ABSTRACT Geopolitical risks have emerged as a significant factor influencing the resilience of transnational food supply chains. This paper systematically reviews the foundational theories and key issues related to the resilience of transnational food supply chains from the geopolitical risk's perspective. Literature analysis indicate that geopolitical risks primarily affect the resilience of China's transnational food supply chains: supply uncertainty, price uncertainty and logistics uncertainty. Additionally, review of empirical studies on the impact of geopolitical risks on the resilience of transnational food supply chains reveals that existing research generally supports the view that geopolitical risks significantly diminish the resilience of China's transnational food supply chains, although variations exist across different grain varieties and over time regarding the extent and nature of these impacts. Finally, this paper proposes future research directions, including identifying the transmission pathways of geopolitical risks affecting China's transnational food supply chains, uncovering the behavioral logic of multiple actors within these chains under geopolitical risks, systematically assessing the resilience of key nodes and the overall risk level of China's transnational food supply chains, conducting an in‐depth exploration of the reconstruction pathways for these chains, and designing strategies to integrate the interests of diverse stakeholders in transnational food supply chains.

ABSTRACT Zombie firms—businesses that persist despite chronic financial underperformance—have become a growing focus of economic research. Yet, the literature remains conceptually fragmented and methodologically diverse. This study offers a structured and comprehensive overview of zombie firm scholarship by combining bibliometric analysis with qualitative content analysis. Using a dataset of 160 peer‐reviewed articles, we map the intellectual landscape of the field, identifying publication trends, key research clusters, influential authors, and patterns of collaboration. Our analysis reveals five dominant thematic clusters: zombie lending and banking behavior, resource misallocation and productivity traps, firm performance and capital structure, government intervention and policy design, and regional and sectoral case studies. We find that the field has shifted from Japan‐centric studies to more globally dispersed research, particularly in China and parts of Europe, with a notable increase in publications following the COVID‐19 crisis. The findings highlight gaps in definitional standardization, methodological convergence, and interdisciplinary integration. The study also identifies emerging trends, outlines directions for future research, and provides a valuable foundation for policymakers seeking a deeper understanding of zombie firm dynamics.

ABSTRACT This review investigates the transformation of the financial services sector through the implementation of artificial intelligence (AI). The study employed a TCCM framework based systematic literature review integrated with content analysis to extract meaningful insights from 96 articles published between 2010 and 2024. Drawing upon the emerging literature on AI‐enabled significant transformation in the financial industry, the study identifies four themes: (1) leveraging algorithms for enhanced business decision‐making and fraud detection, (2) predictive analytics in financial decision‐making, (3) AI‐driven robo‐advising and personalized financial services, and (4) challenges surrounding compliance and trust. We also trace the evolution of AI adoption in finance, highlighting a significant acceleration in implementation. While AI has transformed areas such as trading, credit scoring, and customer support, challenges remain in the areas of using AI ethically, data privacy, and regulatory compliance. Our findings reveal a noticeable absence of robust theoretical frameworks in existing research. To address these gaps, we propose future research directions, including exploring novel theories such as Prospect Theory, utilizing data governance frameworks to expand the geographical scope beyond major markets. This review provides a comprehensive analysis of AI's influence on the financial services sector and offers recommendations for future research in this rapidly evolving field.

ABSTRACT This paper provides a comprehensive review of LGBTQ‐supportive corporate policies, analyzing their impact on organizational outcomes across diverse industries and geographic contexts. Drawing on theoretical frameworks such as the Resource‐Based View, Stakeholder Theory, and Agency Theory, the study highlights the multifaceted benefits of these policies, including enhanced innovation, improved financial performance, and increased employee engagement. Additionally, the paper examines challenges in implementing LGBTQ‐supportive policies, such as economic constraints, legislative barriers, and internal corporate resistance. Comparative case studies from technology, finance, retail, pharmaceutical, and hospitality sectors illustrate best practices and the role of corporate governance in fostering inclusivity. The paper also identifies critical research gaps, emphasizing the need for longitudinal studies, intersectionality analyses, and regional investigations to better understand the global dynamics of LGBTQ‐supportive policies. By synthesizing empirical evidence with actionable recommendations, this study underscores the strategic and ethical imperatives of fostering workplace diversity, offering a roadmap for organizations to achieve sustainable growth and social equity.

ABSTRACT This meta‐study analyzes the productivity effects of industrial robots. More than 1800 estimates from 85 primary studies are collected. The meta‐analytic evidence suggests that robotization has so far provided, at best, a small boost to productivity. There is strong evidence of publication bias in the positive direction. These findings are observed across all measures of productivity used in the primary literature and are robust to several modern meta‐analytic estimators. My analysis of the drivers of heterogeneity among the findings of primary studies points to diminishing returns to robot adoption. I also find evidence that econometric methods, the level of analysis, as well as the choice of control variables and robot data, can influence the effect size. Finally, several explanatory factors for the emergence of a productivity paradox in the context of robotics are discussed.

