Environmental sustainability and multifaceted development: multi-criteria decision models with applications

Abstract

In recent years, decision makers, policy analysts, and other actors, have become increasingly aware of sustainability, and begun to combine economic, social and environmental criteria in their efforts to maintain competitiveness, long-term growth and development. In multiple stakeholder settings, the presence of diverse objectives and conflicting criteria often leads to a complex multi-criteria decision problem. The multi-criteria decision analysis (MCDA) offers an integrated framework to model and study sustainability criteria and related inter-criteria relationships. In this paper, we review some of the most significant literature on environmental sustainability, and categorise it to show how and why MCDA models are widely used and becoming increasingly popular. Our systematic analysis suggests that, there has been significant growth in environmental applications of MCDA in diverse areas, ranging from energy management and policy to land use, recycling management and sustainable tourism. Among the various MCDA methods and techniques, analytical hierarchy process, TOPSIS, and goal programming are the most frequently used approaches. Many authors use a combination of different MCDA techniques to balance various factors important to achieve sustainability related goals. We expect sustainability related criteria to be an essential consideration in most future multi-criteria models.

1 Introduction

The relation between environment and economic growth can be rooted in Nordhaus’s research (1991), where he pointed out that the reduction of emissions will limit their impact and ensure greater economic growth in the future. His economic growth model (Dynamic Integrated Climate-Economy model) firstly takes into account the benefits and the consequences of greenhouse emissions and the cost of their reduction. In the last 2 decades, a key topic for the research community has been modelling relationships between environmental sustainability, economic growth and human welfare. The policymakers and other (public and private) actors explore suitable trade-offs, while reconciling economic, social and environmental objectives. Each stakeholder has to tackle varied and competing objectives, leading to complex multi-criteria decision making. Many researchers have relied on the multi-criteria decision analysis (MCDA) or multi-objective models as formal methodologies using the available technical information to balance stakeholder values and promote solutions, fostering environmental sustainability. Pohekar and Ramachandran (2004) presented a survey of MCDA methods, techniques and their applications to sustainable energy planning, and concluded that the most frequently used techniques are analytical hierarchy process (AHP), ELECTRE (ELimination Et Choix Traduisant la REalité—elimination and choice expressing reality) and PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations). Huanga et al. (2011) studied MCDA trends and applications in environmental sciences between 2000 and 2009, concluding that, despite its limitations, AHP is a popular tool. Their study pointed out that the number of MCDA papers increased 7.5 times during the period, and they believe that the main reason was the increased availability of data and user-friendly modelling software. Wang et al. (2009) reviewed MCDA applications modelling sustainable energy decisions, considering their technical, economic, environmental and social aspects. They concluded that investment and CO₂ emissions are the two leading criteria, and AHP is the most used tool to model the sustainable energy decision process. The previous reviews suggested that, there has been a significant growth in environmental applications of MCDA over the last several years across all areas.

Our paper fills a research gap by studying environmental sustainability focused MCDA applications, including more areas, such as construction, manufacturing, supply chain and logistics, tourism and policy planning. The number of publications using MCDA and incorporating environmental sustainability criteria has mainly increased since 2011. This paper has two aims. First, we present a comprehensive review of the most significant literature on environmental sustainability, and categorise to show how and why MCDA models are becoming more popular in this area. Second, we use the literature review to identify the conceptual content of the field, and thus, contribute to the theory development and understanding of the latest techniques and applications.

The paper is organised as the following. In Sect. 2, we briefly introduce various MCDA approaches and popular techniques used. In Sect. 3, we discuss the methodology we adopted to search, analyse, classify and categorise the literature. Section 4 discusses MCDA with an emphasis on sustainability in the following seven areas: (i) energy, water resources management; (ii) construction, agriculture, forestry, land use and farming management; (iii) recycling management; (iv) manufacturing, supply chain and logistics, transportation management; (v) emissions, remediation and abatement strategies; (vi) policy planning and sustainability; (vii) tourism and events management. We present our conclusions in Sect. 5.

2 Decision support methods applied to environmental sustainability

The MCDA includes different approaches, classified into three main families: value measurement, outranking and goal programming (GP) models. We briefly summarise the main characteristics, advantages and disadvantages of these MCDA methods.

The aim of the value-measure approach is to construct a unique function aggregating partial preferences on multiple criteria. For instance AHP is “a theory of measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales” (Saaty 2008, p. 83). One of its primary advantages is that, it is scalable, and can easily adjust in size to accommodate a variety of decision-making problems, because of its hierarchical structure. One of the biggest criticisms of AHP is that, its general form is susceptible to rank reversal. An extension to AHP is the analytic network process (ANP), which is a general theory of relative measurement used to derive composite priority ratio scales from individual ratio scales, representing relative measurements of the influence of elements, that interact with respect to control criteria. The ANP can capture the outcome of dependence and feedback within and between the criteria. The AHP and ANP are both theories of relative measurement of intangible criteria (Saaty 2016).

In addition, the data envelopment analysis (DEA) is a non-parametric mathematical tool, introduced in the late 1970s (Charnes et al. 1978), which is capable of handling multiple inputs and outputs; thus, the model’s efficiency can be analysed and quantified. The disadvantage is that, it does not deal with imprecise data, because it assumes that all inputs and outputs are known exactly.

The outranking methods were developed considering implementation and scalability issues for practical problems. The popular ELECTRE, along with its many iterations (I, II, III, IV, IS, TRI), is an outranking method based on concordance analysis. It considers uncertainty and vagueness; however, outranking does not directly identify the strengths and weaknesses of various alternatives. The PROMETHEE, which is often used to elicit weights among the various preference choices, is available to the decision maker (DM). Wątróbski et al. (2019) presented a generalised framework of various MCDA techniques, that can help DM to choose the most suitable MCDA method based on the problem description.

The popular compromise solution methods include VIKOR (translated from Serbian as multi-criteria optimisation and compromise solution) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The VIKOR is a technique focusing on ranking and selecting from a set of alternatives. It introduces the multi-criteria ranking index based on the particular measure of ‘‘closeness’’ to the ‘‘ideal’’ solution (Opricovic 1998). In particular, VIKOR is helpful in a situation, where the DM is unable, or does not know how to express his/her preference at the beginning of system design.

The GP models are quite popular because of their simplicity, tractability and diversity of applications. The central idea of the GP method is to determine the aspiration levels of an objective function and minimise any (positive or negative) deviations from these levels. When the DM strives to optimise simultaneously “p” different conflicting criteria f_i, i ∈ I = {1,2,…,p}, the GP model is an aggregating methodology, that enables to obtain the best achievable compromise by the DM. The DM’s preferences can be represented using two main approaches: (a) assign weights and calculate the sum of the deviation variables multiplied by their individual weights, as in the weighted GP (WGP), known as the non-preemptive GP model; (b) rank order goal deviations by priority, often referred to as a preemptive formulation, as in lexicographic GP (LGP).

