A framework model for assessing sustainability impacts of urban development

A framework model for assessing sustainability impacts of urban development

Available online at www.sciencedirect.com Accounting Forum 33 (2009) 209–224 A framework model for assessing sustainability impacts of urban develop...

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Available online at www.sciencedirect.com

Accounting Forum 33 (2009) 209–224

A framework model for assessing sustainability impacts of urban development Yangang Xing a,∗ , R. Malcolm W. Horner a , Mohamed A. El-Haram a , Jan Bebbington b a

Construction Management Research Unit, Division of Civil Engineering, University of Dundee, Fulton Building, Dundee DD1 4HN, Scotland, United Kingdom b Centre for Social and Environmental Accounting Research, School of Management, University of St. Andrews, St. Andrews KY16 9SS, Scotland, United Kingdom

Abstract Urban man-made assets have impacts not just on those who develop, build and operate them, but on people who may be quite remote from them. For example, the impact of a building on greenhouse gas emissions arising from fossil fuel use, pollution caused by travel to work patterns and employment opportunities provided by urban developments may be far removed from their immediate locality. There is a growing recognition of the need to internalize these external costs and benefits in accountancy frameworks, drawing on experiences in accounting for sustainable development. This desire, however, presents major challenges in identifying, evaluating and allocating the external environmental, social and economic costs and benefits of an urban environment. This paper reports on the development of an Urban Development Sustainability Assessment Model (UD-SAM) which allows decision makers to identify sustainability indicators (economic, environmental and social) and which may lead to more holistic evaluation of the sustainability impact of elements of the urban environment. The UD-SAM builds on a sustainability assessment model (SAM) developed originally in the oil industry. This paper describes how SAM has been tailored for the construction industry and urban sustainability assessment, and how a set of generic sustainable development indicators have been identified and validated by stakeholders. © 2008 Elsevier Ltd. All rights reserved. Keywords: Sustainability assessment; Full cost accounting; Built environment; Urban environment; Sustainable development indicators

1. Introduction Urban development has special importance within the broader context of sustainability. In 2005, the world’s urban population was 3.17 billion out of a world total of 6.45 billion (UN-HABITAT, 2007). Current trends predict that the number of urban dwellers will keep rising, reaching almost 5 billion by 2030 out of a world total of 8.1 billion (UNHABITAT, 2007). Due to the density of populations and the intensity of economic and social activities, urban areas are also major consumers of resources, producers of waste and pollution, degraders of the environment, and foci for social problems. Building and construction activities worldwide consume 3 billion tons of raw materials each year, or 40% of total global use (Roodman & Lenssen, 1995). Construction, mainly for urban man-made assets, accounts for around 10% of national GDP globally (Howard, 2000). At the same time, there is a growing requirement for the ∗

Corresponding author. E-mail address: [email protected] (Y. Xing).

0155-9982/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.accfor.2008.09.003


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construction sector in the UK and in other countries to adopt the principles of sustainability in their activities and polices (Augenbroe & Pearce, 1998; Brandon, 2005; Curwell, Yates, Howard, Bordass, & Doggart, 1999; Department for Trade & Industry, 2006; Organisation for Economic Co-operation and Development, 2002, 2003; United States Green Building Council, 2003; Walton et al., 2005). As a result, environmental and societal issues are increasingly being considered alongside functional and economic aspects of built environment by architects, surveyors, engineers, project managers and others responsible for making key decisions throughout the different stages in delivering an urban development project. Consequently, there is a demand for tools to support those decision makers in finding more sustainable solutions. For example, in the United Kingdom, some 25% of new office buildings have an environmental assessment (Hasegawa, 2002). Although sustainability assessment criteria are available, there is no single, robust methodology that can simultaneously quantify and assess all three dimensions (economic, social and environmental) of urban development. Full cost accounting (FCA) has been identified as one way forward to analyse the environmental, social and economic costs and benefits at different spatial scales and at different stages in the life cycle (SUE-MoT, 2004b). The aim of this paper is to present the development of an integrated framework—an Urban Development Sustainable Assessment Model (UD-SAM) for assessment of economic, environmental and social impacts of buildings in the context of urban developments. This paper includes the following sections: background of this research, structure of UD-SAM, impact categories in the UD-SAM and a conclusion. 2. Background There are currently several methods available and in use for the evaluation of environmental impacts of buildings and urban developments (SUE-MoT, 2004a). Much attention has focused on environmental impacts assessment, for example BREEAM (UK, Building Research Establishment, Environmental Assessment Method), ENVEST (UK, an offshoot of BRE’s assessment method), LEED (USA, Leadership in Energy and Environmental Design), BEES (USA, Building for Environment and Economic Sustainability), and ATHENA (Canada, this is the name of an institute similar to those listed above). The issues covered by these assessment tools are mainly related to the use of fossil fuels, materials and land along with the pollution impact of buildings/urban developments. Integration of social and economic impacts into assessment has received less attention. As a result, existing tools cannot be described as integrated sustainability assessment tools. In order to develop an integrated assessment tool, one of the principal challenges facing developers and users is the difficulty of comparing apples and pears: that is, of measuring costs and values which are expressed in different units. Difficulties also arise in comparing alternatives and options across different projects and communicating assessment results across difference disciplines and to different groups of stakeholders. FCA (for recent published reviews see Bebbington, 2007; Bebbington, Gray, & Kirk, 2001; Lamberton, 2005) is an accounting tool that seeks to identify external costs associated with a particular activity and to incorporate this information in decision-making processes (Bebbington et al., 2001). The assumption underlying the desire for FCA is that if one were to account for externalities then society could be better informed as to which options would be more likely to make sustainable development achievable. There has been some work in the field of entity level FCA (Atkinson, 2000; Bebbington et al., 2001; Bebbington & Gray, 2001; Casella Stanger, Forum for the Future, & Carillion, 2002), but so far none has focused specifically on urban sustainability assessment. This has arisen for two reasons. First, most accounting work is directed at the corporate level rather than the urban development level. Second, the complexity of urban sustainability assessment (both in terms of scientific uncertainty and ideological diversity) requires a multi-dimensional approach to assess the potential impacts of urban development, thereby increasing the complexity of the task (Bebbington, 2007). In order to develop a robust model for assessing urban sustainability impacts and identify a most appropriate FCA model to be tailored for the urban sustainability assessment, existing sustainability accounting models were reviewed (Xing, Bebbington, Horner, & El-Haram, 2006). Applications, tools, findings and problems identified in each model have been analysed and it is evident that sustainability accounting models are currently fragmentary in nature and targeted on different issues and business domains. The existing models and frameworks can be broadly categorised into the following four groups: (1) Project evaluation models (Antheaume, 2004; Baxter, Bebbington, & Cutteridge, 2004; Bebbington, 2007; Construction Industry Research and Information Association, 2001; Lamberton, 2000).

