Empirical Case Research Articles

Who Reviews Whom, Where, and Why? Evidence from the Peer Review Process of the OECD Development Assistance Committee

Abstract The study of international organizations’ (IOs) peer review systems has focused largely on their efficacy in disseminating best practices, with mixed results. This paper informs the debate from a new angle: We evaluate the extent to which decisions about who reviews whom and where result from bureaucratic guidelines, or whether these decisions are shaped by the particularistic interests of member states that would need to be considered in efficacy evaluations of peer reviews. Our empirical case is the OECD Development Assistance Committee (DAC) which requires that DAC donors have their practices reviewed by two peer examiners every few years. Using quantitative and qualitative methods, we study (i) the assignment of peer examiners (1962–2020) and (ii) the selection of recipient countries visited for in-depth assessment during the review (1994–2020). Our analyses show that the choice of peer examiners is driven by the IO’s bureaucratic process. The selection of recipient countries for field visits is also largely in line with Secretariat guidelines, with some room for the preferences of reviewed donors to play a role.

Shifting agrarian labour regimes, ecology, and the crisis for Dalit women’s work in India

Abstract Building on the differentiated analysis of India’s agrarian crisis, this article argues for centring ecology in understanding the crisis faced by agricultural labour. The empirical case is of landless Dalit women in Punjab, India, experiencing the shift from a cotton-dominated labour regime to a paddy-dominated one. It delineates the materiality(s) of commodity, workplace, and body associated with the two regimes and explores its contingent intersections with social reproduction, caste oppression, capital’s strategies, and the state. Overall, the article argues that labour’s agrarian crisis is both produced through ecology and manifests in/as ecology across different moments and levels of analysis.

Temporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems.

Detecting anomalies in distributed systems through log analysis remains challenging due to the complex temporal dependencies between log events, the diverse manifestation of system states, and the intricate causal relationships across distributed components. This paper introduces a TLAN (Temporal Logical Attention Network), a novel deep learning framework that integrates temporal sequence modeling with logical dependency analysis for robust anomaly detection in distributed system logs. Our approach makes three key contributions: (1) a temporal logical attention mechanism that explicitly models both time-series patterns and logical dependencies between log events across distributed components, (2) a multi-scale feature extraction module that captures system behaviors at different temporal granularities while preserving causal relationships, and (3) an adaptive threshold strategy that dynamically adjusts detection sensitivity based on system load and component interactions. Extensive experiments on a large-scale synthetic distributed system log dataset show that TLAN outperforms existing methods by achieving a 9.4% improvement in F1-score and reducing false alarms by 15.3% while maintaining low latency in real-time detection. The framework demonstrates particular effectiveness in identifying complex anomalies that involve multiple interacting components and cascading failures. Through comprehensive empirical analysis and case studies, we validate that TLAN can effectively capture both temporal patterns and logical correlations in log sequences, making it especially suitable for modern distributed architectures. Our approach also shows strong generalization capability across different system scales and deployment scenarios, supported by thorough ablation studies and performance evaluations.

Criminal Liability of Legal Entities for a Just and Equitable Society: A Theoretic and Empirical Case

Objective: This article examines the main provisions of criminal liability of legal entities in a comparative context, focusing on the prevention of corporate crimes and the establishment of justice in law enforcement practices. The aim of the study is to develop and substantiate effective mechanisms that promote responsible corporate behavior and ensure that economic activities contribute to sustainable development and human well-being. Method: The research also aims to provide recommendations for enhancing current legal frameworks to better address corporate misconduct, emphasizing the role that criminal liability can play in fostering economic security, fair competition, and social equity. Results and Discussion: The findings highlight key aspects of implementing robust legal mechanisms to combat corporate crime. The conclusions emphasize that by adopting international best practices and adapting them to the local context, it is possible to create an effective legal framework. Research Implications: This framework will help to reduce corporate crime rates, strengthen economic security, and improve the overall business climate in the country. Originality/Value: The relevance of the study is underscored by the growing importance of addressing corporate crime in a way that aligns with human lifestyle considerations and the United Nations' Sustainable Development Goals (SDGs). Criminal liability of legal entities is important for achieving SDG 16 ("Peace, Justice, and Strong Institutions") and SDG 8 ("Decent Work and Economic Growth").