To tackle the decision making under uncertainty, the stochastic GP (SGP) variant assumes that, the goal values are stochastic and follow a specific probability distribution. One of the most popular techniques to solve SGP models is chance constrained programming (CCP), developed by Charnes and Cooper (1952, 1959). The CCP technique selects certain random variables as functions of random variables with known distributions, so as (a) to maximise a function of both classes of random variable subject and (b) to constrain these variables that must be maintained at the prescribed levels of probability. Another way to include randomness in the GP model is to consider the so-called scenario-based models. If DM assumes that the space of all possible events or scenarios Ω = {ω₁,ω₂,…, ω_N} with the associated probabilities p(ωs) = ps is finite, then the objective functions and corresponding goals depend on the scenario ωs. If DM does not know the precise aspiration levels, then a Fuzzy GP (FGP) is ideal for modelling and decision-making.

The simulation and heuristic models have been combined with GP models to provide unique information or analytical power to deal with complex problems. In particular, the heuristic algorithms can increase search diversity among the solution spaces, and thereby, increase the probability of finding the preferred solution.

For an extensive review of existing models and the relative mathematical formulations, we direct the reader’s attention to books and reviews (e.g. Greco et al. 2016; Colapinto et al. 2017).

3 Methodology

Methodologically, literature reviews can be comprehended as content analysis, combining quantitative and qualitative aspects to assess descriptive and content criteria. Our analysis only includes papers in peer-reviewed scientific journals or outlets, mainly in English, indexed in Scopus (www.scopus.com). The data for the literature review was obtained by keyword search in Environmental science, using the search terms environmental sustainability/sustainable in combination with “multi-objective models” or “multiobjective models” or “multiple objective models”; “mcdm” or “mcda” or “multicriteria decision making” or “multicriteria decision aid” or “multi-criteria decision aid” or “multi-criteria decision making” or “multiple criteria decision making”; and “GP” or “goal programming” or “goal program”. The search yielded 841 items, the various combinations based on the search parameters are presented in Table 1. The search period covers papers published during years 1993 to 2017.

Table 1 Summary of search criteria

After preliminary screening and eliminating duplicates and qualitative and/or unrelated papers, 512 papers fit the scope of this review up to September 2017 (See “Appendix” for details). Figure 1 presents the classification of 512 articles, namely 478 journal articles (11 in press, 93.36%), 23 conference papers (4.49%) and 11 books/book chapters (2.15%).

Fig. 1

Number of publications per year (1993–2017)

Figure 1 shows that interest in the topic is increasing. This positive trend is also reflected by the increase in public funding; since year 2013, the researchers have received funds from public institutions as well. The number of papers backed by research grants increased from one in 2013 to 49 (9.6%) in 2017. The leading institution is the National Natural Science Foundation of China (24 projects out of 58¹), followed by the Swiss National Science Foundation (4 projects) and Ministry of Science and Technology of Taiwan (3 projects).

Most of the papers were co-authored by at least 3 researchers (28.7%; average 3.55; min = 1; max = 15). We identified top authors in the area of environmental sustainability based on the number of publications (Table 2). Based on the origin of the papers, it can be inferred that, scientific contributions from European Union countries were pivotal in the area of environmental sustainability.

Table 2 Top authors in the field

From a geographical point of view, it is apparent that most contributions were from the United States (117), followed by China (96), Italy (96), Spain (94), Iran (65) and the United Kingdom (58). If we look at the contribution by region (continent) (Fig. 2), Europe leads (41.21%), followed by Asia (20.90%) and North America (12.50%). Figure 2 presents the number of publications based on region. This ranking can be inferred by the fact that three of the six leading published authors are from European countries, counterbalancing American research productivity. A significant proportion of papers were the result of international collaboration; in particular, multiple continental origin collaborations account for 21.88%.

Fig. 2

Number of publications by region

The international collaborations account for 32.2%, of which 67.88% are by authors from different continents. The international collaborations (between countries on the same continent) again confirm the leading role of Europe (23.03%), followed by Asia (6.06%). We did not identify significant differences between different topics/areas. From a longitudinal perspective, it is clear that the geographic distribution of authors has not changed over time, as illustrated in Fig. 3.

Fig. 3

Longitudinal geographic trends

Table 3 lists the journals that published most papers; they account for around 48% of them (with a low concentration but a large dispersion), and they published papers in all areas because of the multidisciplinary nature of the subject. The publications have appeared in top journals with an average 5-Years Impact Factor (IF5) of 4.16. The IF5 is computed as a ratio over a 5-year window; more precisely, the numerator is the number of citations in the current year to all items published in a journal in the previous 5 years. IF5 allows to better capture the impact of a journal in certain fields, that on average, might take longer than others to attract the bulk of their citations (Vanclay 2012).

Table 3 Top journals based on number of publications

4 MCDA and environmental sustainability application domain

In the broad area of environmental sustainability, we categorised papers using MCDA methods into seven main application domains starting from the subject areas identified by Scopus, as illustrated in Fig. 4:

Fig. 4

MCDA and sustainability—application domains

• Energy and Water Resources Management: 92 papers

• Construction, Agriculture, Forestry and Land Use (urban architecture), Farming Management: 125 papers

• Recycling Management: 57 papers

• Manufacturing, Supply Chain and Logistics, Transportation Management: 123 papers

• Emissions, Remediation and Abatement Strategies: 21 papers

• Policy Planning and Sustainability: 82 papers

• Tourism and Events Management: 12 papers

Europe and America are the pioneer countries in the policy planning and sustainability applications during the 1990s, whereas Asia and Oceania joined in the 2000s. As shown in Fig. 5,² publications are increasing in all regions and in all the previous identified seven areas of application domains (see the number on the x axis), but Europe is outperforming in all identified application areas, except in manufacturing, supply chain and logistics, transportation management, where Asia plays a relevant role.

Fig. 5

Number of publications in each area by region and period

In the following paragraphs, we provided key findings in all seven areas. Because there are many papers, we focused on the most cited ones; indeed, citations are standard means by which authors acknowledge the source of models, methods, ideas and findings, and are often used as a rough measure of a paper’s importance in the field.

4.1 Energy and water resources management

The sustainability has redefined the key considerations for energy policy, modelling and management. The ability to include diverse criteria makes MCDA an attractive tool in decision-making and policy planning. The multi-criteria optimisation models, incorporating economic and social criteria, reduced emissions and consumption, and integration with various forms of renewable sources, have been studied by several authors. The following papers represent a brief review of the most cited papers and emerging trends in energy and water resources management. Although renewable energy sources have been widely viewed as non-emitting, they might present social issues, such as land use management. All the papers focus on the three pillars of sustainability, namely, economic, social and environmental effects.

Eichhorn et al. (2017) used a GIS (geographic information system) based on multi-criteria approach to identify suitable locations for locating wind turbines in Germany. Although wind is an important variable renewable energy source, it can have conflicts with environmental habitat protection and human wellbeing in densely populated regions. The approach presented leads to ideal siting of wind turbines, and it significantly contributed to sustainable energy output by reducing the number of turbines needed per area. Lombardi et al. (2017)analysed two different methods for ranking evaluation criteria in a multi-criteria decision support tool for use in urban energy planning. They defined and ranked five criteria related to economic, reduced energy and emissions, using the “measuring attractiveness” by a categorical based evaluation technique (MACBETH) and the playing cards method. The two approaches have been applied to research smart city projects.

