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Executive function deficits in autism spectrum disorder analyzed through parental perspectives
Background: Executive function (EF) challenges pose difficulties to everyday functioning and autonomy for autism spectrum disorder (ASD). While research has investigated these impairments, results remain inconsistent regarding which aspects of EF (i.e., response inhibition, working memory, and mental flexibility) are most prominent, particularly in applied contexts. Much research has focused on laboratory settings or clinical assessments that may not fully capture the daily challenges faced by individuals with ASD. Objective: The current study is looking at parental perspectives on how EF deficits manifest in everyday life for individuals with ASD, particularly concerning social communication. Method: Semi-structured interviews were conducted with 25 parents of individuals with ASD (aged 1425years) to understand parental views on the EF challenges faced by their adolescent and young adult offspring. Thematic analysis is employed with ATLAS.ti to identify key themes that reflect the real-life challenges associated with EF deficits. Results: The results showed that response inhibition, especially impulsivity and interruptions, has potential risks on social interactions and academic performance, usually leading to social isolation. Deficits in working memory brought challenging outcomes of their own; the issues of retention, comprehension, and preparation difficulties were more salient. Mental flexibility challenges presented considerable obstacles to both academic and social situations and included task switching and adaptation to changed circumstances. Conclusion: The deficits in response inhibition, working memory, and mental flexibility made a significant contribution to the challenges of social communication and overall functioning in individuals with ASD, highlighting the importance of specific interventions. The Author(s) 2026. -
The effectiveness of proactive coping intervention for students with learning disabilities
The presence of Learning Disabilities (LD) increases the possibility of psychological distress due to the negative school experiences. Apart from academic difficulties, students with LD are facing social and emotional problems related to their disabilities. If the psychological distress evolves over time without proper management, it may lead to psychosocial maladjustment. Previous research has shown that proactive coping helps minimize stress and maladjustment issues and is a predictor of success in people with LD. In comparison to students without LD, students with LD in Kerala have lower proactive coping and are more maladjusted. Hence, the current study has tailored an intervention to enhance proactive coping for students with LD. The present study followed the quasi-experimental research design to examine the effectiveness of the intervention on students with LD. A total of 200 participants from various schools across Kerala were initially selected using a multistage random sampling method. Subsequently, participants exhibiting the lowest scores in proactive coping were identified, and then 60 of them were randomly assigned to either the experimental or control group for the intervention. Proactive Coping Inventory for Adolescents and Adjustment Inventory for School Students were the tools used in this study. The data collected from the experimental and control groups following the intervention were analysed using Mixed analysis of variance and Repeated Measures of ANOVA. The findings of the study showed that the proactive coping intervention has significantly enhanced the proactive coping and social emotional adjustment of students with LD. Using these proactive coping interventions in remedial instruction will enable the students to develop a healthy coping style that benefits their personal growth. The Author(s) 2025. -
Traditional beliefs and practices associated with relieving psychological problems of pregnant women of the Zeliang tribe
In Indigenous and resource-limited communities, emotional distress during pregnancy is often understood and managed through culturally grounded belief systems rather than biomedical frameworks. This qualitative study explores how pregnant women of the Zeliang tribe in Benreu village, Nagaland, perceive, interpret, and cope with emotional distress using traditional beliefs and practices. Guided by community psychology, cultural safety frameworks, and Lazarus and Folkmans Transactional Model of Stress and Coping, semi-structured interviews were conducted with ten pregnant women and two traditional healers. Data were analyzed using reflexive thematic analysis. Three interconnected themes were generated. First, emotional vulnerability and cultural conceptions of pregnancy revealed that fear, sadness, and emotional instability were interpreted through spiritual and ancestral meanings rather than psychiatric categories. Second, healing practices as emotional regulation tools illustrated how ritual chanting, fumigation, protective threads, and herbal