AN EMPIRICAL ANALYSIS OF DIGITAL TRANSFORMATION IN THE ACCOUNTING FIELD AND ROLE OF ACCOUNTANTS: A REVIEW OF LITERATURE

In today's rapidly evolving business landscape, digital transformation has emerged as a crucial force reshaping various industries, including accounting. This empirical study delves into the profound impact of digital transformation on the accounting field and the evolving roles and responsibilities of accountants within this dynamic context. Through a comprehensive analysis of empirical data and case studies, this research investigates the multiple facets of digital transformation in accounting. It scrutinizes the adoption of advanced technologies such as Artificial Intelligence (AI), Blockchain, Cloud Computing, and Big Data Analytics, and their influence on the accounting ecosystem. The study uncovers the ways in which these technologies streamline processes, enhance accuracy, and improve decision-making in accounting practices. This research sheds light on the changing roles of accountants. It reveals that accountants are transitioning from traditional number-crunchers to strategic advisors and data analysts. The study highlights the importance of digital literacy and adaptability as critical skills for accountants in this new era. This empirical analysis highlights the necessity for accounting professionals and firms to embrace digital transformation to remain competitive and relevant in the modern business environment. It offers valuable insights for policymakers, educators, and industry practitioners to navigate the evolving landscape of accounting in the digital age.

TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution.

The scale and scope of comparative trait data are expanding at unprecedented rates, and recent advances in evolutionary modeling and simulation sometimes struggle to match this pace. Well-organized and flexible applications for conducting large-scale simulations of evolution hold promise in this context for understanding models and more so our ability to confidently estimate them with real trait data sampled from nature. We introduce TraitTrainR, an R package designed to facilitate efficient, large-scale simulations under complex models of continuous trait evolution. TraitTrainR employs several output formats, supports popular trait data transformations, accommodates multi-trait evolution, and exhibits flexibility in defining input parameter space and model stacking. Moreover, TraitTrainR permits measurement error, allowing for investigation of its potential impacts on evolutionary inference. We envision a wealth of applications of TraitTrainR, and we demonstrate one such example by examining the problem of evolutionary model selection in three empirical phylogenetic case studies. Collectively, these demonstrations of applying TraitTrainR to explore problems in model selection underscores its utility and broader promise for addressing key questions, including those related to experimental design and statistical power, in comparative biology. TraitTrainR is developed in R 4.4.0 and is freely available at https://github.com/radamsRHA/TraitTrainR/, which includes detailed documentation, quick-start guides, and a step-by-step tutorial.

Design of Oral English Teaching Quality Evaluation System Based on AHP-Fuzzy Algorithm

In the evolving landscape of English oral language instruction, the integration of online and offline (blended) teaching methodologies has emerged as a significant approach to enhance learning outcomes. This study addresses the need for a robust and nuanced evaluation framework capable of assessing the quality of blended English oral language teaching. Motivated by the limitations of traditional evaluation methods in capturing the complexities and subjective nuances of blended teaching environments, we propose a novel evaluation model that leverages the Analytic Hierarchy Process (AHP) and Fuzzy Association Analysis. This paper outlines a systematic approach to construct a comprehensive evaluation indicator system tailored to the specific demands of English oral language teaching. Utilizing AHP, we determine the relative weights of various evaluation indicators, laying a solid foundation for a structured assessment framework. Subsequently, Fuzzy Association Analysis is employed to handle the inherent uncertainties and subjectivities associated with teaching quality assessment, thereby facilitating a more accurate and holistic evaluation. An empirical case study is presented to demonstrate the practical application of our proposed AHP-Fuzzy model in evaluating the quality of a specific blended English oral language teaching program. The results underscore the model’s effectiveness in providing a detailed and nuanced assessment of teaching quality, highlighting its superiority over traditional evaluation methods in addressing the complexities of blended teaching environments.

The Effectiveness of Digital Learning Platforms in Enhancing Student Engagement and Academic Performance

This review explores the factors influencing the effectiveness of digital learning platforms (DLPs) in enhancing student engagement and academic performance. It identifies key factors such as technological infrastructure, the role of instructors, and student characteristics, which significantly impact the effectiveness of DLPs. Technological infrastructure, including platform availability, network connectivity, and device requirements, plays a crucial role in ensuring accessibility and usability. The instructor's role in adopting active teaching strategies and providing personalized support is also essential for maximizing student success in digital learning environments. Furthermore, student characteristics such as prior knowledge, learning preferences, and technological proficiency influence their ability to engage with and benefit from DLPs. The review presents evidence from empirical studies, case studies, and meta-analyses that demonstrate the positive impact of digital platforms on student engagement and academic outcomes, particularly in blended learning environments. The discussion emphasizes the importance of personalized learning and the need for further research in areas such as cross-cultural comparisons, long-term effectiveness, and equity in access to technology. Recommendations for higher education institutions to optimize the use of DLPs and ensure equitable access for all students are also provided.

