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This article delves into the evaluation of Germany's Module 5 funding scheme, which aids companies in creating decarbonization plans. The analysis covers 175 transformation plans, revealing significant reductions in Scope 1 and 2 emissions, with Scope 3 emissions posing greater challenges. The article highlights the importance of strategic planning and the role of policy instruments in driving industrial decarbonization. It also compares Germany's approach with international policies, such as those in the United States and Switzerland. The evaluation underscores the need for more robust Scope 3 accounting and implementation tracking to ensure long-term success. By examining the effectiveness of Module 5, the article offers valuable insights into the future of corporate decarbonization efforts in Germany.
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Abstract
This paper presents the first scientific analysis of Germany’s Module 5 funding program, which supports companies in developing strategic decarbonization plans for individual or multiple sites in Germany. Introduced in 2021 as part of the federal funding scheme “Energy and Resource Efficiency in the Economy,” Module 5 focuses exclusively on planning rather than technical implementation. It supports the development of greenhouse gas (GHG) reduction pathways aligned with the GHG Protocol, covering Scope 1 (direct emissions), Scope 2 (indirect emissions from purchased energy), and optionally Scope 3 (value chain emissions). The analysis builds on data from 175 transformation plans evaluated in 2024 as part of an official program review commissioned by the Federal Ministry for Economic Affairs and Climate Action (BMWK). While the dataset and basic evaluation originate from that review, the aggregation, interpretation, and reassessment presented here were conducted independently by the authors. Findings confirm that most companies met or exceeded the program’s requirement to demonstrate a 40% reduction potential in Scope 1 and/or Scope 2 emissions over ten years, largely through photovoltaic installations, renewable electricity procurement, and process optimization. Scope 3 was addressed in approximately 35% of the plans but contributed little to overall reductions. Some companies included broader Scope 3 categories beyond travel or energy procurement, though methodological consistency varied. This study offers new insights into the evaluation of planning-based climate policy instruments. It highlights methodological limitations due to the absence of implementation tracking and provides policy recommendations regarding SME inclusion, Scope 3 integration, and ex-post verification mechanisms.
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Introduction
Germany has committed to achieving climate neutrality by 2045, as outlined in the Federal Climate Action Act (KSG, 2019/15.07.2024). A key element of the legislation is reducing greenhouse gas (GHG) emissions across all sectors. To support the transition to a decarbonized industrial sector, the "Energy and Resource Efficiency in the Economy" funding scheme was launched by the German Federal Government in 2019, providing financial support through initially four, now six, funding modules, each addressing different aspects of energy and resource efficiency in the industry.
Among international policy instruments, strategic decarbonization planning is increasingly recognized as a critical element of climate governance. The United States Department of Energy, for instance, published a sector-specific Industrial Decarbonization Roadmap in 2022, linked to large-scale implementation programs under the Inflation Reduction Act (United States Department of Energy, 2022). Switzerland has adopted a sector-wide transformation approach through its “Branchenfahrpläne” and the small and medium-sized enterprise (SME) focused initiative “EnergieSchweiz für KMU,” coordinated through the federal climate strategy (EnergieSchweiz, 2025; Federal Office for the Environment, 2023; Langfristige Klimastrategie—Ergänzung für NDC 2031–2035, 2025).
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Germany’s Module 5 complements this international trend with a distinct national approach. Introduced in 2021, it exclusively supports the conceptual planning of decarbonization efforts for either individual or multiple company sites within Germany. Unlike the other modules of the funding scheme, it does not fund the implementation of technical measures. Instead, it enables companies to develop “transformation plans” that outline GHG reduction pathways across Scope 1 (direct emissions from owned or controlled sources), Scope 2 (indirect emissions from purchased electricity, heating and cooling), and optionally Scope 3 (upstream and downstream value chain emissions).
The classification of these emissions follows the internationally recognized GHG Protocol standard, which serves as the basis for corporate climate accounting. Figure 1 illustrates the segmentation of emissions across upstream, operational, and downstream activities, aligned with the system boundaries defined in the GHG protocol.
