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HEES-Based IFVR for Energy-Saving Application Using DCDC Converter
The rapid response capabilities of high-conducting electromagnetic energy storage (HEES) devices are advantageous for mitigating sudden fluctuations in voltage and power. However, the cost of HEES coils significantly exceeds that of traditional battery energy storage solutions. To enhance the efficiency of energy use and diminish the costs associated with energy storage across multiline power distribution systems, this study presents an innovative approach involving an interline dc flexible voltage restorer (IFVR) configuration. This approach utilizes a single HEES coil connected to several compensating circuits. The innovation introduces a currentvoltage (VI) chopper assembly with multiple input/output power connections, enabling the connection of one HEES coil to various power lines. This setup ensures the independent management of energy exchanges for any compensated line. Importantly, when multiple power lines require compensation simultaneously, the HEES coil can be selectively activated to prioritize compensation based on the designated order of importance of the lines. The practicality of this method is confirmed through technical verification, demonstrating its ability to sustain transient voltage stability during voltage increases and decreases on multiple lines. These scenarios may arise from fluctuations in output voltage from power external supplies or variations in load demand from locally connected loads. 2021 IEEE. -
Government Support Mechanism in Perishable Food Supply Chain: A Transition from Sustainability to Circularity
The transition from sustainability to circularity within the food supply chain (FSC) is intricate and multifaceted. Governmental efforts involve educating the perishable food sector about the advantages of circularity. The transition to circularity necessitates a reassessment of current business models and an emphasis on innovative practices. Therefore, the purpose of this article is to identify the potential enablers of government support mechanism in the transition from sustainability to circularity in perishable FSC. Furthermore, the study ranks the enablers according to their respective significance, adopting fuzzy simple additive weighting (SAW) method. Fuzzy SAW approach is selected as it can handle uncertainty and vagueness in the decision-making process, which is common when dealing with qualitative factors and subjective judgments. The study evaluates seven alternatives in relation to four criteria using the fuzzy SAW method. The findings from the study highlight fostering collaborative partnerships, innovative infrastructural support, and enforcing regulations and standards as the top three ranked enablers. The study contributes to the existing literature on sustainability and circularity in FSCs. The results from the study can assist the industry in focusing efforts on circularity and help businesses align practices with government policies. 1973-2011 IEEE. -
Provably Adaptive Trust Dynamics in Context-Aware Zero-Trust Systems: A Formal Framework for Continuous Verification
Zero-Trust (ZT) requires continuous, context-aware evaluation of authentication and authorization decisions. This paper introduces Zero-Trust Hybrid Adaptive Authentication (ZeTHAA), a continuous authentication and authorization framework integrating contextual attributes, authentication strength, behavioral evidence, and retry dynamics. ZeTHAA utilizes a probabilistic risk model and dual-policy thresholds to partition outcomes into allow, step-up, and block regions, enabling precise control over security-usability trade-offs. The system introduces a global admissibility predicate to distinguish hard violations from probabilistic soft violations. Attribute importance is dynamically derived from entropy and Beta-posterior distribution, enabling robust cold-start initialization and online recalibration. ZeTHAA presents a unified composite attack surface covering credential compromise, attribute forgery, and post-grant hijacking, modeling retry behavior with exponential risk escalation and temporal decay. A large-scale synthetic dataset capturing realistic authentication flows, adversarial and temporal patterns, was used to evaluate ZeTHAA against heuristic, logistic regression, random forest, XGBoost, and isolation forest baselines. ZeTHAA produced a more expressive risk distribution and significantly higher attack detection and efficiency while minimizing user friction. ZeTHAA outperformed baseline models, with Recall and Area Under the Curve (AUC) exceeding 79% and 15.1%, respectively. F1-Score showed increases of 48%-147%, with efficiency boost of 20-65%, while reducing the cost per attack by up to 39.6%. Benchmarks against frameworks from Dasu et al. and Matiushin et al. showed a 57.5% lead in F1-Score, more than double increase in detection rate, while blocking 70.78% more attacks. Additional analysis shows that ZeTHAA provides a mathematically grounded foundation for Zero-Trust systems, aligns with NIST standards, offering improved security guarantees and adaptive enforcement. 2013 IEEE. -
Adversarial Shadows in Digital Forensics: New Insights Into File Fragment Classification Vulnerabilities and Defenses