The recent literature also focused on environmental sustainability, especially on meeting emission reduction goals. Santoyo-Castelazo and Azapagic (2014) proposed a methodological MCDA framework to assess the sustainability of energy systems through 17 criteria, spanning economic, social and environmental factors. They used the framework to study electricity supply in Mexico, considering the country’s key energy drivers and climate change targets by the year 2050. The current business-as-usual approach of using only fossil fuel is unsustainable, irrespective of the criteria preference. The most suitable solution is to combine renewable sources and nuclear power. Madlener and Stagl (2005) proposed a methodology for designing a renewable energy policy integrating environmental, social and economic factors, leading to more sustainable development. The authors used a participatory multi-criteria evaluation process to account for stakeholder preferences, and accommodate different mature technologies to enable the use of diverse energy sources. Afgan and Carvalho (2002) demonstrated the potential of multi-criteria evaluation of complex new and renewable technology systems. Their aim was to define energy indicators, used in the assessment of energy systems, that meet energy, environment, social and economic sustainability criteria.

Several papers have studied the role of bioenergy as a viable renewable energy source. Buchholz et al. (2007, 2009a) outline the problems of setting extensive bioenergy systems, and recommend multi MCDA as the suitable tool for a participatory, transparent, timely and informed evaluation of sustainable bioenergy systems. Buckholz et al. (2009a) reviewed the suitability of 4 MCDA tools for assessing the sustainability of bioenergy systems using data from a bioenergy case study in Uganda. The four tools propose widely varying solutions, but social criteria inclusion was decisive in the viability of any bioenergy project. Elghali et al. (2007) also developed a methodology using MCDA to establish a sustainability framework for the assessment of bioenergy systems. Their model incorporates the three dimensions of sustainability, namely, economic viability, social acceptability and environmental performance. They applied their model to study sustainable development policies in the United Kingdom, integrating and reconciling the interests and concerns of diverse stakeholder groups. As renewable energy sources and technologies become more reliable, effective and cost efficient, DMs ideally need to make prudent choices considering all aspects of sustainability.

4.2 Construction, agriculture, forestry and land use (urban architecture) and farming management

Recently the literature has focused on the key role of the construction industry. As many environmentally friendly prefabricated components are entering the market, stakeholders need information about their environmental, technical and aesthetic aspects. Moving away from the anecdotal evidence or cost-based evaluation, DMs have to cope with multi-criteria decision-making problems, that are highly intensive in knowledge and involve partial information and uncertainty. Bansal et al. (2017) provided an analytical tool (based on AHP) to evaluate the applicability of prefabricated or on-site construction methods. Heravi et al. (2017) created a new Grey-Utility-ELECTRE method to rank feasible alternatives for industrial buildings (a large segment of the construction industry), and to use the ordered weighted averaging aggregation operator to aggregate environmental, social and economic criteria.

Moretti et al. (2017) conducted a MCDA (based on AHP) of four cement powders, to calculate and analyse the environmental, health and socio-economic effects of their production processes. They proved that it is inappropriate to consider only one parameter to identify the ‘best’ cement powder, but that several impact categories should be considered and analysed if different, often conflicting interests are to be pursued.

The land use is another crucial topic. Zavadskas and Antucheviciene (2007) dealt with the problem of the reuse of derelict buildings; they ranked available building regeneration alternatives by combining the economic benefits of regeneration with the environmental potential and the social interest. Similar to the previous research, they consider the current state of abandoned buildings and their environment, regeneration possibilities and the environmental impact of different redevelopment alternatives. To deal with the incomplete and inconsistent information available, the authors suggest a fuzzy method of multiple-criteria complex proportional evaluation of the projects. Even sustainable forest management (SFM) strategies should fulfil ecological, economic and social functions without causing damage to other ecosystems. Linking pressures on the environment, caused by human activities with changes of environmental state parameters, Wolfslehner and Vacik (2008) used ANP to evaluate the performance of four management strategies with regard to the Pressure-State-Response framework on SFM. They modelled priorities for indicators and alternatives with ANP, resulting from the interconnections to other indicators and their respective cumulative importance. This approach improves understanding and depiction of the network of human influences and their impacts on forest ecosystems, and overcomes the limitations of more traditional flat-dimensioned indicator sets. Similarly, Waeber et al. (2013) endeavoured to develop and evaluate alternative forest management strategies in the context of climate change. They used an AHP to balance competing values and objectives, and test the alternatives against each other, considering timber, wildlife, fire risk reduction and carbon.

4.3 Recycling management

To foster improvements in the reuse of resources, it is important to use models incorporating sustainability efforts. The MCDA, as applied to water reuse and solid waste disposal, balances the three pillars of sustainability. Below, we reviewed top cited papers and recent trends in promoting solid waste and water recycling. Chhipi-Shrestha et al. (2017) discussed model conceptualisation and development for wastewater treatment (WWT). They developed a multi-criteria decision support tool called FitWater, using fuzzy weighted averages to aggregate different criteria and generate a final score. The proposed tool is user-friendly, and the authors used an example to demonstrate its application.

For a wastewater treatment technology to be judged sustainable, it must comply with environmental, socio-cultural and economic needs. Bottero et al. (2011) applied AHP and ANP methods to select the most sustainable wastewater treatment systems, and argued that there are a number of opportunities to expand on other applications. Zeng et al. (2007) described hierarchy grey relational analysis for optimal selection of wastewater treatment alternatives, based on the application of AHP and grey relational analysis (GRA). They explained that the approach can be applied for complicated multi-criteria decision-making problems to obtain rational and scientific results.

Hyde et al. (2005) proposed a distance-based uncertainty approach for water resource decision making, and explored the need to consider the economic, environment and social implications in regional water resources planning. Among the various steps of MCDA, they focused on the uncertainty in criteria weights. The paper describes two existing sensitivity methods and proposes a new distance-based approach. The authors applied their proposed method to three case studies, and the results indicated that simultaneous consideration of the uncertainty in criteria weights should be an integral part of the decision-making process. Arlinghaus et al. (2002) reviewed the literature regarding the inputs needed for sustainable inland fisheries in industrialised countries. To understand the problems facing sustainable inland fisheries management, the authors described the inland fisheries environment, its benefits, negative impacts and constraints, alongside historical management, paradigms, trends and current practices. Huang and Xia (2001) pointed out that the current water-quality management needs significant improvement and analysed recent developments, advances, challenges and barriers associated with water-quality management practices. They examined a number of related methodologies, applications, and policy implementations, including MCDA and multiple objective programming techniques. Raju et al. (2000) presented an implementation of MCDA analysis for an irrigation management case study in Spain. The criteria used to rank alternatives consisted of economic factors, such as initial cost of irrigation system, maintenance cost, crop profitability, extent of European subsidies; environmental factors, such as water volume, water quality after irrigation, efficiency of water use, resistance to floods or droughts; and social factors, such as the employment of rural labour and non-cultivated areas. They formulated alternative policies by mixing factors, such as irrigation system, water pricing, water allocation, crop distribution, fertiliser use and subsidies received. They used PROMETHEE- 2, EXPROM-2, ELECTRE-3, ELECTRE-4 and compromise programming (CP) techniques to rank the alternatives, and the suggested solution indicating that, all five MCDA techniques choose the same alternative strategy.

