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AI-Powered Transformation in Home Textiles: Efficiency, Sustainability, and Consumer Experience
Background The home textile sector, including bed linens, towels, and curtains, is under pressure from rising consumer expectations, stricter sustainability standards, and supply chain uncertainties. Artificial intelligence (AI) is emerging as a strategic enabler, offering innovative solutions across design, production, quality control, logistics, and customer interaction. Methods The scope includes a scoping review (20152025) of peer-reviewed literature and reputable industry reports, supplemented by documented corporate cases in home textiles. Inclusion required explicit metrics (e.g., yield %, energy or water usage, forecast error) or reproducible descriptions of AI workflows. Results Analysis shows that AI improves efficiency and competitiveness through multiple pathways: (i) trend forecasting and generative design tools; (ii) optimized color matching and dyeing via machine learning and spectral systems; (iii) automated defect detection and predictive maintenance using computer vision and IoT; (iv) cutting-room efficiency through AI nesting algorithms; (v) supply chain resilience with demand sensing and drone-assisted inventory checks; and (vi) blockchain-based platforms that ensure cotton traceability. On the consumer side, AI enhances personalization and supports the growth of smart bedding products. These applications reduce waste, improve product quality, and reinforce sustainability initiatives. Conclusion AI complements rather than replaces human creativity and craftsmanship. Organizations in the home textile industry that embrace AI strategically across design studios, mill operations, and retail channels can achieve measurable improvements in productivity, sustainability, and consumer trust, positioning themselves for long-term competitive advantage. 2025, Textile Association (India). All rights reserved. -
Modeling Flood-Induced Cascading Disruptions in the Indian Electronics Supply Chain Using Influence Network Analysis
This study investigates flood induced disruptions in the Indian electronics supply chain using influence network analysis. Monsoon floods are recurring hazards that significantly impact economic activities, logistics, and industrial productivity. This study integrates district-level rainfall data (2020 to 2025) with supply chain network models to quantify cascading failures. The methodology applies rainfall thresholds (? 300 mm/month) to identify flood-prone districts and constructs a stochastic influence matrix representing inter-firm dependencies. Flood propagation dynamics are modeled iteratively with a propagation coefficient (? = 0.6) and convergence threshold (? = 10-4). The resulting disruption profiles are mapped onto company-level revenues calibrated to India-specific scales, adjusted for disruption durations (two months per year). This approach produces district and company-level economic loss estimates consistent with observed flood impacts (e.g., Chennai 2015 flood losses of USD 3 to 5 billion). Key contributions include linking meteorological hazards to systemic supply chain failures, demonstrating economic vulnerabilities at district and sectoral scales, and providing a framework for resilience planning. 2026 Binghamton University Libraries. All rights reserved. -
Reducing Systemic Bias in Behavioral Targeting Using Explainable AI: The HARMONIA Complex Systems Approach
Behavioral targeting is a key part of the modern advertising web's algorithmic engine. However, it is unclear whether optimization processes worsen bias, promote unchecked spread in filter bubbles or lower overall users' trust levels. This paper introduces HARMONIA (Holistic Adaptive Regulatory Model for Optimizing Non-transparent Intelligent Advertising), a comprehensive, data-driven Explainable Artificial Intelligence (XAI) framework aimed at transforming behavioral targeting via transparency, interpretability, and adaptive ethical regulation. This paper conducted a comprehensive Explorative Data Analysis (EDA) on the public Criteo Display Advertising Dataset, which contains over 45 million records, to identify patterns in high-dimensional user-ad interaction space. This analysis uncovered latent behavioral signals that affect the relevance of ads based on users' online behavior. The analysis identified four interrelated behavioral dynamics: ad fatigue attenuation, diurnal engagement oscillations, device-driven preference divergence, and category-affinity dominance. These dynamics served as the foundational architectural principles for HARMONIA's design. The method uses gradient boosted prediction models and a multilayer explainability stack that includes SHAP for global interpretability, LIME for local surrogate approximation, and counterfactual reasoning for causal transparency. Quantitative evaluation indicates that HARMONIA maintains relevance accuracy (approximately 1.2% CTR), achieves a 31% enhancement in transparency metrics, and a 27% improvement in user-trust indices, while concurrently reducing systemic entropy by nearly one-third. This research redefines personalization to be self-explanatory and ethically sound AI by incorporating explainability as a regulatory mechanism in the adaptive ecosystem of complex digital advertising. This system takes explainable computational marketing from an idea to a full-scale implementation. 2026 Binghamton University Libraries. All rights reserved. -