The paper is a comprehensive survey of adversarial attacks on file fragment classification (FFC) models - a relatively unexplored area in digital forensics, given the increasing application of machine learning techniques. Unlike image or text classification adversarial attacks, adversarial attacks on FFC exploit statistical and structural properties at the byte level in systems that lack semantic or perceptual knowledge. Such properties necessitate the use of domain-specific defense strategies, as the defense strategies adopted from other domains are typically not effective for the problems of FFC. The survey comprehensively evaluates attack mechanisms relevant to FFC, including evasion and poisoning attacks, and discusses their impact on forensic reliability. It highlights the absence of domain-specific benchmarks, robust evaluation protocols, and systematic research on the adversarial robustness of FFC. The paper also discusses the different types of byte level perturbations that can happen in fragment data, and it sets specific research priorities for raising the reliability of machine learning-based digital evidence recovery and security. The paper provides building blocks for future work, offering practical insights for development in ensuring file fragment classification systems utilized in forensics are secure. 2013 IEEE. -
A New Versatile Discrete Distribution for Censored Data: Frequentist and Bayesian Methods With Real-Life Applications
This study introduces a novel and highly flexible class of discrete probability distributions tailored to model the diverse monotonic failure-rate patterns frequently observed in stock-market data. The proposed distribution accommodates outliers effectively and serves as a discrete analogue of the exponential law, enabling analysts to derive robust and interpretable insights into market dynamics. Fundamental mathematical characteristics of the distributionsuch as the probability-generating function, mean, and varianceare thoroughly derived. The model is further extended to handle Type-II censored data, enhancing its applicability to real-world scenarios where incomplete observations are common. Parameter estimation is performed using both maximum-likelihood and Bayesian approaches, with a special focus on techniques suitable for censored samples. The performance and reliability of the estimators are examined through extensive simulation studies. To validate the practical utility of the model, it is applied to five real stock-market datasets obtained from Indiastat. The results demonstrate a superior empirical fit, affirming the models relevance in capturing the underlying patterns of financial time series. This distribution provides a valuable tool for analysts and researchers in the fields of financial statistics, risk modeling, and market behavior analysis. 2013 IEEE. -
Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach
Social media hashtags function as critical organizational markers in digital discourse, yet traditional weighting methods fail to capture their dynamic significance across temporal and contextual dimensions. This paper presents a novel thermodynamic framework that conceptualizes social network activity as system 'temperature', applying statistical mechanics principles to model hashtag importance as process innovation. We establish mathematical foundations based on the Maxwell-Boltzmann distribution, providing an information-theoretic justification for dynamic hashtag weighting. Our approach incorporates activation thresholds and power-law scaling behaviors through a temperature-dependent function, with Simple Moving Average techniques implemented to stabilize temperature estimation, mathematically reducing variance by a factor of 1/N. Empirical evaluation using Twitter discourse from the US Presidential Election demonstrates unprecedented improvements in clustering performance: Silhouette Scores increased from 0.0126 to 0.9070 for Trump-related content and from 0.0105 to 0.8220 for Biden-related content, while Calinski-Harabasz Scores improved from 65.51 to nearly 98 million. These findings establish a rigorous mathematical bridge between thermodynamic systems and social media behavior, contributing to computational social science by providing a theoretical framework that significantly enhances discourse community detection in politically polarized environments. The approach enables more accurate identification of topic clusters, revealing distinct discourse patterns that conventional methods fail to capture. 2025 The Authors. -
A Novel SHiP Vector Machine for Network Intrusion Detection
In this paper, network intrusion detection is proposed using an improved version of the support vector machine model to detect DoS attacks. Here, the SVM model considers the weight parameter along with the kernel to find the best decision boundary that separates the data into DoS and normal. The proposed model provides a novel kernel trick that reduces the overlapping of data. The intrusion detection system aims to construct an ideal system that can detect attacks with very high performance using a ShiP vector machine(Sophisticated High Performance Vector Machine). The framework comprises three major steps: data collection and preprocessing, Recursive Feature Elimination (RFE) based feature selection, and the ShiP Vector Machine classification strategy. The system is evaluated using the DoS dataset from UNSWNB15 and real time PSD-23 sniffer dataset. DoS data is generated by extracting the normal and DoS attacks from the UNSWNB15 dataset. Experimental results show that the proposed ShiP vector machine shows outstanding performance by achieving 96.44 % accuracy on the DoS dataset and 90.12 % accuracy for real time PSD-23 data. 2013 IEEE. -