remedies functioned as embodied coping mechanisms supported by intergenerational kin networks. Third, traditional healers roles in psychosocial support highlighted their function as trusted interpreters of distress who provide narrative explanation, reassurance, and culturally congruent guidance. Participants also described a complementary care pathway in which biomedical services were used for physical monitoring while emotional and spiritual concerns were addressed through traditional systems. The findings indicate that traditional healing within the Zeliang community operates as a culturally embedded model of perinatal emotional care integrating spiritual, relational, and symbolic dimensions of well-being. The study underscores the importance of culturally safe maternal mental health approaches that respect Indigenous explanatory systems and encourage collaboration between biomedical providers and community-based healing structures. The Author(s) 2026. -
A review of artificial intelligence enhanced cognitive behavioural therapy using the BECK AI BOT for mental health interventions
The integration of artificial intelligence (AI) and cognitive behaviour therapy (CBT) is a revolutionary solution to the global mental health issue, characterized by increasing need and decreased access to treatment. This research investigates the potential of AI-fortified cognitive behavioural therapy technologies, including chatbots, virtual reality, and adaptive learning modules, to enhance the efficacy, accessibility, and individualization of treatment for anxiety, depression, and PTSD. The study evaluates the scalability, ethical issues, and therapeutic efficacy of the therapies by combining peer-reviewed and experimental data. The suggested methodology combines AI-driven conversational therapy with predictive modelling to deliver individualized, real-time mental health treatment. In this study, a conceptual chatbot prototype, designated BECK-AI BOT, was developed to illustrate the applications interface and functionality, enhancing accessibility for both patients and therapists in the future. This study does not present new clinical trial data. All reported symptom-reduction and engagement findings are drawn from previously published studies of existing AI-driven CBT systems (e.g., Woebot, Wysa, Eleos, Limbic). The present work offers a narrative synthesis of current evidence and introduces a conceptual architecture and prototype (BECK-AI BOT), without evaluating it clinically. Notwithstanding these difficulties, problems persist, including a lack of long-term efficacy statistics, cultural sensitivity issues, and moral reservations about over-reliance on AI during emergencies. The argument comes in the form of AI possibly improving, not replacing, human therapists, emphasizing hybrid systems for fair treatment. Future research needs to advance emotional intelligence within AI, which combines AI-driven conversational therapy and predictive modelling to deliver real-time, personalized mental health services. The Author(s) 2026. -
The moderating effect of gender on the relationship between digital intelligence and digital amnesia
Digital amnesia refers to the phenomenon where people tend to forget information that they store digitally, and relying heavily on digital devices to remember the information. The ease of access to digital devices may encourage digital dependence, which could lead to digital amnesia. This study provides a preliminary understanding of the association between digital intelligence and digital amnesia among college students and the moderating role of gender in the relationship. This cross-sectional study has employed a stratified random sampling technique to recruit 1265 students via the survey method. The results revealed a significant negative association between digital amnesia and digital intelligence. Findings also indicated that males reported having higher level of digital amnesia, and females reported higher level of digital intelligence. Furthermore, gender played a significant moderator role between digital amnesia and digital intelligence. Overall, this study has provided a novel finding of the moderating role of gender in relationship between digital amnesia and digital intelligence in the Indian context. Furthermore, the scores of digital amnesia in this study raise a concern over the effectiveness of current sex education in India. The scores may underscore the need for educational initiatives that address the adverse effects of digital amnesia and emphasize the importance of promoting digital intelligence. The Author(s) 2025. -
Internalized stigma among patients with common mental disorders in South India