Complex Systems Mapping of Fiscal Growth Dynamics at Strategic Maritime Chokepoints Using Time-Series Slopes
This study examines how maritime and trading states allocate public resources between defence, health, and economic growth around three strategic chokepoints the Strait of Malacca, the Strait of Hormuz, and the Suez Canal. The analysis extends the classic guns versus butter framing by treating defence and health spending as co-evolving components of an interconnected fiscal-growth system. Using World Development Indicators data (1999-2024), trend slopes are estimated for military spending (% of GDP), healthcare spending (% of GDP), and GDP growth (annual %). Two derived indicators are computed, a defence-to-health slope ratio (military slope/health slope) and a fiscal-balance proxy (health slope - military slope). Augmented Dickey-Fuller tests are used to assess stationarity (unit-root behaviour), and Granger causality tests to examine whether GDP growth temporally precedes changes in spending shares. Hormuz chokepoint states show non-negative health slopes (e.g., UAE +0.1199) alongside negative GDP growth slopes in some cases (e.g., Qatar -0.4754). Suez chokepoint states exhibit negative defence slopes (e.g., Egypt -0.0899) with comparatively small or negative health slopes (e.g., Egypt -0.0211). The United States is included as an external benchmark because it is the largest trading nation by monetary trade volume and is directly or indirectly coupled to chokepoint flows; it shows health +0.1758 and military -0.0116 (ratio -0.0657). These quantified configurations support chokepoint-specific fiscal regimes and provide a compact visual map of security, health, growth dynamics in a small integrated complex systems. @ Binghamton (The ORB), 2026. -
Behavioral Biases as Drivers of Complexity in Stock Markets: An Agent-Based Modeling Approach
By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and greatly increase volatility. The market shifts from a stable, rational regime to a highly volatile, complex regime characterized by contagion and fragile liquidity as the proportion of biased actors rises. Overall, the findings show that the complexity and systemic instability of emerging markets are primarily driven by behavioral heterogeneity. 2026 Binghamton University Libraries. All rights reserved. -
A Multi-Layer Complex Adaptive System Framework for AI-Driven Robo-Advisory Services
The rapid integration of Artificial Intelligence (AI) into investment advisory services has changed financial decision-making, giving rise to adaptive robo-advisory systems capable of real-time analysis, personal recommendations, and autonomous portfolio optimization. Existing research evaluates these systems primarily through technological performance or investor adoption, overlooking the complex feedback-driven interactions that emerge when AI analytics, data environments, and human behavior operate together. This study addresses this gap by conceptualizing AI-enabled robo-advisors as a multi-layered Complex Adaptive System comprising historical data, real-time data, AI analytics, investor perception, and decision-making layers. A simulation model grounded in machine learning dynamics, behavioral finance, and complexity theory is developed to capture nonlinear interactions, adaptive learning, and emergent investor responses. Results show that historical data acts as a stabilizing memory, real-time data amplifies short-term volatility, AI analytics self-organize toward performance equilibrium, and investor perception evolves through nonlinear trust thresholds that ultimately drive decision lock-in. Complexity measures reveal that adaptive intelligence is concentrated in the historical and perception layers, while the decision layer becomes increasingly deterministic as feedback loops strengthen. The findings provide a unified system-level understanding of robo-advisory ecosystems and highlight the need for governance structures that incorporate transparency, behavioral dynamics, and adaptive model monitoring. This framework offers a foundation for designing more resilient, trustworthy, and sustainable AI-driven financial advisory systems. 2026 Binghamton University Libraries. All rights reserved. -
Regional Drought Modulation by ENSO and IOD as Indicated by the Standardized Precipitation Index