A Quantum-Enhanced Artificial Neural Network Model for Efficient Medical Image Compression
The ability to effectively store and transmit high-resolution images such as MRI and CT scans without losing quality is critical to modernizing medical imaging. Traditional compression methods risk losing essential medical image data, which requires perfect detail for diagnosis. Quantum algorithms use superposition and entanglement to compress faster while preserving important information. This research presents a Quantum-enhanced Artificial Neural Network (QANN) model that combines quantum feature extraction with classical neural network topologies to improve image compression. Our approach consists of converting standardized classical data into quantum states, controlling these states using parameterized quantum circuits, and measuring the resulting states to produce enhanced feature vectors. The quantum-enhanced features are fed into a traditional neural network for image compression. The experimental results clearly show that our QANN framework outperforms standard models in terms of accurate reconstructed images, reduced size, and increased space-saving percentage, especially when dealing with large and complicated datasets. The QANN model demonstrates how quantum computing can significantly enhance the effectiveness of medical image processing solutions. Kaggle brain CT and MRI datasets and COVID-CXNet chest x-ray images are used. The proposed QANN model improves peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Using quantum technology, the image size is reduced for MRI (73.3 %), X-ray (74.1%), and CT-SCAN (71.8%) to save space. 2025 IEEE. -
Positive ageing: self-compassion as a mediator between forgiveness and psychological well-being in older adults
Purpose: Positive aging aims to promote the physical health and psychological well-being of older adults for them to age successfully. Under the domain of positive aging, this study aims to explore the mediating role of self-compassion between forgiveness and psychological well-being in older adults. Design/methodology/approach: It was based on a quantitative research design, with a sample of 250 individuals within the age group of 6075 years. Data was collected using Self-compassion Scale (2003), Heartland Forgiveness Scale (2005) and Psychological Well-being Scale. Analysis was performed using Pearsons correlation, linear regression, followed by the generalised linear model of mediation. Findings: The results revealed a significant (p ? 0.001), high and positive correlation between self-compassion and forgiveness (r = 0.821), forgiveness and psychological well-being (r = 0.852) and self-compassion and psychological well-being (r = 0.802). Linear regression suggested that self-compassion and forgiveness are significant (p ? 0.001) predictors of psychological well-being, causing a variance of 75.6%. Mediation revealed significant (p ? 0.001) direct, indirect and total effect between the variables, showing that self-compassion partially mediates the relationship between forgiveness and psychological well-being. Research limitations/implications: The findings provide valuable insights on how fostering self-compassion along with forgiveness can improve psychological well-being among the elderly, however, research on additional variables, drawing comparisons between gender, economic status and clinical populations can be further explored. Nevertheless, this study can be used to develop interventions and therapeutic techniques to enhance self-compassion and forgiveness to improve psychological well-being among older adults. Originality/value: As per the best knowledge of the researcher, this work is original as it is a primary research and no data has been collected of a similar nature from the participants. 2024, Emerald Publishing Limited. -
Role of psychological well-being, quality of life and distress tolerance in caregivers of geriatric population: an Indian exploratory study
Purpose: This study aims to gain an understanding of how caring for an ageing population affects caregivers psychological well-being, quality of life and ability to tolerate distress. This study provides valuable insights into the challenges faced by family caregivers and underscores the critical need for comprehensive support systems. Design/methodology/approach: A correlational method and cross-sectional research design was used for the study. For this, a sample of 200 caregivers in the age range of 2560 years who were taking care of the geriatric population above the age of 70 years for a minimum of one year were chosen. Four questionnaires ? Burden Scale for Family Caregivers, Psychological Well-Being Scale, World Health Organizations Quality of Life Scale-BRIEF version and Distress Tolerance Scale were chosen. Correlation and multivariate regression were calculated using statistical package for social sciences (SPSS) 21 and Jamovi 3.4.1. Findings: This study found that there is a negative correlation of caregiver burden with psychological well-being, quality of life and distress tolerance. The sub-domains of self-acceptance, psychological health and tolerance levels