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Fig. 1. Signature of sustainability performance of an oil field development (reproduced from Baxter et al., 2004).

(2) Organisational models (Bebbington & Gray, 2001; Bent, 2004; BSO/Origin, 1990, 1991, 1992, 1993, 1994, 1995; Taplin, Bent, & Aeron-Thomas, 2006; United States’ Environmental Protection Agency, 1996). (3) Sectoral models (Atkinson, 2000; Jones, 1996, 2003; Macaulay, 1999; Rubenstein, 1994). (4) Other frameworks related to sustainability assessment (Birkin, 2000, 2001; Castro & Chousa, 2006; Ekins & Simon, 1998, 1999, 2001; Geibler, Liedtke, Wallbaum, & Schaller, 2006; Lamberton, 2005; Perrini & Tencati, 2006; Schaltegger, Bennett, & Burritt, 2006). A review of these models and frameworks resulted in the identification of a particular model that showed more promise than some of the others. In particular, the sustainability assessment model (SAM; see for more detail Baxter et al., 2004; Bebbington, 2007) was identified as being an appropriate base to use for developing an urban developmentbased assessment tool. There were three reasons for this choice. First, the SAM considers social, economic and environmental aspects in the one tool. Many of the other tools/approaches reviewed concentrated on one element only (primarily environment). Second, SAM is better developed than most reviewed in that it had been used by British Petroleum (BP) in practical contexts to evaluate sustainable development performance of projects. It has also been applied to a variety of projects (not only oil and gas development) thereby providing insight into how the SAM could cope with different project contexts (see also Frame & Cavanagh, in press). Third, and related to the second point, experience of using this tool has been reported in the public domain in a way that provides transparency about how it is constructed (most specially in Bebbington, 2007). In combination, this made the SAM the most potentially useful model to develop for this project (for more detail see Xing et al., 2006). The SAM originated in BP in 1999. In the SAM, the impacts of a project are categorised into the following four groups: economic impacts, environmental impacts, social impacts and natural resource consumption. Sustainability indicators are traditionally categorised in three dimensions, namely economic, environmental and social impacts. In the BP case, and given the nature of oil and gas extraction, the use of resources such as water, fossil fuel reserves, land and other materials are among the most important factors to consider in sustainability assessment. It could be argued, however, that resource use and environment pollution damage could be collapsed into a more generic category of ‘environment’. The SAM assesses these impacts of a project over its life cycle, crucially including product use (which in the case of an oil and gas development accounts for the majority of the impact of a project). These impacts include the direct environmental and social impacts as well as broader social costs and benefits. SAM generates a sustainability ‘signature’, which presents monetised impacts in each of the four dimensions: social, environmental, resource and economic. Different colours indicate different sub-categories in each dimension (with each category consisting of a physical measurement of impact which is subsequently converted into a monetary measure—see Gasparatos et al., in press, for a discussion of the problems with monetisation). An example of a SAM signature is provided in Fig. 1 with the main categories of impact identified. The SAM has also been used in other settings in New Zealand (see, in particular Frame & Cavanagh, in press). Having decided that the SAM framework and approach was the most useful for this project, it was necessary to customise the SAM to the urban environment. Specifically a model of the impacts of an urban development was needed as well as identifying particular indicators for a SAM type assessment. International, national, and local sustainability indicators, national strategies for sustainable construction, major sustainable building and urban assessment tools and