Understanding the modulation of drought by large-scale oceanatmosphere teleconnections is crucial for strengthening drought prediction and resilience in India. This study investigates the influence of the El NiSouthern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on meteorological drought characteristics across India from 1950 to 2024 using the Standardized Precipitation Index (SPI) at a 12-month timescale. Drought events were quantified in terms of frequency, duration, severity, and intensity and linked to ENSOIOD variability through composite, correlation, and mediation analyses. Results reveal that El Ni events consistently correspond to widespread and severe droughts, particularly over central and southern India, with drought frequency exceeding 30% and SPI < ?1.5. Conversely, La Ni phases enhance monsoon rainfall and alleviate drought conditions across much of the subcontinent. Spatial correlations demonstrate that ENSO exerts a stronger, more coherent influence on both rainfall and SPI than the IOD, while positive IOD phases can partly offset El Ni-driven drought in limited regions. Mediation and wavelet coherence analyses confirm ENSOs dominant control at interannual (48 year) timescales and reveal secondary, episodic modulation by the IOD. These findings highlight the complex, evolving dynamics between Pacific and Indian Ocean drivers in shaping Indias hydroclimate variability. The study underscores the need for integrated ENSOIOD monitoring and inclusion of multi-ocean indicators in Indias drought early warning and seasonal forecast frameworks. 2026 Binghamton University Libraries. All rights reserved. -
Modelling Complex Psychological and Behavioral Dynamics: Analyzing Perception and Psychological Ownership in Gen Z's Re-subscription Intentions towards OTT Platforms
This study explores the complex dynamics between perception, psychological ownership, and re-subscription intentions among Gen Z users of OTT platforms, specifically examining how perceived benefits and perceived drawbacks shape user behavior and investigating the moderating role of psychological ownership in this context. The research focuses on a sample of Gen Z users from India who actively engage with OTT platforms, and data were collected through a structured questionnaire comprising three sections; a structural equation modeling (SEM) technique was applied to analyze the data obtained from 304 valid responses. The analysis reveals that perceived benefits significantly enhance Gen Z's resubscription intentions, while perceived drawbacks have a negative impact; moreover, the study highlights that psychological ownership moderates the influence of perceived drawbacks, mitigating their adverse effect on resubscription intentions. Although the study is limited to Gen Z users in India and focuses on a specific set of independent constructs, future research could expand this scope by incorporating other generational cohorts and a broader range of influencing factors to deepen the understanding of user behavior in diverse contexts. This research contributes to the broader literature on consumer behavior in the digital landscape by modeling the interaction between psychological and perceptual factors within a complex system, providing empirical evidence on the moderating role of psychological ownership and emphasizing the importance of these dynamics in designing effective engagement strategies for OTT platforms. Insights from this study underscore the significance of enhancing user perception factors to boost re-subscription rates, and industry practitioners are encouraged to focus on delivering personalized and memorable digital experiences to strengthen psychological ownership and minimize perceived drawbacks. The study also highlights practical strategies for OTT platforms, such as developing high-quality content, intuitive interfaces, and fostering a sense of community and ownership among users, with a focus on addressing perceived drawbacks and enhancing the social value of these platforms as crucial measures for retaining Gen Z users. As one of the first studies to employ complex systems modeling techniques to understand the interplay between perception factors and psychological ownership in influencing re-subscription intentions among Gen Z OTT users, the findings offer valuable insights for the online service industry to refine their service delivery and user engagement strategies. 2025, Binghamton University Libraries. All rights reserved. -
Exploring the Interplay Between Economic Growth and Sustainable Development: A Complex Systems Approach to GSDP and SDGs in Indian States
Pursuing Sustainable Development Goals (SDGs) necessitates aligning business and management practices on a global scale. This paper delves into the intricate dynamics between Gross State Domestic Product (GSDP) and SDGs across diverse states in India, offering nuanced insights to policymakers, businesses, and stakeholders. This paper explores the dynamic relationship between Gross State Domestic Product (GSDP) and the Sustainable Development Goals (SDGs) in the context of India's diverse states by applying modern machine learning techniques such as XG boost, Decision trees, and K mean clustering. The study delves into how economic growth influences the progress towards SDGs. The research integrates complex systems methodologies, combining exploratory data analysis, correlation analysis, and clustering to offer actionable insights for policymakers and businesses. The paper emphasizes the need for tailored strategies that consider the economic development stages of states to achieve sustainable development goals more effectively. Through this multidimensional approach, the study provides a comprehensive understanding of how GSDP can guide the pursuit of SDGs and proposes innovative, data-driven solutions for fostering sustainable growth across India. 2025, Binghamton University Libraries. All rights reserved. -
Orchestrating Complexity: The Art of Virtual Leadership in System Modelling
