Gridlock in compromise, or is multi-objective optimisation possible in renewable energy planning? A stakeholder analysis using scenario-MCDA

ABSTRACT

The energy and climate crises are driving renewable energy, but it is currently facing obstacles in leading countries. Balancing environmental, social and economic interests has become complex at the regional level due to spatial trade-offs in a contested space. To investigate stakeholder willingness to compromise on a joint ranking on wind and solar energy sites, multi-criteria decision analysis (MCDA) planning support was explored. Using a two-part stakeholder survey, four groups were identified: ‘advocates’ who were satisfied with the site ranking (66%), ‘realists’ who were willing to compromise despite previous disagreement (13%), ‘dissenters’ not accepting (35%), and ‘dogmatists’ not engaging. Planning decisions and stakeholder engagement are underpinned by distinct attitudes towards the role of (democratic) planning and sustainable development. The use of trade-off analysis can ensure transparency and trace back stakeholder interests in making planning decisions. However, decision quality factors also need to be considered to ensure a thorough planning reflection.

KEYWORDS:

• Multi-objective optimisation
• wind energy
• solar energy
• stakeholder analysis
• scenario-MCDA
• trade-offs

1. Introduction

Compromise is an essential part of decision-making that involves balancing different interests and goals, which can sometimes conflict with one another (Schneider et al. 2015; van Harreveld et al. 2009; Mayer and Freund 2022). In the context of renewable energy transition, the development of wind and solar energy often leads to competing sustainability goals and cross-disciplinary trade-offs (e.g. Bhardwaj et al. 2019; Holley et al. 2019; Tafarte and Lehmann 2020; Reitz, Goshen, and Ohlhorst 2022). While renewable energy is vital for climate protection and energy security (Wiertz, Kuhn, and Mattissek 2023; Bosch and Schmidt 2020), concerns about landscape quality, wildlife protection, health effects, land use, and monument protection provide opportunity costs to the energy transition (Deignan and Hoffman-Goetz 2015; Bunzel et al. 2019; Schuster, Bulling, and Köppel 2015; Lucchi 2023). While technological ideas for wind and solar energy are classified as viable, their implementation and development therefore often include social and political reservations (Dütschke, Schneider, and Wesche 2017; Farias and Pinheiro 2020; Firestone 2019). This situation creates what is known as a ‘wicked problem’ (Biehl et al. 2022).

1.1. Challenges in spatial planning

The energy transition has significant implications for available space and its impact on land users, potentially leading to winners and losers (cf. Weber and Köppel 2022; Becker, Moss, and Naumann 2016). The decentralisation of energy through wind and solar energy can result in the redistribution of power among institutions and bring about physical transformations, including changes in landscapes and infrastructure (Brisbois, 2019; Becker et al., 2016; Blaschke et al., 2013; Eichhorn, Tafarte, and Thrän 2017). Moreover, it is closely intertwined with local energy conflicts and national energy policies (cf. Lindvall 2023; Becker, Moss, and Naumann 2016). Spatial planning plays a critical role in reconciling the diverse interests of stakeholders and ensuring the achievement of sustainability goals by identifying suitable locations for developing renewable energy (Blotevogel, Danielzyk, and Münter 2014; Erbguth 2019; Reimer, Getimēs, and Blotevogel 2014; Seht 2021). Spatial planning aims to accommodate the interests touched upon within a given space (cf. Cowell 2010).

Multi-level spatial planning systems are common in countries like Germany, Austria, and Sweden, with different levels ranging from the state to the municipal level and the regional level serving as an intermediary (Biehl, Köppel, and Grimm 2021; Larsson, Emmelin, and Vindelstam 2014; Geissler et al. 2022). While these systems offer potential for reconciling national and local interests, they also present challenges such as inconsistent structures, inequalities, and power dynamics (Biehl, Köppel, and Grimm 2021). Planners play a critical role in moderating the planning process and balancing the formal requirements and stakeholder interests necessary for spatial zoning (Tietz 2012; Cowell and Laurentis 2021; Davies, Watret, and Gubbins 2014; Grip and Blomqvist 2021; Mostegl, Pröbstl-Haider, and Haider 2017). However, this can become complex when dealing with different alternatives and conflicting values (Weber, Biehl, and Köppel 2019; Mander 2008; Jessup 2010). Strategic environmental assessment helps analyze planning alternatives, but more alternative approaches are in demand to enhance the decision-making process (Rehhausen et al. 2018; Geißler 2013; Jiricka-Pürrer, Bösch, and Pröbstl-Haider 2018). The availability of suitable sites for wind and solar energy is often cited as a factor contributing to gridlock situations (Biehl, Köppel, and Grimm 2021; Hajto et al. 2017; Kirkegaard et al. 2022; Müller and Morton 2021; Spijkerboer et al. 2021 for offshore wind energy; Tafarte and Lehmann 2021). It suggests that stakeholder compromises are essential to support satisfaction with land use allocation (Wiehe et al. 2021; Wiehe, Haaren, and Walter 2020; Tafarte, Geiger, and Lehmann 2022; Weber and Köppel 2022).

1.2. MCDA for balancing support

Multi-criteria decision analysis (MCDA) is attributed a useful framework for comprehensive decision-making in various settings like personal decision-making and complex policy decisions in government and business (e.g. Chaouachi, Covrig, and Ardelean 2017 for offshore wind energy; Hanssen et al. 2018 for onshore wind energy; Spyridonidou et al. 2021 for solar energy; Abu Taha and Daim 2013; Huang, Keisler, and Linkov 2011; Cinelli, Coles, and Kirwan 2014; Beaudrie et al. 2021). As planning support tools, they can be used in a variety of settings and method applications (compare also Brucker, Macharis, and Verbeke 2013 for group-MCDA; Tourki, Keisler, and Linkov 2013 for scenario-MCDA; Doljak, Stanojević, and Miljanović 2021 for GIS-MCDA). MCDAs typically involve identifying a set of alternatives, criteria, and weighting the importance of each criterion for coming to a preferred solution (Wäger 2007). Thus, MCDA is credited advantages such as identifying trade-offs, transparent weighting and preference assignment, enabling stakeholder involvement, and visualising decision options (Siksnelyte et al. 2018; Kumar 2020; e.g. Huang, Keisler, and Linkov 2011; Gonzalez and Enríquez-de-Salamanca 2018; Adem Esmail and Geneletti 2018; Abu Taha and Daim 2013; Brucker, Macharis, and Verbeke 2013).