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other sustainability assessment systems have been used to achieve this task. The difficulties of accounting for all the sustainability impacts due to a lack of adequate scientific and technical knowledge have been recognised (Common, 2007). However, a holistic picture of all the possible impacts is considered an essential pre-requisite for the delivery of an integrated assessment tool. 3. Structure of the Urban Development Sustainability Assessment Model (UD-SAM) The aim of the UD-SAM is to allow analysis of the environmental, social and economic costs and benefits in monetary terms at different stages in the life cycle of an urban environment. There are four main stages in developing the UD-SAM: describing the life cycle of a building in the context of urban development, identification of relevant sustainable development indicators, the quantification (monetisation) process, and presenting the output from the process in order to support decision making. Most of the existing building assessment tools consider land use and environmental impacts (SUE-MoT, 2004a), leaving out social impacts. As a result, the SAM expands the range of impacts to be considered. In addition, most of the building assessment tools starts from materials extraction and ends at disposal. In the development of the UD-SAM, the urban planning stage was incorporated as part of the life cycle analysis process. Thus the life cycle starts from the urban planning stage, goes through design, construction, operation and maintenance, to demolition. This life cycle sets the boundary for urban sustainability assessment. In this UD-SAM model, a set of generic sustainability impacts categories has been developed based on a systematic literature review and validated by stakeholders. This set of indicators serves to specify the requirements for data extraction and filtration. The data extraction and filtering process consists of two major tasks: the first task is to identify the most important generic sustainable development impacts; the second task is to select the most relevant indicators, through stakeholder participation approaches, for assessing the urban environment. The significant impacts identified in this way will subsequently be monetised (where possible and appropriate—see Heinzerling & Ackerman, 2002; Miller & Patassin, 2005 for discussion of issues in this context) and Xing, Horner, El-Haram, and Bebbington (2007) for a review of a range of monetisation tools. The following section focuses on presenting the development of the UD-SAM impacts categories (issues regarding monetization are beyond the scope of this paper). The structure of the UD-SAM can be seen in Fig. 2. 4. Impact categories in the Urban Development Sustainability Assessment Model There is a large number of environmental, social and economic indicators being developed to assist with sustainability assessment (see, for example, CRISP, 2003; Deelstra & Boyd, 1998; Mega & Pedersen, 1998; Warhurst, 2002; Wong, 1995). Generally, these indicators are usually used in isolation to analyse the performance of projects, companies, sectors and countries as they relate to one of the three dimensions of sustainability. No robust model that has integrated all three dimensions (environmental, social and economic) into a single framework currently exists. The impact categories in the UD-SAM were created by following a process which integrated top-down approaches (consolidation of existing sustainable development indicators (SDIs)) and bottom up wider-stakeholder engagement approaches (via a workshop and questionnaire survey). Using the top-down approach, 24 sets of indicators were chosen based on an analysis of over 600 sets of SDIs. Major impacts categories were extracted from the 24 SDIs reviewed. In parallel to this work, a workshop was conducted where participants were asked to identify important impacts of urban development. Participants at the workshop were all experts in built environment (including academic and practitioners) and the workshop focused on sustainability assessment. As a result, it is plausible to assert that this constituted a group of experts who are likely to been knowledgeable about the impacts that arise from built environment. All the impacts identified in the workshop were grouped by type and the frequency by which impacts were identified was counted. This resulted in a list of significant impacts as identified in the workshop. Finally, a questionnaire survey was also carried out with respondents being asked to give scores to each impact listed in the questionnaires (themselves drawn from the SDIs review). Significant impacts were identified by ranking the average scores of each impact on a questionnaire. The three sets of results were cross mapped and consolidated. A single table was created to present the impacts identified in the three exercises.

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Fig. 2. Structure of UD-SAM.

4.1. Consolidation existing sustainable development indicators Based on the existing literature (Bourdeau & Nibel, 2004; CRISP, 2003; SUE-MoT, 2004a,b,c) we identified over 600 SDIs in several sustainability-related categories. We applied an integrated process to identify the UD-SAM impacts categories (Fig. 3). We used our judgement to identify 24 sets of indicators which seemed to us to be the most important (that is were produced by influential organisations or which had widespread impact) and which covered various spatial scales. A detailed review of the 24 sets of indicators was carried out in three parts. First, an initial review was made of international, national and local initiatives to develop SDI systems. This was followed by a review of SDIs for the construction sector and urban environment. The last part was a review of wellbeing and happiness indicators. Only the SDI systems with detailed measurement criteria were selected; other schemes incorporating abstract principles were not included at this stage. The major impacts categories with their frequencies of occurrence are presented in Table 1 and each element of the review is described in more detail below.

