Inter-port interactions in the Le Havre-Hamburg range: A scenario analysis using a nonautonomous Lotka Volterra model

Marasco, Addolorata; Romano, Alessandro

doi:10.1016/j.jtrangeo.2018.04.018

Cited by 23 publications

(20 citation statements)

References 36 publications

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“…Moreover, we assume the parameters in the Lotka-Volterra ecosystem model as constants, but the causal factors associated with the parameters may vary over time in reality, changing the parameters from constants to functions of time. To generalize our findings, future research should study other technology ecosystems in diverse industries and model the parameters as functions of time if necessary [19, 27]. Despite these limitations, the modeling results of the passenger aircraft ecosystem do provide important pointers to designers, entrepreneurs, and government officials when they make important decisions on technology development.…”

Section: Resultsmentioning

confidence: 95%

A case against the trickle-down effect in technology ecosystems

et al. 2019

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Technology evolution describes a change in a technology performance over time. The modeling of technology evolution is crucial for designers, entrepreneurs, and government officials to set reasonable R&D targets, invest in promising technology, and develop effective incentive policies. Scientists and engineers have developed several mathematical functions such as logistic function and exponential function (Moore’s Law) to model technology evolution. However, these models focus on how a technology evolves in isolation and do not consider how the technology interacts with other technologies. Here, we extend the Lotka-Volterra equations from community ecology to model a technology ecosystem with system, component, and fundamental layers. We model the technology ecosystem of passenger aircraft using the Lotka-Volterra equations. The results show limited trickle-down effect in the technology ecosystem, where we refer to the impact from an upper layer technology to a lower layer technology as a trickle-down effect. The limited trickle-down effect suggests that the advance of the system technology (passenger aircraft) is not able to automatically promote the performance of the component technology (turbofan aero-engine) and the fundamental technology (engine blade superalloy) that constitute the system. Our research warns that it may not be effective to maintain the prosperity of a technology ecosystem through government incentives on system technologies only. Decision makers should consider supporting the innovations of key component or fundamental technologies.

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Section: Resultsmentioning

confidence: 95%

A case against the trickle-down effect in technology ecosystems

et al. 2019

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“…For an accurate description of the model and the relative formal proof, we refer the reader to [ 15 ], [ 16 ], and [ 17 ]. The model was originally designed to analyse the interactions among competitive firms [ 18 ], but it was applied later to an array of contexts such as the study of interactions among renewable energy sources and oil prices [ 19 ], inter-port interactions [ 20 ] and tourism dynamics [ 16 ]. Indeed, the model aims to examine how entities interact to allocate a scarce resource in an established niche.…”

Section: Methodsmentioning

confidence: 99%

Unpredictable spillovers among water uses? An analysis of agricultural, industrial, and household uses of water in the Balkans

Focacci

Quintavalla

2020

PLoS ONE

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In times of water shortage, it becomes increasingly relevant for policymakers to understand the existing relationships between different types of water use, so as to encourage efficient water management. This article makes use of yearly data on agricultural, industrial, and household water use in the Balkan countries of Bulgaria, Romania, and Serbia. It does so to identify the potential interactions among these three categories of water use. Using a deterministic model based on differential equations, we provide an analysis of the interactions among these different sectors of water use for the period between 2008 and 2017. Results show that interactions among these different categories do not remain constant over periods of time, either across or within the countries analysed. We find that, for most countries, industrial and household water uses are more likely to be characterised by mutualism and competition, instead of a predator-prey relationship. Agricultural water use, on the other hand, takes on the role of predator against the other two.

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“…These peaks roughly correspond to the two structural breaks that we identify (see Section 3). To analyze these data, we apply the integrable nonautonomous Lotka-Volterra model developed in Marasco et al [16] and Marasco and Romano [17]. For an accurate description of the model and the relative formal proof, we refer the reader to Marasco et al [16].…”

Section: Methodsmentioning

confidence: 99%

“…For these reasons, we try to shed new light on this debate by adopting a novel methodology that allows us to capture changes in the way in which energy sources interact. In particular, we use the integrable nonautonomous Lotka-Volterra (LV) model developed in Marasco et al [16] and Marasco and Romano [17] to study the interaction among energy sources (for a list of the possible kinds of interactions, see Table 1). The advantage of this method is twofold.…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Study of the Interactions between Oil Price and Renewable Energy Sources Stock Prices

2019

Self Cite

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In this article, we apply an integrable nonautonomous Lotka–Volterra model to study the relationship between oil and renewable energy stock prices between 2006 and 2016. The advantage of this innovative approach is that it allows us to study the simultaneous interaction among n stock indices at any point in time. In line with previous studies, we find that the relationship between oil and renewables is characterized by major structural breaks taking place in 2008 and around 2013. The first structural break might be caused by the financial crisis, whereas more studies are required to advance a hypothesis on the causes behind the second structural break. Our main finding is that oil is always in a predator–prey relationship with wind, whereas it proceeds in mutualism with solar after 2012. Moreover, we find that solar and wind proceed in mutualism between 2008 and 2013 but have a rivalrous interaction before (competition) and after (predator–prey) that period. We explore the possible reasons behind these patterns and their policy implications.

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Inter-port interactions in the Le Havre-Hamburg range: A scenario analysis using a nonautonomous Lotka Volterra model

Cited by 23 publications

References 36 publications

A case against the trickle-down effect in technology ecosystems

A case against the trickle-down effect in technology ecosystems

Unpredictable spillovers among water uses? An analysis of agricultural, industrial, and household uses of water in the Balkans

A Quantitative Study of the Interactions between Oil Price and Renewable Energy Sources Stock Prices

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