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Performance Evaluation of Refractory Bodies Fabricated from Composite Oxide Powders Beneficiated from Black Al-dross
Aluminum Oxide (Corundum, ?-Al2O3) and Magnesium-Aluminum Oxides (Spinel, MgAl2O4) are highly desired refractory materials due to their ability to withstand high-temperature service conditions without corroding and cracking. They are present in composite form in black Aluminum Dross (Al-dross), a hazardous industrial waste. 1 Kg batch of this composite powder was beneficiated from Al-dross to 98+% purity after removing the hazardous Aluminum Nitride (AlN) by aqueous treatment of Al-dross in an environment-friendly manner. The treated slurry was oven dried, ball milled to fine powder, hydraulically pressed, and sintered at 1500 C/6 h into solid cylinders (50 mm diameter 20 mm height). The structural phase analysis of the sintered product (refractory blocks) revealed a highly crystalline XRD pattern with peaks pertaining to only ?-Al2O3 and MgAl2O4. The blocks with Rockwell Hardness values of 4850 HRC, were subjected to thermal shock cycling by following the guidelines of IS 1528 (heat quench between 1000 C and air at ambient) which successfully withstood > 100 shock cycles without failure. SEM was employed to study the fracture surface in an as-sintered state and after thermal shock cycling, to reveal a fine-grained microstructure with clear grain boundaries in the as-sintered state to a glassy matrix with fine cracks at the end of the thermal shock cycle test. The potential for utilization of Al-dross for refractory applications was thus established. 2023 -
Plasma sprayed magnesium aluminate and alumina composite coatings from waste aluminum dross
The absence of structured waste management practices for tons of black aluminum dross (Al-dross) when land-filled affects the ecosystem we live in. Researchers and technologists are now working towards three goals (a) minimization of Al-dross production (b) reducing its toxic effects on the environment and (c) treating the Al-dross to beneficiate useful materials from it in an environmentally friendly manner and to generate useful industrial products. The third aspect has been addressed in this study. Al-dross is an aluminum industry generated waste that mainly contains Al metal (oxidized during processing), Aluminum Nitride (AlN), ?-aluminum oxide (?-Al2O3) and magnesium aluminate (MgAl2O4). The oxides are highly suitable for refractory and thermally insulating material applications, but AlN is detrimental for two reasons - (a) thermal conductivity higher than the oxides and (b) carcinogenic gas evolution during processing. Hence AlN must be removed from Al-dross for further processing into refractories. In this work, AlN with minor quantities of halides were removed from Al-dross to extract the major useful refractory oxide constituents in an environmentally friendly manner. The process methodology involved sieving Al-dross to < 600 m particles, aqueous media treatment to remove the nitrides in the form of NH3 gas, oven drying and calcination at 10001150 C for 2 h (in an electrical muffle furnace in ambient air atmosphere) to obtain a mixture of the composite oxide powder of ? 99.0% purity. The calcined compound was mixed with suitable organic binders and sieved to obtain plasma sprayable powder and plasma spray-coated onto bond coated (commercial NiCrAlY) steel substrates. XRD and SEM with EDS facility were used to characterize the powders and coatings. A polished metallographic cross-section was prepared to study the microstructure and interface characteristics. The findings are presented. 2022 -
Sprouting in Seeds Aided by Nitrogen Sourced from Ammonia Fumes Leached from Aluminum Dross
Nitrogen and water are nutrients essential for the sprouting of seeds and healthy growth of plants. The seeds derive nitrogen from ammonia (NH3), found in ammonium hydroxide commonly added as manure to the soil. In a materials synthesis process, NH3 gas was released when Aluminum-dross (Al-dross), a hazardous industrial foundry waste was beneficiated to extract useful materials (metallic Al, oxides of Al and Mg, etc.) from the waste. Chemical tests, SEM with EDS and XRD were used to characterize sieved black Al-dross (starting raw material) before and after the beneficiation process. Al-dross also contained significant quantities of aluminum nitride (AlN). When treated with an aqueous media (plain or carbonated water), the AlN reacted to release NH3 gas fumes. This work explored the potential of using this gas to act as a source of nitrogen to accelerate the sprouting of seeds and plant germination. Vegetable and fruit seeds were sown in the soil that was directly infused with the NH3 released from Al-dross for two hours, followed by several (8 to 12) hours of self-diffusion time for homogeneous distribution of the gas in the soil. Five pairs of soils (untreated regular and NH3 fumes treated soils) were prepared under similar conditions. 5 different vegetable and fruit seedlings were planted in these pairs of soils. The germination patterns and growth of the sprouts with time were observed. The seeds that preferred an alkaline environment for germination (e.g., ridge gourd and watermelon seeds) sprouted early and in good health in the NH3 treated soil. Seeds preferring acidic soils did not germinate well in NH3 fume-infused soils. The experiments confirmed the viability of the novel concept, where the waste ammonia fumes released from Al-dross could be favorably generated and used in a controlled manner to promote sprouting of certain agricultural seedlings. 2023 Elsevier Ltd. All rights reserved. -