So far MCDA includes limited practical application, as in Norway (Hanssen et al. 2018) or to a limited extent in Sweden (Manolan Kandy et al. 2022; Mörtberg et al. 2019), but multiple research on. The ‘practical test’ to resolve trade-offs, i.e. compromising using MCDA in planning arenas has been subject to minor investigation. Several MCDA decision tools have been developed for stakeholder environments (e.g. Danielson, Ekenberg, and Komendantova 2018 on energy transition policies; Giuffrida 2020 on transport scenarios; Höfer, Nitzsch, and Madlener 2019 on energy transformation; Keseru, Coosemans, and Macharis 2021 on transport mobility; Lode et al. 2021 on energy communities; Lück and Nyga 2018 on water infrastructure; Macharis, Turcksin, and Lebeau 2012 on transport; te Boveldt, Keseru, and Macharis 2021 on spatial planning; Latinopoulos and Kechagia 2015 on wind energy siting). Yet few studies have focused on practical stakeholder MCDA evaluations, particularly in wind and solar energy planning (Lerche et al. 2019 on biogas sites; Marttunen et al. 2015 on procedural MCDA use). Späth et al. (2018) found that MCDA facilitated agreement and acceptance of alternative rankings in a game on transmission grids. However, Lehmann et al. (2021) were unable to find a consensus on sustainability criteria ranking among interest groups in a similar game on onshore wind energy planning. Beaudrie et al. (2021) found that MCDA improved transparency and communication but may not have led to greater satisfaction with planning outcomes. These findings contradict the benefits of MCDA for trade-off evaluation that are highlighted in the literature. MCDA might face barriers like political or institutional decisions (Gribat et al. 2017; Weber and Köppel 2022 for offshore wind energy planning), and sector-based (‘siloed’) thinking, hindering the ability to ‘think out of the box’ (Jacklin-Jarvis and Potter 2017). Practical evaluations of MCDA support in renewable energy planning and stakeholder engagement can therefore provide valuable insights into the use of MCDA and planning justifications (cf. Weber and Köppel 2022).

1.3. Motivation and research questions

Stakeholder satisfaction with planning decisions and potential side-effects in energy transition, like opportunity costs, are contentious issues that require further investigation (Maqbool, Deng, and Rashid 2020; Tafarte, Geiger, and Lehmann 2022; cf. Lennon and Scott 2017). Opportunity costs can entail those costs a landowner gives up when constructing renewable energy, such as natural resources (Albanito et al. 2022). How diverse land use interests, including those of the public and private sectors, are reconciled through consensus-based processes appears as a crucial driver of spatial planning decision related to the energy transition (Reimer and Blotevogel 2012; Pascali and Bagaini 2019). This requires finding common ground that satisfies all parties and can be a multifaceted task. MCDA-based decision support tools may be used to promote an optimisation of different objectives in spatial decision-making for renewable energy, overcoming gridlock situations. However, whether it is feasible to achieve compromise solutions remains unclear (cf. Tafarte and Lehmann 2021). To address this gap, in this paper a two-part stakeholder survey was conducted using regional multi-criteria scenarios to evaluate stakeholder acceptance of selected siting scenarios for renewable energy. The aim was to assess the extent of stakeholder’s willingness to compromise for renewable energy targets, and identify potential implementation challenges to planning support with scenario-MCDA.

The survey scenarios in the study included decentralised and land-intensive renewable technologies such as wind energy, ground-mounted solar, and agricultural photovoltaics (agri-PV), using the scenario framework developed by Weber, Steinkamp, and Reichenbach (2023). The scenario framework visually demonstrates how changes in spatial planning criteria, which were previously restricted, impact the achievement of spatial wind energy targets. This tool can assist decision-makers in identifying viable locations for transitioning to renewable energy. This survey builds thus upon current research on the significant role of social factors in energy transition, which can lead to challenging situations that are ‘wicked’ to resolve (Biehl et al. 2022). The survey explores how local and regional empowerment supports the formation of a broader consensus through diversified scope of action and alternative approaches, such as the openness of renewable energy mixes, including ground-mounted PV and wind energy. It innovates both in methodology and scope by offering a comprehensive analysis of stakeholder attitudes towards spatial planning decisions, as well as the trade-offs involved in the transition to sustainable energy, by using MCDA. The three following questions were explored:

1. Do opinions and values change using scenario-MCDA when planning for wind and solar energy under spatial energy targets?

2. Can compromises be found or does sectoral thinking persist, i.e. can the added value on the part of the stakeholders be identified?

3. Do stakeholders agree to multi-objective optimisation using scenario-MCDA as planning support tool?

2. Materials and methods

In this paper, two online surveys were used for conducting and evaluating scenario-MCDA in a two-part stakeholder analysis. A snowball sampling approach was employed to capture stakeholders’ interests on spatial siting scenarios for wind and solar energy (section 2.1). The stakeholders’ ranking of scenarios was performed using PAPRIKA aggregation method (‘Potentially All Pairwise RanKings of all possible Alternatives’) by Hansen and Ombler (2008) (section 2.2.1). A content analysis followed by a SWOT analysis (Strength-weaknesses-opportunities-threats analysis) (cf. Benzaghta et al. 2021) was carried out to evaluate the common scenario ranking and stakeholder attitudes toward MCDA methodology and compromise (section 2.2.2) (Figure 1).

Figure 1. Methodology for stakeholder analysis using an MCDA approach.

2.1. Sampling technique

2.1.1. Stakeholder selection criteria

A qualitative sampling design was employed that aimed to select stakeholders with diverse and contrasting interests in renewable energy planning through a deliberate selection process and the use of the snowball method (Flick 2009). Stakeholders were selected from the German renewable energy planning community, as recent policy adjustments have introduced new planning concepts. Specifically, spatial wind energy targets have been introduced to promote wind energy development¹ (Reutter et al. 2022; Kment 2022). Planning thus may encounter trade-offs in areas that have not yet been considered, known as ‘high hanging fruit’ areas (Hendrischke 2022; cf. Ammermann and Bernotat 2022). High-hanging fruit areas are referred to sites which may have more impacts compared to other sites, yet are only available (cf. Agardy, Di Sciara, and Christie 2011 for marine spatial planning; Orenstein et al. 2019 for spatial planning). Approached stakeholders were chosen based on the following criteria (Fachagentur Windenergie an Land 2017; compare also Carnoye and Lopes 2015):

• Stakeholders involved in the land-use planning process for renewable energy sources with a focus on wind energy, especially at the regional planning level

• Stakeholders involved in wind energy planning in general, such as research institutions, funding agencies (foundations), centres of competences

• Stakeholders are participants in planning processes as public interest groups, or planning authorities, e.g. regional planners, permitting agencies

Stakeholders were grouped into three survey groups, since it enabled to embrace potential different value systems and emotions, associated with different institutions and areas (Devine-Wright 2009; Pavlowsky, Koch, and Gliedt 2023; Kühne et al. 2022; Zaunbrecher, Arning, and Ziefle 2018; Deignan and Hoffman-Goetz 2015) (Table 1).

Table 1. Characteristics of survey groups.

Survey group no.	Characteristics
#1	Stakeholders involved in renewable energy planning were contacted through snowballing, and then randomly distributed to the survey group.
#2
#3	Stakeholders approached on an event with a flyer that contained a QR code linking to the survey. The event ‘Species Conservation and Wind Energy Planning – Quo Vadis?’, organised by the Berlin Institute of Technology in Berlin, Germany on March 21, 2023, included a variety of participants who were involved in wind energy planning (regional planning agencies, conservation organisations, ministries, research institutions, wind energy project developers, planners, and funding agencies).

2.1.2. Representativity

The sampling method aimed to achieve approximate representativeness of renewable energy stakeholder sectors. During the snowball sampling phase, at least one respondent from each target stakeholder group could be accommodated (Table 2).