Fig. 3. A system structure for the FCA-based urban SAM; A process to identify UD-SAM impacts categories.


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Table 1 Impacts categories and their frequency of occurrence in the selected indicators set. Headline indicators (10 sets)

Construction and urban related indicators (10 sets)

Wellbeing and happiness indicators (four sets)

Total (24 sets)

Environmental impacts Pollution Greenhouse gases emissions Waste Fossil fuel Materials Land Water Nuisance Biodiversity

10 10 10 10 10 10 9 9 8

10 10 10 10 10 8 9 8 8

4 4 4 4 4 3 3 3 1

24 24 24 24 23 21 21 20 17

Social impacts Health Crime and security Community participation Mobility Education Housing condition Satisfaction Poverty Family

9 10 9 8 9 8 7 7 2

8 5 4 5 3 4 4 2 0

4 4 3 3 3 3 3 4 4

21 19 16 16 15 15 14 13 6

9 8 5 0 0

4 3 3 5 3

4 0 0 0 0

17 11 8 5 3

Economic impacts Employment Economic growth Economic capacity Whole life costs Whole life revenue

4.1.1. International/national/local sustainable development indicators One of the earliest attempts to develop international SDIs was carried out by the United Nations Commission for Sustainable Development (UNCSD) in 1993. The 1992 Earth Summit (UNCSD, 1993) recognised the important role that indicators can play in helping countries to make informed decisions concerning sustainable development. The UNCSD indicators system (UNCSD, 2001) provides a detailed description of key sustainable development themes and sub-themes and an approach to the development of indicators of sustainable development for use in decision-making processes at the national level. Since 2006, the UN Division for Sustainable Development has reviewed the 2001 set of indicators (UNCSD, 2006). In order to monitor sustainability progress in urban contexts, the European Common Indicators (ECI) was launched in 1999. ECI has 10 generic indicators ranging from global climatic change to ecological footprint (Tarzia, 2003). EU directives on Environmental Impact Assessment (EU, 2001) declared that “[t]he environmental impact assessment shall identify, describe and assess, in an appropriate manner . . . the direct and indirect effects of a project on: human beings, fauna and flora; soil, water, air, climate and landscape; the interaction between the(se) factors; material assets and the cultural heritage.” In the UK, a Strategic Environmental Assessment (SEA) is mandatory for plans and programmes. In order to embrace wider sustainability objectives in England and Wales, Sustainability Appraisal (SA) is mandatory for Regional Spatial Strategies and Local Development Documents (ODPM, 2005). These sorts of assessments create, defacto, SDI sets as well. The UK Strategy for Sustainable Development published in March 2005 (Department for Environment, Food and Rural Affairs, 2005), created UK headline SDIs (Defra, 2007) with these SDIs being grouped around four shared priorities areas (namely sustainable consumption and production; climate change and energy; natural resource protection and environmental enhancement; and sustainable communities). With some minor variations, the Scottish Executive developed a set of similar indicators for Scotland (SE, 2006). In a similar vein, the Australian Department of the