This paper explores the dynamics of virtual leadership within global remote work environments, focusing on the application of complex system modelling to understand and enhance leadership efficacy. The application of computational modelling has been a regular feature in economics, science and technology fields, however its application in virtual leadership with linkage to sport leadership appears to be a novel concept. Adopting a multidisciplinary approach, this paper incorporates Game Theory as a conceptual framework to make the leadership model more relevant and applicable that can offer simpler understanding of complex play of leadership drivers. The model incorporates five key leadership dimensional drivers such as communication, culture, motivation, trust, and technology as agents that influence change in other agents, specifically team members. The research attempts to discover approach for understanding leadership and team behavior through Relational Leadership dynamic in business as well as in sport environment. 2025, Binghamton University Libraries. All rights reserved. -
Enhancing Online Education Through Sentiment Analysis and Complex Systems Modelling
This research explores the application of sentiment analysis through the lens of complex systems modelling to enhance the quality of online certification courses, with a particular focus on global platforms such as Coursera. The COVID-19 pandemic catalyzed significant growth in online learning, creating an urgent need for adaptive and student-centric approaches to ensure relevance and effectiveness. Leveraging unstructured textual data from student reviews of courses, this study integrates methodologies from systems science, computer science, and education to address real-world challenges in online education. By employing both lexiconbased (SentiWordNet and VADER) and supervised machine learning techniques (Multinomial Naive Bayes, Support Vector Machine, and Stochastic Gradient Descent), the research conducts a detailed sentiment analysis to identify patterns, emergent behaviours, and feedback loops inherent in course design and delivery. Findings reveal that Support Vector Machine achieves the highest accuracy at 97.3%, offering insights that guide iterative improvements in course content and pedagogical strategies. The study demonstrates how interdisciplinary approaches to sentiment analysis can inform responsive education environments, aligning with broader societal goals of accessibility, inclusivity, and quality in online learning ecosystems. 2025, Binghamton University Libraries. All rights reserved. -
Leveraging Usage of AI in education: Knowledge, Attitude and Behavioral Analysis on Students
The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how students awareness, beliefs, and actions towards AI in educational situations are influenced by demographic characteristics. This research attempts to offer insights into practical methods for utilizing AI in education while addressing potential obstacles and minimizing negative effects through a thorough analysis of data gathered from students across a range of demographic backgrounds. 2025, Binghamton University Libraries. All rights reserved. -
Determinants of Auditor Choice: Evidence from Sharia Commercial Banks in Indonesia
This research aims to determine the impact of corporate governance, firm complexity, foreign ownership, and ownership concentration towards auditor choice for Sharia commercial banks in Indonesia in 2016-2023. Firm size is also accounted for as a control variable. This research was conducted using a quantitative approach using the logit logistic regression analysis method through the Eviews 13 software. The sampling method was carried out using a purposive sampling method, which produced a sample of 9 Sharia commercial banks in Indonesia with a total of 72 observations. This study aims to provide an overview of the factors that Sharia commercial banks in Indonesia consider in choosing their external auditors, namely between Big 4 and non-Big Four auditors, which differ from other companies and industries. The results show that in partial analysis, corporate governance mechanisms and ownership concentration significantly and negatively affect auditor choice. Meanwhile, firm complexity and foreign ownership do not affect auditor choice. Low demands cause the negative influence of ownership concentration due to the private nature of the banks and efforts to achieve efficiency in audit fees while maintaining the same quality standards. 2025, Creative Publishing House. All rights reserved. -
A SYSTEMATIC RESEARCH REVIEW AND META-ANALYSIS OF ENVIRONMENTAL SCIENCES AND MANAGEMENT MODELS