Table 2. Number of respondents in the three survey groups for the first part survey. Stakeholders could also select more than one category. Therefore, the numbers do not add up to the total number of respondents. During the second part survey, participation changed slightly, but overall consultation remained.

	Survey group #1		Survey group #2		Survey group #3
	First part	Second part	First part	Second part	First part	Second part
Planning offices	2	3	3	2	3	2
Regional planning agencies	3	3	4	1	6	2
Cities and municipalities	0	0	2	2	0	0
Project developers, energy suppliers, citizen wind corporations	1	1	4	4	2	1
Environment associations	2	1	7	2	1	1
Energy associations	2	1	1	1	1	0
Forest associations	0	0	0	1	0	0
Landscape and tourism associations	0	0	1	0	0	0
Forestry authority and state forestry offices	1	1	0	0	0	0
Nature conservation agencies and state environmental agencies	4	5	1	1	3	1
Permitting agencies	0	0	0	0	0	1
Research	2	1	5	1	2	0
Funding agencies (foundations)	2	2	0	2	1	1
Centres of Competence	1	1	2	1	1	1
Other	0	1	4	2	0	0
Number of participated stakeholders	18 (100%)	20 (111%)	26 (100%)	20 (77%)	17 (100%)	10 (59%)
Sum of participated stakeholders (first-part survey)	61 (100%)
Sum of participated stakeholders (second-part survey)	50 (82%)

2.2. Two-part online survey using scenario-MCDA

A two-part online survey was used to inquire about stakeholder preferences for energy target achievement in renewable energy siting (section 2.2.1) and then to evaluate the respective results and willingness to compromise (section 2.2.2).

2.2.1. First-part online-survey

2.2.1.1. Multi-criteria scenario selection

In the first part survey, a MCDA ranking of scenarios for wind and solar energy planning was carried out. The scenarios and respective criteria for ranking were derived from a scenario framework by Weber et al. (2023) on a regional case in Germany (compare section 1.1). The scenario framework was found suitable as, first, it illustrates how spatial planning criteria affect spatial wind energy targets to aid decision makers in identifying suitable sites for the energy transition. As wind energy is already well developed, planners increasingly face trade-off situations, which will also affect other countries striving for energy transition (Reitz, Goshen, and Ohlhorst 2022; cf. also Lehmann et al. 2021; Mahlooji, Gumilar, and Madani 2020; McKenna et al. 2022; as discussed in Punt 2017). Second, the case addresses the regional planning level, which plays a crucial role in coordinating land use development between federal and local authorities (Blotevogel, Danielzyk, and Münter 2014; Erbguth 2019).

Weber, Steinkamp, and Reichenbach (2023) found that achieving wind energy targets is feasible by opening up and combining a small share of previously restricted large land uses (‘high-hanging fruit’ areas) (Weber, Steinkamp, and Reichenbach 2023). Their scenario framework is established on the case where only 1.67% of the region's area was identified as suitable for wind energy, despite the requirement of designating another 0.53% of the area to meet federal targets of 2.2% for the region (cf. Regionale Planungsgemeinschaft Havelland-Fläming 2020) (Figure 2).

Figure 2. Case situation of th

e scenario framework taken from Weber, Steinkamp, and Reichenbach (2023). Identified areas for wind energy only embrace 1.67% of the region’s area, leaving a delta to meet the state-specific area targets of 2.2%, values according to Regionale Planungsgemeinschaft Havelland-Fläming (2020).

The scenario framework by Weber, Steinkamp, and Reichenbach (2023) presented an appropriate setting for assessing stakeholder compromise regarding the opening of areas for wind energy use that were formerly excluded, known as ‘high-hanging fruit’ areas. The areas represent particularly large sites and are intended to diffuse real hard conflicts between nature conservation and species protection. These were specifically those areas related to human recreation and landscape such as landscape protection areas, open spaces, nature parks, coniferous forests, and settlement buffers (Regionale Planungsgemeinschaft Havelland-Fläming 2020; Weber, Steinkamp, and Reichenbach 2023). Landscape protection areas and nature parks, which are protection areas for recreation and landscape aesthetics among others, make up a significant share of Germany’s land area, covering roughly one-third and one-fourth, respectively (Bundesamt für Naturschutz 2023a, 2023b). In addition, federal legislation has allowed the use of landscape protection areas for wind energy projects until the spatial wind energy targets are met.² Open space areas were also explored as a planning criterion to preserve visual landscape axes, and large-scale bird priority zones for species protection (Weber, Steinkamp, and Reichenbach 2023). Also, criteria for ground-mounted solar and agri-PV projects were included in the framework by Weber, Steinkamp, and Reichenbach (2023) to explore land availability for closing the wind energy target gap alternatively with solar energy (cf. Hazboun and Boudet 2020) (Table 3).

Table 3. Criteria used in this scenario-MCDA, which have been derived from the scenario framework by Weber, Steinkamp, and Reichenbach (2023). The cliparts were previously published in Weber, Steinkamp, and Reichenbach (2023).

Criterion	Explanation
Priority zones for bird species	Priority zones for bird species are designated areas that are likely to cluster frequent site-related occurrences of bird or bat species, e.g. for the red kite or the osprey (Kompetenzzentrum Naturschutz und Energiewende 2021). Priority zones may have been identified through habitat modelling, which extrapolates suitable areas for bird or bat species based on breeding sites and land use (Weber, Steinkamp, and Reichenbach 2023).
Coniferous forest	Forest areas in this assessment are coniferous stands, which are partly open to use for wind energy. Conflicting interests on developing wind energy in forests yet remain, e.g. with bird and bat conservation, and aesthetics (Bunzel et al. 2019; Enevoldsen 2016; Reers et al. 2017; van der Werf et al. 2009; Karakislak and Schneider 2023).
Landscape protection areas	Landscape protection areas are protected areas under nature conservation legislation. They are designed to preserve the general character of the landscape, including for recreation and tourism. Wind energy is not restricted until spatial energy targets are met.^5
Nature Park	Nature Parks are protected areas under nature conservation legislation, often covering large areas of landscape, which have been created through long-standing forms of landscape management. They usually combine several other categories of protection.^6 Wind energy is partly developed in nature parks (Deshaies and Herrero-Luque 2015).
Open space areas	Open space areas comprise the regionally valuable and interconnected parts of the open space (i.e. undeveloped, open areas). It is a category of planning that serves, for example, to preserve the landscape and prevent landscape fragmentation (cf. Regionale Planungsgemeinschaft Havelland-Fläming 2020).
Settlement buffers	Settlement buffers from wind turbines, which exceed the noise protection buffers, are often set by decision-makers to ensure the acceptance of wind energy by local residents (cf. Regionale Planungsgemeinschaft Havelland-Fläming 2020; Felber and Stoeglehner 2014; Langer et al. 2023).
Ground-mounted solar complements the wind energy delta	Ground-mounted photovoltaic systems are elevated modules for electricity generation that are placed in the landscape (cf. Awan et al. 2020; Beylot et al. 2014 on environmental impacts). They are often installed along motorways and railways, for example, as these sites are eligible for subsidies.^7 It is assumed that ground-mounted photovoltaic systems will be developed at these supported locations. In some federal states, regional planning also provides for ground-mounted PV systems only at these locations (Einig 2022).
Agri-PV complements the wind energy delta	Agri-PV (agricultural photovoltaics) are elevated modules installed on agricultural land that enable energy and agricultural production on the same area. For example, berries can be grown under the modules and synergy effects (shading, altered water balance) can be used (Efremov, Sanduleac, and Braga 2022; Amaducci, Yin, and Colauzzi 2018; Barron-Gafford et al. 2019).