were most impacted for the caregivers. Through multivariate regression, it was found that the caregiver burden significantly predicted psychological well-being and quality of life. Research limitations/implications: This study focuses on the English-speaking caregivers which may overlook the diverse linguistic and cultural variations within the broader caregiver community in India and the data collection exclusively targeted family caregivers providing support to geriatric population without chronic illnesses. This restriction could potentially limit the generalizability of the findings to the broader caregiving context. Practical implications: The implications of this research are that for caregivers, this study underscores the importance of tailored support programmes that address the negative impact of caregiver burden on psychological well-being and quality of life. Health-care professionals can use the findings to incorporate mental health assessments and interventions within caregiving contexts, recognizing the interconnected nature of these variables. Policymakers can use the findings to inform policies related to caregiver support and health-care resource allocation. Originality/value: In India, the social norm is that children are expected to take care of their parents when they become old. Taking care of elderly parents can be challenging, even emotionally. As a result, this study will focus on how caregivers psychological well-being, quality of life and ability to tolerate distress are affected. Consequently, promoting the creation of community support groups and workplace mental health programmes which could give caregivers a forum to voice their concerns. 2024, Emerald Publishing Limited. -
Does integrated store service quality determine omnichannel customer lifetime value? Role of commitment, relationship proneness, and relationship program receptiveness
Purpose: Building on the relationship marketing and stimulus-organism-response (SOR) theory, the purpose of this paper is to study the impact of the integrated store service quality (ISSQ) on the omnichannel customer lifetime value (CLV). The mediating role of customer commitment (affective, normative and continuance) and relationship program receptiveness with the moderating role of customer relationship proneness were relied upon to better understand the omnichannel customer profitability metric (CLV). Design/methodology/approach: The study is descriptive and relies upon the cross-sectional data collected using the self-administered structured questionnaires from 785 omnichannel shoppers. A purposive sampling technique was performed in the study. Structural equation modeling was performed using the SMART-PLS 4.0 software to analyze the data. Findings: The results indicate that omnichannel customer commitment (affective, normative and continuance) differentially mediates the relationship between ISSQ and relationship program receptiveness, subsequently impacting the omnichannel CLV. The customer relationship proneness significantly and positively moderated the relationships between different dimensions of customer commitment and relationship program receptiveness. Research limitations/implications: The study relied upon the cross-sectional data from the Indian population aged above 18years for testing the proposed model. Further studies could test the model across different populations to generalize the study results. Originality/value: This study addresses the need to investigate the omnichannel retail store customer profitability and their relationship performance with the store. By testing the customer relationship management model in the omnichannel retail store context, this study is the first to show that ISSQ will impact the customer profitability and relationship performance metric (CLV) through omnichannel customer commitment and relationship program receptiveness. The moderating effect of customer relationship proneness on a few proposed hypotheses was also tested to give managerial recommendations. 2024, Emerald Publishing Limited. -
Routing TQM through HR strategies to achieve organizational effectiveness: themediating role of HR outcomes in India
Purpose: The present research focuses on improving the awareness related to soft total quality management (TQM) practices by looking from the viewpoint of strategic human resources (HR). In addition, it is intended to reflect on the resulting soft TQM-HR outcomes and determine the mediating effect between soft TQM-HR strategies and organizational effectiveness (OE). Design/methodology/approach: An exploratory research methodology with an online survey technique was adopted for the study. Three hundred and three managerial-level personnel from nine large Indian manufacturing organizations participated in the research. A theoretical model is projected and verified using correlation and mediation analysis. Findings: The results show that commitment, reduced turnover intentions and satisfaction levels of employees mediate the relationship between resources, development and retention strategies and OE. However, the retention strategy has the strongest association with the OE of the three strategies. Also, of the three HR outcomes, satisfaction was strongly associated with OE. The analysis proved that the proposed model is an acceptable fit. Practical implications: Implementing HR-related TQM strategies will likely impact OE since it elicits positive HR outcomes such as commitment, reduced turnover intention and satisfaction. Recognizing human resources as a unique strategic asset will help HR managers devise adequate resourcing, development and retention strategies instrumental in executing TQM. Originality/value: The present micro study is unique in scrutinizing the influence of soft TQM-HR practices on organizational effectiveness by analysing the mediating effects of commitment, reduced turnover intention and satisfaction in Indian large-scale manufacturing organizations. The study is unique since no literature deciphers the linkages between HR strategies and organizational effectiveness in the Indian manufacturing sector. 2023, Emerald Publishing Limited. -
