Abstract

As a major contributor to overall carbon emissions and energy consumption, the housing sector has great potential to reduce energy consumption, whether by reducing the number of appliances, heating temperature or floor space. Consumption patterns encompass how people choose and consume products that satisfy their needs and wants. However, wants, and to some extent needs, are influenced by various factors and existing material and non-material (infra)structures, especially in the housing sector. Focusing on the floor area, this article aims to identify potentials towards lower consumption lifestyles by applying the Avoid-Shift-Improve framework in the residential sector. Through a conceptual review, the article explores what shapes current patterns of space use and outlines potential future pathways. Starting from the macro level, the article examines existing and emerging (societal) trends with (potential) impacts on housing consumption. It then looks at the structural development of households affected by the studied trends. At the micro level, the article provides an overview of the potential impact of individual behaviour on space use patterns within different categories of housing behaviour. The article identifies the potential for social and technical change in the housing sector and concludes that promoting non-materialistic narratives (avoid), offering alternative and innovative solutions to satisfy people’s spatial needs (shift) and designing flexible buildings (improve) appear to be effective ways for fostering behavioural change towards more efficient use of space.

Keywords: housing sector; energy consumption; lifestyle; consumption pattern; behavioural changes

Key messages

  • The study identifies potentials to reduce space use in the housing sector.

  • The Avoid-Shift-Improve framework was used as the analytical framework.

  • Identified trends can prevent downsizing by influencing household structure and consumption.

  • Non-materialist narrative, social and technical innovation can drive change towards space reduction.

Introduction

The housing sector is a major contributor to CO2 emissions. In 2020 all phases of construction, use and operation accounted for at least 37 per cent of global CO2 emissions, and heating and cooling, cooking, and the use of appliances are responsible for at least 28 per cent of these emissions (United Nations, Human Rights Council, 2022). The increase in the amount of living space per capita, which has been observed worldwide in recent decades, results in, on the one hand, the need for more building materials and, on the other hand, an increase in energy consumption during the use phase of the dwelling. Reducing the floor area therefore not only reduces the energy demand in the use phase of the building but also has the largest potential for reducing the emissions from materials in the building sector (Zhong et al, 2021). This type of demand reduction is therefore the most effective approach to reducing the carbon footprint of the housing sector.

A household is defined as a social unit consisting of a person living alone or a group of people living together in the same dwelling (Eurostat, 2017; Merriam-Webster, 2023). Household structure, which refers to household demography, living arrangements and household economics (Sociology, 2019), varies across cultures and countries and evolves over time, influenced by dynamic socioeconomic trends. Housing satisfies the need for shelter, one of the basic needs to which every individual is entitled (Doyal and Gough, 1984). However, in addition to satisfying this basic need, the form of housing and housing-related behaviours play a role in the self-expression and sense of belonging of individuals, making a house a symbol of self (Newmark and Thompson, 1977).

The link between consumption patterns and lifestyle has been discussed in several studies in recent decades (for example, Reusswig et al, 2003; Gram-Hanssen, 2012; Oliveira et al, 2020). Gram-Hanssen (2012) argues that an individual’s values and attitudes shape their lifestyle and can be observed through their different types of consumption in all areas, from food to housing to clothing. Similarly, Bosserman (1983) defines lifestyle as a pattern of consumption that reflects values, tastes and preferences. Many studies have addressed this link in different sectors such as energy, food, housing and transport (Reusswig et al, 2003; Hubacek et al, 2007; Gram-Hanssen, 2012; Saleem and Ali, 2019). Moreover, the ever-increasing environmental impacts of Western lifestyles and consumption patterns, especially in the housing sector, have already been addressed (Bjørn et al, 2018; Saleem and Ali, 2019).

The way we consume and how these patterns relate to our needs has also been addressed in the literature. Coelho et al (2020: 21) define consumption patterns as ‘[t]he process by which people search, purchase and consume products in a way to meet all their needs or desires’. Consumption patterns are directly defined by how and which needs and desires we want to satisfy, which in turn should be an indicator of a growing quality of life. While classical economic theories predict a linear correlation between our consumption growth and quality of life, recent empirical evidence suggests a weak link between the two, showing no or even a negative contribution of consumption to quality of life (Jackson, 2005; Vita et al, 2019). Moreover, at the macro level, after a certain threshold, the satisfaction of human needs increasingly depends on non-material factors (Sen, 1988; Vita et al, 2019), such as social ties and psychological well-being (Sirgy, 2002).

Considering the fluidity and changeability of lifestyles, theories recognise that people are not determined by static parameters at a personal or situational level but by dynamic and interactive ones (Walters, 2006). Studies show that housing needs and preferences are influenced by factors such as societal norms, working styles and income levels (see, for example, Højrup, 2003; Benedikter, 2012). Social structures, on the other hand, are shaped by individuals’ ‘habitus’, as they continuously find new solutions and solve problems based on their intuition and past social experiences (Bourdieu, 1987). Meadows (1999) refers to ‘leverage points’ as the places in a complex system where small interventions can lead to large changes. The author lists several ‘places to intervene’ in the systems to evoke transformative changes, for example, changes in parameters, information flow and the system’s goal. Tröger et al (2022) support this framework and argue that changes in situations, such as infrastructure and available options, as well as changes in people’s mindsets, can lead to fundamental changes in behavioural patterns.

