While information technology (IT) serves as a new source of sustainable competitive advantage for firms, it also induces hyperturbulent environments (or hyperturbulence) that erode that sustainable competitive advantage. In this paper, we posit that these contradictions might be due to cross-level nonlinear causality between firm-level IT-based strategic actions and collective-level IT-induced ...

This paper investigates the nature of the causal linkage between stock markets and foreign exchange markets in Australia, Canada, Japan, Switzerland, and UK from 1992:1 to 2005:12. Recently developed cointegration tests are employed and no evidence of a long-run relationship between the variables is found. Three variations of the Granger causality test are carried out and causality from exchang...

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential...

Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. We introduce a method, based on nonlinear state space reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not covered by the current Granger causality paradigm)....

Effective connectivity refers to the influence one neural system exerts on another and corresponds to the parameter of a model that tries to explain the observed dependencies. In this sense, effective connectivity corresponds to the intuitive notion of coupling or directed causal influence. Traditional measures to quantify the effective connectivity include model-based methods, such as dynamic ...

Quantifying causality between variables from observed time series data is of great importance in various disciplines but also a challenging task, especially when the observed data are short. Unlike the conventional methods, we find it possible to detect causality only with very short time series data, based on embedding theory of an attractor for nonlinear dynamics. Specifically, we first show ...

Theories on the relationship between money and inflation had largely been shaped around the positive relationship and money causality for inflation before the Post-Keynesians. Since the 1980s, this idea emerged that there might be no correlation between money growth and inflation. In the case of existence, the causality is reversed, so money is endogenous somehow. However, practically there is ...

The interaction between the private and public sectors is one of main focuses economics. They affect each other positively or negatively. This paper aims to determine potential dynamic impacts investments on in Turkey by running asymmetric causality detect a structural relationship two using nonlinear time-varying causality. result illustrates that there crowding-out effect from investment. On ...

Fast sweeping methods are a class of efficient iterative methods for solving steady state hyperbolic PDEs. They utilize the Gauss-Seidel iterations and alternating sweeping strategy to cover a family of characteristics of the hyperbolic PDEs in a certain direction simultaneously in each sweeping order. The first order fast sweeping method for solving Eikonal equations (Zhao in Math Comput 74:60...