Recently Hornsby et al. (2017) presented a case study of solid waste management in Naples, Italy. The purpose of the research was to test and validate the need for an appropriate participatory and scientifically sound decision-making process, because technical aspects cannot be the only criteria for good decision-making and cannot guarantee lasting success. They assessed the viability of a biomass fuel plant using the three pillars of sustainability. Keivanpour et al. (2017) proposed a holistic approach to end of life (EoL) aircraft treatment, considering lean management, sustainable development and the global business environment. They proposed an integrated optimisation framework based on a fuzzy interactive approach and genetic algorithm, to support strategic and managerial decision-making that considers sustainability. Hung et al. (2007) reviewed several models developed to support decision making in municipal solid waste management, and proposed a model that combines multi-criteria decision making and a consensus analysis model. They validated the model in a food waste management case study in Taiwan. Morrissey and Browne (2004) reviewed various types of models used in municipal waste management, and highlighted major shortcomings in these models. Because of these shortcomings, future research in the area should combine multi-criteria modelling and sustainable waste management, to enable suitable decisions involving all stakeholders in the community. It is particularly important to consider criteria related to the three aspects of sustainability—environmental, economic and social. Costi et al. (2004) presented a decision support system for solid waste management in the development of integrated incineration, disposal, treatment and recycling programs. The main goal of the decision support system is to suggest the optimal number, kinds and location of active plants. The decision support tool is based on a constrained non-linear optimisation problem. The authors paid particular attention to environmental impacts, especially the incinerator process and emissions.

In summary, several water purification and recyclable solid waste management technologies exist today. The MCDA models, incorporating multi-stakeholder preferences, are an ideally suited and popular way to consider sustainability related factors.

4.4 Manufacturing, supply chain and logistics and transportation management

Over the last decade, there has been overwhelming acceptance of sustainable practices in manufacturing, production and logistics. As consumers are increasingly aware of global warming and its damaging effects on environment, companies have started to take critical steps to include sustainable aspects in their manufacturing, distribution and transportation processes. To that effect, most companies have started to streamline their supply chain operations to make them more socially, environmentally and economically acceptable. Typical issues in this area include potential trade-offs between competing objectives, the optimisation of multiple criteria to maximise profit and revenue, environmental impact, customer satisfaction, energy consumption, reuse capability, which have all been studied in literature. The top cited papers in this area have used a rich set of MCDA techniques to model diverse problems, including supplier selection, reverse logistics, green supply chain indicators, remanufacturing, lifecycle assessment and others.

The supplier selection problems have been frequently studied using several hybrid techniques, including fuzzy-TOPSIS, fuzzy-VIKOR and AHP-VIKOR. Chai et al. (2013) presented a systematic literature review of the supplier selection problems, studied using MCDA and other techniques. Govindan et al. (2013) used a fuzzy multi-criteria approach to supplier performance in sustainable supply chains. The weighting criteria for the model employs triangular fuzzy numbers to signify subjective expert preferences, followed by fuzzy TOPSIS method, to rank the suppliers. They used a hypothesised example to demonstrate the applicability of their results. Shen et al. (2013) developed a fuzzy multi-criteria approach for green supplier evaluation. They provided an application to an automotive service provider. Rostamzadeh et al. (2015) developed a quantitative evaluation model, based on fuzzy set theory and VIKOR, to evaluate green supply chain indicators. The authors presented an application of the method to laptop manufacturing in Malaysia. They ranked eco-design, green production, purchasing, recycling, transportation and warehousing as the most significant criteria. Luthra et al. (2017) developed a framework to address the issue of sustainable supplier selection on the economic, environmental and social lines using an integrated AHP-VIKOR approach. The novelty of their work consisted in combining two significant MCDA techniques; while the AHP technique computes the weights relating to the three dimensions, the VIKOR method ranks the sustainable suppliers. They validated the proposed framework using a case study of a leading automotive company in India. Pask et al. (2017) presented several sustainability indicators to assess potential investment choices for industrial ovens using fuzzy set theory and a Monte Carlo simulation incorporating uncertainty. The seven sustainability indicators hypothesised, include environment, economic and social criteria. They validated the proposed hybrid approach using a case study in the manufacturing industry.

The performance measurement of sustainable supply chains must take a multidimensional viewpoint, when optimised across the triple bottom line (TBL). Erol et al. (2011) used a fuzzy entropy and fuzzy multi-attribute utility theory to evaluate and compare the performance of supply chains using several sustainability measures. The authors developed an alert system, that enables DMs to take suitable action. They tested their model with data from a retail (grocery) supply chain in Turkey. Eltayeb et al. (2011) used data from a structured survey to assess whether green supply chain initiatives have influenced the environmental, economic, cost reduction and intangible effects of certified manufacturing companies. Their findings indicated that the eco-design has positive effects on all four outcomes; the reverse logistics has significant positive effects on cost reduction, but green purchasing has no positive effect on any outcomes. Their work clearly emphasises the role of design, reuse and recycle as important criteria in product development and manufacturing. The authors also referred to previously published work to confirm the intrinsic importance of green initiatives to a firm. Rodger and George (2017) developed a model balancing economic, environmental and social criteria for natural gas supply chain sustainability, mitigating cyber security risks. The authors use a fuzzy integrated linguistic operator weighted average to balance the aspects of TBL, and develop a sustainability maximisation multi-criteria model.

The remanufacturing and recycling offer enormous economic and cost saving opportunities, but require careful consideration of environmental aspects. Jiang et al. (2011) developed a multi-criteria decision making model to select remanufacturing technology, using AHP with six criteria, spanning economic and environmental aspects. The authors presented a numerical application of the model to remanufacture the engine control valve.

In the construction industry, sustainable practice is not restricted to buildings and industries. Santos et al. (2017) presented a model to determine an order of preference for alternative scenarios using TOPSIS for sustainable pavement management. They used a lifecycle costing–assessment (LCC–LCA) approach to optimise material selection and application timings in cases of conflicting objectives. The main advantage of this approach is that, it jointly considers economic, environmental and recycling criteria for sustainable pavement solutions.

In summary, the hybrid techniques combining MCDA techniques and fuzzy based models have gained popularity in the research community, because of their ability to incorporate random choices. Different options are used to model multi-criteria problems in manufacturing, supply chain and logistics and transportation management.

4.5 Emissions, remediation and abatement strategies

The major opportunities for sustainability arise in developing amenable strategies for reducing emissions and abatement. Several authors have used combinations of multi-criteria techniques, including AHP, TOPSIS and ELECTRE. The most cited papers in the area of emissions, remediation and abatement strategies are as follows.

Khan et al. (2004) developed a lifecycle assessment index as an alternative to LCA, incorporating environmental sustainability for product and process evaluation and decision-making. They developed an AHP model to derive the relative importance of different factors namely, environment, health and safety, cost and socio-political and technical feasibility. They considered several criteria within each factor, and presented a numerical validation to evaluate three power generation sources. Macleod et al. (2007) surveyed the use of MCDA approaches to support integrated decision making for catchment management. They argued for the integration of spatial technologies, such as GIS, combined with MCDA.

Ng et al. (2013) analysed existing building environmental assessment models for evaluating operational carbon emissions. They consider the weighting of energy efficiency and emission levels across various environmental performance indicators. Their conclusions highlight the need for greater transparency in auditing and benchmarking various building assessment models.

