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What is beautiful is good: An evalutation of effectiveness of attractiveness in celebrity endorsements
The studies in the field of marketing have shown that characteristics of the source will influence persuasiveness of an advertisement. Attractiveness is one such celebrity characteristic that is widely studied by researchers in the field of marketing. However, still, literature failed to explain how attractiveness of celebrity endorsers influenced purchase intentions. This study tried to fill this gap by modelling the influence of celebrity attractiveness on purchase intention. It also evaluated the effect of respondents' gender on the model. The data collection for the study were carried out during March - June 2017. The study found that the effect of celebrity attractiveness on purchase intention was mediated by celebrity brand fit, attitude towards the advertisement, and attitude towards the brand. The study also evaluated the moderating effect of respondents' gender using chi- square analysis, which found no significant model difference among male and female respondents. These findings indicated that celebrity attractiveness created purchase intention in a mediated manner among the respondents, irrespective of their gender. 2018, Associated Management Consultants Private Limited. -
What is Remembered in Pandemic: A Commentary on the Mediated Memories of Piety in COVID-19
The paper explores how the experiences of the present pandemic are shaped by the memories of popular religious piety during past pandemics and epidemics. Taking insights from the works of Astrid Erll and Reinhart Koselleck, the process remembering-imagining system within the context of the pandemic is discussed by tracing the reemergence of pandemic deities and narratives of piety in India. Using digitally documented and disseminated narratives on piety emerging during COVID-19, an attempt is made to understand how these narratives shape the experiences, responses, and collective memory of the pandemic. Through a discussion of the shift in the imagination of political leadership and the moral responsibilities of the community, an attempt is made to highlight the mode in which the narratives on piety shape the contours of a time that is otherwise unimaginable. The mediated memories of popular religious piety make it possible to remember similar crisis times and to imagine and reinstate the social order that is threatened by this sudden unimaginable crisis. The paper thus argues that within the context of India, popular religious piety, though often overlooked, becomes a significant part of making sense and shaping the experiences of the pandemic time. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
What Keeps Secondary School Teachers Motivated? A Qualitative Study from Urban Indian Classrooms
Teacher motivation is widely recognized as central to instructional quality and teacher retention, yet limited research has examined how it is experienced and sustained within policy-driven, high-pressure school systems. This qualitative study explores how secondary school teachers in Bengaluru, India, understand and maintain motivation in their everyday professional practice. Drawing on six in-depth interviews and reflexive thematic analysis, five interrelated drivers were identified: student engagement, emotional connection, instructional autonomy, collegial support, and recognition. Teachers described motivation not as a stable trait, but as a dynamic process continually shaped through relationships, daily pedagogical decisions, mentoring roles, creative planning, and small acts of professional agency. By foregrounding teachers lived experiences, the findings complement large-scale motivation research and offer insight into how motivation is relationally constructed and negotiated within structural constraints. The study underscores the importance of school environments that protect autonomy, acknowledge emotional labour, and cultivate trust as conditions for sustaining long-term teacher engagement. The Author(s) 2026 -
What Numbers Never Revealed: Tracing Dalit Christian Modernity Through Malayalam Literature
Kerala has a long-standing history of Christianity as well as conversions. Conversions can be dated back to the fifteenth and sixteenth centuries, which saw a large number of slave caste conversions. For the slave castes of KeralaPulayas and ParayasChristianity offered a salvation from the circle of pollution. Scriptures provided the slave castes new vistas of knowledge which they encultured to form a counter discourse against the public sphere set up by the dominant castes. The public sphere of the Malayalee psyche was formed by the ideas of caste pollution, which restricted the slave castes from accessing the social space. A new Dalit perspective on the religious consciousness of the converted Christians will show the role of the Bible, Original Sin, and Repentance on their daily lives. Dalit Christian literature becomes the primary source where Christianity metamorphoses into an oppositional force in resisting oppression as well as in creating a social space with agency. 2022 Indian Institute of Management, Ahmedabad. -