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Environment and Heritage (EnvironmentAustralia, 2001) and a private organisation in Japan (JFS, 2007) have also developed systems for measuring national sustainability performance. Based on local Agenda 21 (UNCSD, 1993), local governments have developed SDIs for their own cities since 1993. Based on an Internet research and a survey carried out by the authors in 2006, only few of these SDIs are still in use and accessible through the Internet. Two sets of local SDIs (Bristol-City-Council, 2005; Plymouth-City-Council, 1995) were identified as live projects and their SDIs are similar to the UNCSD indicators (UNCSD, 1993). In summary, international and national SDIs are fairly consistent in terms of themes and sub-themes. Compared to local SDIs, indicators for measuring national performance give a high-level idea of the current state and the evolution of trends (for example, economic development, education, health), with local SDIs being less aggregated to allow them to be understood by their users (for example, the number of noise complaints received by a City Council in a year). 4.1.2. Construction and urban sustainable development indicators There are several sustainable construction and urban development assessment tools that have been implemented around the world (Bourdeau & Nibel, 2004; BRE, 1998, 2006; Forberg & Malmborg, 2004). The best-known building assessment tools in the UK are BREEAM (see BRE, 1998, 2006), and in USA the Leadership in Energy and Environmental Design Green Building Rating System (LEED, see USGBC, 2007) which was created by the U.S. Green Building Council (USGBC) is also popular. The use of these two tools is growing as awareness of sustainable development has increased and they also appear to have been in part responsible for a shift in industry attitudes towards environmental design. There are two dominant assessment systems currently used in Hong Kong, HK-BEAM (Hong Kong Building Environmental Assessment Method) and CEPAS (Comprehensive Environmental Performance Assessment Scheme). HK-BEAM was initiated in 1996 by using UK BREEAM as a template. The overall structure and detailed criteria were modified to suit the Hong Kong context, for example, the compact city form. However, the influence of LEED is also evident in this approach (for example, recognising site aspects and using similar certification levels to LEED). The CEPAS is positioned as a new tool to fill in some of the gaps not fully addressed by HK-BEAM (for example, it addresses human factors and their surroundings, see also Cole, 2006). Launched by Natural Resources Canada, the GBTool has been under development since 1996, though responsibility was handed over to the International Initiative for a Sustainable Built Environment in 2002. In order to accommodate demands for regional authorities, it contains regionally relevant benchmarks. BEES (Building for Environmental and Economic Sustainability) measures the environmental performance of building products by using a life-cycle assessment approach specified in the ISO 14040 series of standards. BEES was developed by the US National Institute of Standards and Technology with support from the US Environmental Protection Agency’s Environmentally Preferable Purchasing Program (Lippiatt, 2002). BEES includes environmental and economic performance data for nearly 200 building products and allows environmental and economic performances to be aggregated into a score for overall performance using weights defined by users. The Sustainable Construction Strategy (Department for Trade & Industry, 2006) builds on the UK Government’s principles for sustainable development (Defra, 2005) and sought to develop a vision for the future highlighting key issues relevant to existing government targets across the spectrum of sustainability aspects. Those issues include cost, facilities management, materials, water (flood risk), climate change/energy, water quality, waste, aesthetics, safety, skills, equity and respect for people. Sustainable construction: company indicators (CIRIA, 2001) provides guidance on how to use indicators to set company targets and derive direct benefit from sustainability reporting and benchmarking of company performance, while contributing to industry-wide measurement and progress. It identifies a series of quantitative measures (indicators) against which companies can measure their performance (strategic indicators) and the activities they undertake (operational indicators). Strategic indicators include environmental (for example, percentage of projects for which an environmental assessment has been undertaken, percentage of projects for which whole life costs were calculated) social (including, percentage of projects that include a plan for stakeholder dialogue, average client satisfaction using the KPI approach), and economic (such as, profit before tax and interest as a percentage of sales, profit before tax and interest per employee). The Dow Jones Sustainability Indexes (DJSI), launched in 1999, was developed to track financial performance of leading sustainability-driven companies. It was formulated to provide asset managers with benchmarks to manage sustainability portfolios (DJSI, 2006; Hotia, McAleera, & Pauwelsb, 2005; Knoepfel, 2001). Assessment criteria include environmental (from eco-efficiency to reporting), social (from philanthropy, human capital development to reporting) and economic (from codes of conduct to risk and crisis management) with some specific criteria for individual industry.


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In a EU project PROPOLIS (Planning and Research of Policies for Land Use and Transport for Increasing Urban Sustainability) following the project SPARTACUS (System for Planning and Research in Towns and Cities for Urban Sustainability), a set of indicators was developed for measuring urban sustainability (Lautso et al., 2004). This set of indicators has broad coverage of transportation related impacts, such as transport investment costs, transport user benefits, and exposure to NO2 from transport (Lautso et al., 2004). In addition, the Sustainable Project Appraisal Routine (SPeAR® ) (ARUP, 2007; Raman, 2005) focuses on the key elements of environmental protection, social equity, economic viability and efficient use of natural resources. To summarise, these tools differ in the level of detail addressed but are similar in terms of seeking to address sustainable development. 4.1.3. Wellbeing, happiness and other indicators It has been argued that the key question for how sustainability may be pursued concerns how economic and social development can be achieved globally without endangering the earth’s ecosystems (Sustainable Europe Research Institute, 2006). The core of this concept is to secure and, where appropriate, increase the quality of life for humans, as a precondition for individual happiness. Therefore, sustainable development could be seen to mean providing the right conditions to create a lasting increase in the happiness and wellbeing of all humans (SERI, 2006). In this section, indicators developed and used for measuring wellbeing and happiness are outlined. In the early 1970s, Nobel laureate James Tobin and William Nordhaus highlighted that “GDP (Gross Domestic Products) is not a measure of welfare” and proposed a Measure of Economic Welfare (MEW) by adding to GNP (Gross National Product) the value of household services and leisure, subtracting the cost of capital consumption and of ‘bad effects’ such as pollution, and excluding from GNP defensive expenditure such as police services to combat crime (Nordhaus & Tobin, 1973). Similar indexes have been developed since the 1990s, such as the Index of Sustainable Economic Welfare (ISEW; see Cobb & Cobb, 1994) and the Genuine Progress Indicators (GPI; see Venetoulist & Cobb, 2004). These use similar methods to ‘correct’ GDP so that it may be seen to be more akin to a measure of welfare and may, therefore be a measure of relative SD performance. Likewise, the UK’s New Economics Foundation publishes a Happy Planet Index (HPI; see Marks, Simms, Thompson, & Abdallah, 2006) which looks for countries where people live long and happy lives without damaging the planet. The HPI combines data on life expectancy, surveys on life satisfaction and the consumption of natural resources. Measures for happiness and wellbeing have also been developed by various international and private institutions (Bruno & Stutzer, 2002; Richard, 2006; Romina, Johansson, & d’Ercole, 2006) but to date there is no consensus on the best measure. Most of these measures are not systematically used by policy-makers due to measurement, weighting and indicator selection problems. Some of them, however, are popular among different stakeholders and HPI, ISEW and GPI have been computed by researchers for a number of countries. In summary, Table 1 outlines those impacts that are widely used in SDI sets. There is more coherence and agreement around indicators under the environmental section but there is also good levels of agreement for many social and (to a lesser extent) economic impacts. It should be noted that the elements within Table 1 are not independent of each other (especially in the social impacts category). What Table 1 does provide us with, however, is a defendable starting set of impacts that have consistently been identified as being relevant to sustainable development assessment. The next step undertaken in the project was to explore the robustness of these impact categories with those who are active in the built environment and sustainable development debate. 4.2. Identify important impacts with stakeholders It has been asserted that stakeholder engagement is an important element for improving confidence in a sustainability assessment (Blackstock, Kelly, & Horsey, 2007; Mayumi & Giampietro, 2006). Further, it is often argued that sustainability issues can most valuably be addressed through the development of more transparent and dialogic approaches to modelling (Bebbington, 2007; Bebbington, Brown, & Frame, 2007; Bebbington, Brown, Frame, & Thomson, 2007b). As a result, and in order to refine and improve confidence in the UD-SAM impact categories identified in the previous section, a workshop was conducted and a questionnaire survey was carried out to ascertain if the categories identified in Table 1 are appropriate. One caution must be noted here regarding stakeholder involvement. In the main, stakeholders who were surveyed for this paper work in developed world contexts (albeit that participants at the conferences came from as far afield as New Zealand and included those working in mainland Europe as well as North America). As such, the views of these stakeholders are likely to reflect their context. If participants from the developing world were asked to complete the