An et al. (2017) developed a methodology for assessing the sustainability of four technologies used to mitigate the environmental effects of groundwater damage. They used an AHP method to determine relative weights of competing technologies with respect to eight criteria. They also used ELECTRE to rank the alternatives with regard to sustainability performance. Onu et al. (2017) applied a fuzzy TOPSIS approach to select the sustainable acid rain control methods, considering economic, environmental, social, technical and institutional criteria. The advantage of using TOPSIS over other MCDA techniques lies in its ease of use and ability to handle quantitative and qualitative data. The model indicates that non-emitting energy sources are the ideal technology solution, in addition to pollution abatement devices. Wang et al. (2017) used an MCDA framework to analyse the impact of air pollution on socio-economic development. They proposed a novel TOPSIS method to evaluate the effect of major air pollutants (SO₂, NO₂, O₃, CO and fine particulate matter 2.5 and 10) on economic development. They demonstrated the method, with a case study of Wuhan City in China, for the years 1996 to 2015.

4.6 Policy planning and sustainability

Today, many international institutions and governments are seeking a balance between the environment, society and the economy. The policymakers can use various sustainability assessment methods and multi-dimensional frameworks, based on the interactions and trade-offs between economic, energy and environmental indicators (the so-called E3). However, energy economics researchers have been studying the relationships between energy consumption, economic growth and the environment with inconsistent results. In the last decade, researchers have focused on the development of adequate quantitative models for environmental policy analysis, to understand the effects of environmental policies. In this area, we find many MCDA applications. For instance, Oliveira and Antunes (2012) assess the trade-offs between maximising of GDP and employment levels, and minimising of energy imports and environmental impact. Henriques and Antunes (2012) used a multi-objective linear programming model, based on input–output analysis, to discuss the influence of the measures adopted by the Portuguese government on economic growth, social wellbeing, energy consumption, and their impact on the environment. San Cristóbal (2012) develops a GP model based on an environmental/input–output linear programming model, and applies it to the Spanish economy. Jayaraman et al. (2015a, b) proposed a weighted GP model, that integrates efficient resource allocation to achieve simultaneously sustainability related goals for GDP growth, electricity consumption and green house gas (GHG) emissions in the United Arab Emirates. Expanding the scope of their research, Jayaraman et al. (2017a) developed a weighted GP model for sustainability planning for Gulf Cooperation Countries. Jayaraman et al. (2017b, c) studied a fuzzy GP application for efficient resource allocation to achieve sustainability related goals, and presented a scenario based stochastic GP model for sustainability planning. They apply both fuzzy and stochastic variants of the models to the United Arab Emirates.

The sustainability can be addressed at different geographical levels. For instance Graymore et al. (2009) introduced a hybrid model using GIS and MCDA to guide regional sustainability; they pointed out how MCDA can bring together sustainability criteria from the three pillars—social, economic and environmental, to provide an integrated sustainability assessment for the Glenelg Hopkins Catchment Management Authority area, in Victoria (Australia). More recently, Tan et al. (2017) pointed out that, the fuzzy logic theory has been widely used for sustainability assessment. They introduced the adaptive neuro-fuzzy inference system (ANFIS) approach for country level sustainability assessment. These membership functions and fuzzy rules are generated from 128 training samples. Of the three different types of non-linear membership functions employed, they mentioned that the Gaussian membership function is the best for country sustainability assessment.

4.7 Tourism and events management

Environmental sustainability in tourism has attracted attention recently in the last decade; particularly, because this is one of the most dynamic industries in many countries. In this area, the MCDA models are mainly used to design indicators enabling tourism managers to diagnose the destination’s environment, and to evaluate issues that require improvement to make tourist activities sustainable. Lozano-Oyola et al. (2012) suggested a method based on goal programming to construct composite indicators for Spanish cultural tourism destinations.

The governments have to plan sustainable and resilient policy regarding rural housing development in (mass) tourism areas near reservoirs to control ecological consequences. Jeong et al. (2016) presented a hybrid model combining GIS and MCDA with the fuzzy DEMATEL method to map rural housing suitability in (mass) tourism areas.

A sustainable approach has been applied to events management as well. The public and private agencies consider the sustainability performance (based on environmental, social and economic aspects) of events as a key issue in the context of sustainable development. Scrucca et al. (2016) presented a new quali-quantitative method (EBI 2012—an Italian acronym for “Low Impact Events”), which was developed to measure the sustainability of the 2014 World Orienteering Championship, held in Italy, taking into account all its potential impacts.

5 Discussion and main results

Our review shows that the application of MCDA tools in environmental sustainability has increased significantly over the last years. We evidenced remarkable progress in the quantity and quality of research. The most commonly studied problems in the reviewed literature were those in construction, agriculture, forestry and land use (urban architecture), farming management (25%), manufacturing, supply Chain and logistics and transportation management (24%). The discussion presented in this paper makes it clear that, in many applications, the use of both qualitative and quantitative information is fundamental, because different data typologies have to be accounted for. In particular, the qualitative information allows to incorporate informal knowledge and generate more holistic criteria/indicators. This is a significant reason why MCDA is suitable for sustainability assessment. Indeed, many authors rely on a combination of different models, from picking the right model for the right criteria, in all analysed areas.

By their nature, the MCDA models integrate multiple views of decision problems. They might improve understanding among multiple DMs, and facilitate strategies of building consensus and reaching policy compromises. Indeed, several analysed papers proposed the use of MCDA tools for consensus building and advocate the utility of this application. The existence of conflicting objectives explains the use of different decision models to prioritise and optimise DM choices; AHP, multi-objective optimisation and TOPSIS (Table 4) are the most used methods, accounting for around 20% of cases, and 24% if we include hybrid models. We confirm the findings by Pohekar and Ramachandran (2004) and Huanga et al. (2011) about the dominant position of the AHP method.

Table 4 Main models used in environmental sustainability

Other popular MCDA models include ANP, DEMATEL, ELECTRE, VIKOR and PROMETHEE (Fig. 6). Given the imprecise information commonly encountered in the sustainability scenarios, the fuzzy information is used in almost all models. Our review indicates that, future research in this area need to consider the advantages of combining complementary environmental evaluation tools, because they produce more comprehensive analyses and ensure that relevant issues are not disregarded.

Fig. 6

Distribution of MCDA models in the 7 areas

6 Conclusions

Creating a sustainable society is a challenging global task, and indeed many papers are the result of international collaboration combining different perspectives. Our review shows that the outlets are not mainly mathematical journals, but titles dealing with all aspects of environment management, or with management monitoring and assessment of ecological and environmental indicators. This indicates that the audience are heterogeneous, and corresponds to a multi stakeholder approach. However, the collaboration between universities and the industry is still limited, though the university-government collaboration is more expanded.

Many countries include environmental sustainability in their agenda (Vié et al. 2019; Jayaraman et al. 2017a, b). This trend leads to a virtuous cycle that partly explains the increasing number of papers in this area, and confirms the findings in the study by Huang et al. (2011). Nowadays, more data are available, because governments and agencies require monitoring. Moreover, as we have shown, national research funds are allocated to support the challenges the world faces over the coming decades.

This paper summarises the essential aspects of MCDA techniques and outlines various models which can be utilised to address the core issues for achieving the goals of sustainability. However, our review does have some limitations. First, the Scopus database may not include certain fields or areas, or all potential outlets. Second, we have not included the qualitative papers and those that were not published in English. However, our sample is a good representation of the current state of practice and its evolution, and it further supports the idea that, the field of MCDA includes methods able to develop a decision-analytic framework applied to environmental sustainability.