What We Think Others Think and Do About Climate Change: A Multicountry Test of Pluralistic Ignorance and Public-Consensus Messaging
Most people believe in human-caused climate change, yet this public consensus can be collectively underestimated (pluralistic ignorance). Across two studies using primary data (n = 3,653 adult participants; 11 countries) and secondary data (ns = 60,230 and 22,496 adult participants; 55 countries), we tested (a) the generalizability of pluralistic ignorance about climate-change beliefs, (b) the effects of a public-consensus intervention on climate action, and (c) the possibility that cultural tightness-looseness might serve as a country-level predictor of pluralistic ignorance. In Study 1, people across 11 countries underestimated the prevalence of proclimate views by at least 7.5% in Indonesia (90% credible interval, or CrI = [5.0, 10.1]), and up to 20.8% in Brazil (90% CrI = [18.2, 23.4]. Providing information about the actual public consensus on climate change was largely ineffective, except for a slight increase in willingness to express ones proclimate opinion, ? = 0.05 (90% CrI = [?0.02, 0.11]). In Study 2, pluralistic ignorance about willingness to contribute financially to fight climate change was slightly more pronounced in looser than tighter cultures, highlighting the particular need for pluralistic-ignorance research in these countries. The Author(s) 2025. -
Whats the best time to give work? A study on relationship between employee moods and performance at different time intervals
Employees change their behavior many times in a day due to many factors. It is not uncommon to see any employee being agitated over petty issues at work place. This paper aims at identifying meaning, relationships between moods and performance. Employees decision-making abilities depend on mood and his mood depend on his personality, work environment variables such as protocols, procedures, work events, dynamics of formal and informal communication. We equate this daily swing to three-time frames named morning, afternoon and evening. Our attempt has been to try to establish a relationship between moods and emotions and employee performance which can increase the productivity level of the employee. This research intends to establish a more robust relationship and involves better evaluative and interpretive models to cope with the non-linearitys related to the complexity of the model and facilitate better decision-making with more accurate and intricate or comprehensive yet simple approach. Development of such relationship will help managers in dealing with the employees and take measures to increase productivity by adopting suggestions and conclusions from this study. IJSTR2019. -
Wheat Disease Diagnosis using Transfer Learning on Convolutional Neural Networks
Wheat disease identification is essential for agricultural output and food security. Traditional diagnostic approaches are slow, ineffective, and need expert assistance, restricting their ability to grow in agriculture. Suggested innovative diagnostic method uses transfer learning on convolutional neural networks (CNNs) to effectively identify and classify wheat leaf diseases. To increase model predictions, high-quality image datasets from open-access platforms are normalised, resized, and augmented. The proposed CNN model performed best with 98.90% accuracy, 98.87% precision, and 98.80% recall. Transfer learning improved model performance by recycling knowledge from pre-trained CNN architectures, reducing training time and enhancing feature extraction. The results show improved precision as well as strength over standard methods and before. This technology helps farmers and agricultural professionals make timely disease management and crop management decisions. To improve disease recognition, future study may use a wider dataset range and other CNN designs. 2025 IEEE. -
Wheat Grain Identification Using Explainable Artificial Intelligence
This research delves into the innovative application of Explainable Artificial Intelligence (XAI) within wheat grain identification. Employing sophisticated machine learning models augmented by XAI techniques, the study aims to enhance the transparency and comprehensibility of decision-making processes associated with classifying wheat grains. Key objectives include refining model accuracy, imparting insights into critical identification-influencing characteristics, and developing an intuitive user interface tailored for end users, particularly farmers. Through a methodical analysis, the research underscores the significance of XAI in detecting flaws and fine-tuning the model, ultimately bolstering its reliability. The findings of this investigation carry implications for advancing agricultural practices, fostering stakeholder trust, and adapting to the ever-evolving dynamics of the environment. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Wheat Yield Prediction using Temporal Fusion Transformers
