In a broader sense, co-creation means the joint effort of bringing something new to fruition through acts of collective creativity (Sanders & Stappers, 2008) which can be manifested in both tangible (making something together) or intangible (learning something together) outcomes (Puerari et al., 2018). Recently, the concepts of co-creation or co- production have been applied to describe the processes of participation in urban planning and design. Both terms place particular emphasis on the partnerships formed between citizens and the public sector, in which a high level of citizen involvement is pivotal. Participation has been defined through its different levels of citizen involvement, ranging from non-participation to greater degrees of citizen control (Arnstein, 1969) indicating the different levels of influence a participant can have on a participatory process. From the perspective of urban planning, citizen participation is beginning to be described as co-creation when citizens’ roles become more prominent, presenting aspects of self-organisation, increased commitment and a sense of ownership of the process (Puerari et al., 2018). Recent research is exploring new methods of urban planning in which citizens, the municipality and private organisations co-create new planning rules (Bisschops & Beunen, 2019). However, co-creation along with co-production and participation, often used interchangeably, have become popular catchphrases and are considered as processes which are of virtue in themselves. Furthermore, while there is substantial research on these processes, the research conducted on the outcomes of enhanced participation remains rather limited (Voorberg et al., 2015). This highlights the ambiguity in terms of interpretation; is co-creation a methodology, a set of tools to enhance and drive a process, or a goal in itself? (Puerari et al., 2018). There have often been cases where participation, co-creation and co-production have been used decoratively, as a form of justification and validation of decisions already made (Armeni, 2016). In the provision of public spaces, co-creation/co-production may specifically involve housing (Brandsen & Helderman, 2012; Chatterton, 2016) and placemaking: “placemaking in public space implies engaging in the practice of urban planning and design beyond an expert culture. Such collaboration can be described as co-creation.” (Eggertsen Teder, 2019, p.290). As in participation, co-creation requires the sharing of decision-making powers, the creation of  joint knowledge and the assignation of abilities between communities, while urban professionals and local authorities should draw attention to the active involvement of community members. Furthermore, co-creation does not take place in a vacuum, but always occurs within socio- spatial contexts. This points to the objective of co-creation as a tool to influence locally relevant policy through innovation that is “place-based”. To conclude, co-creation can be perceived as a process that is both transdisciplinary in its application, and as a tool for achieving transdisciplinarity on a broader scale through a systematic integration in existing standard practices in urban planning, housing design and architecture. Despite the persisting ambiguity in its definition, co-creation processes can provide more inclusive platforms for revisiting and informing formal and informal knowledge on sustainable and affordable housing.

The term Critical Utopian Action Research (CAR) was inspired by critical theory originating in the Scandinavian action research milieu (Nielsen & Nielsen, 2006; Gunnarson et al., 2016). CUAR advocates a critique of social structures, as these are often the barriers to human development (Coghlan & Brydon-Miller, 2014; Hansen et al., 2016). In this tradition, the role of the researcher is to raise awareness of societal problems. CUAR was inspired by (1) critical theory, (2) the work of Kurt Lewin, (3) socio- technical action research and (4) future research. (Coghlan & Brydon-Miller, 2014). CUAR researchers function as facilitators of free spaces (Bladt & Nielsen, 2013), that is to say, they create forums and arenas to foster deliberations, dialogues and joint activities. These spaces serve as laboratories where social learning and imagination are developed in order to enable “new forms of social learning between citizens and scientists" (Egmose, 2015, p.1). The CUAR framework was developed by Kurt Aagaard Nielsen and Birger Steen Nielsen (Nielsen & Nielsen, 2006). The tradition of CUAR emerged for the practical application of critical knowledge through analysing modernity in the social sciences, and in cultural and philosophical studies. This theoretical, methodological, and practical framework was inspired by some relevant critical theorists, such as Theodor W. Adorno and Max Horkheimer.  