Appendix

Source title	Authors
6th International Conference on Environmental Informatics, ISEIS 2007	Monprapussorn et al. (2014)
8th International Conference on Environmental Engineering, ICEE 2011	Medineckiene et al. (2011)
Agricultural Water Management	Blanco-Gutiérrez et al. (2011)
Agronomy for Sustainable Development	Sadok et al. (2009), Colomb et al. (2013), Liu and Zhang (2013) and Wohlfender-Bühler et al. (2016)
American Journal of Environmental Sciences	Babaie-Kafaky et al. (2009)
American Water Works Association Annual Conference and Exposition (ACE 2009)	Liner and De Monsabert (2009)
Aquaculture Economics and Management	Sylvia (1997) and Martinez-Cordero and Leung (2004)
Archives of Environmental Protection	Mahmood et al. (2017)
ASABE—9th International Drainage Symposium 2010	Noory et al. (2010)
Biomass and Bioenergy	Ziolkowska (2013), Sinclair et al. (2015) and Vaidya and Mayer (2016)
Biomass Supply Chains for Bioenergy and Biorefining	Sacchelli (2016)
Building and Environment	Tiwari and Parikh (2000), Zavadskas and Antucheviciene (2007, 2010), ALwaer and Clements-Croome (2010), San-José Lombera and Garrucho Aprea (2010), Wang et al. (2010), Pons and Aguado (2012) and Samani et al. (2015)
Business Strategy and the Environment	Dou et al. (2015), Escrig-Olmedo et al. (2017) and Raut et al. (2017)
Cahiers Agricultures	Colomb and Glandières (2014)
Canadian Journal of Civil Engineering	Upadhyaya and Moore (2012)
Canadian Journal of Forest Research	Diaz-Balteiro et al. (2016)
Carpathian Journal of Earth and Environmental Sciences	Onose et al. (2015)
Clean Technologies and Environmental Policy	Dorini et al. (2011), Vinodh and Girubha (2012), Akhtar et al. (2014), Liew et al. (2014), Sedláková et al. (2015), Santos et al. (2016), Ubando et al. (2016), Kumar et al. (2017a, b), Patole et al. (2017) and Vo et al. (2017)
Computers, Environment and Urban Systems	Cao et al. (2012)
17th IEEE International Conference on Environment and Electrical Engineering, 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2017	Giacomini et al. (2017)
Critical Reviews in Environmental Science and Technology	Chang et al. (2011)
Desalination	Sa-nguanduan and Nititvattananon (2011), Grubert et al. (2014), Aliewi et al. (2017) and Lior (2017)
Desalination and Water Treatment	Afgan and Darwish (2011).
Ecological Applications	Schwenk et al. (2012)
Ecological Complexity	Graymore et al. (2009)
Ecological Economics	van Pelt (1993), Madlener and Stagl (2005), Sell et al. (2006), Thankappan et al. (2006), Gamper and Turcanu Prato (2007), Prato and Herath (2007), Parra-López et al. (2008), Erol et al. (2011) and Garmendia and Gamboa (2012)
Ecological Indicators	Mendoza and Prabhu (2004), Sattler et al. (2010), Wolfslehner and Vacik (2011), Lozano-Oyola et al. (2012), Pelzer et al. (2012), Ferretti and Pomarico (2013), Herva and Roca (2013), Cabello et al.(2014), Pinar et al. (2014), Hadian and Madani (2015), Michailidou et al. (2015), Rostamzadeh et al. (2015), Govindan et al. (2016a, b), Molinos-Senante et al. (2016), Veisi et al. (2016) and He et al. (2017)
Ecological Modelling	Bouman et al. (1998), You et al. (2014)
Ecological Modelling
ECOS 2015—28th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems	Milutinović et al. (2015)
Ecosystem Services	Nin et al. (2016)
EM: Air and Waste Management Association’s Magazine for Environmental Managers	McPhee and Powell (2011)
Energy	Bose and Anandalingam (1996), Afgan and Carvalho (2002), Lipošćak et al. (2006), Cowan et al. (2010), Jovanovic et al. (2010), Henriques and Antunes (2012), Pérez-Fortes et al. (2012), Scarpellini et al. (2013), Cartelle Barros et al. (2015), Ren et al. (2015), Zhang et al. (2015), Shakouri and Aliakbarisani (2016), Zhong et al. (2016), Büyüközkan and Karabulut (2017), Eichhorn et al. (2017) and Zhang et al. (2017)
Energy Policy	Buchholz et al. (2007), Elghali et al. (2007), Buchholz et al. (2009b), Phdungsilp (2010), Perimenis et al. (2011), San Cristóbal (2012), Hong et al. (2013), Morimoto (2013), Maxim (2014), Goldrath et al. (2015), Jayaraman et al. (2015), Klein and Whalley (2015), Moreira et al. (2015), Chanthawong and Dhakal (2016), Cai et al. (2017) and Gambelli et al. (2017)
Energy Sources, Part B: Economics, Planning and Policy	Polatidis and Haralambopoulos (2007)
Environment and Livelihoods in Tropical Coastal Zones: Managing Agriculture-Fishery-Aquaculture Conflicts	Trung et al. (2006)
Environment and Planning B: Planning and Design	Nagurney (2015)
Environment International	Li et al. (2014)
Environment Systems and Decisions	Collier et al. (2013), Pagsuyoin et al. (2015) and Collier et al. (2017).
Environment, Development and Sustainability	Latinopoulos et al. (2012), Sironen et al. (2015) and Qureshi et al. (2017)
Environmental Earth Sciences	Pourebrahim and Mokhtar (2016)
Environmental Engineering and Management Journal	De Luca et al. (2015)
Environmental Engineering Science	Hu et al. (2011) and Soltani et al. (2013)
Environmental Geology	Van Cauwenbergh et al. (2008)
Environmental Health: A Global Access Science Source	Macmillan et al. (2016)
Environmental Impact Assessment Review	Browne and Ryan (2011), Schetke et al. (2012), González et al.(2013), Ng et al.(2013), Blancas et al. (2015), Pardo-Bosch and Aguado (2016), Scrucca et al. (2016), Wellington and Lewis (2016), Sierra et al. (2017) and Tan et al. (2017)
Environmental Management	Manoliadis (2001), Brody et al. (2004), Hill et al. (2006), Liu (2007), Marttunen and Hämäläinen (2008), Vizzari and Modica (2013), Marušák et al. (2015), Uhde et al. (2015) and Seghezzo et al. (2017)
Environmental Modelling and Software	Bottero et al. (2011) and Carpani et al. (2012).
Environmental Monitoring and Assessment	Ohman et al. (2007), Pandey et al. (2012) and Azarnivand and Chitsaz (2015)
Environmental Practice	Kropp and Lein (2013)
Environmental Progress and Sustainable Energy	Dinh et al. (2009) and Kuleli Pak et al. (2017)
Environmental Science and Policy	Marques et al. (2015), Curiel-Esparza et al. (2016) and Diaz-Sarachaga et al. (2017)
Environmental Science and Pollution Research	Asif and Chen (2016), Pitz et al. (2016) and Nujoom et al. (2017)
Environmental Science and Technology	Adhitya et al. (2011), Sparrevik et al. (2012) and Zhang et al. (2014)
