While cities have become gradually more vertical and complex over the past century, our methods for conceptualising their characteristics and measuring their forms and functions are still largely based in a horizontal mindset. Recent work has sought to shift urban discourse towards understanding cities according to their volumetric properties. Moving the debate further, this paper approaches volumetric urbanism from a morphological perspective, setting out a research agenda that operationalises the concept as a means of better capturing the morphological characteristics of cities as volumetric entities. First, we deconstruct volumetric urbanism into the five basic building blocks that define volumetric morphologies: density, functional mix, compaction and compression, complex networks and interaction intensity. Next, we propose two methods for capturing the urban volumetrics of cities based on spatial and network interaction and apply them to a hypothetical case and a preliminary study of Hong Kong. We conclude by arguing that a volumetric approach is required to capture the complex form of compressed, multi-layered and highly connected cities. In response, urban morphological and planning discourses must move away from the horizontal analytical mindset, embrace a multi-layered three-dimensional view of cities and place greater emphasis on spatial configurations and network relations by measuring interaction.

Planning for dynamic cities is a perennial problem that continues to grow in importance in a rapidly changing world. This paper presents a conceptual framework to understand urban change through a complex adaptive systems approach. This framework includes a process of (1) describing the system through setting boundaries and identifying the properties of the system, (2) identifying the patterns of change across scales and (3) mapping the change over time. The framework firstly, offers a tool to urban planners to approach some of the complexities of urban change and secondly, a foundation to engage with the challenge of developing alternative sustainable development models that are able to deal with the reality of complex, dynamic and interconnected urban systems and to cope with change and uncertainty in ways that build positive resilience and support regenerative design and development.

The deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.

Complexity science offers valuable conceptual and analytical tools for addressing multifaceted socio-technical challenges in policymaking, promoting a holistic, dynamic, and adaptive framework that moves beyond traditional linear approaches. Despite its potential, complexity science has struggled to gain traction in the mainstream policy debates. This article examines the non-technical-human and organisational-barriers impeding the adoption of complexity science in policymaking and proposes strategies to overcome these obstacles. The barriers fall into three categories: management, institutional, and political challenges; communication and trust issues; and ethical considerations. The article synthesises insights from 37 interviews with complexity and policy experts to understand challenges and identify effective strategies. The findings reveal that entrenched governance structures, short-term political incentives, and limited awareness of complexity concepts among policymakers hinder the adoption of complexity-informed approaches. Additionally, a preference for simpler, more immediate solutions further obstructs the integration of complexity science into policymaking. Ethical considerations, such as data privacy and potential biases within models, also present significant challenges. Several strategies are identified to overcome these barriers, including fostering interdisciplinary collaboration, enhancing transparency in model development, and establishing experimental policy labs. The findings highlight the need for targeted training programs to equip policymakers with the skills to navigate complex systems and emphasise the importance of establishing platforms for interdisciplinary dialogue. These strategies aim to build capacity, improve understanding, foster trust, and encourage more adaptive and holistic policymaking approaches, ultimately facilitating the integration of complexity science into mainstream policymaking.