Introduction: Common mental disorders (CMDs), include depressive disorders and anxiety disorders, which are highly prevalent. There exists a huge stigma around mental health, and this challenge becomes further magnified in CMDs, especially in LMICs like India. Despite this burden, there is limited scientific evidence on the internalized stigma in CMDs. To address this evidence gap, this study aims to describe internalized stigma and its correlates among patients with CMDs attending the Psychiatry Outpatient Department (OPD) of an academic teaching hospital in South India. Materials and methods: A structured socio-demographic and morbidity questionnaire, along with the Internalized Stigma of Mental Illness (ISMI) Scale, was administered to 119 patients aged 18 years or older who were diagnosed with CMDs according to ICD-10 criteria. Patients with severe mental disorders and psychosis, epilepsy, intellectual disability, organic mental disorders, and those requiring hospital admissions, were excluded from the study. Results: A mild to moderate level of internalized stigma was reported among patients with common mental disorders. Age and history of suicidal thought were significant predictors of internalized stigma. Conclusion: Youth and those who have a history of suicidal thoughts tend to experience greater internalized stigma. A multi-pronged approach is needed to address internalized stigma, which includes a combination of education and awareness programs, peer support programs, psychotherapy, and medication adherence. Addressing stigma can positively influence help-seeking behavior, treatment compliance, and outcomes, thereby improving quality of life. The Author(s) 2025. -
Compact LoRa Patch Antenna Optimization Using Dual Random Starfish Aggregation Coupled Transformer Network for Vital Sign Detection in Breast Cancer WBANs
The rapid advancement of Wireless Body Area Networks (WBANs) has created a growing demand for compact, efficient, and reliable antenna systems to support continuous health monitoring, particularly for breast cancer applications. Recent methods, including CPW-fed patch antennas, artificial neural network (ANN)-driven models, and wearable textile antennas, have improved antenna design automation and flexibility. However, challenges such as signal distortion from body proximity, gain reduction under bending, Specific Absorption Rate (SAR) compliance, and lack of adaptive tuning continue to limit practical deployment. To overcome these limitations, this study presents a compact LoRa patch antenna optimized using a novel Dual Random Starfish Aggregation Coupled Transformer Network (Dual-Ran-SACTN) framework. This system combines the Starfish Optimization Algorithm (SFOA), a Random-Coupled Neural Network (RCCN), and a Dual-Aggregation Transformer Network (DuAT) to enhance convergence speed and learning efficiency. The antenna, designed in CST Microwave Studio, measures only 80נ60mm2 (0.23??נ0.17??), offering a lightweight and wearable structure for continuous vital sign monitoring. The proposed model exhibits a bidirectional radiation pattern in the E-plane and an omnidirectional pattern in the H-plane, achieving a peak gain of 2.12dBi and a high radiation efficiency of 99.8% at 868MHz. Additionally, the design maintains low SAR and stable performance under bending, making it robust for wearable WBAN applications. This work offers a real-time, energy-efficient solution for intelligent breast cancer monitoring through adaptive antenna optimization. This model supports practical applications such as continuous breast cancer monitoring, wearable health diagnostics, and real-time WBAN-based physiological signal tracking. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
3D Printed Skin Graft Scaffolds as Potential Alternative for the Cellulitis-Induced Skin Damages
Cellulitis is a bacterial infection starting from damaging the skin and soft tissue of the body and eventually leading to affect the immune and circulatory system. Demarked erythema, warmth, edema, and tenderness are symptoms of cellulitis affected skin. Unfortunately, due to the symptoms mimicry more than 30% of patients admitted to the hospitals are misdiagnosed as cellulitis. The existing treatment methods for the cellulitis include antibiotics and treatments associated to symptoms. Three-dimensional printing (3D printing) is emerging and innovating technology for the skin and other medical treatments. The combination of antibiotics with hydrogel and their integration with 3D printing technology can be a potential alternative to traditional dressing and solution-based approach. Current review article looks into the feasibility of 3D printing technology to manage the cellulitis-induced skin damages based on existing reports on 3D printed hydrogels for other skin problems. Review article provides insights into the cellulitis-induced skin damage, biomaterials and hydrogels in other skin damages, infections, wounds and scope of integrating 3D printing to treat to treat cellulitis. Review article projects the feasibility of 3D printed hydrogels, biomaterials, dressings, and artificial skin patches as possible solution to cellulitis-based skin damages. Furthermore, this review highlights the safety and regulatory challenges in employing 3D printing technologies for the cellulitis treatment. Current review article is first report proposing the possibility of 3D printing as alternative treatment for the cellulitis-based skin damages. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Deep learning based classification of microplastic in edible food using optical microscopy images
