Empirical Case Research Articles

Sustainable Corporate Banking Strategies and Emerging Market Opportunities: Advancing the U.S. Financial Sector through Innovation and Global Partnerships

Sustainable corporate banking strategies are increasingly recognized as pivotal to enhancing U.S. financial institutions’ competitiveness and long-term growth. This paper investigates how organizational agility, operational efficiency, and innovation adoption reinforce banks’ resilience within volatile global environments. By synthesizing insights from recent empirical findings and case studies, we illustrate how cutting-edge technologies such as Artificial Intelligence (AI), Robotic Process Automation (RPA), and big-data analytics streamline complex corporate banking processes and bolster strategic partnerships with fintech enterprises. In turn, these collaborations catalyze the development of specialized financial services, ESG-aligned lending programs, and product portfolios tailored to the specific realities of emerging markets. Empirical evidence suggests that organizational structures supporting flexibility and robust risk-management frameworks enable institutions to navigate regulatory heterogeneity, leverage innovative funding mechanisms, and deliver sustainable value across diverse geographies. Additionally, the proliferation of blockchain-based payment infrastructures and integrated analytics platforms proves instrumental in reducing costs and expediting cross-border transactions. Through a comparative assessment of corporate banking’s digital transformation and market expansion strategies, we emphasize how banks can optimize operational capabilities, broaden client bases, and strengthen global networks. This research ultimately contributes to the existing body of knowledge by articulating a clear set of recommendations for U.S. financial institutions seeking to expand into emerging markets sustainably, balancing risk mitigation with socioeconomic impact.

Sustainable Innovation Management: Balancing Economic Growth and Environmental Responsibility

Sustainable innovation management (SIM) is increasingly recognized as a pivotal framework for addressing the dual challenges of economic growth and environmental responsibility. In response to escalating global pressures, this review explores how SIM can drive sustainable development by balancing profitability with ecological stewardship. Drawing on recent academic and industry sources, the paper examines the intersection of circular economy principles, emerging technologies, and policy frameworks in shaping sustainable innovation strategies. The review is structured around three key pillars: the integration of technologies, such as artificial intelligence, blockchain, and the Internet of things in sustainable operations; the influence of regulatory drivers, including carbon pricing and environmental, social, and governance standards; and empirical case studies that highlight both challenges and success factors in SIM adoption. By synthesizing real-world applications across sectors and geographies, this study provides qualitative insights and quantitative indicators (e.g., CO2 reduction, return on investment, material reuse rates) to inform practical strategies for business leaders and policymakers. Addressing gaps such as the lack of global harmonization in sustainability metrics and the under-representation of developing economies, this review contributes to a more inclusive and actionable understanding of SIM. This paper concludes by offering future research directions and policy recommendations aimed at accelerating the transition toward sustainable and circular business models.

New Quality Productive Forces, Factor Allocation, and High-Quality Development of New Energy Vehicle Enterprises

The rapid development of new quality productive forces has brought both opportunities and challenges to the high-quality growth of new energy vehicle enterprises. This study investigates how factor allocation optimization can facilitate sustainable development in this emerging industry through theoretical analysis and empirical case studies. By examining the dynamic relationship between technological innovation, resource allocation efficiency, and enterprise performance, the research identifies key drivers for industrial upgrading. The findings demonstrate that effective factor reallocation significantly enhances production efficiency and innovation capability in new energy vehicle companies. Case studies reveal that enterprises adopting advanced production technologies while optimizing capital and human resources achieve notable improvements in market competitiveness. The study proposes practical recommendations for policymakers and industry practitioners, emphasizing the importance of establishing supportive institutional environments and promoting cross-sector collaboration. These insights contribute to the ongoing discourse on industrial transformation and provide valuable references for achieving high-quality development in strategic emerging industries. The research outcomes offer theoretical foundations for understanding the evolution of new quality productive forces and practical guidance for enterprise-level decision-making in the rapidly changing automotive sector.