In this survey, these criteria were used to construct scenarios that reflect different preferences for siting wind energy and show a balance of land use types that minimises the overall potential impact on the land (cf. Ram, Montibeller, and Morton 2011; Stewart et al. 2013). The scenarios used in this survey were treated as a simulated case to allow stakeholders to participate and contribute their perspectives across spatial boundaries (Table 4).

Table 4. Criteria, criteria levels and combined scenarios to only close the gap (‘delta’) for spatial wind energy target achievement of 2.2% of the regional area, on the basis on multi-criteria scenarios from Weber, Steinkamp, and Reichenbach (2023). The arrow indicates how to read the table.

Criteria and levels for closing the ‘delta’ in wind energy planning Scenarios	Bird priority zones	Coniferous forests	Landscape protection	Nature parks	Open space areas	Settlement buffers	Ground-mounted solar complements the wind energy delta	Agri-PV complements the wind energy delta
Wind energy in bird priorities zones (for the red kite, osprey)	10%	8%	0%	0%	0%	1000 m	0.31% ^c	0.76% ^c
Wind energy in coniferous forests	0%	12%	0%	0%	0%	1000 m	0.31% ^c	0.76% ^c
Wind energy in landscape protection areas	0%	8%	3%	0%	0%	1000 m	0.31% ^c	0.76% ^c
Wind energy in nature parks and landscape protection areas	0%	8%	1.5%	1%	0%	1000 m	0.31% ^c	0.76% ^c
Wind energy in open space areas	0%	8%	0%	0%	4%	1000 m	0.31% ^c	0.76% ^c
Reduced buffer to settlements and wind energy in open space areas	0%	8%	0%	0%	1.2%	800 m	0.31% ^c	0.76% ^c
Complementing wind energy with ground-mounted solar energy partially	0%	8%	0%	0%	0%	1000 m	0.56% ^a	0%
Complementing wind energy with agri-PV partially	0%	8%	0%	0%	0%	1000 m	0%	1.11% ^b
Explanations	^a 0.31% of the area to meet solar energy targets + 0.25% of the area for solar energy to complement the wind energy delta = 0.56%
	^b 0.76% of the area to meet solar energy targets by agri-PV + 0.35% of the area for agri-PV to complement the wind energy delta = 1.11%
	^c In parallel, solar energy is being develpoped in line with the development targets of the Renewable Energy Act and translated into the area required, according to Weber, Steinkamp, and Reichenbach (2023)

2.2.1.2. MCDA method ‘PAPRIKA’ for criteria weighing and aggregation

As several geospatial MCDA techniques are available (Yatsalo et al. 2016 on Decerns software for applying different MCDA approaches; Aliyu 2015 on spatial MCDAs; Malczewski and Jankowski 2020 on trends in spatial MCDAs), a choice had to be made to serve as an example analysis method for aggregating stakeholder preferences and ranking scenarios. Linkov (2023) and Giove et al. (2009) argue that different MCDA methods lead to similar conclusions when preferences are strong (compare also Huang, Keisler, and Linkov 2011). The ‘Potentially All Pairwise RanKings of all possible Alternatives’ (PAPRIKA) MCDA method by Hansen and Ombler (2008) appeared appropriate for identifying stakeholder trade-off decisions and for ranking scenarios by example. PAPRIKA is an indirect weighing approach that uses a software-based system to score and weight criteria (1000 minds 2023a). The method involves choice-based questions to determine stakeholder preferences for criteria. Two criteria are compared using software (1000 minds 2023b), with stakeholders indicating their preference for one over the other (Figure 3).

Figure 3. Indirect weighing of two criteria each using the PAPRIKA method and the software 1000 minds. Percentages indicate the percentage of land (criterion) required for wind (or solar) energy per scenario to meet the spatial wind energy target of 2.2%.

From these choices, scores and weights for criteria and scenarios are determined using linear regression.³ PAPRIKA compares all possible combinations of the criteria and generates a ranking of the alternatives. Each time a stakeholder ranks a pair of hypothetical criteria alternatives, all other pairs are automatically identified and eliminated via the logical property of transitivity.⁴ This reduces the total number of possible evaluations and makes them manageable in practice, unlike the commonly used Analytic Hierarchy Process (AHP) MCDA approach (e.g. a pairwise comparison of 7 × 7 criteria would not require 47 decisions as in AHP, but only 15, for example) (Hansen and Ombler 2008). The advantage of using indirect evaluation methods is that deciding between alternative criteria is cognitively easier to handle and easy to apply, i.e. referred to as decision paralysis (Adriatico et al. 2022; Huber et al. 2012). The PAPRIKA method has been applied in various disciplines, including the energy sector (Francis et al. 2022 on smart local energy systems; Ford et al. 2014 on energy priorities; Ford et al. 2017 on PV uptake), and environmental sectors (Carnero 2020 on waste segregation; Olde et al. 2017 on sustainable agriculture; Graff and McIntyre 2014 on restoration scenarios).

To assess the consistency of the scenario ranking, stakeholders were asked about their preferred land use for wind energy and renewable energy mix before making PAPRIKA trade-off decisions. Final questions aimed to gauge the stakeholders’ level of agreement with the ranking. Demographic information such as sector, and involvement in renewable energy were also collected (see Supplemental Materials).

2.2.2. Second-part online survey

2.2.2.1. Questionnaire

In the second part of the survey, stakeholders were reapproached and asked to evaluate the overall ranking of the different scenarios for wind and ground-mounted solar energy. Stakeholders were then asked to evaluate this compromise on ranking that had been agreed upon. The questions aimed to gather information on their attitudes, decision-making experiences, external obstacles, and the personal evaluation of the scenario-MCDA approach. Open-ended questions were used to avoid biased responses (see Supplemental Materials).

2.2.2.2. Additional trade-offs between sustainability goals

To provide stakeholders with information for the post-evaluation of the rankings, additional information on further impacted sustainability goals was given, such as ‘climate protection through CO₂ reduction potential of wind energy systems in the electricity mix (tCO₂)’, ‘reduction of CO₂ sequestration potential through forest clearance for wind energy systems in the forest (tCO₂)’, ‘dual land use under wind turbines (e.g. agriculture) (km²)’ and ‘employment potential’. Tabular data showed how parameters of the following sustainability goals evolve, especially between wind and solar energy alternatives (see Supplemental Materials).

2.3. Qualitative content analysis

2.3.1. Inductive category building

The evaluation of the open-ended questions in both parts of the survey followed a qualitative content analysis method based on Kuckartz (2019) and Mayring (2015) (compare also Kuckartz 2012; Mayring 2016). A coding system was developed to classify and summarise stakeholder responses, with themes emerging inductively (see Supplemental Materials). The approach was hermeneutic, allowing flexibility in the coding process. MAXQDA software was used for technical support in coding and analysis (VERBI Software 2023).

