Wicked facets of the German energy transition – examples from the electricity, heating, transport, and industry sectors

Figures & data

Table 1. List of properties for wicked problems (based on Rittel and Webber 1973).

Properties of wicked problems	Description
(1) No clear definition	The formulation of the wicked problem as such is the problem. The classic approach of (A) identifying the problem and (B) finding solutions is not applicable here. Wicked problems would require problem-solvers to know all viable solutions before describing the issue in detail.
(2) No boundary lines	Wicked problems have no boundary lines, i.e. problem-solvers never know whether they are finished. Therefore, decision-makers stop problem-solving at their discretion if they run out of ‘time, money or patience’ (Rittel and Webber, 162).
(3) Better-or-worse answers	Solutions to wicked problems are not ‘true-or-false’, but ‘better-or-worse’ solutions. Formal decision-making rules do not exist, but personal bias, values and ideological or cultural constraints play a significant role in finding solutions.
(4) No test for solutions	There is neither an ultimate nor an immediate test for solving a wicked problem. The full consequences of solutions can neither be tested nor predicted, i.e. they unfold once solutions are implemented.
(5) One-shot approach	Actions, decisions and solutions are irreversible, and the consequences are usually far-reaching. Every answer to a wicked problem is, therefore, a one-shot operation. There is no carte blanche for trial-and-error solutions with unforeseen consequences, as every attempt counts.
(6) Infinite set of potential solutions	Wicked problems have no enumerable solutions (including those not even thought of). No criteria enable decision-makers to prove that all solutions to a wicked problem have been considered. Therefore, the scope of solutions and the selection of solutions is a matter of judgement.
(7) Uniqueness	‘Every wicked problem is essentially unique’ (Rittel and Webber 1973, 164). Even if situations seem similar, solutions for one problem cannot be transferred to another problem, as a characteristic, a property, or a framework condition might differ from the previous problem (Rittel 1972, 393).
(8) Causal Webs	When solving one wicked problem, a new problem may arise. Therefore, every wicked problem ‘can be viewed as a nested system of another problem’ (Brinkerhoff 2014, 333).
(9) Numerous explanations	The way a wicked problem is explained determines how the problem is solved. As views and beliefs of stakeholders involved often contrast, explanations are not given objectively, and bias prevails. ‘The analyst's ‘world view’ is the strongest determining factor in explaining a wicked problem’ (Rittel and Webber 1973, 166).
(10) Normative framing (no right to be wrong)	‘Wicked problems demand acting while displaying great resistance to change. This […] can generate […] individual risks for would-be problem solvers who may be held to have no right to be wrong yet may be morally obliged to act’ (Duckett et al. 2016, 46). Therefore, contesting the decisions and outcomes, pursuing adaptive strategies, and revising unintended faulty conclusions are always necessary.

Table 2. Overview of wickedness frameworks.

Framework	Characteristics	Primary source(s)
2-point-frame	Clusters the 10 characteristics into social capriciousness (dynamism and contestation of social goals and norms) and ecological panarchy (embeddedness and interaction of multiple systems)	Craig (2020)
	Wickedness spectrum: Degree of complexity of problem and stakeholder propensity	Alford and Head (2017),
3-point-frame	Categorising the 10 attributes into ontological claims, epistemological claims and methodological claims	Catron (1981)
	Defining characteristics: uncertainty-complexity-divergence	Head (2008), Newman and Head (2017)
	Categorising the 10 attributes into non-resolvability, multi-actor environments, and problem definition	Danken, Dribbisch, and Lange (2016)
5-point-frame	Attributes: goals, uncertainty, variables, connections, dynamics (congruent with five-dimensional operationalisations of complex problems in psychology)	Kirschke et al. (2019)
6-point-frame	Aggregation of attributes: You will not understand the problem until you have developed a solution. Wicked problems have no stopping rule. Solutions to WP are not right or wrong. Every WP is essentially unique and novel. Every solution to a WP is a ‘one-shot operation’. WP have no given alternative solutions	Tatham and Houghton (2011)
7-point-frame	Attributes: complexity, contingency, ambiguity, temporality, politicisation, and normativity (congruent with policy models and literature)	Grundmann (2017)
10-plus-4-point frame	Super-wicked problems: 10 attributes plus: time is running out; those who cause the problem also seek to provide a solution; the central authority needed to address them is weak or non-existent; irrational discounting occurs that pushes responses to the future	Lazarus (2009), Levin et al. (2012)

Table 3. Overview of selected operationalisation approaches for the wickedness concept.