Data-Driven Environmental Risk Management and Sustainability Analytics (Second Edition)

Environmental risk management (ERM) and sustainability analytics have undergone a paradigm shift from reactive, compliance-based frameworks to advanced, predictive, and data-driven methodologies. This second edition of "Data-Driven Environmental Risk Management and Sustainability Analytics" critically explores the integration of contemporary technologies such as machine learning (ML), artificial intelligence (AI), blockchain, Internet of Things (IoT), quantum computing, and cloud computing within ERM frameworks. The manuscript reviews the evolution of ERM strategies, emphasizing the transformative role of predictive analytics, real-time monitoring, and multi-stakeholder collaboration in addressing global environmental challenges including climate change, biodiversity loss, and resource depletion. Through empirical case studies on coastal flooding and urban water resource management, the research demonstrates the practical effectiveness of advanced analytics in mitigating environmental risks and enhancing resilience. Furthermore, the manuscript highlights key policy frameworks and governance models promoting transparency, data security, and sustainable development practices globally. The study concludes with actionable recommendations and identifies research gaps concerning data integration, quantum computing applications, and the ethical dimensions of emerging technologies in sustainability analytics. This edition aims to provide policymakers, researchers, practitioners, and industry professionals with actionable insights into designing and implementing robust, data-driven environmental risk management strategies aligned with sustainable development objectives.

Coupling Analysis of “Demand–Satisfaction” for Rural Public Service Facilities Based on the Kano Model with Importance–Performance Analysis: A Case Study of Gaoqing County, Zibo City

In the context of people-oriented and high-quality development, improving the quality of rural public service facilities is an important way to promote rural revitalization. However, at present, there are problems such as imbalanced resource allocation, single service functions, and low service quality in regard to rural public service facilities in general, and the contradiction between supply and demand is becoming increasingly prominent. Only by effectively grasping the correlation between residents’ needs and their satisfaction with such facilities can the precise allocation of service facilities be carried out. In this study, Gaoqing County, Zibo City, Shandong Province, is selected as the empirical case. By applying the Kano model and Importance–Performance Analysis (IPA) through the use of questionnaire surveys and expert interviews, we develop an integrated “demand–satisfaction” analytical framework to propose targeted optimization strategies for rural public service facilities. Based on the Kano model, the essential, desired, and attractive needs of rural residents for various types of facilities were identified. Combining the IPA model, the coupling and coordination relationship between demand and satisfaction was further analyzed, and rural public service facilities were analyzed and categorized accordingly. The research results show that educational institution facilities, healthcare facilities, and market facilities have the highest demand, while cultural, sports, and technological facilities have relatively low demand. Based on the analysis results, this study proposes an optimization strategy for the classification and grading of the “demand–satisfaction” coupling relationship of public service facilities. It provides a scientific basis for the layout optimization of rural public service facilities, and also provides an effective reference for the sustainable development and service quality improvement and upgrading of rural areas.

Coordinated Multimodal Transportation Infrastructure Planning in Megacities: An Agent-AI-Discrete Network Design Problem Approach Based on Chat-GPT

The Discrete Network Design Problem (DNDP) has mainly been used in unimodal infrastructure planning in small cities. This is because it does not consider differences in traveler mode choice. To address the challenges of multimodal transportation infrastructure planning in megacities, this study proposes a new Agent-AI DNDP (AA-DNDP) framework. AA-DNDP extends the traditional DNDP by incorporating mode-choice functionality. In each simulation iteration, the Agent-AI calls Chat-GPT via API, using the attributes of the origin and destination as prompts to generate a mode choice. Based on the selected transportation mode, the Agent-AI records the associated travel time and path. By aggregating the travel times and paths across a large number of Agent-AI simulations, two key indicators are derived: average using time (AUT) and path usage frequency (PUF). These metrics are then used to evaluate the suitability of different infrastructure planning strategies. Using the DNDP framework, a large number of multimodal transportation infrastructure planning schemes for the megacity are generated. By analyzing variations in AUT and PUF across these schemes, the most suitable planning configuration is identified. Chongqing was selected as the empirical case with which to evaluate the effectiveness of the proposed AA-DNDP framework. The results demonstrate that AA-DNDP can effectively assess the rationality of existing transportation infrastructure planning and identify theoretically optimal configurations based on AUT and PUF. The case study further confirms that AA-DNDP enhances the evaluation of network efficiency and facilitates coordinated multimodal infrastructure planning, offering a more practical and data-informed approach to improving transportation systems in megacities.