A Comprehensive Analysis of The Retail Giant: An In-Depth Study of Costco

As a leader in the US membership-based warehouse retail chain, Costco provides consumers with high-quality and low-price goods through high-volume procurement and a streamlined supply chain and cultivates a loyal customer base through the membership fee model. This study provides an in-depth analysis of Costco's market performance, competitive advantages, SWOT analysis, and risk assessment to evaluate the company's operating conditions and development prospects comprehensively. The financial data shows that Costco's revenue continues to grow, and profitability is solid. However, it still faces increasing competitive pressure from online retailers and risk factors such as economic volatility and supply chain disruptions. According to the study, Costco should actively invest in digital transformation, explore multichannel retail strategies, and focus on expansion opportunities in emerging markets. At the same time, companies must continue to focus on cost control and operational efficiency and strengthen cybersquatting and sustainability initiatives. Through internal and external training, Costco can consolidate its leading position in the retail industry, navigate the rapidly changing market environment, and achieve long-term stable growth. Based on empirical analysis and case studies, this study aims to objectively evaluate Costco's strengths and weaknesses and provide reference suggestions for its future development.

Analysis of the Resolution Process for Fiduciary Guarantee Embezzlement in the Criminal Investigation Unit of Payakumbuh Police

One of the criminal acts related to assets is embezzlement, which often occurs within financial or banking institutions. The increasing public reliance on financial institutions for business and trade activities indicates a growing demand for goods and services. This research aims to analyze the resolution process for fiduciary guarantee embezzlement and identify the challenges and efforts undertaken by the Criminal Investigation Unit of the Payakumbuh Police. Employing empirical research methods, including interviews and case studies, analyzed through a descriptive-qualitative approach, this study utilizes primary data. The findings indicate that in 2023, out of 22 reported cases of fiduciary guarantee embezzlement, only 4 were resolved. The resolution process prioritized out-of-court settlements. However, challenges include the reluctance of fiduciary givers to respond to police summons. Efforts have been made to locate the fiduciary givers and the associated guaranteed objects.

Le rôle des proximités cognitives différenciées dans le changement organisationnel

Abstract Enterprise, as human endeavours, is often faced with dilemmas that threaten their growth, if not their very existence. In some situations, change is the reasonable recourse for setting the record straight. Africa’s small and medium-sized enterprises (SMEs) are no exception, although some present more contrasting realities that call for profound change. This text presents an empirical case of an African SME exposed to internal cultural shocks that are hindering its growth. A ‶management situation″ that cannot be accommodated by single models as a solution to be implemented. Our research strategy is based on a case study approach, mobilizing data through a long series of participant observations. Keywords: Organisationnel-Change; Cognitive-Proximity; management; Africa

Abundance-mediated species interactions.

Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance-mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non-detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease- or predator-mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three-species network involving coyotes (Canis latrans), fishers (Pekania pennanti), and American marten (Martes americana) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance-mediated interactions rather than simple co-occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research.

Application of Mixed-Mode Ventilation to Enhance Indoor Air Quality and Energy Efficiency in School Buildings

Indoor air quality and energy efficiency are instrumental aspects of school facility design and construction, as they directly affect the physical well-being, comfort, and academic output of both pupils and staff. The challenge of balancing the need for adequate ventilation to enhance indoor air quality with the goal of reducing energy consumption has long been a topic of debate. The implementation of mixed-mode ventilation systems with automated controls presents a promising solution to address this issue. However, a comprehensive literature review on this subject is still missing. To address this gap, this review examines the potential application of mixed-mode ventilation systems as a solution to attaining improved energy savings without compromising indoor air quality and thermal comfort in educational environments. Mixed-mode ventilation systems, which combine natural ventilation and mechanical ventilation, provide the versatility to alternate between or merge both methods based on real-time indoor and outdoor environmental conditions. By analyzing empirical studies, case studies, and theoretical models, this review investigates the efficacy of mixed-mode ventilation systems in minimizing energy use and enhancing indoor air quality. Essential elements such as operable windows, sensors, and sophisticated control technologies are evaluated to illustrate how mixed-mode ventilation systems dynamically optimize ventilation to sustain comfortable and healthy indoor climates. This paper further addresses the challenges linked to the design and implementation of mixed-mode ventilation systems, including complexities in control and the necessity for climate-adaptive strategies. The findings suggest that mixed-mode ventilation systems can considerably lower heating, ventilation, and air conditioning energy usage, with energy savings ranging from 20% to 60% across various climate zones, while also enhancing indoor air quality with advanced control systems and data-driven control strategies. In conclusion, mixed-mode ventilation systems offer a promising approach for school buildings to achieve energy efficiency and effective ventilation without sacrificing indoor environment quality.