Source	Application	Methods	Wickedness framework
FitzGibbon and Mensah (2012)	Climate change in Ghana	using primary data from expert interviews; ‘diagnostic and prescriptive with a qualitative analytical slant’	10-point-frame
Thollander, Palm, and Hedbrant (2019)	Energy efficiency – energy-related empirical phenomena	literature review of 19 energy-related articles mentioning the terms ‘wicked problem’	10-point-frame
Brunnengräber et al. (2014) and Brunnengräber (2019)	Nuclear waste governance	argumentative reasoning	6-point-frame and 10-point-frame
May, Jochim, and Pump (2013)	Limits of policy processing – financial crisis, climate change, health care, K-12 education, drug abuse, food safety, critical infrastructure, obesity epidemic, ocean health, terrorism, extreme events	desktop-approach	No direct link to wickedness literature, yet similar categories to Alford and Head (2017) – nature of the problem and evidence for linkages among relevant policymaking institutions
Peters (2018)	—	surveys with experts in the field of policy studies to identify wicked problems	10-point-frame
Peters and Tarpey (2019)	Policy issues: climate change, food policy, health care policy, income inequality, obesity, or poverty	expert surveys with academic public policy researchers to analyse six public policy problems	10-point-frame and super-wicked problems framework
Kirschke, Borchardt, and Newig (2017)	German water management	gradual-numerical and qualitative approach to complex problems; semi-structured expert interviews	5-point-frame
Kirschke, Zhang, and Meyer (2018)	Wicked problems in the water-soil-nexus in China	questionnaire for focus-group discussions within the author team	5-point-frame
Levin et al. (2012)	Climate change as a super-wicked problem	reasoning approach	Super-wicked problems framework
Conradie (2020)	Climate change	logical reasoning

Table 4. Generic differences (and similarities) between the four analysed case studies.

Criteria	Case 1	Case 2	Case 3	Case 4
Case study description	Decarbonising the electricity sector by installing onshore wind farms	Decarbonising the space heating and cooling sector by installing shallow geothermal energy systems	Decarbonising the transport mobility sector by transforming road mobility	Decarbonising the industry sector by transforming the German chemical sector
Problem definition	Stagnating installation of onshore wind farms, un-harmonised policy mix for wind development, highly politicised issue (heterogeneous and fragmented actors)	Little progress in increasing the share of RES in space heating and cooling	Insufficient emission reduction in the (sub)sector	No coherent and feasible decarbonisation pathway identified (decarbonisation targets are not coordinated centrally, heterogeneity of actors)
Case boundaries	German onshore wind power development	German building stock, only space heating and cooling (not industrial process heat/cold)	German transport sector with a focus on road mobility, excluding shipping, aviation, and biking	German chemical industry
Energy transition sector	Electricity	Heating/cooling	Transport	Industry
Transition phase/stage: pre-development, take-off, breakthrough, stabilisation (cf. Rotmans et al. 2001; Laes et al. 2014)	Breakthrough, on the verge of acceleration (Markard 2018; Markard, Geels, and Raven 2020)	Take-off	Take-off (early)	Take-Off (early)
Technological readiness	Technological solutions exist and are market-ready but need to be upscaled.	Proven technological solutions exist and are already used/applied.	Low-emission technologies such as electric vehicles are available and have been starting to diffuse. Decarbonising the transport sector requires changes in other technological systems (such as grids, electricity production, possibly e-fuels etc.), where upscaling is still necessary.	Some technological solutions exist but are not market-ready / up-scaleable (green hydrogen), and others are still in the R&D phase (methane pyrolysis). Few technologies are market-ready and upscaled (power-to-heat)
Spatial dimension & affected sectors of transition solutions	Public sector (federal, state, regional and municipal) Industry sector (wind energy industry) Private sector (land-owners, individuals etc.)	Building sector	Public sector, private sector, industry sector, individual level	Industry sector, company-level
Energy systems’ perspective – supply or demand or social infrastructure (cf. van Graaf and Sovacool 2020)	Energy supply infrastructure (systems of energy conversion)	Energy supply infrastructure (systems of energy conversion)	Demand infrastructure	Demand infrastructure
Analytical level: macro-, meso-, micro-level; sector, subsector, subsystem	Meso-level & subsystem (one energy transition solution within a sector)	Meso-level & subsystem (one energy transition solution within a sector)	Macro-level & entire subsector	Macro-level & entire subsector

Figure 1. Historical greenhouse gas (GHG) emissions and reduction targets in CO₂ equivalents in Germany, in total until 2050 (a) and disaggregated by sector until 2030 (b). Overall GHG reduction targets are relative to 1990 levels. Emissions from space heating and cooling are predominantly accounted for in the buildings sector (fuel combustion in residential and commercial buildings) but also occur in the energy supply sector (e.g. district heating, electrified heating and cooling). Source Bundes-Klimaschutzgesetz (KSG 2021).