Fig. 1
Categorization of GHG emissions across Scopes 1, 2, and 3, based on the GHG Protocol system boundaries. Own illustration based on Bhatia et al. (2011)
During the observation period (2021–2023), eligible costs under Module 5 included external consultancy, emissions data collection and analysis, stakeholder workshops, and third-party validation of transformation plans. Internal personnel costs, however, were explicitly excluded from funding eligibility. To qualify for funding, companies had to demonstrate in their plan the technical potential to reduce Scope 1 and Scope 2 emissions by at least 40% within ten years. This was not a binding implementation commitment, but a scenario-based assessment. Scope 3 reductions were encouraged but not mandatory.
To reflect differing financial capabilities, SME could receive up to 60% of eligible costs, while large enterprises (LE) could receive at up to 50%. The maximum grant amount per transformation plan was €80,000.
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While the funding amount varies depending on the size of the company, businesses who were part of the Initiative Energy Efficiency and Climate Protection Network (Initiative Energieeffizienz- und Klimaschutz-Netzwerke, IEEEKN) could apply for a 10 percentage points higher funding rate (Deutsche Energie-Agentur GmbH). The IEEEKN is a joint effort by the German Federal Government and industry associations to promote knowledge sharing, mutual support, and collaborative action among companies pursuing decarbonization and energy efficiency goals. Participating companies join regional or sector-specific networks where they define joint targets and exchange best practices.
Module 5 fills a strategic gap in Germany’s climate policy landscape. While sector-specific roadmaps (e.g., for steel, glass, and cement) provide macro-level orientation (Bundesministerium für Wirtschaft und Energie, 2020; Bundesverband Glasindustrie e.V.,
2022; Verein Deutscher Zementwerke e.V., 2020), they often lack consideration for site-specific factors, such as infrastructure limitations. Module 5 addresses this blind spot by enabling tailored decarbonization strategies at the facility or corporate level.
Despite their growing policy relevance, planning-focused instruments remain understudied in the academic literature. Most existing research has focused on implementation grants or corporate disclosure frameworks (Junod, 2024; Hettler & Graf-Vlachy, 2023), often overlooking the design and impact of conceptual funding mechanisms.
The data and methodological foundations for this study originate from the official evaluation of Module 5, commissioned by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). This includes the full set of 175 finalized transformation plans as well as the qualitative scoring framework used to assess a representative subsample. While the original evaluation focused on program performance and compliance, the present paper builds on that foundation to provide a scientific analysis. All visualizations, extended interpretations, and analytical comparisons were independently developed by the authors for academic purposes. This paper constitutes the first peer-reviewed publication based on the Module 5 dataset and offers additional insights beyond the scope of the official evaluation report.
Methodology
The evaluation process was initiated approximately one year after the allocation of funding, ensuring that companies had adequate time to develop and submit their transformation plans.
This analysis represents one component of the broader program evaluation and focuses specifically on Module 5, which was evaluated for the first time in 2024. Additional contributions presented at this conference address the other program modules and overarching evaluation results.
The analysis applied both quantitative and qualitative methods. Firstly, data from all 175 finalized transformation plans submitted between 2021 and 2023 were aggregated to assess overall decarbonization targets and structural characteristics. In a second step, a subsample of 30 transformation plans (approximately 17% of the dataset) was selected for in-depth qualitative analysis. Of these, 25 plans were randomly selected by the program administrator, the Association of the German Engineers and the Association for Electrical, Electronic & Information Technologies – Innovation + Technology (VDI/VDE-IT). The subsample was deliberately mixed across small (12), medium (2) and large (11) enterprises to assess reporting quality and patterns as it is not intended to be statistically representative. The remaining 5 plans were purposefully selected based on specific criteria: the plans with the highest and lowest projected CO₂ reductions (in percentage terms), the plan covering the highest number of locations, and the plans with the highest and lowest approved funding amounts.
Considering the random part alone (n = 25), a conservative 95% margin of error for proportions is ≈ ± 19 percentage points. We therefore use the subsample only diagnostically (e.g., reporting quality, internal consistency, methodological patterns).