In precision framing, Machine Learning models are an essential decision-making tool for crop yield prediction. They aid farmers with decisions like which crop to grow and when to grow certain crops during the sowing season. Many Machine Learning algorithms have been used to support agriculture yield prediction research, but it is observed that Deep Learning models outperform the benchmark Machine Learning algorithms with a significant difference in accuracy. However, though these Deep Learning models perform better, they are not preferred or widely used in place of Machine Learning models. This is because Deep Learning methods are black box methods and are not interpretable, i.e., they fail to explain the magnitude of the impact of the features on the output, and this is unsuitable for our use case.In this paper, we propose using Temporal Fusion Transformer (TFT), a novel approach published by Google researchers for wheat yield prediction viewed as a Time Series Forecasting problem statement. TFT is the state-of-the-art attention-based Deep Learning architecture, which combines high-performance forecasting with interpretable insights and feature importance. We have used TFT to perform wheat yield prediction and compare its performance with various Machine Learning and Deep Learning algorithms. 2023 IEEE. -
When cloth colours become markers of caste identities: ritual performance and caste politics in contemporary Kerala
Keralas caste hierarchy, characterised by untouchability and social exclusion, historically provoked protests demanding temple entry and basic rights for marginalised Hindus. In 2024, during the centenary of the 1924 Vaikom Satyagraha, the annual Ashtami festival at the Vaikom Mahadeva Temple featured women participating in the Poothalam ritual procession and wearing colour-coded blouses that signified caste identities. The temple re-emerges as a ritual space where caste distinctions become publicly visible, which transforms a commemorative event into a site for expressing caste identities. This article argues that the colour-coded blouses worn in the ritual procession reconfigure caste as a performative and embodied marker of identity. The article further demonstrates how ritual practices re-inscribe historical hierarchies in contemporary Kerala. The study analyses media narratives and ritual symbolism to connect the historical struggle for equality with contemporary representations of caste in Kerala and draws on theories of social construction, cultural memory, and subaltern identity. 2026 Informa UK Limited, trading as Taylor & Francis Group. -
When will we learn to prioritise safety?
The government cannot absolve itself. It approved the event. It knew the scale of sentiment, emotional pitch, and logistical nightmare, yet it pressed ahead. -
Where is the Ground? Cultural Transmission and Psychological Adaptation of Sri Lankan-Tamil Ethnic Repatriates
This qualitative study aimed to explore the cultural transmission and psychological adaptation of the Indian-origin Sri Lankan Tamil ethnic repatriates (SLTER) in the context of life in repatriation (LIR). Participants were SLTER living in the northern interior regions of Kerala. Thematic analysis derived two major themes, Psychological consequences and expectations of repatriation and Mechanisms for coping with the aftermath of repatriation. Desire for settlements in Sri Lanka despite not holding Sri Lankan citizenship, psychological consequences of repatriation, including longing for the land of origin, manifestations of cultural and emotional shock, and the adoption of food styles analogous to Sri Lankan Tamil Culture (SLTC) were highlighted in the study. Gender and generational differences in psychosomatic symptoms upon arrival were observed. The coping mechanisms included rationalization and language internalization. Participants used ostensive and pointing gestures as initial steps to internalize Indian culture. They are also connected with their Sri Lankan Tamil culture and transmitted that culture to subsequent generations through various socially acceptable forms. They try to find a middle ground between citizenship and refugee status, often feeling torn between their Indian culture and their connection to Sri Lanka due to limited social and economic rights and experiences of marginalization in both countries. Although these aspects have been little investigated, they warrant significant scholarly attention in the context of ethnic repatriation. The Author(s) 2025 -