Table 5. Summary of case study introductions.

Energy Transition Sector	Energy supply (electricity)	Heating/cooling	Transport	Industry
Case study	Installing onshore wind power (short: onshore wind power)	Installing shallow geothermal energy systems (short: shallow geothermal energy systems)	Transforming road mobility (short: road mobility)	Transforming the German chemical industry (short: chemical industry)
Transition targets	GHG emissions reduction of 65% compared to the 1990 baseline (466 MtCO2) Min. 80% of gross electricity from renewable energy sources by 2030 Capacity targets for onshore wind: 115 GW by 2030, 160 GW by 2040	GHG emissions reduction target of 68% in the building sector compared to the 1990 baseline (210 MtCO2) 50% renewable energy sources in the heat supply by 2030 52.8% of new residential buildings to be equipped with heat pumps in 2020 (20% ground source heat pumps)	GHG emissions reduction target of 48% compared to the 1990 baseline (164 MtCO2) GHG-neutrality until 2045	GHG emissions reduction target of 58% for industry sector compared to the 1990 baseline (284 MtCO2)
Transition status in 2021 (considering available information as of mid-2022)	GHG emissions: 247 MtCO2 23.1% share of the electricity mix (*on-and offshore) 56.1 GW cumulative installed capacity (28,230 onshore wind turbines)	GHG emissions in the building sector: 115 MtCO2 16,2%* (199,5 TWh) share of RES in the energy consumption in the sector (* space & process heating/cooling) 9% share of RES supplied by shallow geothermal energy & environmental heat	GHG emissions: 148 MtCO2 Marginal reduction of emissions levels compared to 1990 Technological progress is counteracted by increase in demand	GHG emissions: 181 MtCO2 Alternative production processes and technologies are known; first pilot projects are being tested/upscaled Regulatory framework does not favour low-carbon technologies; conventional technologies are mostly more economically feasible
Exemplary barriers	Polycentric governance increases complexity and value divergence Limited land availability & land use conflicts (military, DVOR stations) Species & nature conservation Lengthy permitting processes (bureaucracy, long communication times, litigation at all levels) Acceptance & participation (hurdles for community wind projects, no mandated procedural or financial participation) Undersubscribed volumes in tender rounds Limited repowering (only ca. 50% within designated areas) Raw materials and skills shortage Inadequately equipped administration (lack of personnel, lack of know-how)	Costly retrofitting Skills shortage Competing use of shallow underground resources (groundwater abstraction, subsurface infrastructure etc.) Groundwater ecosystem protection Adverse thermal interferences are possible in densely populated areas (thermal overexploitation) Insufficient regulatory framework Inefficient permissions of too large capacities Negative public perception	Multi-level governance (EU-level, country-level, local level) increases complexity and requires ‘second-best’ solutions A multitude of conceivable instruments (performance standards, command and control, emissions pricing, fuel taxation, subsidies) Dynamic demand for transport services A multitude of actors, information asymmetry High degree of path dependencies Public acceptance is critical for successful policy implementation. Public acceptance might hinge on unequal distribution of policy impacts (e.g. urban/rural gap)	Limited availability of renewable electricity and hydrogen Insufficient industry regulation: no mandatory decarbonisation targets, no incentives for low-carbon technologies Low technology readiness of key technologies (e.g. electrification of steam crackers, alternative production routes) High costs of alternative technologies and production processes, lacking competitiveness with current fossil-fuel-based technologies) Lack of capacities (personnel, financial, organisational) in companies Decarbonisation is not a prime concern for the companies (short-term competitiveness)

