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We present a model of traffic flow on generic urban road networks based on cellular automata. We apply this model to an existing road network in the Australian city of Melbourne, using empirical data as input. For comparison, we also apply this model to a square-grid network using hypothetical input data. On both networks we compare the effects of non-adaptive vs adaptive traffic lights, in which instantaneous traffic state information feeds back into the traffic signal schedule. We observe that not only do adaptive traffic lights result in better averages of network observables, they also lead to significantly smaller fluctuations in these observables. We furthermore compare two different systems of adaptive traffic signals, one which is informed by the traffic state on both upstream and downstream links, and one which is informed by upstream links only. We find that, in general, both the mean and the fluctuation of the travel time are smallest when using the joint upstream-downstream control strategy.Traffic flow on realistic road networks with adaptive traffic lights Recently, certain types of adaptive or "self-organizing" traffic lights (SOTL) have been receiving attention in the statistical physics literature [17,27,26,28,29]. Selforganizing traffic lights have been investigated in the simple context of a Manhattanlike network in [26]. In such a network each intersection has only two possible signal phases ‡; either eastbound traffic has a green light and northbound traffic has a red light, or vice versa. We have generalized the ideas presented in [26] to handle intersections with multiple signal phases. This generalization from two to multiple phases allows a much richer variety of behavior. With only two signal phases, the only question one can consider is "how long should the active phase run before switching to the other phase." With more than two phases however, the more interesting question of "which phase should we switch to next" also arises.A further significant generalization that we introduce is that we not only consider the state of the upstream links which feed into a given intersection, but also the downstream links which are fed by the intersection. The idea being that not only is it important to give green time to a movement that will allow a congested upstream link to dissipate, but also that it is counterproductive to give green time to a movement that will further congest an already over-saturated downstream link. We find that for the Kew network, with boundary conditions corresponding to morning peak hour, the upstream-downstream adaptive traffic lights are approximately 5% more efficient ‡ Clearly this usage of the word "phase" is unrelated to the usual meaning in statistical mechanics. Its widespread use in the traffic engineering literature hopefully sanctions our use of it here.Traffic flow on realistic road networks with adaptive traffic lights 4 4 5

We present closed-form expressions for approximately N integrals of 2Ndimensional maps. The maps are obtained by travelling wave reductions of the modified Korteweg-de Vries equation and of the sine-Gordon equation, respectively. We provide the integrating factors corresponding to the integrals. Moreover we show how the integrals and the integrating factors relate to the staircase method.

PurposeSmall- and medium-sized enterprises (SMEs) mainly rely on their structure and internal networks to achieve their goals and remain competitive. However, their limited internal capabilities and complex environments can hinder their stability. Thus, this study evaluated the relationships among specific factors toward fostering organizational resilience (OR) in tourism SMEs.Design/methodology/approachA multi-methodological approach was adopted to address this research study, including (1) social network analysis (SNA) to formulate the conceptual model and (2) construct validation through partial least squares path modeling (PLS-PM).FindingsThe six proposed hypotheses were supported. These results suggest that addressing these variables and relationships after considering management style and people development as critical factors can foster OR in tourism SMEs.Research limitations/implicationsThe ideas that were developed were constrained to the organizational domain. Although the results apply to the Mexican context, this limitation can be offset by extending the proposal to other emergent regions or organizations. This can also increase the generalization of the results and foster improvements in the approaches applied.Practical implicationsAcademics and managers must rethink resilience as the final state generated by multiple factors. This requires reconfiguring inner organizational interactions, providing more autonomy to operative units, reinforcing business intelligence and improving feedback mechanisms.Originality/valueThis research study contrasts previous studies because it proposes that SNA be exploited to avail of the advantages it confers in designing the conceptual model. In this regard, we present new relationships to promote OR and provide new avenues in order to improve the analysis of adaptation processes.

This paper analyzes the direction of the causality between crude oil, gold and stock markets for the largest economy in the world with respect to such markets, the US. To do so, we apply non-linear Granger causality tests. We find a nonlinear causal relationship among the three markets considered, with the causality going in all directions, when the full sample and different subsamples are considered. However, we find a unidirectional nonlinear causal relationship between the crude oil and gold market (with the causality only going from oil price changes to gold price changes) when the subsample runs from the first date of any year between the mid-1990s and 2001 to last available data (February 5, 2015). The latter result may explain the lack of consensus existing in the literature about the direction of the causal link between the crude oil and gold markets.

The goal of this study was to examine the interlinkage of renewable energy, technology innovation, human capital, and governance on environment quality by using a panel quantile regression in Asian emerging economies over the period of 1990–2019. The results indicated that higher economic growth, population density, technological innovation in renewable energy, and exploitation of natural resources have significantly raised CO2 emissions in emerging Asia. Furthermore, larger capital, more use of renewable energy, green technology, and human capital development can improve environmental sustainability in Asia. As for governances, proxied by corruption rates, no evidence indicated that it has resulted in more damage, unlike earlier studies have suggested. The findings indicated that the three channels exposed in the Kuznets hypothesis can serve as a reference for proposals for environmental policies (scale of consumption, energy composition, and choice of technologies). There are opportunities to reduce CO2 emissions through investments in human development, investing in new technologies to increase efficiency in energy (generation and consumption), increasing working capital (GCF), and migrating to more environmentally friendly energy. The negative link between carbon dioxide emissions and economic growth, increases in population density, and exploitation of natural resources can compromise the achievement of sustainable environmental goals.

In this paper we study a possible synchronization in volatility changes for some Latin America's stock exchange indexes. We also add the S&P 500 index to the analysis. We suggest a heterogeneity Markov switching model to capture changes in volatilities over time.To solve the problem of uncertainty in modeling each index, we suggest the Bayes Factor to identify the best Markov switching specification as the number of states, if any. We found that, all the daily growth rates for each index are well characterized by low, medium and high volatilities in different periods of time. We suggest some measures of synchronization based on the concordance by the changes in volatilities between the indexes. We show that, the Mexican, Chilean and the S&P 500 indexes are closer to each other than the rest

This article explores and validates the integrated use of the viable system model (VSM) and the partial least squares path modeling (PLS-PM) approach to assess the sustainable management of RAMSAR sites carrying out economic activities. This work adopts a systems-thinking approach integrating systemic methodologies in three phases: (1) the VSM was first used to develop a conceptual model of the organisational problem; (2) PLS-PM was used to propose a construct to outline a solution, as well as to statistically validate the relationships proposed in the conceptual model; finally, (3) through the VSM, the relationships between actors were rethought in order to promote sustainable performance. The results obtained suggest that the joint use of VSM and PLS-PM is an effective approach that aids in the identification of relational and structural pathologies affecting the observed RAMSAR systems. It also proved useful to suggest that relationships can lead to the sustainable performance of the sites under study. It should be noted that the framework of systemic tools is constrained in its application to the organisational domain: assessing two RAMSAR areas in Mexico. Methodologically, this is the first application of the integrated use of VSM and PLS-PM to analyse the management and viability/sustainability of RAMSAR areas from an organisational perspective, opening a new avenue for the analysis and optimisation of management of such areas. This study provides tools to support actors and academics related to RAMSAR sites and opens up a discussion on how to rethink the organisational interactions in order to improve RAMSAR sites’ adaptive capabilities.