Microplastics (MPs), a prevalent pollution in food, water, and ecosystems around the world, have become a serious environmental and health concern. The traditional detection and classification techniques are labor-intensive by nature and do not support extensive, large-scale monitoring. The main emphasis of this study is to generate a novel image dataset via a simple extraction method that will be useful for classification applications in high-consumption edible food by integrating with the deep-learning model. This study compares the efficacy of several Deep learning (DL) architectures, including MobileNetV2, ResNet101V2, ResNet50V2, InceptionV3, EfficientNetB0, and a baseline Convolutional Neural Network (CNN) in classification into three groups: threads, beads, and fragments. The best performance was recorded by MobileNetV2, ResNet101V2, and ResNet50 V2, all with 98 percent test accuracy and weighted F1-scores of 0.986 and 0.983, respectively, which is a strong and consistent MPs classification. The outcome indicates that the DL models, especially ResNet101V2 and MobileNetV2, outperform the baseline CNN in terms of classification accuracy (98%). The present study provides strong, scalable opportunities for Artificial Intelligence (AI) based solutions for the assessment and reduction of MPs contamination globally in edible food. The Author(s) 2026. -
Translating artificial intelligence into socio-economic insight: a hybrid deep learning approach to employee financial well-being
This study aims to translate recent advancements in hybrid artificial intelligence (AI) modeling into a functional tool for assessing individual financial well-being. The objective is to develop a system that aids organizations in understanding employees financial stress, with broader implications for enhancing workplace productivity and societal economic resilience. A deep learning pipeline was developed to classify individuals into three financial well-being categories: Financially Secure, Moderately Stable, and Financially At-Risk. The approach utilizes a structured dataset of 20,000 Indian individuals and implements 15 advanced deep learning models, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), Bidirectional Long Short-Term Memory (BiLSTM), and Wide & Deep networks. Model performance was assessed using standard evaluation metrics, including validation accuracy and ROC-AUC scores. Among the tested models, the hybrid Wide & Deep + CNN configuration yielded the highest performance, achieving a validation accuracy of 99.44% and a perfect ROC-AUC score of 1.0000. These results validate the models capacity for robust classification and real-world applicability to financial profiling. This study demonstrates a practical application of AI in financial decision support systems and contributes to organizational research by offering a scalable solution to assess and mitigate employee financial stress. The Author(s) 2026. -
Application of distinct motivational types in shaping generative AI (GenAI) adoption behaviour
Differing from AI and GenAI adoption, research on traditional systems emphasised extrinsic factors like utility, social influence and innovativeness as predictors of user behaviour. The role of proximal psychological factors like motivation, however, has been overlooked in this context, which becomes essential with this shift towards AI. In the educational sector, the students use of AI shows the possibility of intrinsic factors like motivation in shaping adoption behaviour. This study uses Self-Determination Theory (SDT) and its Organismic Integration Theory (OIT) extension to propose a conceptual map that examines the role of distinct motivational types in shaping students GenAI adoption behaviour. The adoption behaviour of 348 Indian students pursuing higher education was collected through a cross-sectional survey and analysed using structural equation modelling. Findings indicated that autonomous motivation, including intrinsic, identified, and integrated motivation, significantly predicts students intentions to use GenAI tools. The study further examined the moderating role of perceived compatibility, revealing that alignment between users lifestyles and GenAI usage strengthens the impact of controlled motivations. When students feel that AI fits well with their needs and learning requirements, showing high compatibility, external motivators have a stronger effect on their decision to adopt it. This makes compatibility an important new finding and provides additional insights into the motivational types of GenAI adoption in academic contexts. This study extends the body of knowledge by moving beyond the binary treatment of motivation and empirically distinguishing between specific types of motivation. It emphasises the importance of self-determined motivation while showing how the correlations between various motivation types and GenAI usage intentions are conditioned by perceived compatibility. The study also offers practical insights based on the significant results. The Author(s) 2026. -