Table 6. Summary of case study analysis – examples for wickedness dimension #1 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #1 – no clear definition
Case 1: Installing onshore wind energy	TD: Technical definition is clear: more wind turbines must be installed to advance transition in the electricity sector. GD: Socio-political problem definition is less straightforward given myriad explanatory approaches, and no consensus on if, where and how many wind turbines should be installed. Defining a suitable transition pathway & policy mix is highly contested, as, e.g. explanatory approaches for stagnating development vary, incl.: policy drift & governance mismatches: Juerges, Leahy, and Newig (2018); Biehl, Köppel, and Grimm (2021); Reitz, Goshen, and Ohlhorst (2022) conflicts with conservation objectives: Wiehe et al. (2021), Weber, Biehl, and Köppel (2019) vocal opposition & citizen’s discontent: Reusswig et al. (2016), Reusswig, Komendantova, and Battaglini (2018), Hübner et al. (2019), Fachagentur Windenergie an Land (2021), Köppel et al. (2019).
Case 2: Installing shallow geothermal energy systems	TD: Technical definition is clear: more buildings have to be heated and cooled in a renewable and sustainable way to advance transition in the heating/cooling sector. GD: Problem definition is far less straightforward since political, social, ecological and economic aspects have to be considered, and a variety of stakeholders need to be involved, e.g. municipalities, regional supply companies & citizens, which all have differing interests (Brielmann et al. 2011; Hähnlein, Bayer, and Blum 2010). Defining which problem(s) to address and designing a regulatory framework to account for all aspects, e.g. cost-effectiveness and feasibility for proprietors and tenants (cf. Popovski et al. 2019) and availability of resources, is not a straightforward task.
Case 3: Transforming road mobility	TD: Technical definition is clear, and it is technologically feasible to reduce emissions in the transport sector: Various policies are conceivable or in practice, and several channels exist to accomplish sectoral targets. GD: Insecurity prevails on which policies to introduce, i.e. how to reach sectoral targets, including trade-offs and potentially distributional consequences (creating winners and losers).
Case 4: Transforming the chemical industry	TD: The problem definition is clear from a technical perspective: the chemical industry needs to be decarbonised (Geres et al. 2019; Joas et al. 2019). GD: The transformation is far more complex from a social, economic and political perspective, cf. (Bang, Rosendahl, and Böhringer 2022; Díaz et al. 2019; European Commission 2019): maintain competitiveness on a national and international level align decarbonisation pathways with other sustainability goals (like preserving biodiversity), just and inclusive transformation.

Table 7. Summary of case study analysis – examples for wickedness dimension #2 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #2 – no-stopping rule
Case 1: Installing onshore wind energy	TD: Target attainment is easy to assess (measured in cumulative installed capacity), a federal registry for wind turbines exists, and the Federal States need to report new land allocations and cumulative installation annually. GD: De-facto no-stopping rule applies: Given uncertainties about future gross electricity supply (land availability, decommissioning, repowering): Biehl, Köppel, and Grimm (2021) and future electricity demand (direct electrification in other sectors, green hydrogen, increasing/decreasing energy consumption, additional capacities due to exogenous shocks): cf. Löffler et al. (2022) Time lag of policy packages, cf. Lehmann et al. (2022), Römling (2023) and therefore uncertainty if further policy measures are required.
Case 2: Installing shallow geothermal energy systems	TD: Target attainment is easy to assess for individual buildings. GD: Deciding on a stopping rule for the overall decarbonisation pathway is far more complex: interaction between heating networks, geothermal energy, and other renewable energy sources (e.g. solar thermal) subjected to conflicts of interest continued subsidies for fossil-fuelled combined heat and cooling supply regulatory and policy uncertainties, e.g. nature conservation no specification for individual technological contributions to decarbonisation goal in the heating/cooling sector (SPD, BÜNDNIS 90/DIE GRÜNEN & FDP 2021)
Case 3: Transforming road mobility	TD/GD: Lowering transport sector emissions will require operation in a highly dynamic environment: consumer preferences are persistent (i.e. ‘sticky’) & influenced by non-monetary factors (comfort, security, habits) high degree of path dependency in the transport sector (large-scale infrastructure) transport sector transition is highly non-linear, requiring different policy instruments at different transition stages, which respond to sector-specific dynamics in the supply and demand of transport services
Case 4: Transforming the chemical industry	TD: Technical dimension seems clearly defined, stopping when the chemical industry operates carbon neutral. goal is to achieve climate neutrality through electrification and the use of biomass (Joas et al. 2019) remaining complexities: definitions of carbon neutrality, greenhouse gas neutrality, climate neutrality, and the systems’ boundaries. GD: Conflicts of interest arise, e.g. whether biomass should be used as an energy source or a feedstock for the chemical industry – both uses imply trade-offs for biodiversity conservation or food security (Bataille et al. 2018).