2.3.2. Conceptualising and SWOT analysis

The categories and codes developed were transferred to a case-category matrix to structure the content of the stakeholder responses (Kuckartz 2012, 2019). For each category and code, the narrative elements of the stakeholder responses were summarised and presented for each of the three survey groups (see Supplemental Materials). As an explicit analysis of internal and external potentials and barriers, a SWOT analysis was used to evaluate the multi-criteria scenario ranking in a structured way to assess the research questions (cf. Benzaghta et al. 2021).

3. Results

3.1. First-part survey: MCDA ranking of scenarios

3.1.1. Joint stakeholder ranking across all survey groups

For each of the three stakeholder survey groups, a ranking was developed. It displays which spatial criteria sets, i.e. scenarios, should be used to close the gap (‘delta’) for achieving spatial energy targets in the simulated case (section 2.2.1) (Figure 4).

Figure 4. Ranking of scenarios and preference values for scenarios for the three survey groups. The lower the preference value, the more is the preference for the scenario.

The three survey groups display a similar ranking of which scenarios would be preferred. The scenarios of allowing ‘wind energy at 4% in open space areas’, followed by allowing ‘wind energy in nature parks (1%) and landscape protection areas (1.5%)’, and finally ‘complementing the wind energy targets with agri-PV’ were ranked first, second and third place by respondents in survey group #1. Respondents in survey groups #2 and #3 consider allowing ‘wind energy in nature parks (1%) and landscape protection areas (1.5%)’ to be the first choice. Allowing ‘wind energy at 3% in landscape protection areas’ is also ranked second by both groups, while allowing ‘wind energy at 4% in open space areas’ is ranked third.

In general, however, the preference value for all scenarios within the respective groups surveyed is between 10% and about 30%. The preference value indicates the weighting within the ranking. The lower the preference score, the higher the weighting of the scenario. No scenario achieved a very high preference score compared to the other scenarios. This particularly reflects divided stakeholder interests (see Supplemental Materials for criteria values).

3.1.2. Consistency check of individual criteria and renewable energy preferences

Pre-screening questions on demographics, and preferred criteria for spatial target achievement and energy mix were used for consistency checking with the overall scenario findings. In all three survey groups, more than 60% of respondents have been working in the (wind) energy sector for more than 10 years. In addition, 60%−94% of the stakeholders were involved in wind energy issues ‘very often’, depending on the survey group (see Supplemental Materials).

The findings of the consistency check indicate that most respondents favoured a certain share of criteria for wind energy development, giving lower preferences for wind energy in bird priority zones and complementing wind energy with ground-mounted solar. However, there was disagreement among stakeholders about the ‘best’ criteria, since almost every criterion was rated as important by around 25–30% of the stakeholders. Over 64% of respondents preferred coniferous forest sites for reaching spatial wind energy targets, yet this criterion ranked lower in the overall PAPRIKA ranking (compare section 3.1.1). This could be due to the fact that wind energy in forests requires more sites, leading respondents to reconsider their priorities when using the PAPRIKA ranking approach (Figure 5).

Figure 5. Preferred criteria for wind energy development across the three survey groups

The reasons for the marginal changes in criteria weighting in the consistency check can be attributed to comments made by some stakeholders on their rankings. While over 65% of stakeholders across all three groups were satisfied with their own ranking result, some respondents cited the criteria as a reason for their dissatisfaction (see Supplemental Materials). Some stakeholders in the environmental sector argued that the proposed criteria were technically unsuitable. Some even suggested canceling the survey or directing the author and the topic towards ‘suitable dictatorships’, as they perceived a pushing through of wind energy by any means. Other stakeholders highlighted certain spatial criteria such as coniferous forests, landscape protection areas, nature parks, bird priority zones, and settlement buffers, as being incompatible with wind energy. They argued that the alternatives proposed were incoherent and irresponsible. If all stakeholder preferences were combined, none of the criteria were deemed ideal for energy transition, indicating a gridlock situation. Additionally, some stakeholders rejected the rating of the ‘settlement buffers’ criterion, which was perceived incorrectly displayed in the survey. When combined with other criteria, this criterion did not provide a meaningful choice for trade-off decisions (Figure 6).

Figure 6. Acceptance of stakeholders’ own ranking of the scenarios in each survey group using PAPRIKA (left). For stakeholders indicating dissatisfaction with criteria applied, the named criteria a visualised in a word cloud in total. The bigger the word, the more often this criterion is rejected across all survey groups (right).

3.2. Second-part survey: evaluation of compromise

3.2.1. Opinion on common ranking and willingness to compromise

In the second part of the survey, stakeholders’ opinions on the common ranking and willingness to compromise were examined. Results indicate that approx. 66% of stakeholders were satisfied with the overall ranking for achieving the spatial wind energy targets in the simulated case. The ranking was perceived as representing personal preferences, such as low ranking for bird priority zones or high ranking for landscape protection areas. Stakeholders who were not satisfied were particularly critical of wind energy in landscape protection areas and nature parks (approx. 34%). Others also rather preferred wind energy in forests or closer to settlements.

Stakeholder acceptance of the ranking varied across the three survey groups. Overall, 65% of all stakeholders would accept the ranking results, i.e. developing wind energy in open space areas or landscape protection areas and nature parks (cf. section 3.1.1). The acceptance rate was not significantly different from the satisfaction with the ranking, suggesting that compromises may not have been made to a large extent. However, it is possible that stakeholders had already compromised before expressing satisfaction, leading to equivalent satisfaction and acceptance values. Inconsistencies were also found in the second survey group, with most stakeholders satisfied with the ranking, but 20% indicating they would not accept it later on (see Supplemental Materials for detailed arguments) (Figure 7).

Figure 7. Results and arguments regarding opinions on ranking and willingness to compromise. The bubbles show the percentage of agreement (green) or disagreement (orange) with the questions. The word clouds display the most frequently cited arguments. The larger the word, the more times it was mentioned.

Analyzing the detailed number of compromisers by sector (compare Table 4 below), it appears that approx. 13% of stakeholders have compromised, indicating acceptance of the ranking despite prior dissatisfaction. The need for compromise in the energy transition, democratic decision-making, and the overall goal of the energy transition were cited as reasons for the acceptance. In contrast, stakeholders who cannot compromise are mainly concerned about the impact of wind energy on landscapes, forests, and nature, at 35%. Approximately 52% of stakeholders did not feel the need to compromise as their preferences were already reflected in the ranking, and they would accept it (compare Table 4 below).

When examining the stakeholder sectors, it appears that satisfaction and acceptance mostly rely mostly on individual opinions within broader institutions, rather than being limited to a specific sector. However, a general inclination towards landscape conservation and agency institutions can be found not to compromise. Stakeholders from environmental associations and agencies and some regional planning groups showed a reluctance to compromise. Conversely, stakeholders from planning offices, funding agencies (foundations), and energy associations made compromises across survey groups (Table 5).

Table 5. Cross-table of satisfaction and acceptance of ranking across stakeholder sectors. Red frames and shaking hands symbols indicate sectors that are willing to compromise despite dissatisfaction with the ranking (12.9%). Grey frames and lightning bolts indicate sectors that value own perceptions (35.49%).

