EconStor (ZBW Kiel)
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German Economy in Autumn 2025: Economy yet to gain momentum
No full textThe German economy is still awaiting stronger momentum. Leading indicators have stabilized in recent months, and business expectations have seen marked improvement in anticipation of higher public spending. Nonetheless, economic activity is likely to remain broadly flat through the end of the year as U.S. tariff policy continues to weigh on growth. After two years of contraction, however, we expect GDP to increase by a modest 0.1 percent in 2025. From 2026, the federal government is set to make greater use of its newly available fiscal space. We project that expansionary fiscal policy will contribute about 0.6 percentage points to GDP growth in 2026, and approximately half that amount in 2027, and expect GDP to expand by 1.3 percent in 2026 and 1.2 percent in 2027. After accounting for the additional boost from calendar effects in 2026 (around 0.3 percentage points), the underlying pace of expansion remains subdued. While cyclical slack leaves some room for recovery, much of the recent stagnation-output in 2025 is still no higher than in 2019 -reflects structural weaknesses. These are evident in Germany's comparatively weak international performance and the continued loss of export market share. As growth gradually picks up, labor market conditions should improve, with the unemployment rate projected to fall from 6.3 percent in 2025 to 5.8 percent in 2027. Business investment is expected to increase again as sentiment improves, albeit from a low base. Exports are likely to rise moderately from 2026 onwards, though losses in competitiveness will likely continue to erode market shares. The general government deficit is set to widen from 2 percent of GDP in 2025 to 3.5 percent by 2027
Trotz Herausforderungen: Unternehmen und Bevölkerung optimistisch
No full textDie vier großen Megatrends - Digitalisierung, Dekarbonisierung, Deglobalisierung und der demografische Wandel stellen Gesellschaft und Wirtschaft gleichermaßen vor große Herausforderungen (Demary et al., 2021). Dennoch sehen Bevölkerung und Unternehmen bei allen Trends bzw. den möglichen politischen Lösungsansätzen mehr Chancen als Risiken
Legitimacy Building in Entrepreneurial Ecosystems—A Process Perspective for Sustainable Entrepreneurs
No full textThe integration of legitimacy in entrepreneurial ecosystem theory is under‐researched, resulting in scholarly vagueness about how entrepreneurs acquire resources. Our qualitative study with 31 (co‐)founders of startups following the triple bottom line investigates entrepreneurs' daily practices for building legitimacy in entrepreneurial ecosystems. We identify that entrepreneurs follow a sequential process to build legitimacy: 1) engaging and assimilating with culture , 2) establishing and utilizing networks , 3) enhancing visibility , and 4) leveraging the sustainable mission . Following this sequential process builds different levels of legitimacy. Each level grants access to resources from the entrepreneurial ecosystem. We contribute to the scholarly conversation on legitimacy in entrepreneurial ecosystems and provide practical implications for entrepreneurs
Are nations ready for digital transformation? A macroeconomic perspective through the lens of education quality
No full textThe global shift toward digital transformation presents both opportunities and challenges for national economies, particularly in terms of workforce readiness. While many studies assess digital readiness via infrastructure or technological adoption, fewer investigate the preparedness of countries’ future labor forces. This article addresses this research gap by examining how quality of education relates to job automation risk across OECD countries. The goal is to identify which nations are least prepared for digital disruption due to weak educational foundations and high automation exposure. Using data on education expenditure, PISA scores, and the Education Index, compared to the percentage of jobs at high risk of automation, this study applies correlational analysis and a quadrant overview to assess national readiness. Findings show that countries such as Slovakia, Poland, and Greece are least prepared, combining low investment in education and high exposure to automation. Conversely, nations like Finland, Norway, Sweden, and New Zealand exhibit strong readiness, characterized by robust education systems and lower automation risks. This study contributes to the literature by integrating automation vulnerability into national readiness assessments and offers actionable insights for policymakers focused on education reform and workforce development
Why emerging markets weathered federal reserve tightening so well
No full textThe steep rise in US interest rates that started in 2022 led many observers to anticipate severe difficulties for emerging market economies (EMEs). Unlike after the Volcker disinflation of the early 1980s or the bond market turmoil of 1994, however, most EMEs weathered the Fed's monetary tightening in 2022-23 relatively well. In particular, EME dollar credit spreads, an indicator of potential financial distress, rose only moderately in those years before dropping to historically low levels in 2024. To explain these developments, we estimate monthly regressions of EME spreads over the period 2006-2024 on measures of US monetary policy as well as US financial conditions: the VIX volatility index, the foreign exchange value of the dollar, and US corporate high-yield spreads. Following Hoek et al. (2022) and Arteta et al. (2022), we find that "monetary shocks"-increases in US Treasury yields prompted by concerns about rising inflation or hawkish Fed behavior-boost EME spreads, as expected. However, those monetary shocks account for almost none of the variation in spreads in the 1½ decades leading up to the COVID-19 pandemic and contribute only moderately to the rise in spreads in 2022-23. Thus, one reason that the EMEs weathered Fed tightening so well is that, simply put, Fed tightening is no longer as injurious to them as commonly believed; this likely reflects improvements in EME policies since the 1980s and 1990s that have bolstered their resilience. A second reason why EME spreads remained relatively contained in the face of rising interest rates is that US corporate credit markets remained buoyant, and their confidence spilled over to EMEs. We show that US high-yield spreads accounted for the lion's share of the fluctuations in EME spreads over the past couple of decades, dominating not only the effects of monetary shocks but also changes in the VIX and the dollar
Analysing the Compensatory Properties of the Outranking Approach PROMETHEE