Investigating the trade-offs of selected actions and their possible effects on energy consumption in residential buildings, Pérez-Sánchez et al (2022) emphasise the significance of incorporating both social (concerning the household) and technical (concerning the dwelling) changes to address environmental challenges in the building sector. This article builds upon their findings and delves deeper into identifying the potential for these social and technical changes in the EU housing sector, aiming to achieve reduced energy consumption. To accomplish this, the paper:

  • explores the potential and important routes of influences between different factors in the housing sector that affect the amount of space used in dwellings (Figure 1); and

  • applying the Avoid-Shift-Improve (ASI) framework, identifies the social and technical solutions that can potentially orient the impact of those factors towards such positive changes.

The figure consists of four boxes, which are interlinked. The box at the top, ‘Existing and emerging trends’, leads with arrows to all other boxes. There are two in the middle, ‘Household structure and household size’ and ‘Individual behaviour’. The left and right box in the middle also lead to the final box at the bottom, ‘Space use and floor area’.
Figure 1:

Potential routes of influence between different factors in the housing sector (only one-way relationships are considered)

Citation: Consumption and Society 4, 1; 10.1332/27528499Y2024D000000025

With its origins in the early 1990s in Germany, the ASI framework introduces an approach to structure the policy measures to reduce energy consumption and greenhouse gas emissions in line with the 1.5ºC Paris Agreement goal (Dalkmann and Brannigan, 2007). With a focus on the demand side, the framework consists of three pillars: ‘avoid’ refers to reducing the need for services (for example, the need for motorised travel); ‘shift’ addresses changing to more energy-efficient and environmentally friendly means (for example, modal shift from private cars to buses or trains); and ‘improve’ focuses on increasing the efficiency of the service provider (for example, fuel and vehicle efficiency). Initially the framework targeted the transport sector. However, it has been taken up in some other domains as well. For instance, Creutzig et al (2018) and IPCC (2022) use the ASI approach in the discussions for mitigating climate change and illustrate service-oriented solutions in sectors and services such as clothing, appliances, goods and nutrition. Even within the transport sector, the framework is used with different foci (for example, a conceptual framework for transport in response to COVID-19 in TUMI [2020]; and telecommunications in Corral Naveda [2022]).

In line with the ASI framework, the present work reflects on the impact of selected factors on space use and proposes recommendations for improving the social and technical infrastructure to achieve space use reductions as a contribution to reach the Paris climate targets and increase societal well-being. We apply a conceptual review of qualitative and quantitative literature at multiple levels to identify the affecting factors. Figure 2 illustrates the research design and highlights the steps of analysis. The methods and data sources used for the analysis are explained throughout the article in each section.

At the top of this figure is the row filled with the research question, ‘What drives the consumption of space in the residential sector, and how can it be redirected towards reduced space consumption?’. The row below the research question is filled with three different sub-topics, each leading to their own method. The left subtopic, ‘Existing and emerging trends with potential impact on housing consumption’, leads to ‘Rapid literature review secondary analysis of national and official statistics’. The middle subtopic, ‘Exploration of the effects on household structure, household size and space consumption’ leads to ‘Secondary analysis of national and official statistics’. Finally, the right subtopic, ‘Consumption patterns within different behavioural categories’, leads to ‘Meta analysis of quantitative data’. All the columns lead to the output: ‘Identification of the potentials for reducing the space consumption in the household sector’.
Figure 2:

Research design

Citation: Consumption and Society 4, 1; 10.1332/27528499Y2024D000000025

Existing and emerging trends

This chapter examines the selected trends that may have an impact on the use of space in the housing sector, either directly or indirectly through changes in household structure that in turn affect the space use. To select these trends, a rapid literature review was conducted using various combinations of the following keywords in search engines such as Google Scholar and Scopus: trends/factors, effects, residential space use, household structure/composition. The titles and abstracts of approximately 150 studies were scanned, of which 25 were considered potentially relevant. The main text of these studies was analysed with the aim of extracting factors that were considered to have an impact on space use or household structure. Nine studies discussing such factors and the list of trends and factors mentioned in these studies are presented in Table 1. The listed trends and factors were harmonised (for example, wage rates, economic well-being and income are all collapsed into income) and the recurring trends (that is, mentioned more than once) were examined. The resulting factors are ageing population, income, employment, marriage, divorce, births, digitalisation, urbanisation and sharing economy. Additionally, the historical development of these trends was studied through secondary analyses of official national and EU statistics from reputable sources such as the Statistical Office of the European Union (Eurostat) and the Federal Statistical Office of Germany (Destatis).