Data collection
To ensure the quality and reliability of the evaluation, only transformation plans that had been officially approved, completed, and formally verified by the VDI/VDE-IT were included in the analysis. The final dataset therefore consisted exclusively of finalized plans, including validated Scope 1, 2, and 3 emissions data for both the baseline and target years. Applications that were still under review, incomplete, or required revision were excluded from the evaluation.
In addition to the specific indicators for Module 5, the following cross-program indicators were included to support comparability across modules: number of submitted applications, approval rate, regional distribution of funding, company size distribution, estimated cost-efficiency per avoided ton CO₂-eq., and process feedback from applicants via an online survey.
Quantitative assessment and indicators
For the quantitative analysis, 14 indicators were defined and grouped into five thematic categories. These indicators were selected based on their relevance to program goals and their suitability for capturing decarbonization planning effectiveness:
(1).
Program Structure and Coverage (These indicators describe the scope and structural breadth of each transformation plan):
•
Number of considered sites per funding case.
•
Share of completed transformation concepts at corporate level in Germany.
•
Share of transformation concepts receiving the IEEKN member bonus.
(2).
Emission Scope Coverage and Reduction Ambition (This group captures which GHG scopes are addressed and to what extent companies aim to reduce emissions):
•
Number of applications addressing Scope 3 GHG emissions.
•
Absolute GHG emissions in the current state.
•
Absolute GHG emissions in the target state.
•
Planned absolute emission reductions.
•
Annual Scope 1 reduction (in tons CO₂-eq.).
•
Annual Scope 2 reduction (in tons CO₂-eq.).
•
Annual Scope 3 reduction (in tons CO₂-eq.).
(3).
Sectoral Distribution (This indicator reflects how emissions reduction targets vary across different industrial sectors):
•
Distribution of relative GHG reduction targets by NACE Rev. 2 sector (2-digit level).
(4).
Effectiveness and Cost Efficiency (These indicators assess the quality and resource efficiency of the transformation planning process):
•
Specific costs of transformation concepts per ton of avoided CO₂-eq.
•
Average project duration.
•
Average number of identified measures per transformation concept.
(5).
Company Type and Funding Intensity (These indicators describe the funding dynamics in relation to company size):
•
Share of LE receiving the maximum funding amount.
•
Share of SME receiving the maximum funding amount.
Qualitative analysis of transformation plans
In addition to the quantitative analysis, a qualitative evaluation was carried out using a standardized Excel-based scoring template. Each of these categories was independently rated using a four-point scale ranging from (1) Very Good – fully transparent and well-documented, (2) Good – mostly complete with minor gaps, (3) Sufficient – significant shortcomings or unclear assumptions, to (4) Not verifiable – lacks sufficient information for proper assessment. A fifth option ("not relevant") was applied when a criterion was not applicable to the specific plan. For each main category, an average score was calculated across all sub-criteria. These four category scores were then equally weighted and combined into a final composite score per plan, where lower values indicate higher quality and transparency. No further normalization or differential weighting was applied. To improve the consistency of ratings, an initial subset of transformation plans was first reviewed individually by evaluators and then discussed collectively. This helped align expectations and ensure a shared interpretation of the scoring rubric. Evaluators were also encouraged to document notable strengths and weaknesses, including methodological inconsistencies and particularly innovative approaches. The four evaluation categories were as follows:
(1)
Baseline (Assessment of the GHG inventory’s scope, completeness, and methodological rigor):
Completeness of GHG accounting for Scope 1, 2, and 3.
Inclusion of all relevant emission sources (e.g., fuel use, electricity, travel, paper).
Methodological basis (e.g., GHG Protocol, DIN EN ISO 14064).
External verification or certification of the baseline.
Number of sites included in the inventory.
(2)
Target State (Evaluation of the clarity and ambition of future emission reduction targets):
Clarity and credibility of emission reduction targets for each scope.
Ambition level (e.g., ≥ 40% in Scope 1 und Scope 2 within ten years as required).