Environmental Science Research	Minciardi et al. (2011)
Environmental Science: Nano	Erbis et al. (2016)
European Journal of Environmental and Civil Engineering	Terracciano et al. (2015)
Forest Ecology and Management	Martins and Borges (2007) and Giménez et al. (2013)
Forest Policy and Economics	Grošelj et al. (2016).
Forest Science	Pesonen et al. (2001)
Fresenius Environmental Bulletin	Papadaki et al. (2003)
Geoingegneria Ambientale e Mineraria	Abastante et al. (2012) and Bottero et al. (2013)
Geosystem Engineering	Nuong et al. (2011)
Green Energy and Technology	Öztayşi et al. (2013)
Green Logistics and Transportation: A Sustainable Supply Chain Perspective	Bai et al. (2015) and Jabbarzadeh and Fahimnia (2015)
Habitat International	Onur and Tezer (2015) and Jeong et al. (2016)
IAHS-AISH Publication	Simonovic (2001)
Impact Assessment and Project Appraisal	White and Noble (2012)
Industrial and Engineering Chemistry Research	Singh and Lou (2006)
Informes de la Construccion	Neri et al. (2010)
Integrated Environmental Assessment and Management	von Stackelberg (2013) and De Luca et al. (2015)
International Journal of Ecology and Development	John and Sharma (2014)
International Journal of Environment and Pollution	Toman et al. (1999)
International Journal of Environmental Research and Public Health	Moretti et al. (2017)
International Journal of Environmental Science and Technology	Ezebilo and Animasaun (2011), Hu et al. (2012), Tuzkaya (2013) and Afsordegan et al. (2016)
International Journal of Environmental Technology and Management	De Montis and Nijkamp (2006), Munda (2006), Halog and Chan (2008) and Munda et al. (2009)
International Journal of Global Environmental Issues	Awasthi and Omrani (2009)
International Journal of Greenhouse Gas Control	Volkart et al. (2016)
International Journal of Life Cycle Assessment	Pineda-Henson and Culaba (2004), Güereca et al. (2007), Bachmann (2013), Kucukvar et al. (2014), Ren et al. (2015), (2017a, b) and Subramanian et al. (2017)
International Journal of Recycling of Organic Waste in Agriculture	Ganoulis (2012)
International Journal of Sustainable Built Environment	Bansal et al. (2017)
International Journal of Sustainable Development and Planning	Meney and Pantelic (2015)
International Journal of Sustainable Development and World Ecology	Miranda (2001), San-José et al. (2007), Poveda and Lipsett (2014), Salling and Pryn (2015), Ahmed et al. (2016), Demir et al. (2016), Fernandes et al. (2017) and Myllyviita et al. (2017)
International Journal of Sustainable Transportation	Keivanpour et al. (2017)
International Journal of Technology Management and Sustainable Development	Khatri and Srivastava (2016)
International Journal of Water Resources Development	Ghanbarpour et al. (2005)
ITEE 2005—2nd International ICSC Symposium on Information Technologies in Environmental Engineering, Proceedings	Filho et al. (2005)
Journal of Air Transport Management	Karaman and Akman (2017).
Journal of Cleaner Production	Khan et al. (2004), Jiang et al. (2011), Acosta-Alba et al. (2012), Castellini et al. (2012), Ajukumar and Gandhi (2013), Freitas and Magrini (2013), Govindan et al. (2013), Infante et al. (2013), Khalili and Duecker (2013), Oltean-Dumbrava et al. (2013), Yeh and Xu (2013), Liu et al. (2014), Ma and Okudan Kremer (2014), Sacchelli et al. (2014), Santoyo-Castelazo and Azapagic (2014), Ahmed Ali et al. (2015), Alikhani and Azar (2015), Biju et al.(2015), Kannegiesser et al.(2015), Kantas et al. (2015), Lam and Lai (2015),Mota et al. (2015), Pires et al. (2015), Pubule et al. (2015), Zhang and Haapala (2015), Zhao and Li (2015), Aktin and Gergin (2016), Aydiner et al. (2016), Chauhan and Singh (2016), Coskun et al. (2016), Garg and Lam (2016), How et al. (2016), Liang et al. (2016), Mangla et al. (2016), Motevali Haghighi et al. (2016), Oltean-Dumbrava et al. (2016), Onat et al. (2016), Ozcan-Deniz and Zhu (2016), Quader et al. (2016), Renatus and Geldermann (2016), Väisänen et al. (2016), Alencar et al. (2017), Arampantzi and Minis (2017), de Almeida et al. (2017), Hatami-Marbini et al. (2017), Heravi et al. (2017), Hornsby et al. (2017), Kopacz et al. (2017), Limleamthong and Guillén-Gosálbez (2017), Liu et al. (2017), Luthra et al. (2017), Madan Shankar et al. (2017), Onu et al. (2017), Pask et al. (2017), Rahmanpour and Osanloo (2017), Rodger and George (2017), Schmitt et al. (2017) and Sun et al. (2017)
Journal of Environmental Accounting and Management	Marvuglia et al. (2015) and Rochikashvili and Bongaerts (2017)
Journal of Environmental Health Science and Engineering	Ziaabadi et al. (2017)
Journal of Environmental Informatics	Ben-Awuah et al. (2012)
Journal of Environmental Management	Diaz-Balteiro and Romero (2004), Starkl and Brunner (2004), Hyde et al. (2005), Azadi et al. (2007), Zeng et al. (2007), Wolfslehner and Vacik (2008), Balana et al. (2010), Boggia and Cortina (2010), Garfì et al. (2011), Mustajoki et al. (2011), Rowley et al. (2012), Liu et al. (2013), Morio et al. (2013), Volchko et al. (2013), Waeber et al. (2013), Boggia et al. (2014), Bartke et al. (2016), Cappuyns (2016), Diaz-Balteiro et al. (2016) and Zheng et al. (2016)
Journal of Environmental Planning and Management	Tsai et al. (2013), Hossaini et al. (2015), Grilli et al. (2017), Oses et al. (2017) and Thabrew et al. (2017)
Journal of Environmental Quality	Manoliadis (2001)
Journal of Environmental Studies	Pourkhabbaz et al. (2013) and Rezaee et al. (2014)
Journal of Food, Agriculture and Environment	Del Campo Gomis et al. (2010) and Baležentiene and Užupis (2012)
Journal of Hydrology	Safavi et al. (2016)
Journal of Industrial Ecology	Kalbar et al. (2016)
Journal of Material Cycles and Waste Management	Houng and Cheng (2013)
Journal of Materials and Environmental Science	Sivaprakasam et al. (2015)
Journal of Polymers and the Environment	Colwill et al. (2012)
Journal of Sustainable Forestry	Mendoza et al. (2002) and Carabelli et al. (2007)
Journal of the American Water Resources Association	Chen and Tung (2007) and Kim and Chung (2015)
Journal of Transport Geography	Accorsi et al. (2015)
Journal of Water Resources Planning and Management	Liner and De Monsabert (2011), Riegels et al. (2013), Panagopoulos et al. (2014), Li et al. (2015) and Zhou et al. (2015)
