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Decoding Cognitive Control and Cognitive Flexibility as Concomitants for Experiential Avoidance in Social Anxiety
Background and objectives: Avoidance is regarded as a central hallmark of social anxiety. Experiential avoidance is perilous for social anxiety, specifically among university students (young adults). Additionally, cognitive control and cognitive flexibility are crucial components of executive functions for a fulfilling and healthy lifestyle. The current research is a modest attempt to understand how cognitive flexibility and cognitive control affect the emergence of experiential avoidance in social anxiety in young adults. Methods: Using an ex-post facto design, the Social Phobia Inventory was employed to screen university students with social anxiety based on which one hundred and ninety-five were identified. Thereafter, participants completed the standardized measures on experiential avoidance, cognitive control and cognitive flexibility. Results: A stepwise multiple regression analysis was computed wherein the cognitive control predicts an amount of 5% of variance towards experiential avoidance, whereas a 10% of additional variance has been contributed by cognitive flexibility. Interpretation and Conclusions: The statistical outcome indicated that cognitive control is positively associated with experiential avoidance which is a negative correlate to cognitive flexibility among university students. Both also emerged as significant predictors of experiential avoidance and add a cumulative variance of 15% towards the same. This conclusion supports the need for improved and efficient management techniques in counseling and clinical settings. The Author(s) 2024. -
Decoding Cognitive Control and Cognitive Flexibility as Concomitants for Experiential Avoidance in Social Anxiety
Background and objectives: Avoidance is regarded as a central hallmark of social anxiety. Experiential avoidance is perilous for social anxiety, specifically among university students (young adults). Additionally, cognitive control and cognitive flexibility are crucial components of executive functions for a fulfilling and healthy lifestyle. The current research is a modest attempt to understand how cognitive flexibility and cognitive control affect the emergence of experiential avoidance in social anxiety in young adults. Methods: Using an ex-post facto design, the Social Phobia Inventory was employed to screen university students with social anxiety based on which one hundred and ninety-five were identified. Thereafter, participants completed the standardized measures on experiential avoidance, cognitive control and cognitive flexibility. Results: A stepwise multiple regression analysis was computed wherein the cognitive control predicts an amount of 5% of variance towards experiential avoidance, whereas a 10% of additional variance has been contributed by cognitive flexibility. Interpretation and Conclusions: The statistical outcome indicated that cognitive control is positively associated with experiential avoidance which is a negative correlate to cognitive flexibility among university students. Both also emerged as significant predictors of experiential avoidance and add a cumulative variance of 15% towards the same. This conclusion supports the need for improved and efficient management techniques in counseling and clinical settings. The Author(s) 2024 -
Decoding Customer Lifetime Value to Unlock Business Success with Predictive Machine Learning Approach
This study highlights how crucial customers are for a company's success who directly impacts revenue and overall business value. This study focuses on analysis of customer lifetime value, the research uses data from 5000 customers with 8 important features with the main goal of predicting customer lifetime value. Business leaders often face choices about where to invest in marketing, like loyalty programs, incentives and ads or nothing. The study suggests that customer lifetime value is a key metric for making smart decisions, which measures how much a customer spends over their time with a company. To predict this value, the research explored different machine learning models - linear regression, decision tree regressor, random forest, and AutoML regressor. Each model is checked for how well it predicts customer spending habits. The results show that AutoML regression stands out for its accuracy without overcomplicating things. This study offers insights for businesses looking to improve their customer-focused strategies and long-term success. 2024 IEEE. -
Decoding customer sentiments in quick commerce: comparative insights from BlinkIt, Zepto, and JioMart utilizing machine and deep learning models