The Swinging Pendulum of the Game Nations Play in International Relations: A Duplicity Diplomacy

Purpose: This paper endeavours to critically interrogate the concept of "duplicity diplomacy," positing it as an essential framework for understanding the oscillating strategies employed by states amidst the complexities of contemporary international relations. The aim is to unveil the inherent contradictions and strategic necessities that underlie this phenomenon, particularly in the context of an increasingly multipolar global landscape. Materials and Methods: The research employs a qualitative methodology that integrates a multi-faceted analysis of empirical case studies involving significant geopolitical players. This approach encompasses semi-structured interviews with seasoned diplomats to capture experiential insights, a comprehensive content analysis of diplomatic communications to identify patterns and nuances in language and intent, as well as systematic reviews of contemporaneous media portrayals to contextualize public perceptions. By triangulating these methods, the study aims to enrich the understanding of duplicity in statecraft. Findings: The findings indicate that duplicity diplomacy transcends a mere catalogue of deceit, emerging as a strategic necessity reflective of the intricate complexities and contradictions that characterize our current multipolar world. Empirical illustrations reveal how states frequently oscillate between cooperative rhetoric and competitive actions, engaging in ostensible displays of loyalty while simultaneously pursuing self-interested goals through subterfuge. Notably, instances of strategic alliances undermined by covert operations serve to illustrate the double-edged nature of duplicity, where short-term gains often precipitate long-term repercussions that undermine international trust and stability. Implications to Theory, Practice and Policy: The analysis raises substantial questions regarding the ethical frameworks governing diplomatic practice in the context of growing global interdependence. It posits that as the stakes of international interactions escalate, the propensity for duplicity in state behaviour is likely to intensify, necessitating a critical re-evaluation of both scholarly and practical approaches to diplomacy. This discourse invites policymakers and scholars alike to consider how established norms around transparency and accountability can be reconciled with the inherent contradictions of statecraft.

Institutional entrepreneuring for energy poverty: The role of boundary work in developing a collaborative product-service system for household appliances

Institutional entrepreneuring for energy poverty: The role of boundary work in developing a collaborative product-service system for household appliances

Sustainable Water Management in Urban Areas through Smart Water Circulation Systems

Abstract Urbanization is a significant global trend that profoundly impacts water security. By mid-century, a large majority of the global population is expected to reside in urban areas, intensifying challenges related to water scarcity. The International Water Management Institute forecasts that most of the world’s population encounters physical and economic water shortages. In response to these challenges, the potential of recycled water is increasingly being recognized, with global capacity for water reuse projected to rise significantly over the coming years. Implementing smart water circulation systems in urban environments is essential for maintaining water balance and enhancing water use efficiency. This approach involves the integration of diverse recycling technologies with smart water networks, allowing for real-time monitoring and optimization of water resources. Initial applications of these systems in parks and other urban spaces provide valuable opportunities for testing and evaluation. The present study aims to develop a comprehensive concept for smart water circulation systems by analyzing various water treatment technologies, assessing their practical applications in urban settings, and creating frameworks for effective implementation. Through empirical analysis and case studies, this research offers practical insights for policymakers and urban planners to address the pressing challenges of water scarcity, thereby contributing to sustainable water use and improved water security in urban areas.