Breakdown of targets by emission category and site.
Methodological transparency of savings calculations.
Inclusion of expected reductions from funded energy-saving measures.
(3)
Measures to Achieve Targets (Review of proposed decarbonization actions):
Number and type of measures proposed.
Technical feasibility and economic plausibility.
Sectoral appropriateness of proposed strategies.
Whether major emission sources are adequately addressed.
Realism of implementation timelines and resource requirements.
Inclusion of cross-cutting measures (e.g., electrification, hydrogen use).
(4)
Strategic Coherence (Overall assessment of internal logic and integration):
Consistency between baseline, targets, and measures.
Clarity and logical structure of the concept.
Use of external consultants in plan development.
Participation in networks (e.g., IEEKN bonus).
Identification of specific implementation barriers.
Overall coherence and integration of decarbonization strategy
Results
This section presents the aggregated findings of the evaluation, organized in alignment with the applied methodology. It is divided into two parts consisting of a quantitative analysis of all 175 finalized and approved transformation plans, and a qualitative review of a representative sample of 30 transformation plans.
Quantitative analysis of approved transformation plans
Between November 2021 and December 2023, a total of 819 applications were submitted, of which 687 has been granted funding. The number of applications and approvals varied significantly since the start of the funding module. In 2021, only 27 applications were submitted, with just 2 approvals. The numbers increased substantially in 2022, when 431 applications were submitted, of which 332 were approved. In 2023, there were 361 applications, with 353 approvals. However, the submission of further applications and the approval process were halted due to a ruling of the German Constitutional Court regarding federal budget allocations (Judgment of the Second Senate, 2023, November 15), which resulted in a temporary freeze of approvals until February 2024 (Federal Office for Economic Affairs and Export Control, 2024).
Although these figures provide insight into the scale of the program, the evaluation focuses exclusively on 175 cases that had been fully completed and documented. The typical process for Module 5 funding begins with the submission of a funding application by the company, followed by a formal review and approval process conducted by the funding authority. On average, the time from application submission to approval ranges from two to four months. Once approved, the company develops its transformation plan, typically in collaboration with external consultants. The creation and finalization of the plan typically take between six and nine months. After completion, the transformation plan is submitted to the funding authority along with a final report and invoice documentation. Upon verification of completeness and compliance with funding requirements, the funding share is released. The final disbursement typically takes place two to three months after submission of the final documentation. Overall, the structured timeline from initial application to payment spans approximately 12 to 16 months.
The evaluation of these 175 transformation plans reveals that companies have planned significant reductions in their greenhouse gas emissions. The total absolute reduction targets of the transformation plans evaluated for Scope 1 emissions amount to approximately 1.1 million tons of CO₂-eq. (−53%), while Scope 2 emissions are planned to decrease by about 0.8 million tons of CO₂-eq. (−79%). Scope 3 reductions are projected with a decrease of about 0.6 million tons of CO₂-eq. (−2%).
The very high baseline share of Scope-3 emissions in the full dataset (≈90%) is plausible as Scope 3 consists of 15 different categories like purchased goods and services, upstream energy and transport, and downstream use-phase, which typically dominate the footprint. In contrast, Scope 1 and Scope 2 are smaller in such profiles because direct combustion and on-site electricity/heat are only one part each of the value-chain emissions. Furthermore, the planned reductions are concentrated in Scopes 1 and 2 as Module 5 requires applicants to demonstrate ≥ 40% potential reductions specifically in these scopes, while Scope 3 measures are optional and rely on data and actions outside the firm’s direct control. Accordingly, Scope 3 ambition in the plans remain limited even though baseline Scope 3 shares are high. Figure 2 presents the baseline and target GHG emissions across all three scopes, illustrating the relative contribution of each scope to the total planned reduction volume.