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Table 2 Participants in the workshop (37 participants in total). Categories

No. of participants


By sectors Academics Industries Government

29 6 2

78 16 5

By expertises (assumption) Engineering and construction Urban planning Sustainable development Accounting

14 10 10 3

38 27 27 8

By demographic distributions UK Rest of the Europe Asia and Pacific America Africa

15 7 7 6 2

41 19 19 16 5

same exercises we could expect that priorities would differ. Thus, this stakeholder ‘proofing’ of the model unavoidably has a developed world bias. This is not a great problem as long as the model is being used in the developed world context and not inappropriately applied outside of that context. 4.2.1. The workshop A workshop was conducted during the international conference on Whole Life Urban Sustainability and its Assessment which took place in Glasgow on 27th July 2007. Thirty-seven participants took part in the workshop from a wide range of backgrounds (see Table 2). The workshop lasted for about 2 h and each participant was asked to write down what they viewed the most important sustainable development impacts of the built environment to be (up to a maximum of 10 items). The priorities were attached to a white board under three main categories: environmental impacts, social impacts and economic impacts. In total about 180 different impacts were identified by the 37 workshop participants from about 360 post-its notes. Although, some of the impacts had different names (for example, depletion of resources, materials consumption, natural resource use) given they refer to the same general issue they were grouped together. The consolidated results from the workshop are shown in Table 3. Table 3 Significant impacts and their frequency of occurrence from 37 participants. Environmental impacts Energy Depletion of resource Climate changes—CO2 emissions Land use Waste Air pollution Biodiversity Water pollution Noise Ground pollution Sub-total Total number of post-its: 181

Frequency of occurrence 17 16 13 13 11 9 9 6 6 5 105

Social impacts Health Quality of life Crime Transportation Leisure Social capital Security High unemployment Social equity Cultural diversity

Frequency of occurrence 8 6 5 4 4 4 4 3 3 3 44

Economic Impacts Whole life cost Job creation Economic growth Unaffordable housing Socio-economic inequity Economic development Wealth Distribution of wealth Leakage from local economies Built facilities/service

Frequency of occurrence 8 5 3 3 3 2 2 2 2 2 32


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Table 4 Responses from the questionnaire survey. Environmental impacts

Social impacts Avg. score

Energy Water Climate change Air quality Land Material Waste generation Species

4.50 4.36 4.27 3.97 3.92 3.86 3.78 3.72

Economic impacts Avg. score

Quality of education Health care Living Conditions Satisfaction Crime Mobility Social capital Accidents