Redefining Newsrooms: The Role of Artificial Intelligence in Shaping Journalism's Future

This paper seeks to justify why journalism is at the cutting edge of this revolution with Artificial Intelligence (AI); it has become an essential component of various industries. In this study, the author examines the effects of the integration of AI into the current news media industry with an emphasis on the use of AI in executing analytic functions such as writing and verification of information. As for strong points and prospects, AI contributes improvements in terms of effectiveness and time efficiency, yet it brings into focus certain drawbacks concerning ethical aspects of carrying fake news, distorted information, etc., alongside the problem of algorithms’ credibility of algorism-based journalism. In this empirical qualitative case study, the author examines the benefits and limitations of AI’s implementation in journalism. On this point, it presents literature gaps that exist on the effects of AI on ethical considerations and looks at how such organizations can balance the need to use technology and still produce work of the highest ethical standards. According to the findings, while AI may step up the accuracy and credibility that is required in news dissemination, its abuse may also lead to increased biased and fake news. Overall, this research calls for adopting AI technologies in newsrooms, but only after putting this article’s findings into practice alongside human oversight and ethics. Finally, the paper concludes the future of AI journalism and emphasizes sustainable and more responsible ways to create technological advancement within the field of Journalism to make more truthful and reliable news.

Human Factor in Cybersecurity: Behavioral Insights into Phishing and Social Engineering Attacks

In this paper, we explore the role of human behavior in cybersecurity by looking at phishing and social engineering as an example. It will explore the role that psychological and behavioral factors play as vulnerabilities and what may be done to reduce the risk of human error. The methodology used in the study is a systematic review involving existing literature from empirical studies, case analysis, and theoretical frameworks. Part of this research integrates human factors in cybersecurity by integrating findings from psychology, information technology, and organizational behavior on human factors in cybersecurity. Results from the study demonstrate that phishing and social engineering succeed due to cognitive biases, low awareness, and lack of training. It also identifies effective countermeasures: Minimum susceptibility can be reduced through tailored training programs, behavioral nudges, and technical interventions. The research shows that behavioral insights have to be included in the cybersecurity strategy. This increases the organization's overall security posture across all systems, and the value comes from designing interventions to address human vulnerabilities. From a social perspective, the outcomes accentuate the need for broad training and identification battles in people and networks of people. In this study, we offer a novel, interdisciplinary view of human factors in cybersecurity. This book aims to connect the dots between behavioral science and cybersecurity practice, providing action-oriented findings to researchers, practitioners, and practitioners who want the human element out of cyber risk.

Ethnic Identity: Research by Central Asian Scientists

Globalization has changed some aspects of ethnic identity. On a theoretical basis, this article examines the analysis of studies of ethnic identity conducted by scientists in Central Asia. The maintenance and development of ethnic identity in the face of globalization and sociopolitical upheavals is the main topic of this study. Various research approaches to defining ethnic identity, the main stages of its formation, and the influence of political, historical, and sociocultural processes on the formation and change of ethnic identity are considered. Drawing upon research from diverse disciplines such as anthropology, political science, sociology, and psychology, the article delves into the complexities of ethnic identity formation, its significance, and its impact on individuals and communities. Using data from 17 scientific papers indexed by the keyword “ethnic identity” in the Scopus database, the article identifies key factors influencing the formation and understanding of ethnic identity. The author summarizes various approaches to the study of ethnicity, analyzes the factors affecting the formation of ethnic identity, and presents the main conclusions made by Central Asian researchers. Through a synthesis of empirical studies, theoretical frameworks, and case analyses, the article offers insights into the multifaceted nature of ethnic identity within the region. The article represents an important contribution to political science and cultural and sociological aspects of ethnic identity and can be used for further research. Our research reveals a significant interdependence between ethnic identity and historical-political contexts, showing how these factors shape contemporary social reality. Research findings underscore the value of viewing ethnic identity holistically and offer a paradigm for promoting social cohesiveness and cultural continuity in Central Asia.

Green, Alternative or Business as Usual? Critical Geographies of Sustainable Finance

AbstractIn recent years, a growing number of contributions on green finance have emerged, not only within economic geography but also increasingly from disciplines beyond it. With this Special Issue, we aim to engage with the ongoing debate around green and sustainable finance and its challenges, including concerns over greenwashing. Our extended editorial provides structure to this complex discussion by identifying four primary strands of literature that frame the field. Two of these strands adopt a more critical stance, combining analytical approaches and rigorous assessments that question the impact and ‘authenticity’ of green and sustainable finance schemes, approaches and policies. Most of the contributions and empirical case studies featured here align with these critical perspectives, which are introduced in greater depth in the second part of this editorial.