Table 1:

Selected literature on factors influencing space use or household structure
Source Mentioned factors/trends
Blau and van der Klaauw (2013) wage rates, tax and transfer incentives, legal environment, state of the marriage market
Mason (2023) economic well-being
Greenwood et al (2017) fertility,women, employment, marriage, divorce, assortative mating, children living with a single mother, shift in social norms
Wulff et al (2004) ageing population, birth rates, divorce and marriage rate
OECD (2021) teleworking, digitalisation, ageing population, climate change
OECD (2022) COVID-19 pandemic, digital sharing platforms, e-commerce effects, rapid population ageing, urbanisation
Williams (2009) ageing population, couple forming later in life, divorce rates, income, house prices and availability, employment opportunities, social provision for children and the elderly, the age at which young people move into their own homes
Xie et al (2020) urbanisation
Stewart (2006) birth rates, longevity, family disintegration, life expectancy, childhood mortality rate, income, ageing population, employment rate, homeownership
Pérez-Sánchez et al (2022) shareability and economies of scale, flexibility of time and level of services

Ageing population

Rising life expectancy and low birth rates mean that the proportion of older people in Europe’s total population is increasing. The median age in the EU-27 is projected to increase by 4.5 years between 2019 and 2050, reaching 48.2 by the end of this period (European Parliament, 2021). The proportion of the EU population aged 80 and over is projected to increase two and a half times between 2021 and 2100, from 6.0 per cent to 14.6 per cent. The over-65s will account for 31.3 per cent of the EU population by the end of the century. In 2021, their share was only 20.9 per cent, which was already 17 per cent more than a decade earlier (Eurostat, 2023i). In contrast, the population group aged 15 to 65 will shrink by about 10 percentage points over the same period (Eurostat, 2023h). An increase in the median age in Europe has also been observed in recent decades: from 38.4 years in 2001 to 43.7 years in 2019 (European Parliament, 2021).

Income

Economic conditions, including income trends, vary across European countries due to factors such as economic policies, global economic dynamics and regional circumstances. According to recent data from Eurostat (2023f), the EU countries with the highest median disposable incomes in 2022 were Luxembourg, the Netherlands, Austria, Belgium, Denmark and Germany. In contrast, Bulgaria, Slovakia, Romania, Hungary and Greece reported the lowest values. This indicates, that income varies considerably across Europe with the Nordic countries having higher per capita income than the Southeastern and the Baltic states. Furthermore, the Gini coefficient was 29.6 in 2022. In tendency, the Gini coefficient slightly declined over the last ten years across Europe (Eurostat, 2023f). However, many studies highlight a widening gap between rich and poor in many European countries and outline increasing inequality over recent decades (for example, Eurostat, 2010; Blanchet et al, 2019; Hung, 2021). This gap may be influenced by factors such as changes in labour markets, technological advancements, globalisation and policy decisions. Furthermore, growing income disparities in the EU have led to economic consequences, including migration from poorer to wealthier countries and shifts in industrial production, which has also fuelled discontent and support for populist movements, posing a threat to cohesion and democracy within the EU.

Employment

In 2020, 72.3 per cent of the EU population aged between 20 and 64 were employed, 10 per cent more than the rate in 2000. In the same period, with the exception of Greece and Denmark, in all EU countries the employment rate has increased. The absolute employment rates in 2020 separated for males and females of the same age group follow almost the same pattern in the member states with an average EU level of 78.0 per cent for men and 66.5 per cent for women. However, the relative rates compared to the year 2000 differ significantly for men and women. The rate of female employment has risen in all the EU countries except for Romania and the highest jump is observed in Malta where the female employment rate in 2020 is double that of 2000, followed by Bulgaria and Spain with an increase of around 35 per cent in the number of employed women. The change in the male employment rate in the same period ranges between -10.3 per cent in Greece and 29.2 per cent in Bulgaria. The EU average has risen by 3.7 per cent for the male population compared to the major increase of 19 per cent for the female population (Eurostat, 2023c).

Marriage, divorce, childbirth

While the crude marriage rate, that is, the number of marriages during the year per 1,000 persons, in the EU has fallen from 5.2 in 2000 to 3.9 in 2021 (Eurostat, 2023g), the crude divorce rate has fluctuated over the same period, peaking in 2006 and then falling slightly. In 2022, an average of 1.7 divorces per 1,000 persons were reported, showing almost one divorce for every two marriages. Between 2000 and 2017, the average age at first marriage increased in EU member states with available data for both men and women between around 2.1 and 5.5 years. The average age of women at the birth of their first child has also increased over the last two decades in all EU countries between 1.3 and 4.6 years, reaching an average of 29.5 years in 2021. In that year, women in more than a third of EU member states gave birth to their first child at an average age of 30 or more.

Digitalisation

One of the most influential trends of recent decades has been increasing digitalisation. The term refers to the widespread transformation of formerly analogue processes, assets, goods and services into digital ones, enabled by underlying innovations in information and communication technologies (ICT). Across different sectors of the economy and society, the increasing integration of digital technologies is shaping the way businesses and public administrations operate and the way individuals interact with each other and the world around them.

The trend shapes the way people carry out everyday tasks, gather information or communicate in a globalised world. Digital technologies have also helped to reduce transaction costs, increase process efficiency, productivity and competitiveness in various economic sectors and support the creation of entirely new digital goods and services of the so-called ‘digital economy’ (Kravchenko et al, 2019). Disruptive machine learning and artificial intelligence technologies support breaking new scientific ground and creating new industries and markets, ultimately affecting the organisation of societies around the world. As such the digitalisation trend is not only changing technology landscape but is also fundamentally driving socioeconomic transformation processes.