4.27 4.30 4.20 3.86 3.82 3.77 3.57 3.17

Avg. score Economic index Employment Productivity

4.50 4.23 3.83

4.2.2. Questionnaire survey In parallel to the workshop, an MSc student at the University of Dundee (Elisawi, 2007) carried out a questionnaire survey to identify the most significant sustainable development impacts of the built environment (paralleling the workshop event). The questionnaire design was based on a summary of more than 900 indicators, which identified through a process similar to that used with the 24 SDI sets in this paper. Questionnaire participants were asked to indicate the relative importance of each of the listed issues on a scale of 1–5: (where 1 = of little importance; 2 = of some importance; 3 = important; 4 = very important; and 5 = of great importance). Thirty completed questionnaires were returned out of the 100 copies distributed to the participants of the conference on Whole Life Urban Sustainability and its Assessment. The average score for each impact was calculated. Based on the average score, the impacts rated 3 or more are shown in Table 4. There may be some overlap between those in the workshop and those who completed questionnaires (but given the questionnaires were anonymous, it is impossible to ascertain to exact extent of cross over). All those at the conference, however, were either built environment practitioners or academics who have an interest in sustainability assessment. Like those in the workshop, therefore, it is possible to assume that they had knowledge of this subject area. 4.3. Sustainability assessment categories in UD-SAM Table 5 cross maps the outcomes from the three exercises undertaken to generate sustainable development impact categories. In this table, similar impacts have been aligned with each other and as a result a sense of the consensus on various elements can be seen. The consolidation of the three sets of results has allowed the validation of the UDSAM framework which was itself developed by researchers using the original SAM as a template. In UD-SAM, the sustainability assessment categories, which are shown in Fig. 4, are grouped into two divisions: internal impacts and external impacts. The internal impacts include whole life cost and whole life revenue. The external impacts include environmental impacts, social impacts and economic impacts. The environmental impacts identified in Table 5 include fossil fuel reserves, materials, land, water, biodiversity, pollution, greenhouse gases emissions, nuisance and waste. Energy was identified as a significant impact in the workshop and questionnaire survey with impacts related to energy being captured in the three sub-categories: natural resources depletion, emissions (for example, pollution, CO2 emission) and waste. A systems conception of the flows of materials that arise in an urban development was confirmed by the three exercises. For example issues such as fossil fuel reserves and materials occurred in all of the 24 sets of indicators reviewed and have the highest occurrence rate in the workshop exercise (with, respectively, 17 and 16 out of 37 participants noting them as being important and high average scores of 4.5 and 3.9 in the questionnaire). Land, water and biodiversity were also identified as significant impacts across the exercises. Pollutants and greenhouse are two major types of emissions, which appeared in all the 24 sets of SDIs reviewed and have very high average scores in the questionnaire survey (4 and 4.3 respectively). Waste generation appeared in all of the 24 sets of SDIs reviewed and had a very high occurrence rate in the workshop as well. In developing the UD-SAM environmental impacts categories we created three sub-categories: first a sub-category of resource depletion, which has five sub-categories: fossil fuel, materials, land water and biodiversity; second a sub-category of emission (particulate, gaseous and fluid) to capture pollu-

Table 5 Cross mapping impacts identified in three exercises. Impacts

Env. Impacts

Review (24 sets of indicators)


Workshop (37 participants)


Questionnaire (30 responses)

Avg. score up to 5

Fossil fuel reserves Materials Land Water Biodiversity Pollution

24 23 21

4.5 3.9 3.9 4.4 3.7 4.0

Fossil fuels Materials Land Water Biodiversity Particulate emissions Fluid emissions

24 20 24

17 16 13 5 9 9 5 6 13 6 11

energy Materials Land Water Species Air quality

Greenhouse gases emissions Nuisance Waste

Energy Resources/materials consumption Land use Water usage Biodiversity Air pollution Ground pollution Water pollution Climate changes—CO2 emissions Noise Waste

Climate change


Waste generation


Gaseous emissions Wave emissions Waste

Education Health Housing condition Crime

15 21 15 19

Quality of education Health care Living conditions Crime

4.2 4.3 3.9 3.8

Education Health Housing provision Crime/security

Mobility Satisfaction Poverty Family

16 14 13 6

Mobility Satisfaction

4.3 3.9

Physical interconnectivity Wellbeing



Community participation

Eco. Impacts

Whole life value

Consolidated indicators

17 24



Crime Security Transportation

5 4 4

Quality of life Leisure High unemployment

6 4 3 Social capital




Economic growth Economic capacity

11 8 5

Whole life revenue


4 3 3 3 3 2

Social capital


Job creation Leakages from local economies Economic growth Economic development

5 2 3 2



Economic index Productivity

4.0 3.8

Whole life cost Built facilities/service Wealth

8 2 2

Multiplier effects of jobs

Whole life cost Whole life revenue


Whole life costs

Social capital Social equity Cultural diversity Unaffordable housing Socio-economic inequity Distribution of wealth

Y. Xing et al. / Accounting Forum 33 (2009) 209–224

Soc. Impacts



Y. Xing et al. / Accounting Forum 33 (2009) 209–224

Fig. 4. UD-SAM assessment categories.