DREAMS Digital Pedagogical Models for Inclusive Education: A Report From the Virtual Reality Learning Environment (VRLE)
Digital pedagogy is the current need of the hour and it is the social responsibility of facilitators in adopting a growth mindset of innovation. Learners at present are diversified with varied psychosocial concerns in the virtual field. Hence, to integrate a culture of autonomy and inclusivity within the learner's framework digital pedagogical models need to be constructed. This article reports the innovation and application of 21 virtual resources created for DREAMS (Thomas, 2014) program from May 2021-June 2023 using digital software's like CANVA and Adobe, graphic interchange formats (GIPHY App), and memes (Meme Generator App). The virtual reality learning environment (VRLE) was created through zoom platform where these resources were applied as a pedagogical tool throughout the virtual intervention for a period of 6 months. Through this article, contemporary virtual models are explored for personal development of teenagers. There is also a need to work with digital pedagogical models for promotion of inclusive education and positive youth development. 2026, IGI Global Scientific Publishing. All rights reserved. -
Hybrid Deep Learning Based GRU Model for Classifying the Lung Cancer from CT Scan Images
Lung cancer is a potentially fatal condition, posing significant challenges for early detection and treatment within the healthcare domain. Despite extensive efforts, the etiology and cure of cancer remain elusive. However, early detection offers hope for effective treatment. This study explores the application of image processing techniques, including noise reduction, feature extraction, and identification of cancerous regions within the lung, augmented by patient medical history data. Leveraging machine learning and image processing, this research presents a methodology for precise lung cancer categorization and prognosis. While computed tomography (CT) scans are a cornerstone of medical imaging, diagnosing cancer solely through CT scans remains challenging even for seasoned medical professionals. The emergence of computer-assisted diagnostics has revolutionized cancer detection and diagnosis. This study utilizes lung images from the Lung Image Database Consortium (LIDC-IDRI) and evaluates various image preprocessing filters such as median, Gaussian, Wiener, Otsu, and rough body area filters. Subsequently, feature extraction employs the Karhunen-Loeve (KL) methodology, followed by lung tumor classification using a hybrid model comprising a One-Dimensional Convolutional Neural Network (1D-CNN) and a Gated Recurrent Unit (GRU). Experimental findings demonstrate that the proposed model achieves a sensitivity of 99.14%, specificity of 90.00%, F -measure of 95.24%, and accuracy of 95%. 2024 IEEE. -
Sliced Bidirectional Gated Recurrent Unit with Sparrow Search Optimizer for Detecting the Attacks in IoT Environment
In an era characterized by pervasive interconnectivity facilitated by the widespread adoption of Internet of Things (IoT) devices across diverse domains, novel cybersecurity challenges have emerged, underscoring the imperative for robust intrusion detection systems. Conventional security frameworks, constrained by their closed-system architecture, struggle to adapt to the dynamic threat landscape marked by the continual emergence of unprecedented attacks. This paper presents a methodology aimed at mitigating the open set recognition (OSR) challenge within IoT-specific Network Intrusion Detection Schemes (NIDS). Leveraging image-based representations of data, our approach focuses on extracting geographical traffic patterns. We observe that the Recurrent Neural Network exhibits suboptimal classification accuracy and lacks parallelizability for attack analysis tasks. Our investigation concludes that the Sparrow Search Optimization Algorithm (SSOA) serves as a foundation for constructing an effective assault classification model. This research contributes significantly to the field of network security by emphasizing the importance and ramifications of meticulous hyperparameter tuning. It represents a critical stride toward developing IDSs capable of effectively navigating the evolving cyber threat landscape. In the experimental analysis of proposed model reached the accuracy and 0.963% respectively. 2024 IEEE. -
A Deep Learning-Based BCI System for Emotion Classification Using EEG Signals
Electroencephalography-based Brain-Computer Interfacing (EEG-BCI) technologies allow for effortless interaction between external hardware and the human brain through monitoring its electric signals. These systems rely on EEG recordings, which provide non-invasive and real-time neural information through electrodes placed on the scalp. To advance emotion-recognizing efficiency and accuracy, this study proposes a deep learning-based method that can extract valuable temporal and spatial information from EEG signals. The proposed model includes the use of a Graph Convolution Network (GCN) for learning spatial relationships between different EEG channels to model the data in graph form and gain features through that modelling. A Convolutional Autoencoder (CAE) is then used to compress data to low dimensions and to reconstruct it so that major features are not ignored. Furthermore, the model uses an Attention-based Bidirectional Gated Recurrent Unit (ABiGRU) for temporal classification, which can emphasize the most important time steps in both backwards and forward directions. Two standard datasets are employed to test the developed approach. The DEAP dataset is used for emotion recognition with a binary response, and SEED is used with multi-class classification. The model attains great results of 98.12% accuracy on DEAP and 97.58% on SEED datasets. The very high performances show the efficacy of the model for decoding emotional states from EEG signals and very strong potential for real-time emotion recognition in affective computing and BCI. 2026 Seventh Sense Research Group. -