Sharing economy

In traditional markets, consumers buy products and acquire ownership (Dervojeda et al, 2013). However, the sharing of goods and services has become increasingly important in Europe in recent years (Hamari et al, 2016) and the demand for sharing models is expected to grow in the future. While the emergence of new technological capabilities is accelerating the growth of the sharing economy, the literature identifies key motivations for consumers to prefer the sharing economy. In contrast to ownership, which often involves a high financial burden for purchase and maintenance reasons, the sharing economy is financially profitable for consumers, who only have to pay for what they actually use. Owners of shared items have also the opportunity to generate income by sharing them. Motivation in terms of norms such as environmental sustainability is seen as an important predictor of participation in sharing economy business models (Hamari et al, 2016) as sharing economy models are generally expected to be highly sustainable (Prothero et al, 2011). The use of the sharing economy can involve a significant level of personal interaction and community experience, particularly when products are offered by individuals rather than ‘faceless’ companies. There is a growing demand for this type of consumption, leading businesses to shift from transaction-based (that is, primarily focusing on completing a transaction or exchanging goods or services) to experience-based services (that is, the focus is on creating a positive experience for and a sense of connection with customers) that rely on trust (PwC, 2015). Another important consumer trend influencing the development of the sharing economy is the change in what is seen as a status symbol. While property used to be a kind of status symbol, there is a trend away from this understanding, especially among young people (PwC, 2015). In contrast to owning property, users of access driven business models are far less tied down and enjoy the ability to switch products and services at any time.

Urbanisation

Urbanisation has been identified by the European Commission as one of the most influential megatrends for some time. At a global level, the population living in cities, defined as high-density places of at least 50,000 inhabitants, has more than doubled in the last 40 years, from 1.5 billion in 1975 to 3.5 billion in 2015. It is projected to reach 5 billion by 2055, almost 55 per cent of the world’s population. In Europe too, the trend towards urbanisation has intensified in recent decades, with more and more people moving to urban areas (European Commission, 2023). By 2021, more than 70 per cent of Europe’s population already lived in urban areas (World Bank, 2022), and Europe’s urbanisation rate is expected to increase to around 83.7 per cent by 2050 (United Nations, 2018). However, this process is uneven across the continent. While urbanisation rates are already high in Western and Northern Europe, there is still a significant level of rural–urban migration in Eastern Europe and certain rural areas (World Bank, 2022).

There are many reasons for urbanisation in Europe. One the one hand, cities offer a wider choice of jobs and career opportunities in different sectors, especially in services, technology and creative industries. Proximity to businesses, universities and research institutions fosters innovation and economic growth. In addition, urban areas offer a wide range of educational, health and cultural opportunities. High-quality schools and universities, medical facilities, museums, theatres, restaurants and shopping opportunities attract people who value the urban lifestyle and want to benefit from the diverse opportunities (European Commission, 2023).

Impact of trends on household structure and consumption

Household structure

Traditional family structures have changed in many European countries. There is an increase in non-marital partnerships, single-parent families, patchwork families and same-sex partnerships. These changes have implications for social support systems, childcare, housing and legal recognition of partnerships. The nuclear family, with the traditional concept of partners committing to live together and share their lives, remains the dominant family type across Europe but is losing ground in terms of numbers. With the higher number of non-marital cohabiting couples, the proportion of children born out of wedlock is also increasing (Kapella and Rille-Pfeiffer, 2010).

The trend towards starting a family later is noticeable throughout Europe. This is particularly evident in a higher age at first childbirth among women as well as in later first marriages. In 2022, 5.5 per cent of adult women aged 25–54 years in the EU were single parents with children, against 1.1 per cent of adult men (Eurostat, 2023e). In many European countries, the number of childless households is also increasing. The number of single-person households without children in the EU increased by 30.7 per cent from 2009 to 2022 (Eurostat, 2023e). This is the result of various factors such as demographic changes, occupational challenges, higher female participation in education, changing lifestyles and individual preferences.

The share of adults aged 18–24 who still live with their parents increased from 2007 to 2020 and started dropping afterwards. In 2021 an average of 80 per cent was reported in the EU-27. The similar trend is observed for the wider age range of 18–34, however in this age group the figures fluctuate more extremely among the countries, ranging from 16.0 to 76.5 per cent (Eurostat, 2023f). In most EU countries the figures have only changed slightly between 2007 and 2021. Among the few exceptions are Ireland and Portugal, where children stay between three and five years longer with their parents, and Lithuania and Estonia where they leave the parental home around three years earlier than before (Eurostat, 2023d).

Household size

The average size of households in the EU has been shrinking in recent decades, going from an average of 2.4 persons per household in 2007 to 2.2 in 2022 (Eurostat, 2023e). The share of the households occupied by only one or two residents has increased, reaching at least 60 per cent of all EU households in 2022. While the EU average share of single-person households was 26 per cent in 2007, the figure had already risen to 36.2 per cent by 2022, covering more than one-third of the EU households. In the same period the share of two-person households inhabited by childless couples increased by around 5 per cent, reaching almost a quarter of all EU households (Eurostat, 2023e).