Exploring digital age influences on undergraduate students mental health through social media, academic pressure and digital literacy
The research aims to measure the impact of usage of social media, academic pressure, and digital literacy, on mental health. It also aims to measure the mediating role of perceived stress on mental health of undergraduate students. Survey method was used for collecting data from a sample of 565 undergraduate students from state and private universities of Tamil Nadu, Karnataka, Andhra Pradesh, Telangana, and Kerala. EFA and Path analysis was used for testing and validating the conceptual model. The results showed that Social Media Usage increases Perceived Stress and negatively impacts Mental Health Outcomes both directly and indirectly through Perceived Stress. Academic Pressure increases Perceived Stress, which negatively impacts Mental Health Outcomes indirectly. Digital Literacy reduces Perceived Stress and has a positive effect on Mental Health Outcomes both directly and indirectly through reduced stress. Perceived Stress was found to have a significantly negative impact on the Mental Health Outcomes. The demographic variables namely; age, gender, living status, family type, and course type were found to have a significant impact on the usage of social media, academic pressure, digital literacy, perceived stress, and mental health scores of undergraduate students. The study also came up with interventions for managing mental health of under graduate students. The Author(s) 2025. -
Development of flexible FRP butt joints between stiff FRP panels using hybrid resin and kevlar reinforcement for advanced structural applications
The present work focuses on developing a flexible fiber-reinforced polymer (FRP) butt joint between stiff FRP panels (adherends). The goal is to ensure the joint is flexible, moisture-resistant, and abrasion-resistant, while maintaining the original FRP strength and facilitating the casting of complex and modular shapes. To achieve this, an elastomeric resin system comprising polyurethane and polyurea in an optimized ratio of 10:6 (by weight) was formulated for the flexible joint region, whereas isophthalic polyester resin was used in the stiff FRP panels. The joint was reinforced using a hybrid layup of three layers of plain-weave Kevlar fabric, with glass fiber chopped strand mat (CSM) interleaved between the Kevlar layers, over an overlap length of 50mm on both panel edges. Mechanical characterization revealed that the hybrid resin alone exhibited an average tensile strength of 16.3MPa; however, no slip was observed for the 50mm overlap of the reinforced joint, and failure occurred in the adherend. Furthermore, the joint exhibited favorable performance under abrasion, water immersion, low-temperature fatigue, and drop-weight impact testing. These results confirm that the proposed hybrid Resin-Kevlar reinforced joining approach offers a reliable pathway for fabricating flexible, durable, and high-strength FRP joints suitable for advanced structural applications. The Author(s) 2026. -
Assessment of mechanical and micro structural analysis of iron ore tailings and red mud sustainable bricks using multiple linear regression
The synergistic utilization of mining and industrial wastes in the construction industry represents a major step forward in the environmental and sustainable constructions. This research has presented an exploration of the feasibility of combined use of iron ore tailings (IOT) and red mud (RM) in sustainable brick manufacture. The IOT and RM have been blended with ground granulated blast furnace slag (GGBS) and lime solution for the production of bricks without high-temperature kiln-firing. Eight different combinations of (IOT + GGBS) and (RM + GGBS) with varying ratios of the principal components have been used in the sustainable bricks. Multiple regression analysis has been employed to estimate the strength of a different compositions of bricks. The bricks with 70% RM and 30% GGBS have attained the highest strength of 9.68 MPa and the bricks with 70% IOT and 30% GGBS attained the highest strength of 6.25 MPa among various combinations. The water absorption results of 18.7% and 19.02% have fulfilled the IS standards too. The research has revealed that the bonding between bricks and mortar has been influenced by the Si-Al matrix at low calcium content. Additionally, the formation of the delicate Ca-Al-Si phase capable of permeating the brick, has contributed to the constructive brick structure. The study also reinforced the view that the combined use of mining and industrial waste in production of environmentally friendly bricks is viable. The Author(s) 2025. -
Effectiveness of integrated waste minimisation strategies in high-rise residential construction projects