Where to Check Homework? The Emphasis on Supportive Feedback via Social Media by Teachers in CALL and Its Consequences on EFL Learners' Self-assessment, Academic Success, Academic Enjoyment
This study investigates the impact of Facebook-mediated supportive feedback on English as a Foreign Language (EFL) learners' self-assessment, academic enjoyment, and academic success in a Computer-Assisted Language Learning (CALL) context. Using a sequential exploratory methodology, this study holistically investigates the research objectives using qualitative and quantitative approaches. Two intact classrooms of lower-intermediate EFL students in an Iraqi language institute were selected; one class was designated as the experimental group receiving Facebook-mediated tasks and the other as the control group using conventional teaching strategies. Among the tools for data collecting were a teacher-made test, semi-structured interviews, and observation. Compared to the control group, the experimental groupwhich received extra Facebook-mediated tasks and conventional course materialsshowcased notably greater degrees of self-assessment, academic enjoyment, and academic success. Positive perceptions of Facebook-mediated interactions were found through the qualitative analyses of observations and interviews, thereby stressing learners' higher motivation, collaboration, and sense of community. The implications of the study are discussed. 2024, The Pacific Association for Computer Assisted Language Learning (PacCALL). All rights reserved. -
Whether CSR is internalized in corporate India? An empirical study
Purpose: The purpose of this research paper is to examine whether Corporate Social Responsibility is internalized in Corporate India?. Design/Methodology/Approach: The primary data were used to meet this papers main objective. The structured questionnaires were sent to 2100 managerial people in different sectors of corporate through email and finally 318 responses were received. These figures represent an acceptable response rate of 15 %. The collected were analysed and identified the findings with the help of appropriate statistical tools. Findings: The results demonstrate that there is significant difference among senior and top managers of the corporate India towards internalisation of CSR practices. Further, there is no difference between the managers personal profile and their perceptions CSR practices. The identified results are having managerial implications in the Corporate in India. Originality/Value: The authors main contributions are: Theoretical approach particularly stakeholder model of CSR has been discussed and made it link to the present days CSR practices of corporate India. Secondly the identified results are having managerial implications towards successful CSR strategy for the corporate India. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Whether shoppers of tier I city are aware about multi-brand outlets? /
Asian Journal Of Management, Vol.7, Issue 3, ISSN: 0976-495X (Print), 2321-5763 (Online). -
Which is the green generation? Amultigroup analysis of millennials and Generation Zs green consumerism
Purpose This study aimed to investigate how components of green marketing mix (GMM), green product (GPD), green price (GPC), green place (GPL) and green promotion (GPM) influence consumer attitudes (ATT), subjective norms (SNM), perceived behavioural control (PBC) and purchase intention (PI) and finally green consumerism (GCM). Design/methodology/approach Using Smart PLS 4 software and PLS-SEM approach, data were analysed for structural relationships among the components of GMM, ATT, SNM, PBC, PI and GCM. The model evaluates hypotheses linking GPD, GPC, GPL and GPM to ATT, SNM and PBC and examines how ATT, SNM and PBC affect PI and GCM. Findings The study revealed that GMM, as a higher-order construct, positively impacts ATT, SNM and PBC, while ATT, SNM and PBC partially mediate the relation between GMM and PI. PI then ultimately results in GCM. The multigroup analysis indicated there is no significant difference between the age groups examined. Research limitations/implications The study may not generalize to all industries or regions. Future research could explore additional factors like cultural or technological influences, and longitudinal studies may be conducted. Practical implications As environmental concerns grow, marketers should focus on consumer attitudes towards green products. Aligning green attributes with consumer values, transparent pricing and multi-channel communication can enhance ATT, SNM and PBC over green purchases, fostering acceptance and intention. Social implications While the findings promote GCM, their broader impact is contingent on genuine environmental practices. Without systemic changes in production and policy, GCM risks perpetuating superficial sustainability narratives. Originality/value This study advances the field by investigating how GMM influences purchase intentions (PI) among Indias urban Millennials and Generation Z, two generations pivotal to shaping sustainable consumption trends in a high-pollution economy. 2025 Emerald Publishing Limited -