3.2.2. Perception of the process, satisfaction and transparency of weightings

Regarding the perception of the process, half of the stakeholders expressed dissatisfaction with the ranking process, raising concerns about fairness. One particular issue was the perceived lack of fair interest balancing through mean values (for constituting the common ranking), with questions arising about who performs the balancing, what constitutes balancing, and which stakeholders are involved. Stakeholders held varying opinions on this matter, with some fearing that individual groups could skew the ranking due to differing interests or strong lobbies, with no means of correcting this in a participatory or democratic manner. Others advocated for appointing stakeholders to help balance interests, while others believed that an averaged ranking was the fairest approach, allowing all stakeholders to participate democratically (at approx. 53%).

To ensure transparent planning and assessment procedures, 83% of respondents considered communicated ex post-weighting to be desirable, such as by planning authorities after stakeholder participation. There was also disagreement about whether stakeholders felt better perceived in the planning process by employing the scenario ranking, with half agreeing.

Yet, stakeholders from the first and third stakeholder groups, in particular, saw the approach as too complex for them to contribute fully, whereas others felt differently, especially stakeholders from the second group. Opportunities for participation and influence of the planning process were identified for the latter, especially concerning concerns about whether the current statements to plans were adequately addressed by agencies. Others saw the statements as sufficient, with no further opportunities for influence (see Supplemental Materials) (Figure 8).

Figure 8. Results and arguments regarding perception of the process, satisfaction and transparency. The bubbles show the percentage of agreement (green) or disagreement (orange) with the questions. The word clouds display the most frequently cited arguments. The larger the word, the more times it was mentioned.

3.2.3. External obstacles and practicability

When asked about stakeholders’ openness to scenario ranking in planning practice, a mixed picture emerged, with 50% of all respondents agreeing. This finding suggests that the readiness for such an approach depends on the composition of stakeholder groups. While planning offices, energy associations, and research could theoretically envision testing the scenario ranking in practice, regional planning authorities appeared to have a more critical attitude. Environmental agencies were more receptive to scenario ranking, while environmental associations tended to disagree but did not reject the approach outright. Proponents from different groups pointed to their positive experiences with exchange processes between stakeholders and the possibility of participation in decision-making processes. This is linked to the hope of promoting acceptance and taking the interests of as many parties as possible into account. In particular, scenario ranking was well-accepted when used only as a decision-making support. However, critics of scenario ranking saw obstacles to the integration of such an instrument into current practice, with 47% considering the current approach of participation through statements to be sufficient. Some stakeholders rejected the further development of wind energy and therefore also opposed tools that might help identify possible solutions (Table 6).

Table 6. Cross-table on whether stakeholders imagine the scenario process as part of a real planning process. Green frames indicate a preference for scenario processes within sector groups. Orange frames indicate disapproval.

Opinions regarding gaining information through scenario ranking were mixed, with 53% agreeing. While some stakeholders emphasised that the ranking made them reconsider their own opinions and that the alternatives were presented transparently, others found the opposite to be true. The scenarios were perceived as unrealistic and did not provide new insights for decision-making.

When stakeholders evaluated the scenario approach, the strengths of such a tool for solution-focused and transparent negotiation of alternatives were highlighted on the one hand. Stakeholders saw increased opportunities for participation and workable compromises. The approach was perceived as simple and clear, although more knowledge about the criteria used would be needed to arrive at intuitive decisions. On the other hand, therefore, some stakeholders might have also perceived scenario ranking as too complex. The possibility of integrating such a procedure into current planning practice was considered low by critics. Others found it problematic that the ranking did not result in a clear majority in favour of a scenario, and hence, further discussion would be necessary (Figure 9).

Figure 9. Results and arguments regarding external obstacles and practicability. The bubbles show the percentage of agreement (green) or disagreement (orange) with the questions. The word clouds display the most frequently cited arguments. The larger the word, the more times it was mentioned.

3.2.4. SWOT analysis and preliminary conclusion

Using the SWOT analysis, the main argumentation patterns regarding the evaluation of the scenario ranking approach as a planning support tool are visualised. It demonstrates that the valuation of such an approach is split and that the argumentation patterns contradict each other. This reflects differing and opposing viewpoints on planning processes and the role of negotiation within them (Table 7).

Table 7. SWOT analysis and patterns of argumentations, indicating four stakeholder groups toward compromise.

SWOT on scenario-MCDA
Internal analysis	Strength ⇒ Satisfied with overall ranking when own preferences are met ⇒ Compromise is accepted for the higher good of energy transition as long participants are involved ⇒ Compromise is accepted as a democratic decision (legitimacy of decisions) ⇒ Discussing concerns through personal engagement and participation ⇒ Knowledge support and transparency of the planning process ⇒ Awareness of the need for compromise solutions ⇒ Rethinking own opinions ⇒ Solution-oriented approach	Weaknesses ⇒ Not satisfied with overall ranking when own preferences are not met ⇒ Compromise is not accepted as long preferences are not included ⇒ Legitimacy of decision-making is unclear, democratic decisions are not best ⇒ Target scenarios must be defined by planning authorities ⇒ No new knowledge is derived ⇒ No will for engagement as discussions are not meaningful and preferences are not met ⇒ Compromises are unlikely, results are not comprehensible ⇒ Alternatives are only compromises, no good solutions
External analysis	Opportunities ⇒ Simplicity of the approach ⇒ Limited choice makes the subject tangible ⇒ Time is manageable ⇒ Alternative assessment and balancing trade-offs transparently ⇒ Decision-making support tool ⇒ All stakeholders need to participate ⇒ Allows to influence planning in terms of conservation	Threats ⇒ Complexity reduces applicability, knowledge is needed ⇒ Time restrictions ⇒ No ‘problem awareness’ as conservation is considered as non-compromising ⇒ Too little expertise in planning processes ⇒ Mix of methods needed ⇒ Minorities are given minor weight in ranking ⇒ Legitimacy of negotiators is needed ⇒ Current planning is sufficient ⇒ No room in practice for ranking ⇒ No clear majority emerges in alternatives, leaving a range of possibilities

The share of arguments towards scenario ranking and compromise is however not always equal. Based on the stakeholder analysis and SWOT analysis, four distinct groups emerge based on the arguments presented. These groups cannot be categorised necessarily by sector but rather by their stance on compromise and democratic decision-making across sectors. The four groups are:

1. ‘The advocates’ (approximately two-thirds of stakeholders) (The Britannica Dictionary 2023a): A majority agrees with the scenarios to close the energy target gap by opening large landscape categories. Advocates support a course of action.

2. ‘The realists’ (19% of stakeholders) (The Britannica Dictionary 2023d): A small minority suggests a willingness to compromise, although they have previously rated the ranking results critically. Stakeholders prioritise democratic decision-making and the pursuit of the ultimate goal of energy transition while evaluating scenarios transparently and involving participation.

3. ‘The dissenters’ (approximately 35% of stakeholders) (The Britannica Dictionary 2023b): A minority lacks confidence in democratic decision-making and is unwilling to compromise unless their personal preferences are met. They cannot see any value of scenario assessment unless it aligns with their personal values.