The rapid expansion of quick commerce platforms like BlinkIt, Zepto, and JioMart has introduced unique challenges in understanding customer sentiments due to their operational focus on ultra-fast deliveries and hyper-local logistics. This study conducts a comprehensive analysis of sentiment classification methodologies, exploring both traditional ML techniques and advanced DL models to classify customer reviews into positive, negative, and neutral categories. Traditional models, while offering simplicity and interpretability, achieved moderate accuracy (83% with SVM) but struggled to capture the complexities of neutral sentiments. In contrast, DL models, particularly LSTM, achieved superior performance with an accuracy of 88.96% and a macro F1-score of 0.64, leveraging pre-trained embeddings like GloVe to enhance semantic understanding and contextual representation. Further experiments with optimizers, including Adam, RMSprop, SGD, and Nadam, revealed their limited impact on resolving class imbalance and improving neutral sentiment classification. To address these challenges, we integrated hybrid architectures combining GloVe and BERT embeddings, achieving a significant accuracy of 90.69% and demonstrating improved generalization across sentiment classes. However, the classification of neutral sentiments remained a persistent challenge, underscoring the need for advanced techniques like data augmentation and ensemble strategies. This research highlights the importance of adopting hybrid and deep learning-based approaches for sentiment analysis in quick commerce platforms. The findings provide actionable insights for enhancing customer satisfaction and service quality, while also paving the way for future research in domain-specific sentiment classification and scalable solutions for underrepresented sentiment categories. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2026. -
Decoding HERO: Predicting psychological capital with subjective well-being
The positive psychology movement has gained momentum in recent years and organizations have ascribed great importance to employee well-being in light of the favorable outcomes associated with it. The widely researched Psychological Capital (PsyCap) has been consistently linked to well-being across a variety of contexts but a gap still exists in literature about what lies to the 'left' of psychological capital. The present study attempts to fill this gap by examining subjective well being components- positive and negative affect and life satisfaction, as potential antecedents of PsyCap. The Academic PsyCap questionnaire, the Positive and Negative Affect Schedule (PANAS) and the Satisfaction with Life Scale (SWLS) were administered to participants. Results confirmed the expected associations between affect and PsyCap-positive affect positively predicted PsyCap and its four constituents whereas negative affect emerged as a negative predictor of PsyCap and its dimensions. Life satisfaction positively predicted only individuals' total hope scores. Thus, highlighting the role of subjective well-being components as antecedents of PsyCap, these findings suggest that promoting higher positive affect and lower negative affect can do more than just make individuals feel good, rather, it can bolster their reservoirs of crucial psychological resources as well. 2021 Ecological Society of India. All rights reserved. -
Decoding impermanent narratives: A study of transient migrants as digital influencers on YouTube
Students migrate from India annually for higher education in large numbers. Social media has become an essential network for disseminating information related to aspects of migration like student visas, college applications, residence and finances. YouTube engages vigorously in this dispersion of information. Many times, the sources of these kinds of information are found to be transient migrants themselves. YouTubers and influencers like Tushar Bareja, Nidhi Nagori, Gursahib Singh, Bani Singh and Saloni Verma, among others, have made a niche, creating content and sharing information about the experience of being a transient migrant. Much like the status of being transient, creating ones brand on social media is both dynamic and fleeting, which cannot be defined in a sense of permanence. The analysis of content created by YouTube influencers enables an insight into the definition of transient migrant identity. The topics that are covered in the content showcase the particular components of international student life that add to the concept of a transient migrant identity. The article attempts to ask the question of how the YouTube videos made by student migrants end up contributing to the transient migrant identity. It also attempts to decipher how the transient identity itself is packaged as a commodity to be monetized by these student migrant influencers on YouTube. Using theoretical frameworks of influencer culture, social media and migration, the article attempts to unravel the workings of YouTube in commodifying the transient migrant experience. 2025 Intellect Ltd. -
DECODING INTENTIONS TO PURCHASE ORGANIC FOOD PRODUCTS IN AN EMERGING ECONOMY VIA ARTIFICIAL NEURAL NETWORKS