The trend towards smaller households can be explained on the one hand by the decline in marriages and births and the spread of partnerships with separate living arrangements. On the other hand, the progressive demographic ageing and the improvement of the health condition of older people ensure that more and more senior citizens lead an independent household alone or in pairs. In addition to these sociodemographic factors, the high occupational mobility of workers has also promoted the trend towards smaller households (Destatis, 2023).

Floor area and room per capita

While the EU population increased by only about 1.6 per cent between 2009 and 2021, the number of households rose by 8 per cent in this period. The per capita floor area has also increased in recent decades, reaching 48.7m2 in 2021 compared to 41.4m2 in 2009 and 35m2 in 1990 (ODYSSEE-MURE, 2023) and the number of rooms per person has increased from 1.5 in 2009 to 1.6 in 2021. However, this increase in space is not evenly spread across age groups, household types and income groups. In 2021, the lowest overcrowding1 rate in the EU was observed among those aged 65 and over, at 7 per cent compared with an average of 17 per cent, while the younger generation lived mostly in overcrowded dwellings (for example, 28.4 per cent of 12–17-year-olds and 25.7 per cent of 20–29-year-olds) (Eurostat, 2023f). The same trend is observed for the number of rooms per person. On the other hand, almost half of the oldest age group have too many rooms in their dwelling, compared with only 25 per cent of the under-18s. Single and double households in which all or one member is aged over 65 occupy the largest number of rooms per person. A comparison of household composition shows that childless single or double adult households occupy the highest number of rooms per person. Any increase in the number of adults or children reduces the share of rooms per person. The overcrowding rate is also negatively related to the income level, with the lowest income households (quintiles 1 and 2) above the average.

Areas of lifestyles affecting the space use patterns

This chapter explores how certain behaviours and individual habits affect the space use in the housing sector. We built categories and argue how they have a direct effect on floor space (Figure 3). A meta-analysis is conducted to synthesise quantitative data on consumption patterns across these different behaviour categories. Search terms such as space requirements for remote working and frequency of home cooking among EU/German citizens were used to identify relevant studies. Data was obtained from studies, scientific papers, existing databases, and official national and EU statistical portals.

This figure is built like an evenly distributed pie chart consisting of four parts, with ‘Space use pattern’ in the centre. The four parts are ‘Hygiene behaviour’, ‘Leisure behaviour’, ‘Food behaviour’ and ‘Work behaviour’. Each of these parts also offer examples from these categories.
Figure 3:

Behaviour categories influencing residential space use pattern

Citation: Consumption and Society 4, 1; 10.1332/27528499Y2024D000000025

Food-related behaviour

The frequency and style of dining can impact the space dedicated to the dining area. If individuals or households prefer formal dining, a separate dining room may be desired, while those who have casual or informal eating habits may use multipurpose spaces for dining or opt for smaller dining rooms. Food behaviour plays also a significant role in the kitchen design and layout. If individuals frequently engage in cooking meals from scratch, they may prefer ample counter space for food preparation and have additional food processing appliances such as a blender. In contrast, if the individuals rely more on ready-made or take-out meals, a smaller kitchen with less emphasis on cooking space may be preferred, however they might have larger freezers and appliances such as a microwave that also need space and energy. According to the German BMEL (2023) nutrition report, 45 per cent of Germans cook daily, 36 per cent 2–3 times a week and only 18 per cent once a week or less. When it comes to eating out, 15 per cent say they go out frequently, 72 per cent rarely and 13 per cent never (ifd Allensbach, 2022).

The complexity of cooking and the number of people eating the meals can also influence the need for specific or larger appliances. People who cook regularly, or for more household members, may need larger kitchens with larger ovens, freezers and storage. Especially big appliances like big refrigerators, standalone freezers, ovens and dishwashers require additional space and larger kitchens. Kitchen size in the UK, for example, tends to be relative stable, having gone up from 12.27m2 for houses built in the 1930s to its peak of 15.37m2 for houses built in the 1960s and back to 12.61m2 for houses built in the 2010s (Thomas, 2019). Storing and preserving food uses space and energy, while cooling and refrigeration food is especially energy intensive (Eurostat, 2022a). Different types of diets or culinary interest may require specific storage areas for ingredients, spices and kitchen tools. The proximity of supermarkets or fresh food stores in urban areas can increase the number of shopping trips and reduce the need for food storage and refrigeration, resulting in less space usage and energy consumption for refrigeration.

Work behaviour

In 2022, around 75 per cent of the EU population aged between 20 and 64 was employed (Eurostat, 2023b), of which more than 10 per cent worked usually from home (Eurostat, 2023a). However, occurrence and intensity of working from home varies across countries. In a global survey conducted in 2021 and 2022, respondents from European countries worked weekly between 1.2 (Greece) to 1.8 days (Netherlands) in the home office. In Germany, the proportion of employees working at least partly in a home office fell from just under 30 per cent at the beginning of 2021 to around 25 per cent at the end of 2022 (ifo Konjunkturumfragen, 2022). Regarding the daily working time, more than one-third of Hungarians surveyed spent three to five hours a day working from home, 41 per cent spent six to eight hours and 13 per cent more than eight hours (statista, 2022).