They formed a view that science cannot be considered valid unless it is the result of democratic processes. On that same note,  an undemocratic investigation of the world can only lead to an undemocratic reality (Coghlan & Brydon-Miller, 2014). In addition, purely positivist approaches, devoid of critical reflection, neglect fundamental democratic values (McIntosh, 2010). According to CUAR advocates, society cannot be governed in a technocratic way with a purely authoritarian development logic (Coghlan & Brydon-Miller, 2014). CUAR encourages the creation of democratic knowledge with a high level of reflexivity (Elling, 2008). A basic argument used by Lewin was that researchers do not only work for scientific reasons -in the circuit of academically mediated reflexivity, away from other members of society -, but they also work for and together with research participants (McIntosh, 2010; Coghlan & Brydon-Miller, 2014). Lewin’s methodology is relevant for housing studies, as it is institutionalized in the socio-technical tradition of action research and where participants co-operate with researchers in real life  projects. Another important inspiration for the CUAR tradition is future research, a notion introduced by the German philosopher Robert Jungk, who applied tools and created forums for democratic change  for a better future (Jungk & Müllert, 1987; Reason & Bradbury, 2008). According to Jungk, the future is determined by a small elite, while the majority of citizens remain powerless. Therefore, he wanted people not to close their eyes to the future, but to become co-creators of it (Coghlan & Brydon-Miller, 2014). The convergence of critical utopian thinking and everyday knowledge are the key ingredients of CUAR. This research framework provides a unique and useful orientation of imaginative processes towards sustainable social change. CUAR fosters transdisciplinary thinking across a wide range of existing knowledge. By creating new platforms (for example educational platforms, campaigns, or experimental pilot projects) it can give people the opportunity to act upon their values and knowledge.

Building Information Modelling (BIM) is the process of creating a set of digital representations which consists of both graphical and non-graphical data for the entire building cycle  (Eastman et al., 2011). This process involves documenting, gathering, organising, and updating this information throughout the whole life cycle of a building from conception to demolition (Eschenbruch & Bodden, 2018). Beyond the demolition stage BIM can also support circular principles; managing the re-use, recovery, and recycling-potential of a building (Akbarieh et al., 2020; Xue et al., 2021). Whilst the concept of BIM as a process is supported by the International Organisation for Standardisation in ISO 19650-1:2018 (ISO, 2018), the National BIM Standard describes BIM as a digital technology (NBIMS-US, 2015). Despite the origins of BIM dating back to the 1970s, it did not become widely adopted by the Architecture, Engineering and Construction (AEC) industry as a computer design tool until the 2000s (Costa, 2017). The digital building information model uses intelligent objects to store information in the form of three-dimensional geometric components along with its functional characteristics such as type, materials, technical properties, or costs (Eschenbruch & Bodden, 2018). This model forms the basis of a shared knowledge resource to support the various digital workflows of multidisciplinary stakeholders (Chong, Lee and Wang, 2017; Barile et al., 2018). Moreover, it serves the purpose of visualisation, clash detection between different building components, code criteria checking, environmental analysis, and cost estimation to name a few (Kamel & Memari, 2019; Krygiel & Nies, 2008). Therefore, utilising BIM can improve construction accuracy and enhance the built asset’s performance (Kubba, 2017; Love et al., 2013). The building information model facilitates the knowledge transfer between experts and project participants to satisfy end-user needs and support early-stage decision-making (Chong et al., 2017; Lu et al., 2017). Therefore, BIM can be considered a transdisciplinary practice as it communicates AEC, computation, and science (Correia et al., 2017). In the AEC industry implementing BIM involves several stages, which are known as BIM maturity models. The maturity here means the extent of the user’s ability to produce and exchange information. These stages are the milestones, or levels, of collaboration and sharing of information that teams, and organisations aspire to. Defining these milestones is the main purpose of the different BIM maturity models that exist nowadays (Succar et al., 2012). The European Commission (EC) encourages step-by-step maturity models starting from BIM level 0 up to 4, to move the industry from a traditional modelling approach towards an open BIM approach. According to the EC, to reach BIM level 4 “all project, operational documentation and history are linked to objects in the model” (European Commission, 2017). Due to growing concerns over the environmental, economic, and social impacts of the built environment, BIM is increasingly used to facilitate various sustainability analyses. In this regard, the concept of Green BIM initiated as the systematic digitalisation of building life cycles to accomplish established sustainability goals (Barile et al., 2018; Wong & Zhou, 2015). As such BIM has been integrated with Life Cycle Analysis (LCA), Life Cycle Costing Analysis (LCCA), and recently with Social Life Cycle Analysis (S-LCA) (Llatas et al., 2020). Today several BIM applications perform sustainability analysis in conjunction with Green Building Rating Systems (Sartori et al., 2021). In relation to housing BIM plays a crucial role in addressing affordability and sustainability issues from creation to maintenance, as well as the beyond end-of-life phases. However, many challenges remain for it to be fully and inclusively integrated within the AEC practice and for the full potential of BIM to be realised.

