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Structural Causal Models in Strategy: Opportunities and Boundaries
Academy of Management Proceedings, 2023Causality is at the center of all scientific endeavors. From prior research, we know that just like scientists, business leaders, too, make causal assumptions about their environment to guide strategic choices. Causal machine learning has consequently been subject to growing attention in strategic management research and practice.
Schmitt, Carla +2 more
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Structural Modelling, Exogeneity, and Causality
2009This paper deals with causal analysis in the social sciences. We first present a conceptual framework according to which causal analysis is based on a rationale of variation and invariance, and not only on regularity. We then develop a formal framework for causal analysis by means of structural modelling.
Mouchart M, RUSSO, Federica, Wunsch G.
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Causal Structure and Hierarchies of Models
SSRN Electronic Journal, 2011Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson's paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes.
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Causal possibility model structures
The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03., 2004Causality occupies a position of centrality in human reasoning. It plays an essential role in commonsense human decision-making. Determining causes has been a tantalizing goal throughout human history. Proper sacrifices to the gods were thought to bring rewards; failure to make the proper observations to led to disaster.
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Modelling Cyclic Causal Structures
Abstract: Many causal systems studied by sciences such as biology, pharmacology, and economics feature causal cycles. Most accounts of causal modelling currently on the market are, however, explicitly designed for acyclic structures. This chapter focuses on causal cy cles and the challenges such cycles pose for causal modelling.Leuridan, Bert, Gebharter, Alexander
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The causal structure of economic models
Futures, 1977Abstract Large quantitative models of the economy are increasingly being used to prepare short-term and long-term projections. In most cases inspection of each single equation is not sufficient to understand the functioning of a complete model, a situation which sometimes leads to so-called “counter-intuitive” results of model simulations.
Emilio Fontela, Manfred Gilli
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A Causal Model of Hospital Structure
Group & Organization Studies, 1985This article investigates whether hospital organizations evidence similar structural characteristics as do more traditional bureaucratic organizations. A causal model of organizational structure was ap plied to a sample of hospitals. Estimates of the causal model were used to access the similarity between structural arrangements within hos pitals and ...
Hoda Mahmoudi, George A. Miller
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Modeling Document-level Causal Structures for Event Causal Relation Identification
Proceedings of the 2019 Conference of the North, 2019We aim to comprehensively identify all the event causal relations in a document, both within a sentence and across sentences, which is important for reconstructing pivotal event structures. The challenges we identified are two: 1) event causal relations are sparse among all possible event pairs in a document, in addition, 2) few causal relations are ...
Lei Gao +2 more
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Modeling Document Causal Structure with a Hypergraph for Event Causality Identification
Neural NetworksDocument-level event causality identification (ECI) aims to detect causal relations in between event mentions in a document. Some recent approaches model diverse connections in between events, such as syntactic dependency and etc., with a graph neural network for event node representation learning.
Wei Xiang, Cheng Liu, Bang Wang
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