Teleworking has become increasingly common in recent years, especially in the wake of the COVID-19 pandemic (Eurostat, 2022b), with individuals being sometimes forced to use different areas of their homes as offices. The change in the working pattern continued even after the pandemic with more employees willing to work from home and more employers offering this possibility. The arrangement of working space can vary depending on personal preferences, spatial feasibility, occurrence and intensity of working from home as well as the type of work. It can range from using the kitchen table as a desk in the times that it is not used as a dining table, to dedicating a separate room with all office equipment to the home office.

Therefore, the impact of typical home office configurations on housing space consumption can vary widely depending on the setup. A teleworker who moves to a larger house to accommodate their home office can have a significant impact on the household space consumption. In households with several teleworkers, efficient use of existing space (such as a kitchen table) can lead to more energy-efficient home office configurations. Teleworkers use 6.5m2 exclusively (or 4 per cent more than non-teleworkers) and 12.5m2 generally for home offices. Forty-five per cent of telecommuters have a dedicated office, while the rest use shared space in their home (O’Brien and Yazdani Aliabadi, 2020). However, the need for a working space at home is not limited to the employees with teleworking possibility, but also self-employed people and employees who actually cannot work remotely but need to do some preparation for their work (for example, teachers preparing teaching materials).

Leisure behaviour

According to the OECD Time Use Database (2016), the EU population aged between 15 and 64 spends from 241 minutes per day in Portugal to 368 minutes a day in Norway on leisure. Leisure time includes indoor and outdoor activities such as recreation and entertainment that take place during free time. The type and intensity of hobbies people pursue can have an impact on space requirements. Indoor leisure activities may require specific spaces within the home, for example, people who enjoy playing musical instruments may require a designated music room or area with adequate space for their instruments and equipment. Similarly, those who pursue hobbies such as painting or crafting may need a dedicated workspace or studio. However, some other hobbies may not require a dedicated space and allow for multifunctional rooms, such as turning the living room into a gaming area. Outdoor activities require less living space than indoor activities, however some may be less flexible than others. Individuals who enjoy gardening and outdoor games may allocate space for a garden or patio, while people who enjoy outdoor hobbies such as hiking, skiing and surfing may need less space in their home for these activities, and more for storing the necessary equipment.

Some leisure activities allow for some flexibility and leave room for individual preferences in how they are carried out. For example, people who like to exercise may use multipurpose rooms in their homes to do their exercises, create a dedicated fitness area or choose to go to a gym. Leisure behaviour often involves entertainment activities such as watching movies, playing video games or hosting gatherings. This can influence the allocation of space, with the living room or media room being designated as an entertainment hub, equipped with comfortable seating, audiovisual equipment and storage for media. According to Destatis (2013) people in Germany use media (for example, TV, radio, smartphone) for an average of three hours in their leisure time. The impact of the organisation of leisure time on the living space has been a topic of interest in recent studies. The question of whether a separate living room is necessary for leisure activities or socialising has been raised. In the UK, the average living room size is reported to be 17.09m2 (Thomas, 2019).

Hygiene behaviour

Hygiene behaviours include activities related to personal hygiene and household cleanliness, such as showering and laundry. How long and how often we shower or bathe, and how we wash and dry our clothes, can have an impact on space and energy use, particularly in the bathroom. For example, the average room size for newly built bathrooms in the UK is 5.55m2 (Thomas, 2019). The size and layout of residential bathrooms can be influenced by the choice of bathtubs or shower, as the bathtubs tend to be larger than showers. Currently, for example, 35 per cent of all Dutch households have a bathtub (Statista, 2023). The availability and use of bathroom space can vary according to the showering patterns of household members, that is, how often and for how long they shower. In Germany, for example, people shower for 6–10 minutes on average, with 53 per cent of people saying they shower 2–4 times a week or less, 14 per cent showering 5–6 times and 27 per cent showering daily (Yougov, 2021). When multiple household members have similar showering routines, it is probable that they prefer having more than one bathroom.

The frequency of laundry may also have an impact on space use, with the vast majority of respondents (82 per cent) in Austria doing laundry at least once a week and 10 per cent doing so daily (Statista, 2018). This can impact the amount of laundry-related clutter in a home, and the space required for laundry equipment and supplies. As the convenience of frequent laundry appears to be important, washing machines are common household appliances in many European countries, with more than 90 per cent of households in Romania, Austria, Poland, Portugal, Italy, Spain, Germany, the UK and the Netherlands owning one (Statista Global Consumer Survey, 2022). This could lead to larger bathrooms or kitchens as personal washing machines take up more space than shared ones such as those in laundry rooms.

The way of drying clothes can affect the use of space in a home. Clotheslines and racks can take up significant amounts of space depending on their size and placement, while tumble dryers are typically installed in a specific location in the home and may require additional ventilation or plumbing. Although many households choose to use clotheslines or drying racks instead, the ownership rate of tumble dryers in Germany, for example, has increased from 32 per cent in 2000 to 43 per cent in 2021, remaining still much lower than the ownership rate of washing machines (Destatis, 2022).