Purpose. This study investigates the factors influencing consumers intentions to purchase organic food products in an emerging economy. It addresses the knowledge gap regarding the slower growth of the organic food market in these regions despite the global trend toward environmental sustainability. Methodology / approach. A survey approach involving 350 participants was used. Structural equation modeling (SEM) with SmartPLS 4 and Artificial Neural Network (ANN) with IBM SPSS 28 were used to analyse the impact of awareness of need, personal norms, environmental concern, and health consciousness on the intention to purchase organic food products. Results. The study found significant positive influences of awareness of need, personal norms, environmental concern, and health consciousness on the intention to purchase organic food products, explaining 63.1 % of the variance. Both the analysis approaches (PLS-SEM & ANN) revealed that, health consciousness, followed by awareness of need, emerged as the most important factor related to the intention to purchase organic food products. The results highlight the importance of awareness and personal values in driving pro-environmental behaviour. Originality / scientific novelty. This research offers essential insights into the determinants of organic food purchase intentions in an emerging economy. It emphasises the significance of awareness and personal values in fostering sustainable consumption behaviour, addressing a less explored area in existing literature. Practical value / implications. The findings have important implications for policymakers and marketers. Strategies focused on consumer education about the benefits of organic food can enhance awareness and appeal. Understanding core psychological needs and beliefs that shape consumer motivations can guide the development of effective marketing strategies. The study highlights the strong environmental consciousness among consumers and their desire to protect the environment. 2024, Institute of Eastern European Research and Consulting. All rights reserved. -
Decoding math : A review of datasets shaping AI-driven mathematical reasoning
Math problem solving is a fundamental part of the modern era, and artificial intelligence (AI) driven mathematical reasoning has become an essential part of data work. In this literature review, we explore the diverse array of datasets intended to improve AI models capacity to solve mathematical word problems. These datasets not only provided diverse problem sets but also served as benchmarks for evaluating the performance of various deep learning models, including recurrent neural networks (RNNs) and graph-based models. The datasets, particularly GSM8K, posed challenges that even the most sophisticated transformer models struggled to overcome, setting a new standard for the study of AI systems in math problem solving. This literature review aims to provide a comprehensive overview of the evolving landscape of mathematical problem solving, paving the way for future advances in AI-driven mathematical reasoning. 2025, Taru Publications. All rights reserved. -
Decoding Quality of Life in Urban Spaces: A Case Study of Nagpur City, India
Urban Quality of Life (QoL) is becoming increasingly important to individuals due to the global increase in urban populations brought on by rapid population growth and urbanisation processes. To accommodate the inflow of people, cities undergo alterations in physical features concurrently. The development of a city is greatly influenced by urban planning. Cities that develop face overcrowding, shoddy urban planning, poverty, high housing costs, and labour shortages incoherently. This may also result in a lack of investment and poor city management. It makes life more difficult for many individuals and may even increase crime and harm the environment (Zhang, X.Q.,2016). This means that policies and rules should emphasise fostering urban development and enhancing infrastructure, such as buildings and services. Policies should focus on what each location requires and employ various techniques, including rules, market tactics, and spatial planning, to ensure that cities flourish in a positive way. Urban Quality of Life (QoL) refers to how enjoyable living is in a town, considering how residents interact with their surroundings (Das, D., 2008). 2025 selection and editorial matter, Uday Chatterjee, Avishek Bhunia, Jyothi Gupta and Krishnendu Gupta; individual chapters, the contributors. -
Decoding Retail Realities: Traditional Retailers' Outlook on Sales Erosion to Modern Retail Economy