Table 8. Summary of case study analysis – examples for wickedness dimension #3 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #3 – Better-or-worse answers
Case 1: Installing onshore wind energy	TD: Technical choice of turbine or wind farm layout is highly complex, with only ‘better’ solutions: ‘optimal’ solutions for the technical layout and site selection cannot be identified; e.g. algorithm for determining the best wind farm layout will only achieve a locally optimum not global maximum power yield, cf. Feng and Shen (2015) GD: Diversity of values, priorities and interests from a plethora of stakeholders – preventing a ‘right’ or ‘optimal’ decision: Reitz, Goshen, and Ohlhorst (2022), Juerges, Leahy, and Newig (2020), Reusswig et al. (2016)
Case 2: Installing shallow geothermal energy systems	TD: Feasibility of shallow geothermal utilisation is easy to asses & proof of concepts for various geothermal systems exist (Pratiwi and Trutnevyte 2021; Sanner et al. 2003; Tissen et al. 2021; Todorov et al. 2020). GD: The shallow subsurface is affected by many stakeholders with different interests and perspectives (Brielmann et al. 2011; Hähnlein, Bayer, and Blum 2010) & identification, justification and prioritisation among multiple distinct subsurface aspects are complex tasks (García-Gil et al. 2020).
Case 3: Transforming road mobility	TD/GD: Technological solutions need to meet diverse requirements and user preferences from many actors: formulation of ‘optimal’ solutions depends on concepts of fairness and justice; subjected to normative assumptions, political preferences & public acceptance (Creutzig et al. 2020) any successful transformation towards low-emission mobility will create losers (and possibly winners) efficient solutions (e.g. emissions pricing) are likely to affect poorer households adversely (see additional simulation analysis in Appendix C). Policy-makers, therefore, face a difficult efficiency-equity trade-off, which might result in the enactment of less effective (and potentially unequal) policies.
Case 4: Transforming the chemical industry	TD: Uncertainty about which technology to implement for decarbonising a specific process, like hydrogen production (Wietschel et al. 2021). GD: No consensus exists about what a future chemical industry sector should look like: whether: to decrease production and implement sufficiency strategies or to count on green growth and decoupling of economic growth and carbon emissions (Eckert and Kovalevska 2021; Wachsmuth and Duscha 2019) different scenarios & transformation pathways in the scientific debate (Brandes et al. 2021; Burchardt et al. 2021; Joas et al. 2019; Luderer, Kost, and Sörgel 2021)

Table 9. Summary of case study analysis – examples for wickedness dimension #4 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #4 – No test for solutions
Case 1: Installing onshore wind energy	TD/GD: Onshore wind power and its impacts are not easily verifiable and testable (absence of ultimate tests, likelihood of unintended impacts), e.g. unintended socio-environmental and ecological impacts of onshore wind farms (Köppel et al. 2019; Wiehe et al. 2021), which are still difficult to anticipate, predict and manage unintended technical impacts and disturbance effects, e.g. on radio navigation devices (Schrader et al. 2022), which require retrofitting of devices (DFS 2023) impact mitigation requires financial investments, illustrating required trade-offs outcome, effectiveness, and acceptance of, e.g. policy and governance responses, are not verifiable
Case 2: Installing shallow geothermal energy systems	TD: Uncertainty over long-term sustainability in a priori assessments: systems reach steady state after few operational years (Pophillat et al. 2020; Vanhoudt et al. 2011), adverse thermal interferences between systems in densely populated areas can reduce efficiency of installations (Attard et al. 2020; Bloemendal, Jaxa-Rozen, and Olsthoorn 2018) GD: Long-term regulatory planning should ensure optimal and sustainable operation, yet has to deal with uncertainties: few studies on long-term environmental consequences, thus insufficient knowledge on groundwater ecosystem effects (Blum et al. 2021; Hähnlein et al. 2013) information deficit is reflected in legislation: nature and water protection laws do not consider groundwater protection at an ecosystem-level perspective (Hahn, Schweer, and Griebler 2018; Koch et al. 2021)
Case 3: Transforming road mobility	TD: Prevalence of path dependencies & long-term effects of current policies impede just/effective transformation processes, e.g.: widespread use of battery-fuelled electric vehicles requires roll-out of charging infrastructure (Schroeder and Traber 2012) shifting transport from road to rail calls for long-term planning of complex railway infrastructure achieving net-zero emissions might require different solutions than meeting intermediate sectoral goals instruments facilitating the diffusion of ‘niche’ products might prove inefficient in stages of market saturation or in times of low prices for transport fuels (Cats, Susilo, and Reimal 2017; Caulfield et al. 2022) GD: Aforementioned inefficiency implies constant evaluation of the effectiveness and efficiency of any policy mix. Each solution is highly context-specific and might create additional frictions, requiring additional measures. Testing ultimately for solutions is hardly possible.
Case 4: Transforming the chemical industry	TD/GD: This dimension carries a high level of complexity or even wickedness from both technical and governance perspectives: technologies are tested in real-life laboratories and pilot studies, uncertainties regarding their large-scale implementation remain (Joas et al. 2019); financial profitability of new technologies can only be assumed, not tested (Chiappinelli et al. 2021) the same holds for implementing economic and political measures to switch to low- or no-carbon technologies