Fig. 2
GHG emission reductions in Scope 1, 2, and 3: Baseline vs. Target State for n = 175 transformation plans (2021–2023) in kt CO₂-eq. and n = 62 transformation plans (2021–2023) addressing Scope 3 in kt CO₂-eq. Own visualization based on Neusel et al. (2024)
The largest projected Scope 1 reductions are found in the chemical industry (C 20; 13%), professional scientific and technical services (M; 14%), and other economic activities (O; 17%). Scope 2 reductions are most pronounced in the sectors of mechanical engineering (C 28; 15%) and the manufacture of food products (C 10; 21%). Commitments to reduce Scope 3 emissions remain relatively limited, with the largest planned reductions occurring in the energy supply sector (D; 38%) and the transport and logistics sector (H; 35%). Manufacturing industries, particularly those engaged in chemical production, metal processing and automotive manufacturing, show the highest absolute reductions. Figure 3 presents the relative distribution of planned emission reductions by sector and scope.
Fig. 3
Sectoral share of planned GHG emission reductions by scope over the next ten years in %: a Scope 1, b Scope 2, c Scope 3. Sector codes refer to the NACE Rev. 2 classification. A full mapping of sector names to NACE codes is provided in Appendix 1. Own visualization based on unpublished evaluation data compiled by the authors
The regional distribution of submitted transformation plans and their associated emission reduction targets reveals considerable disparities across Germany’s federal states. As shown in Fig. 4, North Rhine-Westphalia submitted the highest number of plans (n = 49), accounting for a cumulative reduction target of over 1 million t CO₂-eq. over ten years. Bavaria and Baden-Württemberg follow in number of plans (n = 30 and n = 35, respectively), but their cumulative reduction targets (377 kt and 361 kt CO₂-eq.) are lower than that of Lower Saxony, which submitted only 17 plans but accounts for 393 kt CO₂-eq. in planned reductions.
This indicates that a higher number of submitted plans does not necessarily correspond to a higher total mitigation volume. Some regions submitted fewer but more ambitious or larger-scale plans, suggesting significant variation in company size, sectoral focus, and mitigation potential across states.
Federal states such as Hesse and Rhineland-Palatinate exhibit moderate levels of participation and reduction ambition, while several others, including Brandenburg, Thuringia, and Mecklenburg-Western Pomerania, show very limited engagement. No plans were submitted from Berlin, Bremen, or Saarland in the evaluated period.
These regional differences are visualized in Fig. 4. Panel (a) shows the number of transformation plans submitted per federal state, while panel (b) illustrates the corresponding cumulative emission reduction targets over the next ten years.
Fig. 4
Geographic distribution of a transformation plans and b cumulative planned GHG emission reductions (Scope 1–3) by German federal state. Own visualization based on unpublished evaluation data compiled by the authors
A similar regional pattern emerges when focusing exclusively on Scope 3 emission reductions. Substantial differences are evident in the extent to which states integrate value-chain emissions into their decarbonization strategies. The highest projected Scope 3 reductions are reported in Lower Saxony (approximately 0.15 million t CO₂-eq.), Baden-Württemberg (0.14 million t CO₂-eq.), and North Rhine-Westphalia (0.11 million t CO₂-eq.). Conversely, states such as Brandenburg and Saarland show limited engagement, both in terms of the number of submitted plans and the scale of planned Scope 3 reductions. These findings are visualized in Fig. 5, which offers a disaggregated overview of state-level Scope 3 commitments and participation rates.
Fig. 5
Geographic distribution of a Scope 3-specific decarbonization plans and b their cumulative planned GHG reductions by German federal state. Own visualization based on unpublished evaluation data compiled by the authors
A total of €7.86 million was allocated to support the development of transformation plans. LE received around 80% of total funding, averaging €37,000 per project. SME received approximately €35,000 on average, though they accounted for a smaller share of total applicants. Notably, around 89% of SME and 96% of LE received the maximum possible funding quotas, indicating that both groups made full use of the available financial support. The average cost per ton of planned GHG reduction was €2.55, based on the emission reduction potentials identified in the transformation plans.