Regression Test List Sharding in a Distributed Test Environment
One of the major issues during the regression test of the new version of Real Time Operating System (RTOS) is the time involved in test case execution. The main reason being a single embedded system device under test (DUT) is used to execute the test list containing several test cases. This traditional method of regression test also leads to wasted productivity of the other devices at hand that could be otherwise used during this regression test. Hence, in this paper, we propose a technique that aims at reducing the overall regression test cycle time of a newer version of a Real Time Operating System (RTOS) by employing a method known as "test-list sharding"in a distributed test environment. In the proposed work, multiple DUTs are connected to the test server via a communication network. The test server executes the test list containing several test cases and performs the test-list sharding, that is, distributing test cases to different DUTs and executing them in parallel. After the test is executed on the DUT, the test results are sent back to the test server which will summarize all the results. In the proposed work, the sharding is done by distributing the test cases without overloading or under loading any of the DUTs. Test list is sharded in such a way that the same tests are not sent to multiple DUTs. The main advantage of the proposed method is that the test sharding can be easily scalable to accommodate any number of devices that can be connected to the test server. Also, the test list sharding is done in a dynamic way so that the tests are distributed to an idle DUT that has completed a test execution and ready for another test to execute. The comparison study of executing a sample test list sequentially on a single DUT and distributed test system with multiple DUTs is performed. Results obtained showed the performance gain in terms of test cycle time reduction, scalability, equal load distribution and effective resource utilization. 2023 EDP Sciences. All rights reserved. -
FISCAL PERFORMANCE OF PANCHAYATI RAJ INSTITUTIONS (PRIs): AN EMPIRICAL ANALYSIS OF THE STATE OF ANDHRA PRADESH IN PRE AND POST-BIFURCATION PERIOD
The effectiveness of democratic decentralisation depends on the financial strength and independence of the local bodies. Financial autonomy is vital to reap the full potential benefits of decentralisation as the transfer of funds, functions, and functionaries will enable local bodies to be institutes of self-governance and not just delivery mechanisms. In the context of persistent fiscal distress across the local bodies, an attempt is made to empirically examine the fiscal performance of Panchayati Raj Institutions (PRIs) in Andhra Pradesh during 2010-11 to 2017-18, i.e. pre- and post-bifurcation periods of the State. The fiscal autonomy and the revenue dependency of PRIs across all three tiers in the State during the same period was also analysed. The study finds that the fiscal autonomy of top tiers, i.e. Mandal Praja Parishads (MPPs) and Zilla Praja Parishads (ZPPs) is negligible in both periods, while Gram Panchayats showed relatively better fiscal autonomy in both periods. 2022 National Institute of Rural Development. All rights reserved. -
INTEGRATING CLIMATE CHANGE, SOCIAL RESPONSIBILITY AND ELECTRONIC FINANCIAL INCLUSION: A PATHWAY TO SUSTAINABLE DEVELOPMENT
Purpose: This study explores the intersection of climate change social responsibility and electronic financial inclusion (EFI) as critical components of sustainable development. The research aims to identify the synergies between these domains and their potential to drive inclusive growth and resilience. Design/Methodology/Approach: The study integrates literature review and case studies to analyse the role of EFI in enhancing access to financial services, particularly for marginalised communities. It also examines corporate social responsibility (CSR) initiatives aimed at mitigating climate change and promoting environmental sustainability. The research study highlights successful integration models and best practices that demonstrate the impact of multistakeholder collaboration. Findings: The findings reveal that EFI significantly contributes to poverty reduction and economic empowerment by expanding financial access in underserved regions. Moreover, corporate initiatives in climate change mitigation, when aligned with social responsibility, enhance business resilience and foster sustainable practices. The study emphasises the importance of supportive policy frameworks and technological innovations in scaling these efforts. Research Limitations/Implications: The studys focus on case studies may limit the generalisability of the findings. Future research could explore broader geographic regions and diverse economic contexts. Originality/Value: This paper contributes to the understanding of how integrating climate action, social responsibility and EFI can create resilient, equitable and sustainable systems. It offers valuable insights for policymakers, businesses and practitioners aiming to advance sustainable development through innovative and inclusive strategies. 2025 Ernesto D. R. S. Gonzalez, Rajeev Sijariya, Amit Kumar Singh and Vikas Garg Published under exclusive licence by Emerald Publishing Limited. -