Table 10. Summary of case study analysis – examples for wickedness dimension #5 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #5 – One-shot approach
Case 1: Installing onshore wind energy	TD: Dismantling of turbines & restoration of landscapes/habitats is possible. From a technical viewpoint, wind power development is reversible, although wind turbines reflect a long investment cycle (two decades), which could lead to sunk costs. largest parts (85–90%) can be recycled (WindEurope 2020), limiting the overall footprint installation of wind farms & technical mitigation measures for impact reduction are linked to investment risks, thus errors or faulty siting decisions reduce revenues GD: Planning and permitting are one-shot decisions, as permits can be revoked or wind farms curtailed if unforeseen impacts occur, cf. Köppel et al. (2019). Wind power development has become a publicly discussed topic (Dehler-Holland, Okoh, and Keles 2022), with broad media coverage and little room for errors.
Case 2: Installing shallow geothermal energy systems	TD: Geothermal installations for space heating and cooling are designed for more than two decades, reflecting long investment cycles in the building sector (Bloemendal, Olsthoorn, and Boons 2014; Saner et al. 2010), which leaves no room for technical planning errors. GD: Regulatory framework would have to address qualitative and quantitative changes in groundwater and ensure long-term planning certainty over several decades.
Case 3: Transforming road mobility	TD: Product lifecycles span over a decade, slowing down ambitions and constraining future opportunities to correct prior decisions if stranded assets should be avoided. GD: Infrastructure investment creates path-dependencies that create ‘lock-in’ situations (Unruh 2000), likely to inhibit any form of transformation: time-intensive planning cycles in transport sector reducing the use of a ‘hegemonial technology’ (fuel-combusting vehicles) will likely face resistance from actors who benefit from the status quo (cf. Falck, Czernich, and Koenen 2021)
Case 4: Transforming the chemical industry	TD: Narrow window of opportunity to decarbonise chemical sector with little to no margin for errors: long lifespans of technologies (e.g. steam crackers) can result in sunk costs for the next decades and prevent a low-carbon transformation of the sector (Janipour et al. 2020; Joas et al. 2019) decarbonising the complex and intertwined value chains requires addressing all aspects of the production process (Geres et al. 2019; Janipour et al. 2020; Kümmerer, Clark, and Zuin 2020) GD: The governance of industrial decarbonisation is characterised by a lot of trial-and-error-processes, e.g. ongoing reform process EU ETS (Dorsch, Flachsland, and Kornek 2020; European Commission 2021b; Joltreau and Sommerfeld 2019; Lilliestam, Patt, and Bersalli 2021) or the German EEG (Luderer, Kost, and Sörgel 2021; BMWK 2022). However, we there is no time left for more attempts at stringent policies as climate change is advancing ever faster.

Table 11. Summary of case study analysis – examples for wickedness dimension #6 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #6 – Infinite set of potential solutions
Case 1: Installing onshore wind energy	TD/GD: There are many technical solutions for transforming the electricity sector, as research continuously identifies innovative solutions, e.g. new wind turbine types or designs, mitigation measures, etc. However, in practice, new approaches are extremely limited: a domination of horizontal axis turbine design, thus limiting applicability of vertical axis or airborne wind farms by actors’ preferences, economic cost pressure and investment risks, and the current regulatory and policy framework (Raschke 2015; Schwarzenberg and Ruß 2016) current policy framework does not enable ‘energy law engineering’ (allowing innovative approaches to be tested and adapted if framework conditions change); although, in theory policies can mandate, incentivise, encourage, and could be set up in myriad ways.
Case 2: Installing shallow geothermal energy systems	TD/GD: Any technical realisation of thermal utilisation of the shallow subsurface is linked to a change in the underground thermal regime. Finding new technical solutions is thus not the key issue of the transition process, rather setting a regulatory framework to establish an acceptable middle way between a multitude of distinct interests.
Case 3: Transforming road mobility	TD: Many technical options are available to curb GHG emissions in the road transport sector. GD: How to align the preferences and perspectives of many fragmented actors (citizens, corporates, authorities) is ambiguous: interdependencies between regulatory and institutional frameworks at multiple levels of governance (local, regional, national, international), tailored, context-specific regulations owing to contemporary developments (such as fluctuations in transport fuel prices or large economic shocks).
Case 4: Transforming the chemical industry	TD: Indefinite number of solutions to decarbonise the (chemical) industry: various low- or no-carbon technologies are already available or will become available in the following years different strategies for decarbonising the operations exist; solutions range from electrifying processes, alternative feedstocks and carbon capture, utilisation and storage to the flexibilisation of energy usage (Ausfelder, Seitz, and von Roen 2018; Geres et al. 2019; Joas et al. 2019) GD: There are many solutions, although their implementation may face challenges on different levels, e.g. lacking public acceptance for carbon capture and utilisation (CCU) (Lee 2019).