Periphery Political Opposition in Algeria’s ‘HIRAK’ movement: challenging the prevailing status

ABSTRACT This paper explores the emergence of Periphery Political Opposition (PPO) in Algeria, focusing on its rise before the 2019 HIRAK protests. It examines how restrictive political conditions drove youth toward subtle, everyday forms of resistance outside traditional movements. Using sociological theories of non-movements and resistance, the study highlights how state control over media and civil society spurred new opposition actors. Through empirical cases of football fans and vloggers, and discourse analysis of their narratives, the paper shows how PPO actors have reshaped Algeria’s political sphere and contributed to broader socio-political transformations.

Research on the Positioning Models and Elemental Guarantees of Convention and Exhibition Buildings in Small and Medium-Sized Cities: Based on Empirical Case Studies

With industrial upgrading and increasingly diversified urban functions in small and medium-sized cities in China, the demand for convention and exhibition buildings has been steadily rising. However, current research mainly focuses on the planning and operation of such buildings in large cities, with a lack of systematic and targeted studies on small and medium-sized cities that have relatively limited resources and varied development orientations. According to data collection and field surveys of convention and exhibition buildings in 148 small and medium-sized cities nationwide, this paper constructs a case database and conducts in-depth research on building types and factor guarantee mechanisms. This study first employs cluster analysis to classify 73 typical cases, incorporating comparative analysis from multiple dimensions such as the city’s economic development level, characteristics of the convention and exhibition industry, primary functions, operational focus, service targets, and planning layout, based on literature review and expert opinions. It then proposes four convention and exhibition building positioning models—market type, production-based type, enclave type and comprehensive type—and analyzes the characteristics of their typical cases. Afterward, through surveys, literature reviews, and expert interviews, this study identifies relevant indicators—such as resource factors and development conditions—and applies the importance index method to select 19 core indicators. These are used to establish a factor guarantee indicator system comprising two levels: “city-related factors” and “regional-related factors”. Subsequently, by analyzing the development strategies and core support factors of different building types using the priority diagram method, this study clarifies the resource demands and development paths for each model. The results indicate that the positioning strategy for convention and exhibition buildings in small and medium-sized cities should align with local industrial foundations and stages of urban development, fostering the formation of differentiated and sustainable development models. This research offers theoretical support and practical guidance for the scientific planning and efficient construction of convention and exhibition buildings in small and medium-sized cities, contributing to improved functionality, regional economic growth, and optimized urban spatial structure.

The Influence of Green Infrastructure on the Acoustic Environment: A Conceptual and Methodological Basis for Quiet Area Assessment in Urban Regions

Urban regions represent complex acoustic environments with few respites from noise other than small or remote patches of green infrastructure (GI). Recent noise action planning in the German Ruhr region indicates that urban expansion is fueling encroachment upon GI and subsequently the loss of quiet areas. A systematic exploration of this loss in Germany is needed. An explorative systematic review on Scopus with snowballing supports the synthesis of a conceptual framework linking acoustically relevant ecosystem services with GI. Our review identifies natural quietness, abatement, connection to nature, positive soundscape perception, fidelity, and bird sound presence as sound-related ecosystem functions or services. Empirical case studies justify the need to better understand the link between GI, ecosystem services, and the acoustic environment. Guidance for quiet area assessments in the EU to address this research gap in noise action planning is an emerging topic and needs further study. To address the knowledge gap and provide quiet area assessment guidance, we present a stratified habitat-based acoustic study design for a multi-community area in the middle of the German Ruhr region. A multi-tier sample of 120 locations across eleven habitat and land use strata in the Ruhr is presented, pointing out the scarcity of protected biotopes and large biotope complexes in the study area. This work is a contribution towards a conceptual and methodological basis for quiet area assessment, especially in German and EU noise action planning.