Impact of dynamic pricing and driver behavior on service quality in ride-hailing operations: a study of Bangalores urban dynamics
Purpose The study evaluates the influence of the dynamic pricing factors, price transparency, seasonality and driver behavior on the ride-hailing services perceived quality. While many technological changes are detected in the service, dissatisfaction continues to persist between customers about prices surging higher and dangerous practices of driving in the service. Design/methodology/approach In the context of an urban area such as Bangalore, service quality and customer satisfaction are mostly a result of dynamic pricing and driver behavior. In order to better understand the associations in these relations, the study utilizes PLS-SEM in quantitative. Findings The study identifies the user-ride-hailing survey key service quality drivers reliability, comfort, responsiveness and safety. Although the results indicate that dynamic pricing can successfully manage demand, this is contingent on whether it is implemented in a transparent manner and with a sense of equity perceived by customers. Driver professionalism is the important variable that strengthens or weakens the effect of pricing policies on customer satisfaction. Research limitations/implications This study contributes to the expanding body of knowledge on urban mobility and provides actionable insights for improving ride-hailing operations in developing economies. Practical implications Implications to industrial stakeholders entail reorienting in driver training and refining algorithms and strategies about dynamic pricing that boost customer trust and loyalty. Originality/value This is one of the few studies that explore the dynamics of urban mobility from developing countries perspective like India. 2025 Emerald Publishing Limited -
The linkage of sustainable development and spirituality at workspace from the perspectives of university teachers
Purpose Sustainability and spirituality are interrelated concepts that hold immense importance in todays world. The purpose of this study is to explore the influence of spirituality (and its dimensions) on sustainability in the educational sector, in addition to examining the role of socio-demographic factors. Design/methodology/approach A quantitative research design was employed using a structured questionnaire. The data were analysed through independent t-tests, analysis of variance, correlation analysis and structural equation modelling (SEM) to assess relationships between socio-demographic factors, workspace spirituality and sustainability. Findings The study found no significant differences in sustainability levels across gender, age or years of work experience. However, significant differences in workspace spirituality were observed between males and females, and across different age groups and experience levels. Positive correlations were found between workspace spirituality and dimensions such as compassion, transcendence and meaningful work, while mindfulness showed a negative correlation. SEM results further indicated that compassion and meaningful work positively influence sustainability, while mindfulness negatively affects it. Transcendence, however, showed no significant impact. Research limitations/implications The study highlights the deep interconnection between spirituality and sustainability and how socio-demographic factors shape this relationship. It provides insights for educational institutions to foster spiritually enriching environments that not only enhance academic outcomes but also promote ethical awareness, personal growth and environmental responsibility. Originality/value This research uniquely bridges gaps between spirituality, sustainability and employee demographics, offering practical implications for creating spiritually fulfilling and sustainable workspaces in the educational sector. 2026 Emerald Publishing Limited -
Diet Coke faces negative publicity
