechanistic Lenses: Lessons for Concept Development

Pattyn, Valérie; Álamos‐Concha, Priscilla; Cambré, Bart; Rihoux, Benoît; Schalembier, Benjamin

doi:10.1080/13876988.2020.1773263

Cited by 9 publications

(11 citation statements)

References 43 publications

(46 reference statements)

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“…We thus conceive it as a passive contextual condition, rather than a causal one. In QCA this distinction is seldom made, with the exception of the two-step QCA variant in which one distinguishes remote and proximate conditions (but various approaches to the conceptualization of remote and proximate exist) (Schneider and Wagemann, 2006;Schneider 2019), and some recent contributions on QCA-PT multimethod designs (see Pattyn et al 2020).…”

Section: Omitted Contextual Conditionsmentioning

confidence: 99%

“…Earlier research had shown that plenty of employees fail to adequately transfer the skills that they had learned in the training to the work environment. Therefore, combining QCA with methods to probe mechanistic causation enabled us to uncover under which combination of conditions (QCA) a training programme would lead to successful training transfer, and how (PT) this happened or 'what worked' in the successful cases (see Pattyn et al 2020;Álamos-Concha et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing

Álamos‐Concha

Pattyn

Rihoux³

et al. 2021

Qual Quant

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What is the most appropriate QCA solution type when engaging in a multimethod design that includes QCA and in-depth process-tracing (PT)? While either the intermediate or the parsimonious solution are generally favored in QCA-only studies, we identify important challenges that can emerge when selecting those solutions in a QCA-PT multimethod study. We particularly highlight the risk of mechanistic heterogeneity, omitted conditions, and draw the attention on the issue of generalization. We discuss each of these intertwined challenges in depth, and explain why the conservative solution is useful to consider in addressing them. We substantiate our arguments by drawing on a recently completed evaluation study that was commissioned by the Flemish ESF Agency in Belgium. In the study, we combined QCA and theory-guided in-depth process-tracing to uncover under what combinations of conditions (QCA) a training programme would lead to successful training transfer and how (PT) this happened in the successful cases. The article highlights the need to carefully consider the selection of solution types in any multimethod design comprising QCA.

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Section: Omitted Contextual Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing

Álamos‐Concha

Pattyn

Rihoux³

et al. 2021

Qual Quant

Self Cite

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“…While the alignment mechanism is about the process of fitting together the social and the technical dimensions, the context is about the combination of crucial causal conditions that jointly and synergistically produce the outcome of interest (El Sawy et al, 2010). Put differently, the alignment mechanism explains the "how" of causation whereas the complex combination of causal conditions (i.e., the context) explains the "why" of causation (Pattyn et al, 2020;Wynn & Williams, 2020). Hence, the generative view points to a relationship between causal mechanisms and their effects which is not fixed but contingent, that is, dependent upon a specific combination of causal conditions (or context).…”

Section: Discussionmentioning

confidence: 99%

Investigating the determinants of inter-organizational information sharing within criminal justice: A context-mechanism-outcome approach

Iannacci

Simeonova

Kawalek

2021

Journal of Information Technology

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Focusing on inter-organizational information sharing in criminal justice, it is found that, while poor project management leads to unsuccessful inter-organizational information sharing, a recipe for success is more demanding as it requires both compatible technologies and good project management implemented either by means of a top-down approach of strategic alignment or an emergent approach of bottom-up alignment. Though unplanned, the latter approach may lead to mistakes that are more correctable than the large mistakes stemming from top-down, deliberate planning. The study is an analysis of context-mechanism-outcome configurations of inter-organizational information sharing activities within criminal justice systems and demonstrates the causal asymmetry between positive and negative cases. Theoretical, methodological, and practical implications are discussed by highlighting the causal role of different types of governance structure in a crisp-set configurational fashion.

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“…Few would argue that mechanistic causation can be directly uncovered with QCA, which applies analytical procedures to establish differences between types of cases. However, the presence of a causal mechanism can be found with process-tracing (PT) methods (Beach and Pedersen 2019;Pattyn et al 2020). Under a mechanistic theory of causation, QCA cannot be used to establish causal relations, but it can be used instrumentally to "find potential causes, select appropriate cases for within-case analysis, and enable cautious generalizations about processes to small, bounded sets of cases" (Beach and Kaas 2020, 9).…”

Section: Mechanistic Theoriesmentioning

confidence: 99%

Introduction: Causation, inferences, and solution types in configurational comparative methods

Haesebrouck

Thomann

2021

Qual Quant

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This special issue addresses questions of causality and validity of different solution types in configurational comparative methods (CCMs). First, what main parameters characterize the debate about correct causal interpretation of solution types? Second, to what extent has this debate been linked to a theory of causation? The special issue contribution by Mahoney and Acosta bases qualitative comparative analysis (QCA) within a regularity theory of causation integrating type-level inferences and counterfactual cases. Swiatczak clarifies how the different algorithms underlying QCA and Coincidence Analysis (CNA) produce non-identical models. Baumgartner defines and benchmarks QCA solution types against the search target of minimal robust sufficiency. Alamos-Concha et al. identify the conservative solution as most appropriate for a multimethod design combining a counterfactual causal understanding at the cross-case level with an in-depth mechanistic explanation at the within-case level. Finally, Mahoney and Owen develop a general set-theoretic framework for the study of necessity and sufficiency in quantitative research using a counterfactual understanding of causality. Our introduction reviews the state of the art, identifies current limitations and open questions regarding the theoretical basis for causal interpretation of QCA solutions.

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Policy Effectiveness through Configurational and Mechanistic Lenses: Lessons for Concept Development

Cited by 9 publications

References 43 publications

Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing

Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing

Investigating the determinants of inter-organizational information sharing within criminal justice: A context-mechanism-outcome approach

Introduction: Causation, inferences, and solution types in configurational comparative methods

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