4. ‘The dogmatists’ (The Britannica Dictionary 2023c): Another group is critical of the further development of renewable energy as it may impact the landscape and is not prepared to discuss possible solutions. Stakeholders did not take part in the survey, thus cannot be quantified.

The scenario ranking approach is viewed positively by the first and second group as it can help them achieve a workable compromise, rethink values, and reconcile multiple goals. For the third group, landscape and nature conservation are more important, leading to the rejection of wind energy as an additional influence due to the perceived lack of political control in conservation. The willingness to compromise or even to engage, as in the fourth group, is therefore low. At the interface between the groups, some stakeholders appear to believe that ‘undemocratic’ decision-making is the only solution to keep the impact of renewable energy on the landscape low. Conversely, others fear that participatory and democratically strong groups may prevent the development of wind energy, hindering the achievement of energy targets.

4. Discussion

In the following, the results are discussed in terms of change in values using scenario-MCDA (section 4.1), willingness to compromise (section 4.2), and agreement with multi-objective optimisation (section 4.3).

4.1. Change in values using scenario-MCDA and attitude to compromise

The survey results highlight the challenges surrounding renewable energy site selection, particularly when balancing competing goals and values such as placing wind energy in previously restricted areas to reach energy targets (Lennon and Scott 2017; Salet 2021; Biehl et al. 2022; Heldeweg 2017; Reitz, Goshen, and Ohlhorst 2022; Skea et al. 2021). To aid decision-making, scenario-MCDA appeared moderately effective in changing stakeholders’ perspectives concerning renewable energy sites and led to reduced potential opportunity costs (cf. also Beaudrie et al. 2021). For example, stakeholders were more open to the idea of wind energy in forests and the significant spatial effects that they can have, compared to other areas (section 3.1). Müller, Flacke, and Buchecker (2022) indicate that there are no different value systems distributed regionally, which is also suggested by this survey. Johnson, Bell, and Teisl (2016) found that scenarios helped to engage in land use planning due to perceived self-efficacy.

Some stakeholders, however, were not receptive to address ‘high-hanging fruit’ areas, though criteria were selected to exclude even stricter requirements for nature and species protection, in order to keep them free from wind energy. This may indicate a risk of dogmatism and a tendency to avoid opposing viewpoints (Battaly 2018). Therefore, the quality decision-making, also when using MCDA, may depend on stakeholders’ knowledge, social norms, and moral obligations. The findings suggest that the key to discussing values is having a corresponding, i.e. willing mindset to the topic ahead, such as towards the energy transition (cf. Hojnik et al. 2021 on willingness to pay for green energy). Scenario-MCDA can only succeed in supporting and encouraging stakeholders if they are willing to acknowledge opposing viewpoints. For a subset of the environmental community, this willingness seems to be no longer the case. This may be due to the perceived lack of overall landscape and nature conservation efforts in Europe (Bloise, Wenzelburger, and Siewert 2022; Rada et al. 2019; Markl-Hummel and Geldermann 2014). Therefore, to avoid biodiversity concerns falling on the developers of renewable energy, integrated approaches to conservation efforts may need to be developed for more effective solutions (Maxwell et al. 2020; Göttert and Starik 2022; Bundesministerium für Naturschutz und Verbraucherschutz 2023 on species aid programmes). Islar and Busch (2016) found that supporting the local focus, i.e. the cohesion and interests of the community, could increase willingness to embrace renewable energy. Effective methods could include financial compensation for opportunity costs (Mundaca, Busch, and Schwer 2018). Whether a financial compensation offered for landscape protection to stakeholders is found adequate, however, also needs to be assessed (Knauf 2022).

4.2. Attitude to compromise

The survey results suggest that there is no single optimal solution in the energy transition, but rather a compromise among stakeholder values needed (Tafarte and Lehmann 2021; Komendantova and Neumueller 2020). The respective interpretation of the role of the decision-making process, influenced by both democratic and anti-democratic elements, affected attitudes towards compromise (cf. Lane 2003; Müller, Flacke, and Buchecker 2022; Slaev et al. 2019; Hübscher 2022; Brody 2003; Pandeya and Shrestha 2016). Decision-makers must manage planning while integrating pluralistic values objectively, selecting the right stakeholders and ensuring their inclusion (Cinque, Sjölander-Lindqvist, and Sandström 2022). Integrating different values regarding renewable energy into decisions appears thus crucial for policy and decision-makers as institutional values can affect the decision-making process (Weber and Köppel 2022).

In some cases, certain stakeholders have advocated for prioritising either conservation or energy targets, leading to the exclusion of other groups. This suggests that compromise may not always be the most favourable solution for some stakeholders in a participatory decision-making setting, with implications for the scope and goals of participation (cf. Scott and O'Neill 2013; Jesuit and Williams 2017 referring to partisanship, and different world views; Sjölander-Lindqvist 2015 on river restoration).

4.3. Agreement on multi-objective optimisation

The survey found that there is a gridlock situation in achieving agreement on multiple goals among a cross-sector group, i.e. a minority of stakeholders (of approx. 35%). Planning support tools thus may not be effective in achieving a complete consensus among stakeholders, as anything that contradicts their perception could be rejected. It highlights the recent political efforts for (high-level) regulation to implement energy goals at lower scales (such as in Germany, Reutter et al. (2022), and Sweden, Swedish Environmental Protection Agency and Swedish Energy Agency (2021)). High-level policy incentives to foster the energy transition, however, may lead to post-political planning, where decisions are made in closed-door settings (Gribat et al. 2017) and stakeholder dissatisfaction may result (Weber and Köppel 2022). While MCDA may counter this risk by starting planning from competing societal interests, i.e. trade-offs, it can also lead to a more agnostic planning approach that recognises different values and realities (cf. Roskamm 2015; Sjölander-Lindqvist and Sandström 2019). As a form of participatory approach from the bottom up, MCDA could at least support the majority of stakeholders negotiating interests that can be translated into policy. Thus, MCDA may support bridging high-level energy goals and on-the-ground realities, promoting a more inclusive process and providing planning justifications (cf. Gribat et al. 2017).

While participation is seen as a superior solution strategy for social problems (Wolff 2022; Klöti 2016), the survey's findings suggest also that there are challenges with implementing it in practice. These challenges can arise when, e.g. goals are not achieved, or the process is dominated by conflict instead of consensus (Klöti 2016). The survey found that some (environmental) stakeholders view engagement as a tool for political elites to pursue their energy transition goals (section 2.2.2 and Supplemental Materials) (cf. Klöti 2016). To ensure the success of participatory event (Arbter 2012), a common attitude among stakeholders on values on democracy and sustainable development appears necessary (Klöti 2016). However, achieving shared worldviews may be challenging, as this survey indicates, and require a form of participation that recognises trade-offs in particular. Consensus in this sense is not necessarily sought, but rather the recognition that there is no consensus, that power relations are exposed and that decisions must be made transparently (Klöti 2016).

Decision makers using MCDA must therefore define what constitutes success when applying it, such as satisfaction with the decision of the majority, possible identification of compensation for opportunity costs, and improved understanding of viewpoints. MCDA could help provide evidence for action and information about stakeholder preferences (Wahlster et al. 2015). However, challenges remain regarding the evaluation of decision quality elements, such as stakeholder knowledge involved in the process and involvement, when applying MCDA (van der Meer et al. 2020; Pickering, Bäckstrand, and Schlosberg 2020).