Temporalities and change in Senegalese and Gambian self-organisation in Germany: accelerated immigration, demographic dynamics, and political opportunities

ABSTRACT Migrant associations have received an increased interest from political and institutional actors as partners in integration work over the last decade. They are also considered important civil society partners in development cooperation. At the same time, migrant associations constantly face changes in the structure and composition of the communities they service as new migrants arrive while others age and establish at their destinations. At the example of Senegalese and Gambian associations in Germany, we analyse modalities of change in associations and their associative landscape. Their case is politically relevant and analytically instructive because of the stark growth of their communities in recent years. Recently-arriving migrants have different needs as asylum seekers than those who have already established themselves and their associations. We develop a temporality framework that incorporates factors triggering associative change in three dimensional vectors: legal-administrative conditions, demographic composition and political opportunity structures. We exemplify their impact of creating various processes of continuity and change through our empirical case. The research is based on qualitative research and 21 semi-structured interviews with representatives of Senegalese and Gambian migrant organisations conducted between September 2020 and May 2021.

Populism in Central and Eastern Europe: Manifestations and Impact in Interdisciplinary Perspective

In light of the increasing autocratization of Central and Eastern Europe (CEE), this thematic cluster focuses on the many manifestations of (right-wing) populism and illiberalism and their impact on CEE politics and societies. The interdisciplinary approach constitutes the main contribution of this cluster, which includes four articles that analyze specific aspects of the “cameleon” of populism. While much of the literature explores the political side of populism, we shed light on its relation to political culture and gender and to contexts such as post-communist economies and war. The post-communist CEE allows us to draw broader conclusions about the manifestations and consequences of populism in power due to the variety of empirical cases within this relatively small region. Not least, the political and institutional success of populism in CEE transcends its physical borders, as leaders like Orbán have long been role models for populists such as Donald Trump, Geert Wilders, and others. Emerging from the EU-funded Marie Skłodowska-Curie Innovative Training Network “Delayed Transformational Fatigue in Central and Eastern Europe: Responding to the Rise of Illiberalism/Populism” (FATIGUE), this cluster is a collaborative project of early career scholars.

An Analysis of the Reasons for MINISO's Marketing Success: A Comprehensive Application of SWOT and Its Submodels

In the era of new retail, digitization and consumption upgrading are transforming the global consumer goods market. The trends of high cost performance and IP co-branding, led by Generation Z, are restructuring the consumer ecology. Traditional retail brands are facing homogenized competition due to e-commerce, but MINISO has achieved counter-trend growth through IP co-branding, supply chain integration, and social media operations. Positioning as Japanese design + extreme cost-effectiveness, the brand has completed the globalization layout since 2013, covering more than 100 countries, and exceeding 10 billion in revenue in 2022. Its innovative marketing strategy has become the focus of academic research. This paper utilizes the SWOT model and its sub-models, combined with empirical cases, to systematically analyze its strategic advantages and potential risks, providing theoretical references for the transformation and upgrading of the retail industry. It is found that MINISOs success stems from its ability to align with the priorities of the SWOT model and translate its strategy into quantifiable actions.

Traditional vs. Non-Traditional Teaching in Secondary Education: A Comparative Analysis

This article provides a comprehensive theoretical comparison of traditional (teacher-centered) and non-traditional (student-centered) instructional methods in secondary education. We review the learning theories underpinning each paradigm – including behaviorism, cognitivism, constructivism, socio-cultural theory, and others – and analyze how these philosophies shape classroom roles and practices. Key dimensions of comparison include the teacher’s and students’ roles, instructional style, classroom environment, and assessment strategies. Empirical studies and case examples illustrate real‐world implementations: for instance, a meta-analysis found that project-based learning significantly outperforms traditional methods in boosting secondary students’ academic outcomes, and a field study in Kolkata reported higher engagement and achievement under constructivist (student-centered) teaching. We discuss pedagogical advantages and challenges of each model: traditional methods offer structure and clear accountability (often easier to manage in large classes) but tend to foster passive learning and rote memorization. In contrast, non-traditional approaches (e.g. inquiry-based, collaborative learning) promote critical thinking and motivation, but require significant teacher preparation, effective scaffolding, and new assessment methods. We conclude that a blended approach – integrating direct instruction with active, project-based, and collaborative elements – is most promising for secondary settings. Such a balanced paradigm can leverage the strengths of both models to prepare students with 21st-century skills and deeper understanding.