Whispered Speech Emotion Recognition with Gender Detection using BiLSTM and DCNN
Emotions are human mental states at a particular instance in time concerning ones circumstances, mood, and relationships with others. Identifying emotions from the whispered speech is complicated as the conversation might be confidential. The representation of the speech relies on the magnitude of its information. Whispered speech is intelligible, a low-intensity signal, and varies from normal speech. Emotion identification is quite tricky from whispered speech. Both prosodic and spectral speech features help to identify emotions. The emotion identification in a whispered speech happens using prosodic speech features such as zero-crossing rate (ZCR), pitch, and spectral features that include spectral centroid, chroma STFT, Mel scale spectrogram, Mel-frequency cepstral coefficient (MFCC), Shifted Delta Cepstrum (SDC), and Spectral Flux. There are two parts to the proposed implementation. Bidirectional Long Short-Term Memory (BiLSTM) helps to identify the gender from the speech sample in the first step with SDC and pitch. The Deep Convolutional Neural Network (DCNN) model helps to identify the emotions in the second step. This implementation is evaluated using the wTIMIT data corpus and gives 98.54% accuracy. Emotions have a dynamic effect on genders, so this implementation performs better than traditional approaches. This approach helps to design online learning management systems, different applications for mobile devices, checking cyber-criminal activities, emotion detection for older people, automatic speaker identification and authentication, forensics, and surveillance. (2023), (Iranian Academic Center for Education). All Rights Reserved. -
Whispered speech emotion recognition with gender detection using hybridopti-gendernet
The Whispered Speech Emotion Recognition (SER) presents special challenges because it does not involve the vibration of vocal folds and less acoustic information, which makes it more difficult to identify the nuances of emotions and gender-related peculiarities than in normal speech. The research presents a new system, HybridOpti-GenderNet, of concurrent whispered speech emotion and gender recognition. It is a framework of six stages are data collection, pre-processing, feature extraction, feature selection, gender detection, and emotion recognition (ER). A Red Butterfly Optimization Algorithm (RBOA), which uses Butterfly Optimization Algorithm (BOA) and Red Kite Optimization Algorithm (ROA) by adjusting the weight to achieve optimal feature selection, is proposed to achieve a better balance between exploration and exploitation. Gender identification is carried out with the proposed HybridOpti-GenderNet, a new hybridization of Bi-LSTM and DCNN, and ER is accomplished with the help of the Attention-Enhanced Hybrid Belief Network (AHBN) that incorporates Deep Belief Network (DBN), Feedforward Neural Network (FNN) & a tailor-made attention mechanism to detect delicate emotional signals. The innovativeness of the given work is that the gender-informed recognition is combined with a high-level optimization and a hybrid deep learning pipeline that enhances the robustness of the analysis of whispered speech significantly. The system was tested in Python and tested on the GeWEC and EMO-DB data, showing superior performance in cases of privacy preservation, noisy conditions, and real-life human-computer interaction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. -
White LED Light-Mediated Eosin Y-Photocatalyzed One-Pot Synthesis of Novel 1,2,4-Triazol-3-Amines By Sequential Addition
Abstract: A facile and proficient, eco-friendly multicomponent synthesis of 12 novel biologically essential 1,2,4-triazol-3-amines via the sequential addition of substituted phenacyl bromide, aromatic aldehyde, hydrazinecarbothioamide, and urea under white LED with eosin Y as a photocatalyst has been developed. The intrinsic advantages are methodology is cost-effective, non-toxic, generates a high yield of product, is column chromatography free and does not need the use of a specific instrument. Surprisingly, our methodology uses moderate conditions and can count the tolerance of a wide variety of electron-donating and electron-withdrawing groups. The analysis and early conclusions give more value and context for the future development of organic synthesis using photocatalysts. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.