According to the transitive dynamics model, people can construct causal structures by linking together configurations of force. The predictions of the model were tested in two experiments in which participants generated new causal relationships by chaining together two (Experiment 1) or three (Experiment 2) causal relations. The predictions of the transitive dynamics model were compared against...

This study highlights how social and commercial enterprises with local global presence, balance their economic goals, to sustainably serve the bottom-of-the-pyramid (BoP) markets, predominantly in emerging economies. Employing lens of transaction cost economics configurational theory, we propose that successful venturing into BoP sensitize firms create appropriate governance mechanisms for redu...

We ask whether strictly causal components form well defined systems when arranged in feedback configurations. The standard interpretation for such configurations induces a fixed-point constraint on the function modelling the component involved. We define strictly causal functions formally, and show that the corresponding fixed-point problem does not always have a well defined solution. We exami...

We ask whether strictly causal components form well defined systems when arranged in feedback configurations. The standard interpretation for such configurations induces a fixed-point constraint on the function modelling the component involved. We define strictly causal functions formally, and show that the corresponding fixed-point problem does not always have a well defined solution. We exami...

The relationship between statistical dependency and causality lies at the heart of all statistical approaches to causal inference. Recent results in the ChaLearn cause-effect pair challenge have shown that causal directionality can be inferred with good accuracy also in Markov indistinguishable configurations thanks to data driven approaches. This paper proposes a supervised machine learning ap...

We investigate the applicability of artificial neural networks (ANNs) in reconstructing a sample image sponge-like microstructure. propose to reconstruct by predicting phase current pixel based on its causal neighbourhood, and subsequently, use non-causal ANN model smooth out reconstructed as form post-processing. also consider impacts different configurations (e.g., number densely connected la...

Empirical evidence has shown that several factors influence whether a compound is represented as several independent components or as a configuration. However, most of the previous research focused on data-driven factors (e.g., modality of the stimuli presented in the experimental task). in one experiment, i analyzed the influence of people’s knowledge about causal mechanisms on compound proces...

Software fault tree analysis (SFTA) is a widely used technique for safety analysis of a system as it helps identify the causal relationship between failures and hazards. Yet, SFTA is difficult to apply to dynamic systems with shifting run-time configurations (eg., autonomous multi-agent systems (MAS)). This paper illustrates the application and use of a product-line approach to SFTA applied to ...