This research advances the comprehension of the processes behind individuals' environmentally friendly behavior using a comprehensive approach. A questionnaire addressed intrapersonal, motivational, relationships, and educational aspects, with environmental science as the primary catalyst for green behavior within a complete theoretical structure.The method is the CADMIACA approach, which is founded on Comprehensive Action Determining Modeling (CADM), together with various Motivational and Interpersonal (MI) theories and the Activity Competence Algorithm(ACA). This framework encompasses various control factors relevant to comprehensively characterizing the factors influencing environmentally friendly behavior, including climate change, energy conservation, recycling, sustainable buying, and contamination.The findings were gathered in the A Coru metropolitan region to experimentally evaluate the causal relationships among the parameters that formed the framework utilizing Structural Equation Modeling (SEM). Findings show that environmentalscience serves as an effective instrument for fostering eco-friendly behavior among residents. The extensive CADMIACA model aligns well with the information since all components incorporated in the framework (intrapersonal, inspiring, social, and institutional) are pivotal in shaping green conduct.Environmental instruction and intrapersonal variables emerged as the primary predictors of green conduct, but social and motivational variables were less prevalent in influencing such behavior. The findings suggest that human conduct plays a vital role in environmental protection. 2025, Rotherham Academic Press Ltd. All rights reserved. -
A concise study on the phytochemistry and antimicrobial efficiency of Artemisia absinthium L.: Phytochemical analysis of plant
This study is meant to elucidate the phytochemical and antibacterial characteristics of wormwood Artemisia absinthium L, a perennial herb from Asteraceae family that has been used extensively in traditional medicine. It has diverse phytochemical composition, including bitter sesquiterpenoid lactones like absinthin, as well as essential oil constituents including camphene, ?-cadinene, guaiazulene, ?-thujone, ?-thujone, and thujyl alcohol esters. Applications of A. absinthium in the past include its ability to treat a wide range of illnesses, from fever to gastrointestinal problems. This study highlights the presence of various phytochemical compounds in plant extract of A. absinthium, such as tannins, saponins, and terpenoids through standardised protocols. Remarkably, this study also reveals its antibacterial capabilities using agar well diffusion method against five different pathogenic bacterial strains, including Escherichia coli (MTCC 443), Salmonella typhi (not sequenced, procured from Chettinad Hospital, Chennai), Staphylococcus aureus (MTCC 3160), Enterococcus faecalis (MTCC 439), and Klebsiella pneumonia (MTCC 109). Testing it against these strains of bacteria highlighted its effectiveness in this area. A. absinthium presents a compelling topic for continued scientific investigation due to its complex phytochemical composition and antimicrobial efficiency. 2026, ScienceIn Publishing. All rights reserved. -
Exploring the pharmaceutical potential of discarded ink glands from Amphioctopus aegina
Ocean is called the Natural Medicine Chest of the New Millennium, as it encompasses diverse marine ecosystems that are rich in bioactive compounds. One of the fascinating organisms is cephalopods as they are known for their inking capabilities. The ink, composed mainly of melanin and mucous, has garnered attention for its diverse bioactive properties. In addition to melanin, components like Quinones, 8-hydroxy-4-quinolone, and various amino acids exhibit anti-oxidant and other therapeutic activities. Researches have shown that cephalopod ink can possess anti-inflammatory, anti-cancer, anti-microbial, anti-hypertensive, anti-ulcerogenic, and antiretroviral properties. However, these ink glands are discarded in the seafood industry. Amphioctopus aegina is one of the octopus species found in Indian waters and is less explored. This study was conducted to explore the chemical composition and pharmaceutical properties of the discarded ink glands of A. aegina. The study revealed the gland of this organism to be rich in bioactive compounds like alkaloids, phenols and flavonoids. Antioxidant studies revealed both aqueous and ethanol extracts showed good antioxidant capability, with remarkable radical scavenging activity, with IC50 values-65.76 g/mL and 51.7 g/mL respectively. The extracts also showed moderate inhibition of protein denaturation and were non-toxic to RAW264.7 cell lines. These findings highlight A. aegina ink as a promising source of therapeutic biomolecules and offer a sustainable approach for valorizing cephalopod waste. 2026, ScienceIn Publishing. All rights reserved. -
Role of Dufour's gland and mandibular gland secretion in Ant Colony organisation and defense mechanisms of Camponotus compressus and Oecophylla smaragdina
Ants are eusocial insects and observed in 3 castes secreting a wide variety of pheromones for surviving in the colony. They can be sex pheromone, trail pheromone and alarm pheromone. These pheromones help in the recruitment of workers, mating, foraging food. These pheromones contain a single compound from a single gland or from two glands. This study analyses the knowledge of these pheromones and their chemical structure. The mandibular gland and Dufours gland of Oecophylla smaragdina and Camponotus compressus were extensively studied to provide a valuable resource in chemical ecology research. Limited research has been done on pheromones released by Oecophylla smaragdina and Camponotus compressus. The Dufour's gland is one of the most well-developed glands, playing vital roles in defense, foraging, information exchange, and reproduction. The chemical components were analyzed using gas chromatography-mass spectrometry. The secretions from the Dufours gland and mandibular gland contained high concentration of n-undecane, which serves as an alarm pheromone, and compositions varied among different castes. This highlights a research gap and the need to investigate the differences in the chemical composition between these two ant species, we analyse the diverse chemicals released from the Dufours gland and the mandibular gland. Authors CC4-NC-ND, ScienceIN. -