Customer Behavior Analysis Using Unsupervised Clustering and Profiling: A Machine Learning Approach
Now-a-days, client conduct models are reliably established on information mining of client information, and each model is supposed to answer one solicitation at one point on schedule. Anticipating client conduct is a problematic and irksome task. Thus, making client conduct models requires the right strategy and approach. Right when an estimate model has been fabricated, it is challenging to restrict it for the motivations driving the advertiser, to pick the very thing displaying moves to make for every client or for the party of clients. Notwithstanding the multifaceted nature of this arrangement, most client models are completely fundamental. As the need might arise, most client conduct investigation models ignore such endless proper factors that the gauges they make are overall not altogether strong. This paper plans to encourage a connection rule mining model to expect client conduct using a typical electronic retail store for data combination and concentrate critical examples from the client conduct data. In this undertaking, a solo grouping of information on the customer's records from a regular food item company's data set will be played out. Customer segmentation is the act of clustering customers into bunches that reflect likenesses among customers in each group. Customers are separated into sections to advance the meaning of every customer to the business. To change items as indicated by unmistakable requirements and practices of the customers. It additionally assists the business with obliging the worries of various kinds of customers. Customers were clustered using a technique known as agglomerative clustering, which is a type of hierarchical clustering. Agglomerative clustering is a method for clustering data in a hierarchical order. It entails merging cases until you reach the appropriate number of clusters. The number of clusters to be produced is determined using the Elbow Method. 2022 IEEE. -
Carbon Dot-Based Fluorescence Resonance Energy Transfer (FRET) Systems for Biomedical, Sensing, and Imaging Applications
Carbon dots (CDs) emerge as a potential group of photo-luminescent nano-materials due to their excellent optical, electrical, and chemical properties, as well as their competence in a wide range of environmental applications. CDs have unique and appealing properties such as excellent stability, low toxicity, water solubility, and derivability. When coupled with CDs, fluorescence resonance energy transfer (FRET) results in the development of highly sensitive ratiometric fluorescence sensor probes with potential applications in bio-imaging, metal sensing, membrane dynamics, and environmental sensing. In this review, the progress and recent developments in CDs based FRET systems utilized for various environmental applications are conferred. An in-depth description is provided regarding the numerous donor/acceptor systems which when integrated with CDs generate efficient FRET systems. The review enables researchers to identify and develop specific systems which can be utilized to generate a FRET pair with potential physicochemical properties that aid the development of the same for various applications. 2023 Wiley-VCH GmbH. -
Facilitating Faculty Development for Training in Multicultural Competence in Health Service Psychology Graduate Programs Through an International Collaboration
A critical aspect of strengthening graduate-level clinical and counseling psychology training in cultural competence is to build capacity among faculty teaching in these programs to provide effective training. We addressed this need through an international collaboration between a university in India and another in the United States that included faculty travel to another country, peer mentoring groups, and review of curricula. This article describes faculty perceptions of this program and its perceived impact on their professional development and outlines curricular and research outcomes that resulted from the program. Across 4 years, a total of eight faculty visits took place with Indian faculty (n = 13) visiting the United States and US faculty (n = 11) visiting India. After each visit, faculty at both institutions responded to open-ended questions about the usefulness of these visits and completed a rating scale at the end of the program through an online survey. Faculty from both countries indicated that the visits contributed to enhanced cultural awareness and sensitivity by broadening their perspectives and learning about cultural similarities and differences. Indian faculty described learning about new pedagogical methods and enhanced motivation to engage in research and publish, along with new collaborative opportunities. US faculty described incorporating cultural competence more centrally in their teaching and clinical supervision through increased commitment, as well as inclusion of more global and diverse content and assignments aimed to increase students cultural competence. These responses provide preliminary support for the usefulness of cultural immersion experiences for faculty professional development. 2024 American Psychological Association Inc.. All rights reserved. -
Is my culture influencing me?: Client experiences of mental illness and psychotherapy in a transitional Indian culture