Land Use Policy	Antunes et al. (2006), Munda (2006), La Rosa et al. (2014), Verburg et al. (2014), Bojesen et al. (2015), Nuuter et al. (2015), Ravier et al. (2015), Ottomano Palmisano et al. (2016 a, b), Chopin et al. (2017) and Osmani and Zhang (2017).
Landscape and Urban Planning	Hajkowicz and Collins (2009)
Landscape Ecology	McAlpine et al. (2010)
Management of Environmental Quality	Pati and Vrat (2010), Bottero (2015) and Stevovic et al. (2017)
Mathematical and Computational Forestry and Natural-Resource Sciences	Sironen et al. (2013)
Mechanism Design for Sustainability: Techniques and Cases	De Felice and Petrillo (2013)
Nature Environment and Pollution Technology	Mor and Ramachandran (2017)
Ocean and Coastal Management	Datta et al. (2010), Pourebrahim et al. (2014), Fetanat and Khorasaninejad (2015) and Najafinasab et al. (2015)
Polish Journal of Environmental Studies	Zarkesh et al. (2012), Mavi et al. (2013) and Gürlük and Uzel (2016)
Proceedings of Institution of Civil Engineers: Waste and Resource Management	Achillas et al. (2010)
Proceedings of the 11th International Conference on Civil, Structural and Environmental Engineering Computing, Civil-Comp 2007	Kokoli et al. (2007)
Proceedings of the 23rd International Conference on Efficiency, Cost, Optimization, Simulation, and Environmental Impact of Energy Systems (ECOS)	Bauer et al. (2010) and Oliveira and Antunes (2012)
Proceedings of the Summer School Francesco Turco	Orrù et al. (2013) and Coppola et al. (2014)
Process Safety and Environmental Protection	Stewart et al. (2003), Azapagic et al. (2013) and Mahjouri et al. (2017)
Progress in Industrial Ecology	Harpet et al. (2013) and Khalili et al. (2013)
Recycling: New Research	Minciardi et al. (2008)
Resources	Schmid et al. (2016)
Resources Policy	Chen et al. (2015) and Bui et al. (2017)
Resources, Conservation and Recycling	Pires et al. (2011), Shen et al. (2013), Antonopoulos et al. (2014), Mirabi et al. (2014), Haji Vahabzadeh et al. (2015), Mangla et al. (2015), Agrawal et al. (2016), Ameli et al. (2016), Inghels et al. (2016), An et al. (2017), Badri Ahmadi et al. (2017) and Santos et al. (2017)
Revista Brasileira de Gestao e Desenvolvimento Regional	de Carvalho et al. (2013)
Proceedings of the 13th International Symposium on River Sedimentation, ISRS 2016	Yazdandoost and Farahani (2017) and Yazdandoost and Khorami (2017)
Science of the Total Environment	Macleod et al. (2007), Katukiza et al. (2010), Sorvari and Seppälä (2010), Cucchiella et al. (2013), Chen et al. (2014), Molinos-Senante et al.(2014), Volchko et al. (2014), Behzadian and Kapelan (2015), Molinos-Senante et al. (2015), Rosén et al. (2015), Kumar et al. (2016), Ren et al. (2106) and Chhipi-Shrestha et al. (2017)
Silva Fennica	Diaz-Balteiroet al. (2011)
Soft Computing Applications for Renewable Energy and Energy Efficiency	Pilar De La Cruz et al. (2014)
Stochastic Environmental Research and Risk Assessment	Xu et al. (2014) and Wang and Chen (2015)
Sustainability	Halog and Manik (2011), Attardi et al. (2012), Cerreta and De Toro (2012) and Kropp and Lein (2012)
Sustainability (Switzerland)	Barata et al. (2014), Chen et al. (2014), Mari et al. (2014), Mitraka et al. (2014), Ortega et al. (2014), Zhao and Guo (2014), Apanavičiene et al. (2015), Canto-Perello et al. (2015), Carnero (2015), Chang et al. (2015), Chen (2015), De Mare et al. (2015), Grafakos et al. (2015), Jang et al. (2015), Jia et al. (2015), Mihai et al. (2015), Park et al. (2015), Wang et al. (2015), Zhao and Guo (2015), Cavallaro et al. (2015), Dobrovolskienė and Tamošiūnienė (2016), Dong et al. (2016),Falcone et al. (2016), Hwang et al. (2016), Li et al. (2016), Lu et al. (2016a, b), Nekhay and Arriaza (2016), Pipatprapa et al. (2016), Pons et al. (2016), Tang et al. (2016), Tsai et al. (2016), Xu et al. (2016), Zhao et al. (2016), Zhou et al. (2016), Chou et al. (2017), García et al. (2017), Grimaldi et al. (2017), Huang et al. (2017), Kluczek (2017), Lombardi et al. (2017), Scharfy et al. (2017), Wang et al. (2017a, b, c), Yu and Su (2017) and Zhou and Hu (2017)
Sustainability Impact Assessment of Land Use Changes	Paracchini et al. (2008)
Sustainability Science	Bausch et al. (2014) and Alyami et al. (2015)
Sustainability: Multi-Disciplinary Perspectives	Petrie et al. (2012)
Sustainable Practices: Concepts, Methodologies, Tools, and Applications	Grigoroudis et al. (2013)
Sustainable Production and Consumption	Atilgan and Azapagic (2016), Gumus et al. (2016) and Onat et al. (2016)
Transportation Research Part D: Transport and Environment	Bryce et al. (2014), Khoo and Teoh (2014), Rao et al. (2015), Ren and Lützen (2015), Izadikhah and Farzipoor Saen (2016) and Umer et al. (2017)
Urban Water Journal	Piratla (2016)
USDA Forest Service—General Technical Report PNW	Mendoza and Martins (2006)
Waste and Biomass Valorization	San Martin et al. (2017)
Waste Management	Costi et al. (2004), Morrissey and Browne (2004), Hung et al. (2007), Minciardi et al. (2008), Zhu and Huang (2011), Karmperis et al. (2013), Josimović et al. (2015), Wibowo and Deng (2015) and de Souza et al. (2016)
Waste Management and Research	Mirdar Harijani et al. (2017)
Water (Switzerland)	Zhang et al. (2014) and Borrego-Marín and Riesgo (2016)
Water and Environment Journal	Kalbar et al. (2013)
Water Policy	Wu et al. (2017)
Water Resources Management	Raju et al. (2000), Calizaya et al. (2010), Fasakhodi et al. (2010), Ferreira and Teegavarapu (2012), Hashemi et al. (2013), Aydin et al. (2014), Kaviani et al. (2014), Toosi and Samani (2014) and Haider et al. (2015)
Water SA	Yilmaz and Harmancioglu (2010)
Water Science and Technology	Makropoulos et al. (2006), Diaper and Sharma (2007), Moura et al. (2011) and Plakas et al. (2016)
Water Science and Technology: Water Supply	Ganoulis (2003) and Hamouda et al. (2012)
WIT Transactions on Ecology and the Environment	Bakopoulou e t al. (2007), Lacquaniti and Sala (2009), Sabokkhiz and Sabokkhiz (2010) and Guerrero et al. (2013)
World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress	Hadian et al. (2012) and Rastgoftar et al. (2012)
WSEAS Transactions on Environment and Development	Duarte et al.