No full textThe PROMETHEE methods are increasingly applied in environmental and public policy decision‐making due to their comprehensiveness and explainability. However, the literature contains differing statements regarding their compensatory properties. Compensation in multiple criteria decision aggregation procedures is commonly understood as allowing a gain in one criterion to offset a loss in another one. In certain domains, such as environmental or public policy decision‐making, it may be undesirable, as some impacts may result in losses too severe to be counterbalanced by good performance on other criteria. Therefore, it may be necessary to limit the extent to which an aggregation procedure permits compensation or to explicitly control it as needed. Guidelines and detailed analytical tools, however, that help users and analysts to control compensation in the PROMETHEE methods remain scarce and often lack transparency. In this study, we analyse the compensatory behaviour of the PROMETHEE I and II methods and identify the key determinants for compensation in these methods. Based on these insights, we develop flow insensitivity intervals to assess the sensitivity of a given decision model towards compensatory effects and provide a set of general guidelines for controlling compensation in the PROMETHEE I and II methods for any given pair of criteria. The findings are illustrated at hand of an environmental management case study. By combining the guidelines with flow insensitivity intervals, users and analysts gain access to measures of varying granularity to evaluate and control compensation in a PROMETHEE decision model
When cohesion meets excellence: Analysing the drivers of synergies between EU R&I funding instruments in EU regions
No full textThis paper introduces a novel approach to measuring synergies between Horizon 2020 and cohesion policy funding in the field of R&I during the 2014-2020 programming period. Leveraging project-level data, we calculate regional cosine similarity indices based on societal grand challenges (SGCs) addressed to assess alignment between the two EU funding instruments in EU NUTS-3 regions. Results indicate that synergies are less likely in rural areas, emerging innovators, and - though not statistically significant - less developed regions, highlighting the role of business environments and innovation ecosystems. Regression analysis reveals that funding alignment is positively linked to the presence of universities and specialization in knowledge-intensive services, though the latter exhibits a nonlinear effect under certain circumstances. However, a higher number of SGCs addressed in smart specialization (S3) policy objectives is negatively associated with thematic funding similarity, likely due to fragmentation and dilution of focus. Regions that prioritize too many SGCs may reduce their ability to develop strong specialization and align different funding sources effectively
Discrimination by microcredit officers: Theory and evidence on disability in Uganda
No full textThis paper studies the relationship between a microfinance institution (MFI) and its loan officers when officers discriminate against a particular group of micro-entrepreneurs. Using survey data from Uganda, we provide evidence that loan officers are more biased than other employees against disabled micro-entrepreneurs. In line with the evidence, we build an agency model of a non-profit MFI and a biased loan officer in charge of granting loans. Since incentive schemes are costly and the MFI's budget is limited, the MFI faces a trade-off between combating discrimination and granting loans. We show that the optimal incentive premium is a non-decreasing function of the MFI's budget. Moreover, even a non-discriminatory welfare-maximizing MFI may let its loan officer discriminate, because eradicating discrimination would come at the cost of too many loans. Observing an MFI's loan allocation biased against a minority group therefore does not imply that the institution is biased against this group
Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis
No full textArtificial intelligence (AI) has quickly emerged as a top technological priority for companies in various sectors, radically altering business operations. However, the existing literature reveals a fragmented and inconsistent understanding of AI adoption dynamics between small and medium enterprises (SMEs) and larger, well-established firms. This dichotomy of the existing research raises important questions about whether the AI tools and application modalities used by these companies are inherently similar or if significant differences exist in their implementation and outcomes due to varying organizational sizes. This study evaluates whether small and large firms' efforts toward implementing AI differ significantly using bibliometric analysis and a systematic literature review from the Web of Science and Scopus databases. A total of 78 peer-reviewed articles were analyzed and categorized states and trends into 10 dimensions: (1) technology readiness, (2) customization, (3) AI tools and needs, (4) data requirements, (5) skills and competencies, (6) financial readiness, (7) management support, (8) market and competitive pressure, (9) partnership and collaboration, and (10) regulatory compliance, based on the technology-organization-environment (TOE) theoretical model. A bibliometric mapping approach was adopted to visualize bibliometric data using VOSviewer. The review brings together collective insights from several leading expert contributors to emphasize areas where SMEs need additional support to fully leverage AI technologies. The results provide pragmatic insights for policymakers, helping them develop tailored approaches for both SMEs and large enterprises to meet their unique needs while acknowledging AI's undeniable role in competitiveness and growth
A systems‐theoretical look at stakeholder theory: Lessons from Bogdanov's Tektology
No full textWe explore how the conversation between stakeholder theory and systems theory can illustrate the unique role of stakeholder management within the system of capitalistic institutions. Toward that end, we call the attention of stakeholder scholars to Alexander Bogdanov's Tektology , an early version of systems theory that raised critical concerns about capitalism. According to Tektology, capitalism fosters individualistic and conflict‐driven mindsets, which stymie society's ability to achieve its full collaborative potential. If stakeholder theory takes this critique on board, it may conceptualize social collaboration as “organized complexity” that can materialize if human actors overcome their reductionist mindsets. This conceptual move highlights novel systems‐theoretical foundations for stakeholder theory's insights into the role of stakeholder mindsets in unlocking collaborative potential within capitalist societies. The resulting added value for stakeholder theory lies in recognizing the collaborative nature of capitalism as an institutional accomplishment facilitated by stakeholder management practices, which operate along non‐linear pathways and generate emergent and counter‐intuitive outcomes