Table 12. Summary of case study analysis – examples for wickedness dimension #7 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #7 – Uniqueness
Case 1: Installing onshore wind energy	TD: Technically, wind power installation cannot be considered unique, as technical solutions were adapted from aviation and shipping (Bruns et al. 2011). GD: Governing the electricity transition and onshore wind installations is unique, given the setting, policy mix, polycentric planning system, governance framework, transition pathway – double-exit strategy, and ambitious transition targets), (cf. Fuchs 2019; Goldthau and Sovacool 2012).
Case 2: Installing shallow geothermal energy systems	TD: Installations and solutions are highly space- and site-dependent, incl.: (hydro-)geological characteristics determine intensity of thermal anomaly propagation & suitable system design (Hähnlein et al. 2013), risks of pre-existing local contaminations (García-Gil et al. 2020; Possemiers, Huysmans, and Batelaan 2014) thermal interferences & anthropogenic structures (basements, underground car parks, urban surface sealing etc.) can alter thermal subsurface regime (Blum et al. 2021; Menberg et al. 2013; Tissen et al. 2019) high installation density affects systems’ performance (interference). GD: Above mentioned factors impede a simple & universal regulatory framework. Large-scale heat transition is a unique and unprecedented transformation process.
Case 3: Transforming road mobility	TD/GD: Transport sector transition hinges on complex socio-technical systems integrating dynamics in technology, social norms and subsequent demand for transportation services. highly space- and time-specific solution set: each city or municipality will likely require unique solutions; demand for transport services is likely to be more elastic (Labandeira, Labeaga, and López-Otero 2017), giving greater weight to exogenous shocks (e.g. fluctuations in fuel prices).
Case 4: Transforming the chemical industry	TD: The chemical sector has never before faced a similarly significant transition; it is unique on both a technical and a governance level. potential pioneer role, as fully decarbonised chemical industries do not exist anywhere yet (The European Chemical Industry Council 2022) chemical industry is characterised by a high degree of uniqueness, complex value chains, diverse company structures which lead to company-specific challenges, dependency on fossil-based substances like Naphtha for many production processes (Joas et al. 2019; Wesseling et al. 2017). GD: No other sector in Germany – except steel production – has a higher risk of carbon leakage (European Commission 2021). Policies have to address this challenge while still being tailored towards different companies and production chains.

Table 13. Summary of case study analysis – examples for wickedness dimension #8 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #8 – Causal webs
Case 1: Installing onshore wind energy	TD/GD: Accelerated wind power installation is symptomatic of the increased need for low-carbon energy. Wind power installations may lead to new technical and socio-political challenges, e.g.: wildlife impacts (Gartman et al. 2014; Voigt, Straka, and Fritze 2019; Warren et al. 2005) interference with radio navigation stations(Schrader et al. 2022b) social and distributional (in)justice (Köppel et al. 2019; Reitz, Goshen, and Ohlhorst 2022) land use conflicts (Biehl, Köppel, and Grimm 2021) provision of materials, personnel and logistics despite worldwide supply bottlenecks (Taylor 2022) future ‘waste legacy problem’ (Jani et al. 2022; Majewski et al. 2022): recycling rotor blades’ composite materials (Karatairi and Bischler 2020)
Case 2: Installing shallow geothermal energy systems	TD: Extensive thermal use of the shallow subsurface (i.e. high density of installed systems) can lead to detrimental thermal interference between individual systems. Lower system efficiencies are associated with higher operating costs and possibly the need for fossil auxiliary technologies (e.g. gas boilers or compression chillers), cf. Miglani, Orehounig, and Carmeliet (2018), Tissen et al. (2019). GD: Shallow geothermal utilisation may entail other trade-offs, incl.: environmental aspects (detrimental changes to groundwater ecosystem, loss of ecosystem services), cf. Blum et al. (2021), Griebler and Avramov (2015), Koch et al. (2021) conflicts of use of shallow groundwater & decreasing profitability of regional supply companies might arise when upscaling the technology
Case 3: Transforming road mobility	TD/GD: Transport systems are embedded in many other socio-economic systems, with ripple-effects from one system to another, which are difficult to predict or evaluate, e.g.: electrifying individual transport requires various scarce natural resources (lithium, cobalt or rare earth metals); resource extraction establishes links to environmental degradation and human health (Banza Lubaba Nkulu et al. 2018) but also creates local resource booms effective recycling of energy storage technologies is subject to extensive research (Harper et al. 2019) transport sector transition may affect competitiveness of industries, primarily if value-chains rely on comparatively cheap and reliable transport facilities
Case 4: Transforming the chemical industry	TD/GD: Chemical industry transition may lead to new technical and socio-political challenges, creating causal webs: increased use of biomass might entail trade-offs in other areas, e.g. biodiversity loss/food security (Bataille et al. 2018; Joas et al. 2019) potential for regional deindustrialisation & loss of competitiveness (European Commission 2021; Evans et al. 2021; Fahl et al. 2021; Johansen et al. 2021) use of intermediary technology (e.g. blue hydrogen) is readily discussed (Bataille et al. 2018; Joas et al. 2019), but could reinforce resource dependency & can be criticised in light of gas shortage socio-technical challenges (food security, deindustrialisation and resource dependency) would imply significant socio-economical risks.