Construction waste has become a significant sustainability concern in fast-growing Indian cities, especially in high-rise residential projects characterised by intensive material flows. This study conducted a comparative analysis of material waste across the various stages of eight high-rise residential projects in Bengaluru, India. Four of the projects followed the conventional method, while the remaining four used an efficient method to reduce material waste. The material usage and generation were recorded for seven phases, each lasting two months, both quantitatively and qualitatively, using data and observations. Additionally, Relative Reduction (RR) values were calculated to assess the effectiveness of the implemented interventions by comparing the projected values for the baseline scenarios of uncontrolled and controlled projects. Uncontrolled projects exhibited an average wastage growth of 23% and negative RR values (? 4.48% to ? 9.15%), indicating a deterioration in waste management performance. At the same time, the sites implementing waste control measures demonstrated waste stability or reduction, with RR values of 713%, due to improvements in site supervision, material storage, batch extraction accuracy, and control of material issues. Material-wise analysis further supported the reduction in waste under controlled conditions. The benchmarking system developed in this research will provide practical support for waste tracking and remedial actions. The study demonstrates, using data, that low-cost, straightforward process interventions can substantially increase the effectiveness of resource use in achieving SDG 11.6 and SDG 12.5. The Author(s) 2026. -
Intellectual capital independent directors and leverage as determinants of sustainable growth in Indian pharmaceutical companies listed in the NSE NIFTY pharma index
This research investigates how Intellectual Capital (IC) influences the Sustainable Growth Rate (SGR) of Indian pharmaceutical firms that are part of the NSE NIFTY Pharma index. This study delves deeper into the moderating influence of Independent Directors and examines the control effect of Leverage (Debt-Equity Ratio) on this relationship. A descriptive research design was utilized, employing panel data from FY 2015 to FY 2024. The dataset was obtained from the Prowess database (CMIE), and the Two-Step System GMM method was utilized with STATA 18 to guarantee a thorough econometric analysis. The findings indicate that Intellectual Capital (IC) plays a crucial role in enhancing SGR, thereby reinforcing the Resource-Based View (RBV). Independent Directors effectively moderate this relationship, strengthening Agency Theory. Nonetheless, leverage has a detrimental effect on SGR, consistent with Pecking Order Theory. Pharmaceutical companies ought to allocate resources towards Intellectual Capital, enhance corporate governance, and uphold appropriate debt levels to ensure sustained long-term growth. This study effectively combines IC, corporate governance, and financial leverage in the Indian pharmaceutical sector, providing valuable concrete insights for policymakers, academics, and industry experts. The Author(s) 2026. -
Bridging tradition and sustainability through a behavioural model for the adoption of green wedding practices
The study aims to develop a behavioural model which indicates the intentions of unmarried people for adoption of green marriages. The study aims to explore the factors which affects the green marriage intentions, and also developing a green marriage intention matrix for categorizing the green marriages. The study is based on the primary data collected from a sample of 480 unmarried people restricting from age groups of 2040 only. Researchers have used Exploratory factor analysis to explore the factors, multiple regression analysis to develop the green marriage intentions model, and correlation analysis. ANOVA method was used to measure the impact of age, gender, and education on environmental attitude and green marriage intentions. It was found from the study that environmental attitude, social influence, perceived barriers, and perceived benefits are the four major factors which affects the green marriage intentions of the people. Further, the green marriage intentions matrix showed four categories of the people based on the environmental attitude and social influence namely; Influential green marriage, Casual green marriage, fashionably Green Marriage, and Eco-conscious green marriage. The study also included a detailed strategic plan with proposed actions to handle the barriers and promoting the green marriage practices along with environmental stewardship. The Author(s) 2025. -
Environmental sustainability and management (ES & EM) practices among Service Sector Institutions in Kathmandu, Nepal