An empirical case study on the effect of Al Aweer sewage plant odours on housing prices in Dubai’s International City

Purpose This study aims to investigate the impact of proximity to the Al Aweer sewage treatment plant (STP) on residential property values in Dubai’s International City. It hypothesises that properties closer to the plant experience greater value diminution due to odour emissions. Design/methodology/approach The research uses traditional hedonic pricing models to analyse the impact of odour emissions on property values. Advanced machine learning techniques and spatial econometric models were considered but deemed less appropriate due to the small, homogeneous data set. The study uses a comprehensive data set of residential flats within International City. Findings The results indicate a significant negative impact of odour emissions on property values. Properties closer to the STP show a marked decrease in value, highlighting the importance of environmental factors in real estate valuation. Originality/value This study is unique in the United Arab Emirates, focusing on the environmental issue of odour emissions in a stigmatised area. It provides valuable insights for policymakers and real estate professionals, emphasising the need for accurate environmental impact assessments in property valuation.

Inclusive Design Process for User-Centered Wearable Products: A Case Study on Lumbar Support for Older Women with Chronic Low Back Pain

This study proposed an Inclusive Design Process Model for User-Centered Wearable Products (IDP-UW), suggesting opportunities, expected outcomes, and practical approaches guided by key design principles to ensure user inclusion and equitable access in the design process. To validate the model, an empirical case study was conducted to develop wearable lumbar support for older women with chronic low back pain. Iterative user interactions were integrated in the inclusive design process. The final prototype, developed through the process, incorporated form factors and materials reflecting the anthropometric characteristics and preferences of participants. Multidimensional evaluations confirmed that the final prototype demonstrated strong performance in walking balance, human error reduction, and subjective satisfaction. Moreover, participants expressed that their participation in the design process enriched their experience, fostering a sense of involvement, authority, achievement, and engagement. This study offers actionable insights addressing the needs of marginalized users, especially for wearable products where body-product interactions are crucial.

Subjective Evaluation of Place Environmental Quality in Conference and Exhibition Buildings in Small- and Medium-Sized Cities: An Empirical Case Study

The environmental quality of conference and exhibition places in small- and medium-sized cities plays a crucial role in attracting exhibitors, fostering the growth of the conference and exhibition industry and enhancing the market competitiveness of these places. However, past decision makers have often adopted planning models from large cities, neglecting the interaction between conference and exhibition places in smaller cities and local lifestyles as well as urban environments. From an “environment-behavior” perspective, this study reveals the unique interaction mechanisms between exhibitors and the built environment within such venues. Moving beyond the limitations of traditional research that focused solely on physical indicators, we place particular emphasis on exhibitors’ behavioral adaptations and their overall exhibition experience in the convention environment. To address this gap, this study employs a mixed-method approach that integrates field surveys, interviews, and questionnaires to systematically collect data from 10 representative cases. First, a preliminary study was conducted to establish an evaluation index system for place environmental quality. Through regression analysis, six key indicators—such as promotional atmosphere, site accessibility, and surrounding urban development conditions—were identified as significant factors influencing place quality. Second, subjective evaluations were conducted based on users’ actual experiences and experts’ professional insights, leading to the development of an importance–performance analysis model to assess value expectations and place environmental performance. The results indicated that users had high expectations for elements such as parking availability, transportation facilities, and the surrounding commercial atmosphere. In contrast, experts emphasized the significance of proximity to urban transportation hubs, site accessibility, and the spatial orientation of public spaces in determining environmental quality. Moreover, differences in evaluations among experts from various fields revealed notable variations in focus and priority considerations. Finally, based on a statistical analysis of the survey results, this study proposes three design recommendations—“adaptation, attraction, and quality enhancement”—to optimize the environmental quality of conference and exhibition places in small- and medium-sized cities, offering both theoretical and practical guidance for future planning, design, and evaluation.

