A system dynamics approach to technology interaction: From asymptotic to cyclic behaviour

Abstract

This paper is an extension and elaboration of previous research on the simulation of three competing technologies that interact. A modified version of the three-technology system is investigated, and some initial system dynamics results are reported illustrating the progression from asymptotic to cyclic behaviour. Technology is considered in this research as a result of innovation, a rate-dependent process that may include several non-linearities due to interaction with the environment and social context. Using bibliometrics as a research data source is an interesting way to trace technology growth patterns very effectively. In this research, the existence of cyclic behaviour in two real life technologies is illustrated using bibliometrics. In this paper, a technology system consisting of three interacting technologies is treated and modelled in a coupled manner where the interacting dynamics is described by the Lotka-Volterra system of differential equations. The effect of interaction between the technologies and the period of cyclic behaviour is illustrated parametrically. Furthermore, the possible uncertain diffusion as well as interaction effect for two of the technologies is also addressed in this research using a Monte Carlo multivariate simulation technique and a system dynamics approach. The research method is exploratory and case based.

An Improved Lotka–Volterra Model Using Quantum Game Theory

“…Step 2: Calculate the final quantum strategy state ( ψ f ) U A andÛ B are local unitary operators for the local manipulation of player A and player B, respectively. A pure quantum strategyÛ(θ, α) is a special unitary group SU(2) operator, which can be described by Equation (5).…”

“…The Lotka-Volterra (L-V) model proposed by Vito Volterra in the early 20th century has long been used to characterize population dynamics of ecological competitors and in the past few decades has been widely introduced to simulate connections between two species [1][2][3]. In the latest century, the L-V model has been widely introduced into social science fields to explore the evolution of strategies when two participants decide between two choices, such as for technological substitution [4][5][6][7], diffusion and competition analysis of the TV and smart phone industries [8], interaction effects between two retailers' competing formats [9], feasibility of using low carbon energy to reduce fossil fuel consumption [10], forecasting the intensity of retailers' competition [11], maritime cluster development [7], armed confrontation [12], and competition in the knowledge diffusion market [13]. Currently, some researchers have shown that an L-V model equation for n-1 species is equivalent to a replicator equation in an evolutionary game for n strategies to create a linkage between the evolutionary game and a fundamental equation of theoretical ecology [14,15].…”

A system thinking approach for harmonizing smart and sustainable city initiatives with United Nations sustainable development goals

“…Systems thinking addressed in context with smart cities considers socioeconomic and environmental characteristics and their dependencies with several systems and subsystems in a model that helps in strategic city planning (Shmelev & Shmeleva, 2018). This paves ways to SUD in smart cities (Pretorius et al, 2014 Thus, we can see that "policy and governance," "research & development" and "partnership" act as enablers, integrators, and connectors in harmonizing and linking smart city initiatives not only with SDG 11 (Sustainable Cities and Communities) but also with other possible SDGs and smart city targets. Hence, these three connectors are termed as "catalyzers" that aid in the harmonization process of smart city initiatives and strategies with SDGs.…”

“…Systems thinking addressed in context with smart cities considers socioeconomic and environmental characteristics and their dependencies with several systems and subsystems in a model that helps in strategic city planning (Shmelev & Shmeleva, 2018). This paves ways to SUD in smart cities (Pretorius et al, 2014).…”

Eco-cities: An integrated system dynamics framework and a concise research taxonomy

“…The initial implementation of the SD approach upon urban development was introduced by Forrester in 1974. The elaboration of SD modeling allows the consideration, in the urban planning models, of the interdependencies among social, ecological, economic and other subsystems that further assist in the assessment of alternative policies for urban sustainability and predict possible divergences with regard to initial planning (Pretorius, Pretorius, & Benade, 2014). However, eco-cities have only been infrequently addressed in literature through the SD approach (Haghshenas et al, 2014;Han, Hayashi, Cao, & Imura, 2009), and more importantly the literature documents the lack of comprehensive SD models regarding ecocities.…”