Table 14. Summary of case study analysis – examples for wickedness dimension #9 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #9 – Numerous explanations
Case 1: Installing onshore wind energy	TD: The motivation for technically installing wind farms is explained with the goal to transform the energy production sector from fossil and fissile energy sources to renewables. GD: The problem of governing, planning and developing onshore wind power can be explained in numerous ways, as shown above.
Case 2: Installing shallow geothermal energy systems	TD/GD: The motivation for geothermal space heating and cooling is mainly rooted in reducing greenhouse gas emissions in the building sector (e.g. Self, Reddy, and Rosen 2013). Recently, the pressing issues of supply reliability and reduced dependence on imported natural gas and heating oil have come into focus.
Case 3: Transforming road mobility	TD/GD: Transport sector transition affects multiple fragmented actors with diverse objectives. The large solution-space and various intersections with other socio-economic domains manifest a large variety of explanations, which is exacerbated by multiple externalities. Describing socially optimal demand and supply levels for transport services is difficult, which adds substantial uncertainty to determining desirable and feasible transformation pathways.
Case 4: Transforming the chemical industry	TD: Different pathways towards net-zero GHG emissions exist, yet all are explained in a similar way (assuming a green growth perspective, arguing that decoupling economic growth and GHG emissions is possible). Different transition scenarios focus on different technologies: Burchardt et al. (2021): enhanced usage of CCS and biomass Joas et al. (2019): prioritisation of green hydrogen and electrification. GD: Various explanations about the goal of decarbonisation exist [green growth narrative or sufficiency strategies, e.g. lowering consumption (Eckert and Kovalevska 2021)]

Table 15. Summary of case study analysis – examples for wickedness dimension #10 in the four cases, incl. supporting arguments (TD: technical domain; GD: governance domain).

Case study	Examples for wickedness dimension #10 – No right to be wrong.
Case 1: Installing onshore wind energy	TD/GD: Actors are responsible for their actions and can be held accountable. Planning and permitting decisions can be challenged before (administrative) courts.
Case 2: Installing shallow geothermal energy systems	TD/GD: Both, a successful heat transition & security of supply in the building sector, and ecosystem concerns & economic profitability are highly relevant for the future. It is crucial to reconcile all aspects through coherent and comprehensive planning, thus planners and decision-makers have ‘no right to be wrong’.
Case 3: Transforming road mobility	TD/GD: Decarbonising the transport sector is a politically delicate task since it entails tremendous distributional consequences and would likely affect poorer households more heavily than wealthier households (see Annex C). Transition instruments in this sector affect many actors, which negates a ‘right to be wrong’ for political decision-makers, which might delay stringent and effective action.
Case 4: Transforming the chemical industry	TD/GD: Framing of decarbonising the chemical sector is not normative (Joas et al. 2019), as decarbonisation is only ever described as technically feasible. The current dominant discourse also displays the need for green growth on a governance level. There are other argumentative lines like sufficiency or the call for a just transition (Eckert and Kovalevska 2021).

Figure 2. Panel a) shows first-order additional costs of transport fuel carbon pricing (35 EUR/tCO₂) among German households. Y-axis shows expenditure quintiles. Expenditure quintile 1 comprises the 20% of German households with the lowest per capita expenditures. Expenditure quintile 5 comprises the 20% of German households with the highest per capita expenditures. The X-axis displays additional costs in per cent of total consumption expenditures. Whiskers represent within-quintile 5th to 95th percentiles. The rhombi represent the mean. The Grey vertical bar represents the difference between first and fifth quintiles’ average additional costs. Panel c) shows household-level expenditure shares for energy, food, goods and services over total household expenditures in Germany. The blue line indicates a polynomially fitted regression line.

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