The client therapy experience has been the focus of many bodies of literature in psychotherapy, even across cultures. While researchers have emphasized on the use of indigenous approaches in Indian psychotherapy, how much of this is applicable in the present scenario? The experience has become increasingly tricky to understand given the complexities arising from the influence of urbanization and westernization. Thus, the present study aimed to explore the experience of mental illness and psychotherapy in modern day India. Using the integrated, holistic idea of the person and their needs, the study conducted semi-structured interviews with ten cis-gender, urban Indian participants between 21 and 39years of age. Data analysis using thematic analysis uncovered the global theme of Transitional Culture Impacting the Therapeutic Experience. The major organizing themes and basic themes have been elaborated as well. In essence, the study concludes that the increased awareness and acceptance of psychotherapy in urban India, combined with the exposure to Western methodologies, may be related to an increase in the expectations for similar therapeutic services. Implications and recommendations have been discussed. The Author(s) 2023. -
Impact of Celebrity Credibility in Social Advertising: A Systematic Review of Rahul Dravids Anti-tobacco Campaign Endorsement
Tobacco cessation programs have had their share of hits and misses. While state-controlled organizations invest in such programs every year, it is hard to trace their effectiveness. This is a bigger challenge when celebrities are enrolled to endorse such programs. Several studies that track celebrity endorsements for marketing commercial products have validated the influence of celebrities on brand-related outcomes. This study provides a systematic review of a celebrity endorsement of an anti-tobacco advertisement. To conduct a systematic review of a celebrity endorsement, we examined the responses of celebrity fans on source (celebrity) credibility factors and their attitude towards the social cause endorsement. A sample of 258 celebrity fans was surveyed using a questionnaire. The survey instrument contained a 15-item scale to measure celebrity factors of physical attractiveness, expertise and trustworthiness. Further, demographic details, social media activity and cigarette consumption details were captured along with cognitive and affective responses towards the anti-tobacco endorsement featuring the celebrity. It was found that physical attractiveness and trustworthiness of the celebrity were found to be influencing the attitude of the fan towards social cause. In addition, the study revealed the significant influence of education on attitude towards social cause in contrast to age and gender as evident in previous studies. The study provides very important insights for advertisers of social causes on effective use of celebrities as part of their communication campaigns. 2021, School of Management Sciences. All rights reserved. -
Transformational Impact of COVID-19 on Savings and Spending Patterns of Indian Rural Households
COVID-19 has spread across the globe at a shocking level and significantly affects the world economy. The pandemic has significantly impacted rural households, the primary workforce for industrialized urban areas, in every sector of rural businesses, including agriculture. Furthermore, the dearth of employment in the primary industry has also adversely influenced rural inhabitants livelihood and financial decisions. COVID-19 changed the perception of people regarding their income and expenditure. This study is intended to analyse the transformation of savings and spending of rural households during COVID-19. A questionnaire was developed using a Likert scale to elicit study variables, and the collected data were analysed using structural equation modelling. The results showed that all types of savings had a positive and significant relationship with the savings motive of rural households during COVID-19. Further, customary and spontaneous spending had a positive and significant relationship spending pattern of rural households. Rural inhabitants were interested in compromising their spending and other forms of savings to have more emergency savings. Earlier studies have examined either the savings or the spending pattern of rural households, and studies on both savings and spending by rural households are very few. The present study thus adds to the existing literature in the field. The Author(s) 2022. -
Siri the Healing Mother: Relational Dynamics Between Mother and Child in a Matrilineal Society
The Siri cult revolves around an oral tradition from Tulunadu in Dakshina Kannada (South Canara), India, featuring a story that unfolds over 15,683 lines. It tells the myth of Siri, a remarkable woman, and her lineage. During the famous Siri Jatre (which means festival), women are possessed by the spirits of Siri and her descendants, such as Abbaga and Daraga. This article explores the ritual space of the Siri cult as a transformative arena for women, where the boundaries between myth and reality blur, allowing for collective healing and psychic reintegration. The ritual performances, particularly during the Siri festival, facilitate a trance-like state in which women embody Siri and her struggles, experiencing emotional release. Through communal participation and embodied identification with Siri, women reclaim their repressed emotions, anxieties, and desires, forging new alternative narratives of motherhood, femininity, and divine womanhood. Importantly, Siris divine presence offers women a symbolic anchora figure who legitimises their grief and challenges male-dominated ideals for women to be obedient, nurturing, and submissive. Taking a psychoanalytical lens, this article examines the ritual space of the Siri cult through the framework of object relations theory to explore the psychic processes. The rituals allow women to externalise their inner conflicts and repressed desires, processing their grief and trauma through symbolic enactment. By situating the Siri cult within a psychoanalytical framework, the study reveals how the myth of Siri functions as a transformative object, allowing women to bridge their individual suffering with communal strength, ultimately achieving a sense of psychic integration and empowerment. 2025 Department of Psychology, University of Allahabad -