Sustainability of the built environment The emergence of the contemporary environmental movement between the 1960s and 1970s and its proposals to remedy the consequences of pollution can be seen as one of the first steps in addressing environmental problems (Scoones, 2007). However, the term “sustainable” only gained wider currency when it was introduced into political discourse by the Club of Rome with its 1972 report “The Limits to Growth”, in which the proposal to change growth trends to be sustainable in the far future was put forward (Grober, 2007; Kopnina & Shoreman-Ouimet, 2015a; Meadows et al., 1972). Since then, the use of the term has grown rapidly, especially after the publication of the 1978 report “Our Common Future”, which became a cornerstone of debates on sustainability and sustainable development (Brundtland et al., 1987; Kopnina & Shoreman-Ouimet, 2015a). Although the two terms are often used indistinctively, the former refers to managing resources without depleting them for future generations, while the latter aims to improve long-term economic well-being and quality of life without compromising the ability of future generations to meet their needs (Kopnina & Shoreman-Ouimet, 2015b; UNESCO, 2015). The Brundtland Report paved the way for the 1992 Earth Summit, which concluded that an effective balance must be found between consumption and conservation of natural resources (Scoones, 2007). In 2000, the United Nations General Assembly published the 8 Millennium Development Goals (UN, 2000), which led to the 17 Sustainable Development Goals (SDGs) published in 2016 (UN, 2016). The 17 SDGs call on all countries to mobilise their efforts to end all forms of poverty, tackle inequalities and combat climate change (UN, 2020; UNDP, 2018). Despite the rapidly growing literature on sustainability, the term remains ambiguous and lacks a clear conceptual foundation (Grober, 2007; Purvis et al., 2019). Murphy (2012) suggests that when defining sustainability, the question should be: Sustainability, of what? However, one of the most prominent interpretations of sustainability is the three pillars concept, which describes the interaction between the social, economic and environmental components of society (Purvis et al., 2019). The environmental pillar aims to improve human well-being by protecting natural capital -e.g. land, air and water- (Morelli, 2011). The economic sustainability pillar focuses on maintaining stable economic growth without damaging natural resources (Dunphy et al., 2000). Social sustainability, on the other hand, aims to preserve social capital and create a practical social framework that provides a comprehensive view of people's needs, communities and culture (Diesendorf, 2000). This latter pillar paved the way for the creation of a fourth pillar that includes human and culture as a focal point in sustainability objectives (RMIT, 2017). Jabareen (2006) describes environmental sustainability as a dynamic, inclusive and multidisciplinary concept that overlaps with other concepts such as resilience, durability and renewability. Morelli (2011) adds that it can be applied at different levels and includes tangible and intangible issues. Portney (2015) takes Morelli's explanation further and advocates that environmental sustainability should also promote industrial efficiency without compromising society's ability to develop (Morelli, 2011; Portney, 2015). Measuring the built environment sustainability level is a complex process that deploys quantitative methods, including (1) indexes (e.g. energy efficiency rate), (2) indicators (e.g. carbon emissions and carbon footprint), (3) benchmarks (e.g. water consumption per capita) and (4) audits (e.g. building management system efficiency) (Arjen, 2015; Berardi, 2012; James, 2014; Kubba, 2012). In recent years, several rating or certification systems and practical guides have been created and developed to measure sustainability, most notably the Building Research Establishment Environmental Assessment Method (BREEAM) introduced in the UK in 1990 (BRE, 2016) and the Leadership in Energy and Environmental Design (LEED) established in the US in 2000 (USGBC, 2018). In addition, other overlapping methodologies and certification frameworks have emerged, such as the European Performance of Buildings Directive (EPBD) in 2002 (EPB, 2003) and the European Framework for Sustainable Buildings, also known as Level(s) in 2020 (EU, 2020), amongst others. The sustainability of the built environment aims to reduce human consumption of natural resources and the production of waste while improving the health and comfort of inhabitants and thus the performance of the built environment elements such as buildings and spaces, and the infrastructure that supports human activities (Berardi, 2012; McLennan, 2004). This aim requires an effective theoretical and practical framework that encompasses at least six domains, including land, water, energy, indoor and outdoor environments, and economic and cultural preservation (Ferwati et al., 2019). More recently, other domains have been added, such as health and comfort, resource use, environmental performance, and cost-benefit and risk (EU, 2020). Sustainability of the built environment also requires comprehensive coordination between the architectural, structural, mechanical, electrical and environmental systems of buildings in the design, construction and operation phases to improve performance and avoid unnecessary resource consumption (Yates & Castro-Lacouture, 2018).