4.4. Limitations

It is important to acknowledge the limitations of the survey, particularly with regard to the selection of stakeholders involved, which may impact individual attitudes toward the energy transition (cf. Buchmayr et al. 2021). However, general trends were still observed among the surveyed groups in terms of preferred scenarios, satisfaction, and acceptance of the ranking and evaluation of the scenario-MCDA. In addition, conducting the survey and scenario evaluation online may lead to more pronounced opinions due to anonymity (cf. Hwang, Kim, and Huh 2014; Rossini 2022). Response behaviour varied slightly in the second group, raising concerns over the seriousness of responses. One stakeholder from groups #1 and #3 respectively made trade-off decisions in less than two seconds, which may be considered unreliable (cf. Francis et al. 2022). Additionally, only selected scenarios were tested using the case reference (Weber, Steinkamp, and Reichenbach 2023). The willingness to compromise could possibly also change in both directions with stronger personal ties to a location, as the stakeholders also indicated that individual case constellations would be more decisive for them (Devine-Wright 2013; cf. also Buchmayr et al. 2021; Müller, Backhaus, and Buchecker 2020). The PAPRIKA-MCDA approach has its nuances, in that it requires careful consideration to ensure scenario sets provide enough data for statistical analysis, but can allow for low bias in stakeholder preference indication (Carnero 2020; Jakubczyk et al. 2022). Its inability to include criterion interactions and potential bias introduced during the ranking of criterion levels must be taken into account. Additionally, trade-off questions that are answered inattentively may compromise the accuracy of the following trade-off questions (Jakubczyk et al. 2022).

5. Conclusions

The energy, climate, and biodiversity crises are driving the demand for renewable energy, but finding suitable sites for wind and solar energy can be complex. Roadblocks arise in countries where wind and solar energy are already in place, limiting the choices to locations with potential higher impacts on landscapes (‘high-hanging-fruit’ areas). Planning decisions become complicated due to the challenges of making compromises and choosing sites. Multi-criteria decision analysis (MCDA) tools can assist in this process, but there is limited research on reconciling multiple spatial targets and stakeholder willingness to compromise on land-use allocation (‘multi-objective optimisation’). This survey assesses stakeholders’ readiness to compromise on potential wind and solar energy sites using scenario-MCDA to meet energy targets and sustainable planning objectives. The survey thus provides contributions to improving policy understanding of how best to implement energy goals at lower levels of planning, while at the same time advancing the progress of energy transitions in stakeholder-driven environments. In a first step, a scenario-MCDA ranking was performed using the PAPRIKA approach as an example among geospatial MCDA approaches (‘Potentially All Pairwise RanKings of all possible Alternatives’) (n = 61). In a second step, stakeholder acceptance of the MCDA ranking and experiences of the benefits and barriers of this approach were analyzed using qualitative content analysis (n = 50).

The scenario-MCDA ranking illustrated that preference was given to scenarios that allow for wind energy in open spaces, landscape protection and nature parks, as well as complementing targets with agri-PV to meet energy needs. However, no scenario received a very high preference, indicating strongly divided stakeholder views. It is found that 66% of stakeholders in the three survey groups were satisfied with the overall rankings as their preferences were met (‘the advocates’). Another 13% of stakeholders would compromise in the interest of democratic decision making, the higher goal of energy transition, and transparent evaluation of scenarios (‘the realists’). Overall, 63% of stakeholders were willing to discuss ranking to exchange knowledge and gain understanding. However, a third group lacked confidence in democracy and were unwilling to compromise unless their personal preferences were met at 35% (‘the dissenters’). They considered participatory discussions pointless unless their preferences came first or they had enough time. A fourth group was critical of wind energy development due to its impact on the landscape and was unwilling to discuss solutions (‘the dogmatists’).

The findings indicated that although a majority of stakeholders agree to survey landscape areas for wind energy, including those previously excluded (‘high-hanging fruit’ areas) to meet energy targets, a small cross-sector group may contribute to a gridlock situation. Environmental associations, as well as some agencies such as forestry, environmental authorities, and regional planners, had a lower level of acceptance of the scenario ranking or approach. Stakeholders from planning offices, funding agencies (foundations), and energy associations appeared more willing to compromise. Yet it was found that the valuations varied across different sectors and were shaped by personal preferences.

The diversity of perspectives on land-use allocation for wind energy and on how to find solutions or compromises among stakeholders can challenge efforts for sustainable development in spatial planning. This includes making decisions about planning criteria, identifying who should be involved and how to involve them, determining which factors need to be weighed and how the weighting should be carried out. The quality of decision-making as well as MCDA decision-support tools appears therefore dependent on the knowledge, social norms, and moral commitments of the MCDA users. The evaluation of such decision-quality elements is still ongoing in research.

While participatory decision-making elements and local or regional empowerment are often associated with ‘solution-finding’, the survey also indicated that reconciling views on democracy and sustainable development (including renewable energy mixes) is a challenging undertaking. It may require a form of participation that goes beyond complete consensus-seeking (i.e. towards agnostic planning focusing on trade-off-analysis). Utilising MCDA planning support can acknowledge trade-offs for a stakeholder majority, while also revealing power relations and enabling transparent decision-making in negotiating values surrounding contested spaces in the energy transition. Given an uncompromising minority, effective and cross-sector conservation approaches may yet be needed to ensure that renewable energy developers do not bear the burden of landscape concerns alone.

Author contributions

The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

Acknowledgements

I am grateful to all participants in the survey. A special thanks to Johann Köppel (TU Berlin) for the profound feedback on the manuscript. Thanks to Anna van den Boom for the illustrations. Thanks to the anonymous reviewers for the comments on the manuscript. This work was supported by the scholarship programme of the German Federal Foundation for the Environment (Deutsche Bundesstiftung Umwelt, DBU).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

I acknowledge support by the German Research Foundation and the Open Access Publication Fund of TU Berlin.

Notes

1 §1 (2) Onshore Wind Energy Act (WindBG).

2 §26 (3) Federal Nature Conservation Act (BNatSchG).

3 Using linear regression, each criterion level is weighted with a criterion score between 0 and 100, which corresponds to the degree of fulfillment of the criterion relative to the level. This value is multiplied by the relative importance (weight) resulting from the stakeholder decisions to obtain the preference value (%) for a criterion. Scenarios are based on different combinations of criteria and levels. Each scenario is weighted to produce a ranking. This is done by multiplying the preference value (weight) of each criterion in a scenario by a criterion score, which indicates the degree to which the scenario meets the criterion. These weighted scores per criterion are then summed to obtain a total score for each rankable alternative. For detailed mathematical calculations see Hansen and Ombler (2008).

4 A transitive relation is a binary relation in mathematics when in a set B the element a is related to the element c, if a is related to b and b is related to c, for a, b, c in B, (Cuemath 2023).

5 §26 (1) and (3) Federal Nature Conservation Law (BnatSchG).

6 §27 (1) Federal Nature Conservation Law (BnatSchG).

7 §37 (1) Renewable Energy Sources Act (EEG).