The traditional retail landscape in Indian metropolises has changed significantly in the last several decades, mostly due to the modern retail economy's growth, including corporate chain stores and e-commerce sites. Small merchants have been gradually displaced as a result of this paradigm shift, which has been exacerbated by changed Foreign Direct Investment (FDI) laws that have brought significant money into the Indian market, as well as a rise in consumer disposable income and the wave of digitalization. This study explores small merchants' consequences as they contend with the growing power of organized retail and e-commerce behemoths. Despite earlier research studies mostly focusing on the organized trade's exponential rise due to changing customer behavior, this paper fills this gap by illuminating the traditional retailers perspective towards the contemporary retail landscape and highlighting the threats to small businesses with a traditional focus. The study uses empirical analysis using tools like SPSS and SEM models to examine the initial troubles faced by small retailers of fast-moving consumer goods (FMCG), highlighting the difficulties they face in competing with the powerful forces of deep discounting, massive sales events, and evolving consumer tastes. This exploratory research analyzed the undermining factors like utilitarian and hedonic, purchasing patterns, menaces, hindrances, pecuniary and location as reasons for the retail paradigm from traditional to modern trade. The outcome emphasized that utilitarian factors like ambience, experience, status, variety, payment modes, single-store distribution and assortment are the drivers behind the explosion of traditional trade by the modern trade in retail economy. 2024 The Author(s). -
Decoding sustainability: A machine learning-based analysis of socioeconomic drivers in global sustainable developmental goals progress
Sustainability, a concept that gained prominence with the Brundtland Report in 1987, is defined as a development approach that addresses present needs without jeopardizing the ability of future generations to meet theirs. Over the years, sustainability has evolved beyond its initial environmental focus, now encompassing economic, social, and political dimensionsmaking it an essential pillar of modern development initiatives. To drive global sustainable development forward, the United Nations adopted the 2030 Agenda, featuring 17 Sustainable Development Goals (SDGs). These goals aim to resolve some of the most pressing challenges faced by humanity, including poverty eradication, climate action, gender equality, and economic growth. The SDG Index, which evaluates a countrys progress toward these goals, helps measure and compare performance across nations. The Intersection of Socioeconomic Factors and SDG Progress is significant for the growth of a country. A countrys Gross Domestic Product (GDP) has often been seen as a key economic indicator, reflecting its ability to invest in sustainable initiatives. However, sustainability is not solely dependent on financial resourcessocial factors play a critical role. To assess the connection between well-being and sustainability, researchers often analyze the Happiness Index alongside SDG scores. Countries demonstrating both high happiness levels and strong sustainability scores provide valuable insights into the relationship between social welfare and global progress. Furthermore, machine learning (ML) techniques have emerged as powerful tools in sustainability research. By analyzing vast datasets, AI-driven approaches can predict trends, optimize resources, and enhance policy implementationaccelerating progress toward a sustainable future. The Evolving Landscape of Sustainability and Its Global Impact is realized using statistical and ML approaches in this study. Rethinking Strategies for a Sustainable Tomorrow is very important in 2025 as we are approaching 2030 very fast. Understanding the underlying factors influencing SDG scores allows nations to refine their approaches to sustainability. By tailoring action plans based on socioeconomic conditions, governments can improve their policies, ensuring both environmental stewardship and enhanced quality of life for their citizens. As global challenges evolve, interdisciplinary approachesspanning technology, economics, and social scienceswill continue to shape sustainability efforts, fostering a future where development aligns seamlessly with environmental and societal well-being. 2026 selection and editorial matter, Siddhartha Bhattacharyya, Jan Plato, Soumyadip Dhar, Naba Kumar Mondal, Ivan Zelinka, Jyoti Sekhar Banerjee and Abhijit Das; individual chapters, the contributors. -
Decoding the alchemy of employee retention: A case of the manufacturing sector of the National Capital Region, India
The ability of a company to retain its staff is referred to as employee retention. It may also be referred to as a decrease in employee attrition or employee turnover rate. Employee retention is one such mechanism which ensures that the human capital stays with the organisation for a longer duration. The study focusses on identifying the drivers of employee retention in the manufacturing industry with respect to certain factors such as mentoring, career development, work environment, job autonomy, and compensation. This research has used the descriptive research design with some elements of exploratory research design. The sample size for the study was 122. Primary data has been collected with the help of a prevalidated questionnaire with multiple-choice closed-ended questions on a five-point Likert scale. The collected data was analysed using Excel and SPSS with statistical tools like T-test, ANOVA, multiple linear regression, etc. A direct positive relation has been found between mentoring, work environment and compensation, and the employees' intention to stay. 2024, IGI Global. -