Discussion and conclusion

The housing sector accounts for a large share of total final energy consumption, mainly driven by the amount of space in this sector and the energy required to heat it. This article examines the trends and factors influencing space use in the housing sector and, by analysing their (potential) impact, suggests social and technical solutions for facilitating the reduction in space use.

The trends examined in this article can have varying direct and indirect impacts on residential energy consumption and space use. For example, the growth of the sharing economy in the housing sector may lead to a reduction in the average size of dwellings per person due to reduced ownership of appliances and storage needs. However, it could also lead to an increase in floor area if certain parts of the dwellings are only rented out occasionally and are not used otherwise. Another example is the urbanisation and densification of urban areas, which often result in limited available living space. Rising rents and property prices in urban centres push people towards smaller living spaces. This shift in consumption patterns is also accompanied by the adoption of sharing models, such as car-sharing and co-working spaces, which encourage sharing resources rather than individual ownership.

Potential changes in household structure resulting from such trends could also impact space use patterns. The growing number of households with only one or two adults and a high per capita area is a consequence of the increasing proportion of people over 65. Delayed childbearing and higher employment rates among women also play a role in forming childless households, which have an above-average per capita area. Higher divorce rates are another trend that increases the need for housing, as more dwellings are required for the same number of people. This situation is exacerbated when shared custody of children requires space in each parent’s home.

In addition to the existing trends outlined in this article, other consumption or behavioural trends may emerge or accelerate due to, or facilitated by, unforeseen adverse events such as those observed in recent years, namely the COVID-19 pandemic and the Russian invasion of Ukraine. In response to these unexpected circumstances, individuals and companies showed signs of short- and long-term behavioural, lifestyle and strategic adjustments that could disrupt historical trends (for example, the increase in teleworking [Lund et al, 2021], digital health seeking [the use of technologies such as internet and communication tools to find and manage information and services related to health] [van Kessel et al, 2023] and online shopping [Said et al, 2023] following COVID-19 and the adoption of energy-saving behaviours [EEA, 2023] and changes in household expenditure trends [Menyhért, 2022] following the energy crisis as a result of the war in Ukraine).

On one hand, the household structure and the (space use) consumption patterns in the residential sector are influenced by external trends and factors; on the other hand, household needs and behaviours are dynamic and constantly evolving, influenced by these factors. Therefore, solutions for reducing consumption in the housing sector should consider these constant changes and their underlying reasons.

Some of the trends analysed in this article (that is, the ones regarding the ageing population, employment, marriage, divorce and childbirth) have an impact on the household structure, which in turn changes the spatial needs of households. Therefore, more flexibility is needed to accommodate the changing living situations. However, the existing buildings that are supposed to satisfy the needs of households are typically designed with static features, resulting in a mismatch between supply and demand (Greden, 2005). As a response, adaptability should be considered a key principle in designing new buildings to achieve resource efficiency. Adaptability refers to the capacity of a building to be modified to accommodate new situations or conditions (Schmidt III and Austin, 2016). This can encompass regular changes such as varying day–night uses or utilising (re)movable partitions to connect the rooms when larger space is needed, as well as long-term adjustments like designing modular apartments that can be combined or separated to align with household needs. Integrating flexibility and adaptability into the design process (as suggested by Özinal and Erman [2021] and Hosseini Raviz et al [2015]) creates spaces that can be easily modified and reconfigured to meet changing needs. Improving the design of the buildings eliminates the need for constant expansion or reconstruction, as spaces can be adapted to meet evolving user requirements.

Some other trends (that is, digitalisation, sharing economy and urbanisation) do not necessarily have a direct impact on the household structure, but they lead to changes in households’ needs and habits and, therefore, influence the space use pattern in the residential sector. While these trends may have the potential to reduce space consumption (for example, higher prices and limited available space in cities leading to decreased living space), they may also increase the need for more space (for example, the uptake of digitalisation leading to the need for additional space to work from home). New approaches and innovative solutions are needed to counteract this increase in space need. To address this, alternatives for more flexible use of existing housing should be promoted. This would involve rethinking how space is used and encouraging individuals to adapt their behaviour to make the most efficient use of available space. Maximising the use of existing space can reduce the need for additional construction and minimise resource consumption. This could include providing communal spaces (recreation facilities, co-working spaces, social events) to reduce the need for additional individual rooms in each dwelling or promoting collective living arrangements. The role of such social innovations in reducing consumption has already been discussed in the literature (for example, Jaeger-Erben et al, 2015; Lorek and Spangenberg, 2019). Raising environmental awareness and reducing barriers for changes could help promote this approach and shift from traditional space use patterns to more innovative ones.

Lastly, consumption patterns, lifestyles and behaviours are influenced by, among other things, social norms and values, which play an important role in shaping our perceptions of what is desirable or acceptable in society. These perceptions are influenced by factors like income, as higher income usually results in higher consumption. Non-materialistic values have been suggested to lead to attitudes of sufficiency and consumption of ‘just enough’ (see, for example, McDonald et al, 2006; Boulanger, 2010). Reorienting social norms towards value-driven and non-materialistic norms may lead to less resource and material-intensive behaviour. By understanding these influences, we can avoid the need for high consumption and work towards promoting sustainable lifestyles and creating a built environment that supports both individual well-being and environmental sustainability.

