Abstract
The crucial need to mitigate and abate the wicked urban sustainability issues compels the desire to leverage digital transformation towards the urban planning and governance that is premised on data or information, that is facilitated by integrated modelling techniques. Propelled by digital transformation, these modelling techniques inform the strategies for cities to further propel towards urban sustainability. These modelling techniques must be cognisant of the interdependencies existing regarding the consumption of key urban resources and services. Presently, a significant research limitation is that of identifying the critical urban systems and the associated urban system elements for consideration in the holistic modelling of cities as complex holistic systems, cognisant of the interdependencies pertaining to the consumption of key urban resources and services. Further to this research limitation is the need to identify and collate these urban systems and capture or represent their relative importance within the integrated modelling endeavours.
The distinct constitutive urban systems, the respective constitutive system elements, and the intra- and intersystem interactions influencing the modelling of cities as integrated complex systems are collated from peer-reviewed global literature qualitatively and analysed quantitatively via data analytics tools, accordingly. This therefore entails the complementary fusion of qualitative and quantitative approaches to collate the distinctive urban systems, urban system elements and interdependencies, and transition towards modelling. Adding to the complexity pertaining to cities modelling is knowledge that though a wide range of data on cities exists in the peer-reviewed citation index repositories, the capacity to utilise this data to inform quantitative modelling is yet to be proven, further reinforcing the identified research limitation.
To address the identified research gap(s) this research study adopted an ecosystems-based approach constituting a two-tier protocol, which leverages qualitative-to-quantitative methods to automatically gather the principal urban systems which operationalise the city as a complex urban ecosystem of systems, and thus impact city models development. This qualitative-to-quantitative protocol was adopted to identify and collate the constitutive urban systems of this urban ecosystem, systems mapping into respective system elements and interdependencies between system elements and facilitate the modular systems modelling of the urban systems, and integrated systems modelling of the holistic urban ecosystem. Henceforth, enabled by systematic literature reviews, data on thirteen (13) urban systems was collated qualitatively from peer-reviewed citation index databases namely ScienceDirect and Scopus, using the duration 2014 – 2024 as a search filtering criterion. Enabled by quantitative analysis methods such as bibliometric analysis, Word2Vec analysis and natural language processing (NLP), the mapping of the urban systems and the integrated urban ecosystem towards the respective system elements, the interactions between the system elements, and the strength of the interactions between the system elements was done. A system dynamics modelling (SDM)
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approach was then adopted to formulate systems constructs of the modular urban systems, and the integrated urban ecosystem of systems to display the system interactions among elements accordingly.
The research findings allude that water, education, food, city logistics, energy, urban buildings, transport, public amenities, infrastructure, communication, governance, healthcare, and waste are the key urban resources and services, driving city operations. Further, enabled by SDM, the urban systems were integrated into a holistic urban ecosystem of systems, with justification for the embedment of some urban system given. Using the main objective function (stock) of the holistic urban ecosystem, urban sustainability – integrated, which entails the quantitative weighted contributions of urban systems, insight on model optimisation was derived. The study, augmented by literature, established total water demand, total energy demand, city logistics operations, urban education services, urban healthcare services, food production, processing, supply and demand, and urban transport operations as the key drivers of urban sustainability.
In the same measure, the study also established greenhouse gas emissions (GHGEs), wastewater, solid waste and climate change as threats towards urban sustainability. Enabled by the sensitivity analysis, the study established the feasibility of optimising mitigatory policies such as emission control, climate change adaptation, water policy, waste management policy and associated wastewater, solid waste and GHGEs intensities, via ranges of values between 4% - 20%, towards improving overall urban ecosystem’s behaviour. A holistic policy approach towards mitigation was found to be the most effective to improve the overall ecosystem’s behaviour. The significance of the study is a data-driven holistic ecosystem modelling approach, leveraging a more instructive methodology of qualitative-to-quantitative modelling techniques, to derive insight towards urban sustainability. Academics, urban policymakers and the other urban sustainability stakeholders will find the study’s findings significant, towards the gaining of insight thereof.