Mass customisation (MC) is a process by which a company approaches its production in a customer-centric manner, developing products and services according to the needs and requirements of each individual customer, while keeping costs near to mass production (Piller, 2004). MC establishes a new relationship between producers and customers which becomes crucial in product development  (Khalili-Araghi & Kolarevic, 2016). Alvin Toffler (1970, 1980) was the first to refer to the MC concept in his books “Future shock”  and “The third wave”. Stanley Davis (1987) later cemented the term in his book “Future Perfect”. But it was not until 1993, when Joseph Pine  developed its practical application to business, that the concept started gaining greater importance in research and practice (Pine, 1993; Brandão et al., 2017; Piller et al., 2005). Nowadays, MC is understood as a multidimensional process embracing a combination of mass production, user-driven technologies, big data, e-commerce and e-business, digital design, and manufacturing technologies (Brandão et al., 2017). In the last twenty years, almost every sector of the economy, from industrial production to consumer products and services, has been influenced by mass customisation. The difference between mass customisation and massive customisation is the ability to relate the contextual features to the product features. This means that a random generation of design alternatives would not be sufficient; these alternatives should be derived from the cultural, technological, environmental and social context, as well as from the individual context of the user (Kolarevic & Duarte, 2019). As a business paradigm,  MC provides an attractive added value by addressing customer needs while using resources efficiently and avoiding an increase in operational costs (Piller & Tseng, 2009). It seeks to incorporate customer co-design processes into the innovation and strategic planning of the business, approaching economies of integration (Piller et al., 2005). As a result, the profitability of MC is achieved through product variety in volume-related economies (Baranauskas et al., 2020; Duray et al., 2000). The space in which it is possible to meet a variety of needs through a mass customisation offering is finite (Piller, 2004). This solution space represents the variety of different customisation units and encompasses the rules to combine them, limiting the set of possibilities in the search of a balance between productivity and flexibility (Salvador et al., 2009). The designer’s responsibility would be to meet the heterogeneities of the users in an efficient way, by setting a solution space and defining the degrees of freedom for the customer within a manufacturer’s production system (Hippel, 2001). Therefore, an important challenge for a company that aims at becoming a mass customizer is to find the right balance between what is determined by the designer and what is left for the user to decide (Kolarevic & Duarte, 2019). Value creation within a stable solution space is one of the major differences between traditional customisation. While a traditional customizer produces unique products and processes, a mass customizer uses stable processes to provide a high range of variety among their products and services (Pine, 1993). This would enable a mass customizer to achieve “near mass production efficiency” but would also mean that the customisation alternatives are limited to certain product features (Pine, 1995). As opposed to the industrial output of mass production, in which the customer selects from options produced by the industry, MC facilitates cultural production, the personalisation of mass products in accordance with individual beliefs. This means that the customer contributes to defining the processes, components, and features that will be involved in the flow of the design and manufacturing process (Kieran & Timberlake, 2004). Products or services that are co-designed by the customer may provide social benefits, resulting in tailor-made, fitting, and resilient outcomes (Piller et al., 2005). Thanks to parametric design and digital fabrication it is now viable to mass-produce non-standard, custom-made products, from tableware and shoes to furniture and building components. These are often customizable through interactive websites (Kolarevic & Duarte, 2019). The incorporation of MC into the housebuilding industry, through supporting, guiding, and informing the user via interactive interfaces (Madrazo et al., 2010), can contribute to a democratisation of housing design, allowing for an empowering, social, and cultural enrichment of our built environment. Our current housing stock is largely homogeneous, while customer demands are increasingly heterogeneous. Implementing MC in the housing industry could address the diverse consumer needs in an affordable and effective way, by creating stable solution spaces that could make good quality housing accessible to more dwellers. Stability and responsiveness are key in the production of highly customised housing. Stability can be achieved through