tion, greenhouse gases emission, fluid emission, and wave emission (such as noise); and the third sub-category of waste. A wide range of social impacts of urban developments were identified from the exercises (ranging from health, crime to equity and poverty). The UD-SAM attempts to deal with this range by identifying two generic categories of social impact. The first arises from how the UD is used, that is, the direct impacts associated with a specific type of building (for example schools/universities have significant impacts on education, and houses have significant impacts on housing provision). At the same time a number of indirect impacts arise which are the outcomes of a particular combination of urban man-made assets. Aspects that fit into this category include crime and security, health, physical connectivity, wellbeing and social capital. Translating the various aspects identified by the exercises into these categories is not straightforward and in reality will depend on the nature of a particular project as well as the context in which that project takes place. We believe, however, that the various aspects in Table 5 cross map to the more generic categories of the UD-SAM. Employment was universally identified as an important economic impact of urban development. According to the results from workshop, economic growth has a relatively low occurrence rate comparing with environmental and social impacts. This might be due to the fact that economic growth often brings negative sustainability impacts (Meadows, Meadows, Randers, & Behrens, 1972; Meadows, Behrens, Meadows, Naill, & Randers, 1974; Meadows, Randers, & Meadows, 2005; Schumacher, 1973). However, the authors argued that ‘multiplier effects of jobs’ that arise from project spending is a component of what the exercise called economic development (with a lack of multiplier being captured in concerns about leakages from local economies). Therefore, in the UD-SAM, multiplier effects of jobs was chosen to indicate the external economic impact of urban development that is directly associated with a project. Whole life costs has the highest occurrence rate among all economic impacts according to the results from the workshop. In the UD-SAM, a category of whole life value was created to capture internal impacts (which can be reflected in an organisation’s accounts). “Whole life value” captures impacts on whole life cost, whole life revenue, and other economic impacts such as economic capacity, economic development and productivity which are associated with the project. To sum up, this set of UD-SAM impacts categories (Fig. 4) was created through a robust process which consolidated existing SDIs across different scales and which was validated by stakeholders. It was developed based on three

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distinct approaches regarding development of SDIs: consolidation of existing SDIs, workshop group exercises and a questionnaire survey. This process enabled the UD-SAM to integrate diverse values of different stakeholders (government, sectors and individuals) into a generic set of categories. It brought together different types of impacts (namely economic, environmental and social) into a single, overall assessment at one or more stages in the building and urban planning cycle. As noted at the outset, urban man-made assets have impacts not just on those who develop, build and operate them, but on people who may be quite remote from them. Therefore, the UD-SAM impacts categories have two divisions: internal impacts and external impacts. The internal impacts include whole life cost and whole life revenue, and the external impacts include environmental, social and economic impacts. Of course, identification of an impact is not the same as an individual accepting responsibility for an impact (see Bebbington, 2007; Bebbington et al., 2001 for a discussion of this issue). The UD-SAM, however, is intended in the first instance to provide a model of all impacts separate from the allocation of responsibility for management of that impact. The UD-SAM impacts categories link together separate impact assessments from different disciplines (accounting, construction, engineering, town planning and transportation) into a set of generic impacts categories suggesting that sustainability impacts can be modelled holistically. The UD-SAM impacts categories can also be used as a learning tool to help its users to gain better understanding of the complexity in the urban development, and to enhance social learning, institutional change and transition to a more sustainable society. 5. Conclusion As was noted at the beginning of this paper, urban development has special importance within the broader context of sustainability. In view of the growing complexity of managing the rapidly evolving urban environment and cities in Europe, there is a need for integrated approaches that assist city planners, developers and councillors in this undertaking (Rotmans & Asselt, 2000; Walton et al., 2005). Although sustainability assessment criteria are available, there is no single, robust methodology that can simultaneously quantify and assess all three dimensions (economic, social and environmental) of urban development. This paper reports the start of a process that seeks to develop of a holistic UD-SAM which allows decision makers to identify sustainability indicators (economic, environmental and social) for different assessment contexts. It brings together different types of impacts into a single, overall assessment at one or more stages in the building and urban planning cycle. At the core of the UD-SAM, a set of UD-SAM impacts categories were created by consolidating existing sustainable development indicators across different scales. This outline set was then validated by stakeholders. This set of generic impacts categories provides an essential pre-requisite for the delivery of an integrated urban sustainability assessment tool. It answers one of the fundamental questions in an integrated urban sustainability assessment: what needs to be measured? It is hoped that this paper contributes to the literature by providing a transparent account of how a set of impacts categories can be generated. The purpose of the paper is not to present sophisticated valuation methods which can be used to populate the UD-SAM (this is the subject of ongoing work). Rather, the paper focuses on presenting a framework model which is mutually agreed by a wide range of stakeholders. Within the broader UD-SAM framework, particular attention has been placed on the development of the set of generic impacts categories. This is for several reasons. First, it simplified the complex issues related to urban development to a smaller set of impacts, so the UD-SAM can be easily used and make the assessment practical. Second, it integrated different values and perspectives to a single framework: it made the assessment relevant. Third, it set guidance on defining boundaries and data extraction. Acknowledgements The financial support of the UK Engineering and Physical Science Research Council within the Sustainable Urban Environment Project is gratefully acknowledged. References Antheaume, N. (2004). Valuing external costs—From theory to practice: Implications for full cost environmental accounting. European Accounting Review, 13, 443–464. Atkinson, G. (2000). Measuring corporate sustainability. Journal of Environmental Planning and Management, 43, 235–252.


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