Qualitative review of transformation plans
A subset of 30 transformation plans (approximately 17% of the total) was selected for qualitative assessment. The qualitative analysis of 30 transformation plans included 25 randomly selected and 5 purposefully chosen cases. The total baseline emissions across these plans amounted to 1.2 million tons of CO₂-eq. Of this, 0.5 million tons were attributed to Scope 1 and Scope 2 emissions. The remainder fell under Scope 3. Compared to the full dataset, where Scope 3 accounts for approximately 90% of baseline emissions, the subsample shows a lower Scope 3 share of around 60%. This difference is explained by the composition of subsample as it includes relatively more SMEs than the full dataset (56% of the random sample vs. 21% of the full sample). As outlined in the Methods, this subsample was designed for qualitative diagnostics of reporting practice rather than statistical representativeness.
Scope-specific averages reveal substantial differences: Scope 1 emissions were reduced by 55%, Scope 2 by 81%, and Scope 3 by only 21%. Figure 6 summarizes the baseline and target emissions for this subsample across all three scopes.
Fig. 6
GHG emission reductions in Scope 1, 2, and 3: Baseline vs. Target State for n = 30 transformation plans (2021–2023) in kt CO₂-eq. and n = 12 transformation plans (2021–2023) addressing Scope 3 in kt CO₂-eq. Own visualization based on Neusel et al. (2024)
Scope 1 and Scope 2 emission reductions consistently exceeded the funding program’s minimum requirement of 40%. However, the reductions in Scope 3 emissions remain significantly lower. The lower apparent Scope 3 ambition reflects composition and coverage: Scope 3 reporting is optional and SMEs are over-represented, often with shorter value chains and site-level boundaries. This indicates that companies, especially SMEs, are either hesitant or limited in their ability to address emissions beyond their direct operations. The data indicates that the integration of Scope 3 reductions into corporate climate strategies remains a major challenge due to the complexity of indirect emissions tracking, a lack of standardized reporting methods, and uncertainties in how supply chain partners will contribute to emission reductions.
Across the 30 transformation plans, a total of 147 distinct measures (nm) were identified. The largest absolute GHG emission reduction was achieved through switching to renewable energy sources (108.8 kt CO2-eq.), while the most commonly proposed category was process optimization (nm = 28).
When considering the average GHG reduction per measure, renewable energy switching and biomass-based solutions stand out, each achieving an average of 4.9 kt CO₂-eq. per measure. In contrast, other categories such as vehicle electrification and building insulation improvements exhibited significantly lower average savings. However, these results should be interpreted with caution. In some categories, the number of identified measures was very low (e.g., only one case for building insulation), making the reported averages highly sensitive to individual project characteristics. Such small sample sizes limit the generalizability of the results and reduce the reliability of comparisons across categories. Figure 7 illustrates the distribution of projected emissions reductions by measure category.
Fig. 7
Projected GHG emission reductions by measure category (kt CO₂-eq.) across n = 30 transformation plans. Own visualization based on Neusel et al. (2024)
Quality assessments of the 30 plans used a standardized rating scale (1 = very good, 2 = good, 3 = sufficient, 4 = not verifiable, and a fifth option for “not:
Scope 1 assessments received an average score of 1.65 for baseline reporting and 1.75 for target projections, indicating that these were well-documented and clearly defined in most plans.
Scope 2 assessments were rated 1.55 for baseline reporting and 1.78 for target projections, demonstrating similarly high levels of accuracy and reliability.
Scope 3 assessments received significantly lower ratings, with an average score of 2.58 for baseline reporting and 2.89 for target projections.
Common deficiencies included missing emission factors, inconsistent energy data, and limited transparency in calculation methodologies. In some plans, proposed hydrogen use lacked site-specific feasibility assessments or cost comparisons with alternatives.
Overall, the results indicate consistent alignment with program criteria in Scope 1 and 2, while Scope 3 coverage and methodological rigor showed greater variability. Implementation feasibility was not assessed within this phase, in line with the ex-ante focus of Module 5.
Discussion
Module 5 has enabled the development of structured decarbonization plans across diverse sectors. Companies have made significant commitments to reduce Scope 1 and 2 emissions, often exceeding the 40% reduction threshold required by the program. These reductions are primarily achieved through established mitigation pathways such as on-site renewable energy, procurement of green electricity, and process optimization, indicating a strong alignment with mainstream decarbonization strategies.