product modularity, defining and producing a set of components that can be combined in the maximum possible ways, attaining responsiveness to different requests while reducing the complexity of product variation. This creates customisation alternatives within the solution space which require a smooth flow of information and effective collaboration between customers, designers, and manufacturers (Khalili-Araghi & Kolarevic, 2018). ICT technologies can help to effectively materialise this multidimensional and interdisciplinary challenge in the Architecture, Engineering and Construction (AEC) industry, as showcased in the Sato PlusHome multifamily block in Finland[1]. Nowadays, there are companies that have integrated a systematic methodology to produce mass customised single-family homes using prefabrication methods, such as Modern Modular[2]. On the other hand, platforms such as BIM that act as collaborative environments for all stakeholders have demonstrated that building performance can be increased and precision improved while reducing construction time. These digital twins offer a basis for fabricated components and enable early cooperation between different disciplines. Parametric tools have the potential to help customisation comply with the manufacturing rules and regulations, and increase the ability to sustainably meet customer requirements, using fewer resources and shorter lead times (Piroozfar et al., 2019). In summary, a mass customisable housing industry could be achieved if the products and services are parametrically defined (i.e., specifying the dimensions, constraints, and relationships between the various components), interactively designed (via a website or an app), digitally fabricated, visualised and evaluated to automatically generate production and assembly data (Kolarevic, 2015). However, for MC to be integrated effectively in the AEC industry, several challenges remain that range from cultural, behavioural and management changes, to technological such as the use of ICTs or those directly applied to the manufacturing process, as for example automating the production and assembly methods, the use of product configurators or managing the variety through the product supply chain (Piroozfar et al., 2019).   [1] Sato PlusHome. ArkOpen / Esko Kahri, Petri Viita and Juhani Väisänen (http://www.open-building.org/conference2011/Project_PlusHome.pdf) [2] The Modern Modular. Resolution: 4 Architecture (https://www.re4a.com/the-modern-modular)

Life Cycle Costing (LCC) is a method used to estimate the overall cost of a building during its different life cycle stages, whether from cradle to grave or within a predetermined timeframe (Nucci et al., 2016; Wouterszoon Jansen et al., 2020). The Standardised Method of Life Cycle Costing (SMLCC) identifies LCC in line with the International Standard ISO 15686-5:2008 as "Methodology for the systematic economic evaluation of life cycle costs over a period of analysis, as defined in the agreed scope." (RICS, 2016). This evaluation can provide a useful breakdown of all costs associated with designing, constructing, operating, maintaining and disposing of this building (Dwaikat & Ali, 2018). Life cycle costs of an asset can be divided into two categories: (1) Initial costs, which are all the costs incurred before the occupation of the house, such as capital investment costs, purchase costs, and construction and installation costs (Goh & Sun, 2016; Kubba, 2010); (2) Future costs, which are those that occur after the occupancy phase of the dwelling. The future costs may involve operational costs, maintenance, occupancy and capital replacement (RICS, 2016). They may also include financing, resale, salvage, and end-of-life costs (Karatas & El-Rayes, 2014; Kubba, 2010; Rad et al., 2021). The costs to be included in a LCC analysis vary depending on its objective, scope and time period. Both the LCC objective and scope also determine whether the assessment will be conducted for the whole building, or for a certain building component or equipment (Liu & Qian, 2019; RICS, 2016). When LCC combines initial and future costs, it needs to consider the time value of money (Islam et al., 2015; Korpi & Ala-Risku, 2008). To do so, future costs need to be discounted to present value using what is known as "Discount Rate" (Islam et al., 2015; Korpi & Ala-Risku, 2008). LCC responds to the needs of the Architectural Engineering Construction (AEC) industry to recognise that value on the long term, as opposed to initial price, should be the focus of project financial assessments (Higham et al., 2015). LCC can be seen as a suitable management method to assess costs and available resources for housing projects, regardless of whether they are new or already exist. LCC looks beyond initial capital investment as it takes future operating and maintenance costs into account (Goh & Sun, 2016). Operating an asset over a 30-year lifespan could cost up to four times as much as the initial design and construction costs (Zanni et al., 2019). The costs associated with energy consumption often represent a large