Environmental sustainability (ES) emerged in response to the felt negative consequences of overexploitation of the environment and natural resources. ES has gained momentum in recent decades in areas of social policy, means of production, development, economy and everyday individual behaviours. The drive towards ES has been firmly based in scientific research which has been dominated by Western developed countries. For a tiny developing country like Nepal, its overall contribution to global environmental pollution and degradation is minimal; however, it has been disproportionately negatively affected by global warming, pollution, etc. There is sparse research on the various measures or state of environmental sustainability standards, policies or behaviours in Nepal. In this quantitative cross-sectional study, five types of Service Sector Institutions (SSI) from Kathmandu, Nepal were studied for their environmental sustainability (ES) and environment management (EM) measures in place at their facilities. SSIs were chosen because they have the distinct characteristic of being directly involved with large sections of populations, and hence hold the potential to pioneer innovative and effective solutions towards fostering environmental sustainability. ES was defined in terms of three measures related to sustainable freshwater use, energy use and waste management. The measures for EM included organizational capacity building and attitudes towards ES. Data was collected directly from representatives of the SSIs through self-report interviews or forms. The 104 SSIs included 25 schools, 26 restaurants, 16 hotels/lodges, 18 banks and 17 health care organizations. Based on frequency distributions and ANOVA tests, it was found that the overall extent of ES and EM practices among the 102 SSIs was dismally low in Kathmandu, Nepal. As given in the figure, educational institutions performed significantly better across all five ES and EM measures indicating highest prevalence of sustainability measures and practices. Banks performed significantly worst across all categories compared to the four other SSIs, indicating least amount of efforts in ES and EM. All five measures of environmental sustainability (ES) and environmental management (EM) were also strongly positively correlated amongst each other. A huge amount of effort is still required to revamp the existing ES and EM policies and organizational norms in Nepal. Moreover, it remaining challenging to change peoples attitudes and behaviours in order to effect lasting positive changes in the future and conserve the local environment better. The Author(s) 2025. -
Analyzing SDGs in high-and-low-emission industries: a comparative study of sustainability reports
This study assesses different Sustainable Development Goals (SDGs) in high- and low-polluting industries through a comparative analysis of sustainability reports. The objective is to evaluate SDG-related terms in reports from 16 companies across four sectorsCement, Automobile, Electric Equipment, and ITover five years. Using Python for data extraction and the text2sdg package in R programming for SDG term detection, the study identifies both prioritized and overlooked SDGs. Results indicate that high and low-polluting industries share similar SDG focus areas. SDGs 6 (Clean Water and Sanitation), 12 (Responsible Consumption and Production), and 13 (Climate Action) received the most attention. In contrast, SDGs 1 (No Poverty), 2 (Zero Hunger), 5 (Gender Equality), 10 (Reduced Inequalities), and 14 (Life Below Water) are consistently underrepresented. The findings suggest that both categories of industries acknowledge the importance of sustainability, yet significant gaps remain in addressing social and environmental challenges. This research contributes to the broader discourse on corporate sustainability and its role in achieving the 2030 Agenda, offering actionable insights for industries to increase their focus on less-considered SDGs. By identifying areas of improvement, the study supports efforts to foster more inclusive and environmentally responsible business practices. The Author(s) 2025. -
Enablers of Circular Practices in Fast Fashion Supply Chains: a Study Towards Sustainable Fashion Development
The fast fashion industry confronts substantial sustainability issues because of its high resource consumption and waste output. The literature reveals that past studies have less focused on circular practices in fast fashion supply chain. This study aims to identify and analyse the potential enablers of circularity within fast fashion supply chains, promoting sustainable production and consumption practices. Through a comprehensive literature review and expert consultations with 12 domain experts from academia, apparel manufacturing, and sustainability practices, sixteen enablers of circularity were identified. To understand the interrelationships and hierarchical structure among the identified enablers, Grey DEMATEL method was employed. The results from the study reveal that sound purchasing policies, reverse logistics and adoption of eco-friendly and recyclable packaging act as the most influential causal enablers, while selection of fibres and consumer awareness and acceptance of recycled, refurbished clothing emerge as key effect enablers. By mapping these interrelationships, the study offers actionable insights for fashion retailers, policymakers, and sustainability practitioners to strengthen circular strategies. The findings contribute to advancing circular economy theory in the fashion sector and provide a practical framework for accelerating the transition towards sustainable and circular business models in fast fashion. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.