However, the analysis reveals substantial limitations in addressing Scope 3 emissions. While 40% of the evaluated transformation plans included some Scope 3 considerations, only a small fraction defined measurable reduction targets. This supports a broader body of research identifying persistent barriers to Scope 3 integration, including limited data availability, low data quality, and methodological inconsistency (Busch et al., 2022; Dahlmann et al., 2023; Hettler & Graf-Vlachy, 2023). In most cases, companies did not address all 15 categories defined under the GHG Protocol. Frequently included categories were business travel, waste, and energy-related activities, whereas more complex categories such as purchased goods, use-phase emissions, or end-of-life treatment were often omitted. Many companies appear to rely on proxy data or sectoral averages, which limits comparability and increases the risk of superficial or selectively framed reporting (Patchell, 2018; Ryan & Tiller, 2022; Schulman et al., 2021). In some cases, Scope 3 is included primarily as a reputational signal rather than being anchored in actionable planning processes (Hoepner & Schneider, 2022).
Legal and economic concerns further compound this issue. Firms hesitate to demand data from suppliers due to contractual uncertainties and concerns over data privacy, as emphasized by Stenzel and Waichman (2023). Moreover, given the voluntary nature of most Scope 3 frameworks, companies lack strong incentives to engage deeply with their value chain unless external pressure through regulation, investors, or sector-specific standards is applied. Yet, as Blanco (2021) argues, credible Scope 3 disclosure is positively associated with Environmental, Social und Governance (ESG) performance and market valuation, suggesting potential for competitive advantage if companies can move from disclosure to decarbonization.
In contrast to the ambitious strategies for direct emissions, most companies continue to treat Scope 3 as peripheral. This reflects a broader misalignment between corporate climate ambition and operational accountability across value chains. While some leading firms are pioneering supplier engagement and product lifecycle emissions tracking, such examples remain exceptions rather than the norm. As Hettler and Graf-Vlachy (2023) suggest, standardized supplier data platforms and automated emission factor libraries could be pivotal in overcoming these barriers, yet they remain underdeveloped in the German funding context.
The regional disparities observed in the dataset reflect differences in both industrial structure and access to consulting and support services. A significantly higher number of plans originate from economically strong states such as Baden-Württemberg, North Rhine-Westphalia, and Bavaria, whereas fewer or none submissions come from structurally weaker regions like Saxony Anhalt and Mecklenburg-Vorpommern. According to federal statistics, Baden-Württemberg and North Rhine-Westphalia lead in gross domestic product from industrial production and host the largest number of industrial establishments. In contrast, regions with lower industrial density, such as Mecklenburg-Vorpommern and Saxony Anhalt, tend to show lower or none participation in the funding program (Statistische Ämter des Bundes und der Länder, 2025a, 2025b). his imbalance underscores the need for more targeted outreach, local capacity-building, and advisory structures to ensure that all regions can equally benefit from such funding instruments.
In terms of enterprise structure, LE dominated participation, yet SME tended to receive proportionally higher funding quotas. Still, SME engagement remains limited and as indicated in the qualitative analysis tends to address Scope 3 only marginally, which may stem from procedural complexity, resource constraints, and skepticism about the practical utility of transformation plans. An additional structural barrier is the exclusion of internal personnel costs from eligible funding, which may have disincentivized companies from allocating in-house resources to strategic planning. Prior studies have shown that reducing administrative hurdles and offering pre-structured templates can significantly improve SME participation (Blanco, 2021; Hettler & Graf-Vlachy, 2023). International experiences support this finding. in Switzerland, the “EnergieSchweiz für KMU” initiative uses standardized energy check-ups and decentralized advisory structures to facilitate access and participation (Business Strategies for Sustainability, 2018). Similarly, in the Netherlands, the Netherlands Enterprise Agency (Rijksdienst voor Ondernemend Nederland, RVO) supports regional hubs that integrate technical assistance with funding advice and decarbonization planning (Dubel, 2022). These embedded technical support systems have proven particularly effective for increasing SME engagement in climate policy instruments.