FINANCIAL DECISION-MAKING POWER AND RISK-TAKING BEHAVIOUR IN INDIAN HOUSEHOLDS
This study aims to examine the impact of decision-making power on risk-taking behaviour in household economies in India. It further explores the relationship between decision-making power, perceived risk-taking behaviour, and actual risk-taking behaviour. Further, the study employs the primary data collected through a structured questionnaire. The snowball sampling method was adopted to gather data from 312 retail investors in the study area. The response rate for the sample size is 91.50%. An OLS regression model was constructed to measure the frequency of trading habits as a proxy for the respondents' risk-taking behaviour. The results indicate that decision-making power significantly impacts investors' risk-taking behaviour in Indian household economies. Additionally, decision-making power has a significant impact on perceived risktaking behaviour. The findings of this study show how decision-making power influences the risk-taking behaviour of retail investors. This study adds value to the literature on behavioural finance and household economies. The results will pertinently support retail investors' decision-making skills in unbiased investment decision-making. 2025 by the author(s). -
Crude complexities: sectoral asymmetries in the Indian stock market response to oil price changes
While many studies have examined the impact of oil price changes on stock market returns, most overlook the asymmetric impact on disaggregated sectoral indices. This study addresses this gap by examining the sector-specific impact of oil price changes in India, one of the largest oil-importing economies. Using monthly data from April 2008 to July 2025 collected from the Bloomberg database, we employed both linear and Non-linear ARDL models to explore the asymmetric impact in short- and long-run relationships. The findings reveal significant heterogeneity in the sectoral responses to oil price changes. While the FMCG, media and pharma sectors do not exhibit cointegration with oil prices, other sectors, namely banking, auto, metal, energy, IT, financial services, and real estate, asymmetrically responded to oil price changes. The negative oil price changes cause stronger and short-run sectoral responses than the positive changes, as confirmed by the Wald test and GIRFs. The error correction terms are negative and statistically significant for all the sectors, which confirms a long-run equilibrium and mean-reverting behaviour. This establishes that sectors react differently to positive and negative oil price changes in the long run. Investors must account for the non-linear relationship between these variables and take appropriate action when forming portfolio strategies. The results suggest that policymakers should monitor and find alternative energy sources to avoid sector-specific vulnerabilities during oil price fluctuations. 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
ESG or financial METRICS? What Retail Investors Really Look for in Decision-making
With the increasing global emphasis on responsible investing, this study explores the tradeoff between ESG and traditional financial metrics in shaping the investment decisions of retail investors in India. A within-subject experimental design was employed at Christ University, India, involving an initial sample of 75 participants, with 55 completing all three experiment rounds. The sample respondents evaluated masked stock profiles across three rounds, where updated financial and ESG information on masked stock was provided at each round. The results indicate that though ESG metrics are getting attention among retail investors, financial metrics are still the main determining factor for investment. It was found that ROE (52 responses), 3-year CAGR Net Profit (36 responses), and P/E ratios (48 responses) are the most influencing factors to make investment decisions. Similarly, ESG factors (Governance, Environmental, and Sustainability scores) are also frequently mentioned, with 74 citations. Retail investors mainly consider profitability and view ESG as risk-mitigating or neutralizing factors. While evaluating the ESG factors, retailers mainly look at the firms environmental concerns, followed by governance and social factors. This result contrasts with the previous studies in this domain, where the literature emphasized governance factors more than environmental factors. These results highlight the integration of ESG elements, as retail investors remain with favorable returns and sacrifice sustainability. Further, this study spots the need for better and quantifiable ESG performance reports to consider alternative data comparable to financial data for better investment decisions. Suresh Gopal, Saravanakrishnan V., Elangovan N., 2025.