proportion of a building’s life cycle costs. For instance, the cumulative value of utility bills is almost half of the cost of a total building life cycle over a 50-year period in some countries (Ahmad & Thaheem, 2018; Inchauste et al., 2018). Prioritising initial cost reduction when selecting a design alternative, regardless of future costs, may not lead to an economically efficient building in the long run (Rad et al., 2021). LCC is a valuable appraising technique for an existing building to predict and assess "whether a project meets the client's performance requirements" (ISO, 2008). Similarly, during the design stages, LCC analysis can be applied to predict the long-term cost performance of a new building or a refurbishing project (Islam et al., 2015; RICS, 2016). Conducting LCC supports the decision-making in the design development stages has a number of benefits (Kubba, 2010). Decisions on building programme requirements, specifications, and systems can affect up to 80% of its environmental performance and operating costs (Bogenstätter, 2000; Goh & Sun, 2016). The absence of comprehensive information about the building's operational performance may result in uninformed decision-making that impacts its life cycle costs and future performance (Alsaadani & Bleil De Souza, 2018; Zanni et al., 2019). LCC can improve the selection of materials in order to reduce negative environmental impact and positively contribute to resourcing efficiency (Rad et al., 2021; Wouterszoon Jansen et al., 2020), in particular when combined with Life Cycle Assessment (LCA). LCA is concerned with the environmental aspects and impacts and the use of resources throughout a product's life cycle (ISO, 2006). Together, LCC and LCA contribute to adopt more comprehensive decisions to promote the sustainability of buildings (Kim, 2014). Therefore, both are part of the requirements of some green building certificates, such as LEED (Hajare & Elwakil, 2020).     LCC can be used to compare design, material, and/or equipment alternatives to find economically compelling solutions that respond to building performance goals, such as maximising human comfort and enhancing energy efficiency (Karatas & El-Rayes, 2014; Rad et al., 2021). Such solutions may have high initial costs but would decrease recurring future cost obligations by selecting the alternative that maximises net savings (Atmaca, 2016; Kubba, 2010; Zanni et al., 2019). LCC is particularly relevant for decisions on energy efficiency measures investments for both new buildings and building retrofitting. Such investments have been argued to be a dominant factor in lowering a building's life cycle cost (Fantozzi et al., 2019; Kazem et al., 2021). The financial effectiveness of such measures on decreasing energy-related operating costs, can be investigated using LCC analysis to compare air-condition systems, glazing options, etc. (Aktacir et al., 2006; Rad et al., 2021). Thus, LCC can be seen as a risk mitigation strategy for owners and occupants to overcome challenges associated with increasing energy prices (Kubba, 2010). The price of investing in energy-efficient measures increase over time. Therefore, LCC has the potential to significantly contribute to tackling housing affordability issues by not only making design decisions based on the building's initial costs but also its impact on future costs – for example energy bills - that will be paid by occupants (Cambier et al., 2021). The input data for a LCC analysis are useful for stakeholders involved in procurement and tendering processes as well as the long-term management of built assets (Korpi & Ala-Risku, 2008). Depending on the LCC scope, these data are extracted from information on installation, operating and maintenance costs and schedules as well as the life cycle performance and the quantity of materials, components and systems, (Goh & Sun, 2016) These information is then translated into cost data along with each element life expectancy in a typical life cycle cost plan (ISO, 2008). Such a process assists the procurement decisions whether for buildings, materials, or systems and/or hiring contractors and labour, in addition to supporting future decisions when needed (RICS, 2016). All this information can be organised using Building Information Modelling (BIM) technology (Kim, 2014; RICS, 2016). BIM is used to organise and structure building information in a digital model. In some countries, it has become mandatory that any procured project by a public sector be delivered in a BIM model to make informed decisions about that project (Government, 2012). Thus, conducting LCC aligns with the adoption purposes of BIM to facilitate the communication and  transfer of building information and data among various stakeholders (Juan & Hsing, 2017; Marzouk et al., 2018). However, conducting LCC is still challenging and not widely adopted in practice. The reliability and various formats of building related-data are some of the main barriers hindering the adoption of LCCs (Goh & Sun, 2016; Islam et al., 2015; Kehily & Underwood, 2017; Zanni et al., 2019).