Decoding the Impact of Social Media on IPL Player Retention Using Sentiment Analysis and Ensemble Learning
This research query contrasted the use of player performance measures and fan sentiment rating scores in predicting player retention in the Indian Premier League (IPL). With the use of quantitative variables such as batting averages and bowling economies and qualitative variables including sentiment and visibility scores in over 1000 Reddit comments and posts, the research utilizes machine learning algorithms such as the Balanced Random Forest Classifier and Easy Ensemble Learning algorithms for enhancing decision-making on retention. In contrast to earlier approaches, which have largely disregarded the role of retention decision-making and qualitative data use in this context, the present study closes this gap by combining fan sentiment measures with visibility. The findings show that although conventional metrics hold, public opinion and sentiment have increasingly become factors in retention policy, particularly in the recent past. The highest performing model, which is a blend of both qualitative and quantitative traits, has an overall accuracy of 88%. The study finds the shift toward a more holistic, integrated approach, with the focus being on the data-driven nature of IPL team management for marketability, off-field pertinence, and on-field performance. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Decoding the Surge in Rural Employment Understanding the Post-pandemic Shift in Rural India
The increase in the rural workforce during and after the lockdown was primarily driven by women entering self-employment in agriculture, where earnings remain significantly low. The movement from casual work to self-employment in the agricultural sector also underlines a larger shift in dynamics in rural areas, arguably exacerbated by the pandemic. The non-manufacturing sector, most importantly the construction sector, absorbed men in the post-pandemic situation, but the same shift is not observed among women. 2026, Economic and Political Weekly. All rights reserved. -
Decoding the X-Ray Flare from MAXI J0709-159 Using Optical Spectroscopy and Multiepoch Photometry
We present a follow-up study on the recent detection of two X-ray flaring events by MAXI/Gas Slit Camera observations in soft and hard X-rays from MAXI J0709-159 in the direction of HD 54786 (LY CMa), on 2022 January 25. The X-ray luminosity during the flare was around 1037 erg s-1 (MAXI), which got reduced to 1032 erg s-1 (NuSTAR) after the flare. We took low-resolution spectra of HD 54786 from the 2.01 m Himalayan Chandra Telescope and the 2.34 m Vainu Bappu Telescope (VBT) facilities in India, on 2022 February 1 and 2. In addition to H? emission, we found emission lines of He i in the optical spectrum of this star. By comparing our spectrum of the object with those from the literature we found that He i lines show variability. Using photometric studies we estimate that the star has an effective temperature of 20,000 K. Although HD 54786 is reported as a supergiant in previous studies, our analysis favors it to be evolving off the main sequence in the color-magnitude diagram. We could not detect any infrared excess, ruling out the possibility of IR emission from a dusty circumstellar disk. Our present study suggests that HD 54786 is a Be/X-ray binary system with a compact object companion, possibly a neutron star. 2022. The Author(s). Published by the American Astronomical Society. -
Decolonising Caste in the Indian Context: The Psyche of the Oppressor
Caste is a social construct as well as a psychological phenomenon. So far, it has been predominantly viewed, understood and researched through the lens of anthropology, sociology, economics and political science. However, very little understanding has been gained in the domain of psychological science with respect to caste in the Indian context. The population of the Global South (includes the regions of Asia, Africa, Latin America and Oceania) cannot be understood with the frameworks and research undertaken by the Global North (Europe and North America, known as the West, the industrialised world) because the knowledge production centres of psychology have predominantly been Euro-American centric, as many critics have pointed out. Although research has been scarce in relation to caste and psychology, it has mostly revolved around the oppressed. Therefore, this article aims to shift the focus from the oppressed to the oppressor. To understand Indian human behaviour and thought, it is essential to view it through the lens of the colonial past, the caste system and religion, which are intertwined with each other. This article aims to look at the psychology of the oppressor in the Indian context through the psychological frameworks of purity and pollution. It also stems from the premise that casteism is inculcated through modelling and intergenerational learning. Hence, the above-mentioned factors help to understand unequal power relations and discrimination, which facilitate the decolonisation of the Indian psyche. It also highlights the influence of colonisation on the mind and behaviour with respect to caste. 2023 Department of Psychology, University of Allahabad. -