ABSTRACT Over the last decades, policymakers have resorted to Incentive Zones to attract foreign investments, boost industrial production (particularly in export‐oriented manufacturing), stimulate circular and cumulative growth processes, and expand exports. These policy instruments are diversified across countries, thus leading to a high degree of heterogeneity in terms of their effectiveness. Based on this, the research aims to analyse the main features and describe different types of incentive zones in terms of contextual factors, features, priorities and objectives, and to map the existing zones in Europe. To achieve this goal, a two‐step analysis has been employed. In the first step, a systematic literature review has allowed us to identify the key factors recognized by the literature to describe incentive zones. Subsequently, according to the defined characteristics, the operating incentive zones in the European Union have been mapped and described. The research provides a first EU‐wide mapping and description of IZs, based on a comprehensive theoretical and data framework. These data might serve to evaluate the primary issues behind IZ functioning, facilitate solving the complex policy harmonization challenges and serve as a foundation for future analyses.

ABSTRACT FinTech has emerged as a transformative force, reshaping the financial landscape. Given the dearth of comprehensive summaries of FinTech research, this systematic literature review (SLR) is complemented by a bibliometric review that presents quantitative and qualitative insights into the existing knowledge in this domain. In this literature review, the study applied the Scientific Procedures and Rationales for Systematic Literature Review (SPAR‐4‐SLR) methodology. After using the inclusion and exclusion criteria, the study considered 1016 published articles from the Scopus database from 2000 to 2024. To identify the most influential research articles in FinTech, the study used citation network, co‐citation network, and trend analysis. Applying bibliometric analysis, the study identified the most prolific journals, authors, countries, and themes in FinTech research. Additionally, content analysis was conducted on 187 highly cited articles and eight distinct clusters were identfied. In the content analysis, emerging themes were identified, including FinTech and its relation to achieving the United Nations Sustainable Development Goals (SDGs), financial inclusion, and sustainability. The study provides valuable insights for academics, policymakers, and regulators to gain a thorough understanding of the FinTech landscape and identify areas for further investigation.

ABSTRACT Granular holdings data containing security‐by‐security portfolio investments features prominently in economics and finance research. One novel source is the granular Securities Holdings Statistics (SHS), managed by the European Central Bank. SHS covers different euro area investors with over 2 billion observations, representing +50 trillion euros in portfolio investments. This comprehensive SHS research review of 102 studies (31 published and 71 working papers) highlights the strong growth in SHS‐based publications, especially since 2022. The review details how granular SHS data has catalyzed research across five fields: banking and finance, international investment, monetary policy, financial markets, and sustainable finance. Addressing the replication crisis in economics, this study emphasizes the need for rigorous data filtering, cleaning, and documentation of aggregation choices when using SHS data. A practitioner's guide is provided to ease future research, enhancing replicability and to minimize non‐standard errors, showcasing best practices through multidimensional time‐series panel analyses of the holdings of different investors and their preferences for euro‐denominated bonds, green bonds, and sustainability‐linked bonds. The review concludes by suggesting potential avenues for future research.

ABSTRACT We present a comprehensive systematic literature review on financial resilience at the individual and household level by employing the integrated ADO (Antecedents, Decisions, Outcomes) and TCM (Theory, Context, Method) framework. Financial resilience has emerged as a critical concept in response to rising financial vulnerabilities and uncertainties at both the individual and household levels, as well as globally. Drawing upon 82 peer‐reviewed articles indexed in Scopus, we synthesize the theoretical foundations, methodological approaches, and contextual diversity within the literature. We identify three core antecedents of financial resilience, namely economic, social, and behavioral, which inform eight categories of financial decisions that lead to improved economic, social, and behavioral outcomes. Our analysis reveals a fragmented yet expanding body of financial resilience research, highlights key conceptual and empirical gaps, and proposes a future research agenda to address them. This review contributes to the growing literature by offering a structured framework to advance both academic inquiry and policy formulation aimed at building individual and household financial resilience.

ABSTRACT This paper begins by investigating the influence of emotions on investment decision‐making (IDM) via a systematic literature review. Contrary to the traditional view of investing, behavioral finance demonstrates that investors are frequently influenced by fallacies and irrationality. The study investigates the connection between emotions and IDM by analyzing research trends, methodologies and theories in the context of financial markets. The findings indicate that emotions influence risk appraisal in an identifiable manner, with investors' subconscious desires influencing both decision‐making and market behavior. The study goes on to propose “The Rational‐Emotional Investing Model” which depicts the mechanisms by which emotions influence investment decisions. The model reflects the importance of emotional stability in decision‐making and points to the need for regulators, investors, and other financial professionals to comprehend the influence of emotions on market behavior.