To summarise, this article highlights potential social and technical changes that could facilitate space use reduction as illustrated in Figure 4. From the social perspective, focusing on households, the need for space consumption can be avoided by promoting non-materialistic narratives and shifted by introducing social innovations in the use of space. From a technical point of view and focusing on buildings, integrating flexibility into design processes can improve space efficiency. It is essential to acknowledge that individual behaviours and habits are shaped by a variety of factors at different levels, including sociodemographics, as well as cultural and geographical identities. Variations in thermal comfort needs across different ages and genders, the tendency in certain cultures to live in large families or host substantial gatherings, and the higher consumption levels typically seen in high-income households are just a few examples of how these factors can impact energy consumption. Recognising and addressing these diverse needs and backgrounds is crucial for understanding and developing effective solutions to the residential sector’s significant space and energy consumption challenges.

The figure is constructed as a field consisting of four rows and three columns. Each row has an overarching topic. The first one is a list of Factors and Trends running from left to right as follows: Income for the first row and column, urbanisation, digitalisation and sharing economy in the second column. The final column consists of the factors: ageing population/marriage employment/childbirth/divorce. Below this first row is the impact of the trend on the household structure, impact (i). The income (column one) shows to have no apparent impact on household structure, as well as the second column (urbanisation/digitalisation/sharing economy). The factors of the last column show a rise in later and shorter marriages with fewer children, as well as an ageing population, an increase in (female) employment and rising divorce rates. This results in more and smaller households. Below this row is impact (ii), it uses arrows (up or downwards) to visualise the trend on space use. This indicates if the amount of space used increases or decreases. The income in column one increases space use. Urbanisation decreases space use, whereas digitalisation increases it. A sharing economy leads to an increase or a decrease. All factors in column three (ageing population/marriage/employment/childbirth/divorce) lead to an increase in used space. The last row supplies solutions for each trend. For the first column (income), reorientations are needed to counteract the negative impact of such factors on our perception, which leads to the solution of promoting non-materialistic narratives. Therefore, using avoidance as a countermeasure. Summarised by the word ‘avoid’. For the second column, new solutions are needed to harness the potential of these trends to reduce consumption while meeting social needs; a shift in social innovations is recommended. Summarised by the word ‘shift’. For the final column, more flexibility is needed to respond to changing living situations and the resulting spatial needs. This leads to the proposal of integrating flexibility into building design processes. Summarised by the word ‘improve’.
Figure 4:

Summary of the studied factors and their impacts, and suggestions for improvement

Citation: Consumption and Society 4, 1; 10.1332/27528499Y2024D000000025

Limitations and outlook

We could identify some important trends based on our literature search. Nevertheless, this conceptual overview has a number of shortcomings. First, we were not able to quantify the importance of each trend based on our analyses as we only selected them qualitatively and derived some implications. Future studies should try to quantify the influences over time and build a more complex framework of influences and effects of these trends on space use. Furthermore, we only analysed the relationships in one direction as illustrated in Figure 1. However, one may assume that the effects are not linear, but are mutually reinforcing, not only in a top-down manner but also in a bottom-up way. We do not suggest the existence of a causal effect as shown in this figure, nor do we deny causality in the other direction. Furthermore, the behavioural categories examined in this article relate to standard and common activities carried out in an average household. Our conclusions highlight the significant impact of habits and behaviours on space requirements and use. However, a more in-depth study of activities, such as childcare or eldercare with specific space requirements, may provide further insights into other types of impacts on space use and should be stimulated by the current research. Additionally, our focus has been solely on activities within dwellings. Yet, there are other behavioural categories that occur outside the home and can significantly influence space use. For instance, mobility behaviour, including transportation preferences (for example, car ownership and having a garage, bike, public transportation), can impact location choices (for example, proximity to the tram lines), the need for specific spaces (for example, parking space) and spatial dimensions (for example, smaller affordable flats in the city centre). Including such activities in future research would provide a comprehensive overview of factors affecting space use pattern and reveal inter-sectoral connections, such as those between the transport and residential sectors.

Note

1

According to Eurostat (2011), a dwelling is defined as overcrowded if the household living in it has at its disposal less than the minimum number of rooms equal to: one room for the household, one room per couple in the household, one room for each single person aged 18 or more, one room per pair of single people of the same gender between 12 and 17 years of age, one room for each single person between 12 and 17 years of age and not included in the previous category, and one room per pair of children under 12 years of age.

Funding

This work was enabled by internal funding from the Fraunhofer Institute for Systems and Innovation Research ISI. The contribution of Josephine Tröger was also made possible through funding from the project H2020 FULFILL - Fundamental decarbonisation through sufficiency by lifestyle changes (Grant agreement ID 101003656), supported by the European Commission.

Acknowledgements

The authors would like to thank Heike Brugger and Elisabeth Dütschke for their valuable guidance and support throughout this research and acknowledge their contributions in reviewing and providing feedback on earlier versions of this manuscript. We are also thankful to David Hutzler and Kevan Skorna for their assistance in data collection.

Conflict of interest

The authors declare that there is no conflict of interest.

References