Countering academisation of VET through local collaboration: A situational analysis from Western Norway

The article aims to demonstrate that although the academisation of vocational education and training (VET) is embedded in larger formations of symbolic power, it is a complex and non-linear process. One unfortunate aspect of academisation is the regulation of VET by external authorities (Billett, 2014), and one way to remedy it is to involve VET actors in shaping vocational education’s purposes (Billett, 2010). The article argues that ethnographic research is essential to understanding the meanings of the academisation of VET. Although taking a particular empirical case as the point of departure, the article will primarily develop a conceptual and methodological framework for dealing with the complexity of the actors, social practices, and institutions involved in shaping the purposes of vocational knowledge practices. The case informing my theoretical reflections is a network of relationships between school leaders, teachers, instructors in companies, a business association, and others who collaborate to provide vocational students with an apprenticeship in a region in Western Norway. The aim is to motivate local youth to choose vocational education, build better connections between schools and workplaces, and thus strengthen VET’s relevance, quality, attractiveness, and social status in the region. I argue for the importance of contextualising academisation processes and the multiple and contradictory ways they influence vocational education. It is important to identify local manifestations and consequences of academisation and the diverse ways local actors in the field of VET deal with them.

Optimizing Employee Recognition Through AI-Driven Insights

As artificial intelligence transforms industries, employee recognition practices are evolving beyond traditional methods to meet the needs of a digitally native workforce. This article synthesizes research on effective recognition strategies while examining how AI can enhance these practices through data-driven insights and personalization. It highlights AI's capacity to identify achievements in real-time and tailor recognition to individual preferences, while acknowledging challenges related to fairness, transparency, and the essential role of human judgment. Drawing on empirical evidence and case studies from technology and healthcare sectors, the article provides practical frameworks for HR leaders to implement AI-powered recognition systems that maintain appropriate human oversight, address algorithmic bias through diverse teams, and provide transparency into decision processes. Organizations that successfully balance technological capabilities with meaningful human involvement can achieve significant improvements in employee satisfaction, motivation, and retention while creating recognition practices that scale effectively in the age of AI.

Policy Optimization for Personalized Interventions in Behavioral Health

Problem definition: Behavioral health interventions, delivered through digital platforms, have the potential to significantly improve health outcomes through education, motivation, reminders, and outreach. We study the problem of optimizing personalized interventions for patients to maximize a long-term outcome, in which interventions are costly and capacity constrained. We assume we have access to a historical data set collected from an initial pilot study. Methodology/results: We present a new approach for this problem that we dub [Formula: see text], which decomposes the state space for a system of patients to the individual level and then approximates one step of policy iteration. Implementing [Formula: see text] simply consists of a prediction task using the data set, alleviating the need for online experimentation. [Formula: see text] is a generic, model-free algorithm that can be used irrespective of the underlying patient behavior model. We derive theoretical guarantees on a simple, special case of the model that is representative of our problem setting. When the initial policy used to collect the data is randomized, we establish an approximation guarantee for [Formula: see text] with respect to the improvement beyond a null policy that does not allocate interventions. We show that this guarantee is robust to estimation errors. We then conduct a rigorous empirical case study using real-world data from a mobile health platform for improving treatment adherence for tuberculosis. Using a validated simulation model, we demonstrate that [Formula: see text] can provide the same efficacy as the status quo approach with approximately half the capacity of interventions. Managerial implications: [Formula: see text] is simple and easy to implement for an organization aiming to improve long-term behavior through targeted interventions, and this paper demonstrates its strong performance both theoretically and empirically, particularly in resource-limited settings. Funding: The authors are grateful for financial research support from the MIT Sloan Health Systems Initiative. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0548 .

Transforming Education Through ICT4D: An empirical review on digital tools and innovative learning solutions

This paper presents an empirical review of the transformative potential of Information and Communication Technologies for Development (ICT4D) in the education sector. It explores how digital tools and innovative learning solutions are reshaping the educational landscape, particularly in developing countries, by enhancing access, quality, and equity in education. The review draws upon recent empirical studies, case studies, and policy reports published between 2020 and 2023 to provide an up-to-date analysis of the opportunities, challenges, and best practices in leveraging ICT4D for educational transformation. The findings highlight the significant progress made in the adoption and integration of digital technologies in education, such as mobile learning, online platforms, and educational software. However, the review also reveals persistent challenges, including the digital divide, infrastructure limitations, and the need for teacher training and support. The paper concludes by proposing a framework for harnessing the transformative power of ICT4D in education, emphasizing the importance of context-specific approaches, multi-stakeholder collaboration, and a focus on sustainability and scalability.