Decolonising the Gateway of India
This article interrogates how a colonial monument, the Gateway of India in Mumbai, former Bombay, continues to carry and be endowed with a title that is a misplaced embodiment of Indian social histories. Built in the 1920s, this monument, definitely a work of architectural grandeur, continues to carry its erroneous rendition and confines Indias vast social histories to the colonial moment, with an anglo-centric focus. As the monument symbolises the memory of the colonial regime, it also signifies its oppression as well as its exit from the subcontinent, rather than witnessing anyone coming to India, except King George in 1911, as the monuments title seems to suggest. A mnemonic device of colonialism, this misleading label needs to be seriously revisited, for it not only romanticises the colonial past but also fails to lead our memories back to certain crucial episodes in earlier social histories, from which the monument and its specific place, Mumbai, are more or less fully absent. 2023 The Author(s). -
Decolonizing Counselling: Integrating Non-Western Perspectives in Mental Health Intervention
This paper discusses the need to decolonize mainstream counseling practices, predominantly influenced by Eurocentric perspectives, by incorporating non-Western views and experiences. It highlights the importance of recognizing the fluidity of self and identity within diverse social and ecological contexts, particularly in countries like India, where mental health issues are on the rise. The paper critiques the limitations of Western therapeutic approaches in non-Western cultures. It emphasizes the significance of integrating local knowledge systems, such as indigenous healing traditions like the Siri cult, which promotes communal healing and addresses the spiritual dimensions of mental health. It advocates for a holistic approach to therapy that incorporates spiritual elements, encouraging self-transcendence and interconnectedness, and ultimately challenges the individualistic focus of Western psychotherapy. Integrating traditional practices and philosophies, such as Bhakti and mindfulness, is essential for fostering a more inclusive and effective mental health framework. The Author(s) 2025 -
Decolonizing English Studies in India: Teaching of Native American Literatures in South Indian Universities
Contemporary higher education emphasizes glocal frameworks that accommodate both global and regional priorities in development. Decolonization of education becomes crucial in this context, where colonization led to the marginalization of Indigenous cultures, including Native American cultural traditions and knowledge systems. Multicultural inclusivity in higher education observes marginalized epistemic systems and gives them a place in the curriculum. By incorporating Native American texts in the English studies university syllabi in India, decolonization is brought into purview. This chapter deals with how the South Indian universities introduce Native American texts. The authors argue that multiculturalism in this context contributes to decolonial pedagogy, and the existing epistemic gap due to colonial oppression is problematized by inspecting the epistemic traditions of former colonies outside India. Content analysis of syllabi in the Central and state universities is the qualitative method used. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Decolonizing Open Science: Southern Interventions
Hegemonic Open Science, emergent from the circuits of knowledge production in the Global North and serving the economic interests of platform capitalism, systematically erase the voices of the subaltern margins from the Global South and the Southern margins inhabiting the North. Framed within an overarching emancipatory narrative of creating access for and empowering the margins through data exchanged on the global free market, hegemonic Open Science processes co-opt and erase Southern epistemologies, working to create and reproduce new enclosures of extraction that serve data colonialism-capitalism. In this essay, drawing on our ongoing negotiations of community-led culture-centered advocacy and activist strategies that resist the racist, gendered, and classed structures of neocolonial knowledge production in the metropole in the North, we attend to Southern practices of Openness that radically disrupt the whiteness of hegemonic Open Science. These decolonizing practices foreground data sovereignty, community ownership, and public ownership of knowledge resources as the bases of resistance to the colonial-capitalist interests of hegemonic Open Science. The Author(s) 2021.