In-vitro antioxidant analysis of Aristolochia indica, Ipomoea obscura, Tylophora indica, Glinus oppositifolius and Abroma augustum from Bankura district, West Bengal
Five therapeutic plants that have been utilized traditionally across the Sonamukhi Block of Bankura District, West Bengal, were tested for antioxidant activity using three assays: ABTS radical scavenging activity, FRAP reduction power, and DPPH free radical scavenging. According to the DPPH assay, Glinus oppositifolius (68.4%) and Ipomoea obscura (23.83%) showed moderate radical-scavenging activity, whereas Aristolochia indica (73.07%), Abroma augustum (52.87%), and Tylophora indica (25%) demonstrated the highest levels. While Glinus oppositifolius (0.685) and Ipomoea obscura (0.401) showed moderate activity in the FRAP assay, Abroma augustum (0.459), Tylophora indica (0.637), and Aristolochia indica (0.545) demonstrated significant reducing power. According to the ABTS assay, Aristolochia indica (90.37%) and Glinus oppositifolius (98.7%) had the highest levels of radical scavenging activity. These findings support the traditional medical usage of these plants, especially Glinus oppositifolius and Aristolochia indica, which showed the most antioxidant qualities. The results highlight the importance of these plants in traditional medicine, shed light on their therapeutic potential, and lay the groundwork for further research on natural antioxidant treatments. Authors CC4-NC-ND, ScienceIN. -
Within-School Socioeconomic Disparities in Academic Achievement: A Qualitative Case Study of Study-Regulation Supports among Indian Secondary Students
Objective: This study explored how socioeconomic contexts shape students study strategies and how these differences relate to academic achievement within the same school setting. Methods and Materials: A single-site qualitative case study was conducted in a private, unaided English-medium CBSE school in Bengaluru, India, enrolling students from diverse socioeconomic status (SES) groups. Thirty students in Grades 89 (aged 1315) were selected through purposive sampling, representing all achievement levels and residence types (day scholars and residential/hostel students). SES classification was informed by parental education/occupation and the Modified Kuppuswamy Scale (2019). Data were collected through semi-structured individual interviews, audio recorded, transcribed verbatim, and analyzed iteratively using line-by-line and focused coding guided by Charmazs grounded theory approach, leading to theme development. Findings: Three themes explained within-school achievement disparities: (1) parental engagement and access to cultural/social capital varied by SES, shaping monitoring, subject support, and study regulation at home; (2) hostel routines and mentoring provided compensatory structures resembling middle-class concerted cultivation, supporting academic regulation for some low-SES residential students; and (3) for low-SES day scholars, teachers and remedial support served as the primary learning resource, often framed in skill-deficit terms rather than culturally responsive pedagogy. Conclusion: Equal access to school resources does not necessarily produce equal outcomes because study regulation develops within unequal family and institutional support ecologies. Equity-oriented, culturally responsive, and relational school practicesalongside targeted academic mentoringmay help reduce persistent achievement gaps. 2025 the authors. -
Toward a Kashmiri Cultural Psychology: Integrating Indigenous Knowledge and Mental Health
This paper presents a critical theoretical intervention addressing epistemic imbalance in mental health research and practice related to Kashmir. It (a) develops conceptual frameworks elucidating indigenous healing rooted in Sufi mysticism, communal networks, and culturally specific coping strategies; (b) identifies and theorizes culturally derived constructs essential for contextually appropriate mental health infrastructures and interventions, emphasizing epistemic justice and locally situated knowledge; and (c) demonstrates culturally grounded interventions that foreground indigenous epistemologies on their own terms, addressing the limitations and potential dominance of Western clinical models. By centering Kashmiriyat, the Valleys indigenous cultural ethos that encompasses communal solidarity, shrine-centered spiritual practices, and historically rooted coping strategies guiding everyday communal and spiritual life, this work reconceptualizes resilience as collective and historically situated. The proposed framework enriches global psychological theory and offers innovative models of culturally congruent and socially transformative interventions for conflict-affected societies. 2026, PsychOpen. All rights reserved.