One of the central programmatic limitations is the lack of follow-up tracking. Module 5 currently supports planning but does not include mechanisms for implementation verification. As a result, it remains unclear whether the proposed measures, particularly those with high emissions reduction potential, are actually realized. This absence of ex-post assessment weakens the ability to link strategic planning efforts with measurable climate outcomes and diminishes the evaluability of the program’s long-term effectiveness. As Hettler and Graf-Vlachy (2023) emphasize, transparent tracking of follow-up actions is essential to prevent decoupling of planning from execution. Based on the evaluation results, we also proposed additional features for future calls, including the systematic documentation of “success stories” and “failure cases.” Since implementation of decarbonization measures often spans several years, capturing these cases could help monitor real-world impacts, highlight transferable strategies, and identify structural barriers. This would support institutional learning and strengthen the program’s ability to bridge the gap between planning and action.
Finally, the role of peer-learning mechanisms and institutional support remains underdeveloped. The IEEKN bonus, intended to promote knowledge exchange and network participation, was rarely claimed. However, peer-driven support structures have been shown to be particularly helpful for first-time applicants and SME (Business Strategies for Sustainability, 2018; Dubel, 2022; Stenzel & Waichman, 2023). Strengthening their integration, for example through regional hubs or sectoral best-practice platforms, could improve both the quality and reach of transformation planning efforts.
Conclusion
Module 5 marks a significant policy innovation by shifting the focus from direct technology investments to strategic decarbonization planning. This evaluation demonstrates that the program has enabled companies to develop structured transformation plans, particularly targeting Scope 1 and Scope 2 emissions. In line with program requirements, most participating firms demonstrated the technical potential to reduce GHG emissions by at least 40% across Scope 1 and/or Scope 2 over a ten-year period. These reductions were primarily based on renewable energy procurement, electrification, and process optimization.
However, the analysis also highlights key limitations. Scope 3 emissions remain only marginally addressed, often included nominally but without robust or measurable strategies. This reflects broader challenges in Scope 3 accounting, including limited data availability, methodological inconsistencies, and a lack of incentives for full disclosure (Busch et al., 2022; Hettler & Graf-Vlachy, 2023; Ryan & Tiller, 2022). Without more standardized and enforceable reporting expectations, Scope 3 will likely remain marginal in many corporate climate strategies.
Another key shortcoming is the current lack of implementation tracking. Module 5 evaluates plans ex ante but offers no mechanism to assess whether proposed measures are implemented or whether actual emissions reductions occur. This undermines the program’s long-term impact assessment and risks decoupling planning quality from real-world decarbonization outcomes.
To enhance the program’s effectiveness, several improvements are recommended:
Introduce mandatory follow-up reporting to assess implementation status and realized impacts.
Strengthen incentives for Scope 3 integration through funding bonuses, support, and benchmarking tools.
Expand advisory services and simplify application processes to better reach SMEs, especially in structurally weaker regions.
Harmonize accounting standards, particularly for Scope 3, to improve consistency and comparability.
Promote stronger use of peer-learning structures such as IEEKN to share best practices.
By expanding the evaluation methodology and refining the program’s design, Module 5 can develop into a more impactful tool for advancing corporate decarbonization in Germany. While the program has laid a solid foundation, long-term success will depend on robust monitoring, stronger Scope 3 incentives, and broader accessibility. Follow-up assessments, clearer reporting, and sector-specific support will be key to ensuring that Module 5 not only guides planning but also drives tangible emissions reductions toward Germany’s 2045 neutrality target.
Acknowledgements
This paper is partially based on results of a project carried out for the German Federal Ministry for Economic Affairs and Climate Action (BMWK). We would like to express our gratitude to the Ministry and the implementing agencies for their support, to the participating companies for their valuable input and our colleagues at Prognos AG and Fraunhofer Institute for Systems and Innovation Research (ISI).
Declarations
Competing interests
The authors declare no competing interests.
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