Research methodology A secondary research method was used to collect data for this case. The authors have made use of newspaper articles and published articles written by journalists and experts, which are available in the public domain. The protagonists name has been masked. Case overview/synopsis This case study examine the controversy surrounding Diet Coke and the dilemma faced by the Coca-Cola vice president of marketing, Henry Kingston, over its product labeling. While Diet Coke has long been favored by health-conscious consumers seeking a low-calorie alternative, concerns over its use of aspartame, an artificial sweetener linked to potential health risks, had sparked consumer backlash, regulatory scrutiny and accusations that the company was misleading consumers with its labeling. The issue gained momentum when former US President Donald Trump publicly switched to regular Coke, citing health concerns over aspartame, further fueling media debates on artificial sweeteners. With increasing pressure from social media, consumer advocacy groups and regulatory bodies questioning whether the term diet misleads consumers into assuming the product is inherently healthier, Coca-Colas senior management team led by its CEO faces a critical dilemma whether to retain the strong brand recognition of Diet Coke or reposition the product with greater transparency. The case highlights the challenges of ethical marketing, corporate responsibility and consumer health awareness in the food and beverage industry, raising crucial questions about balancing brand loyalty with regulatory compliance and evolving consumer expectations. Complexity academic level This case study is suitable for under-graduate and post graduate students studying marketing strategy and brand management courses in business management and commerce streams can use this case. This case can also be used for marketing specialization courses at the undergraduate and postgraduate levels. 2025 Emerald Publishing Limited -
Beyond AR and VR: immersive techniques for effective case teaching
Purpose This study aims to investigate the integration of immersive techniques into case teaching to address the limitations of traditional static methods in management education. It explores how these techniques enhance student engagement, critical thinking and the application of theoretical concepts to real-world scenarios. Design/methodology/approach Adopting a phenomenological and self-reflective methodology, this exploratory study draws insights from the lived experiences of educators and students by using non-technological immersive methods such as roleplay, interviews, industry visits and product exhibitions. Findings The findings reveal that immersive techniques foster deeper cognitive, emotional and behavioral engagement among students, providing a richer understanding of complex business dynamics. However, implementation challenges such as resource constraints and the reliance on external stakeholders are noted. Practical recommendations are provided to overcome these barriers. Practical implications The study highlights scalable and cost-effective immersive methods, making them accessible for institutions with limited technological resources. By bridging the gap between theory and practice, these techniques equip students with the critical skills and competencies required for todays workforce. Originality/value This research contributes to the existing body of literature by focusing on non-technological immersive methods, an area often overshadowed by studies on advanced technologies like virtual reality. It provides a framework for educators to innovate case teaching practices, enhancing the relevance and impact of management education. 2025 Emerald Publishing Limited -
Marketing odyssey for a digitally native brand: a case study of Sunbird Straws
Research methodology: The case study incorporated a combination of primary and secondary data collection approach. The authors interviewed Dr Varghese, the co-founder of Sunbird Straws and the protagonist in this case study. In addition, secondary data was obtained from various sources such as newspaper articles, journal publications and company reports. Case overview/synopsis: On a rosy and vibrant morning in 2017, Dr Saji Varghese, a professor at Christ University in Bangalore, stumbled upon a curved coconut leaf on the campus resembling a straw. This sparked his motivation to transform coconut leaves into a natural straw, prompting him to initiate experiments with coconut leaves in his kitchen. The process of boiling and straining leaves became his method for crafting an eco-friendly straw. After numerous attempts, he successfully produced straws from coconut leaves, introducing a distinctive and creative concept incubated at IIM Bangalore. These unique straws, crafted by Varghese, prioritised environmental friendliness and were also crafted entirely from biodegradable materials, free from harmful chemicals. These straws demonstrated durability in hot and cold beverages for up to 3 h, maintaining their integrity without becoming soggy or leaking. As the business flourished, it reached a critical juncture. The primary challenge centred around product marketing, mainly due to consumer unfamiliarity with such sustainable straws. This was a product that also fell under the category of low involvement for consumers. Raising awareness about the product and persuading consumers to purchase presented a significant hurdle. In response, Varghese assigned his team to develop cost-effective marketing strategies. Given the start-up nature of the business, advertising budgets were constrained, and the objective was to achieve a positive return on advertising spend for every investment in advertising the product. In addition, the focus was on increasing the likelihood of selling the straws on both business-to-business and business-to-consumer levels. In this case study, Vargheses role and predicament exemplify the delicate equilibrium that entrepreneurs frequently grapple with, striking a balance between marketing strategy and return on ad spent to steer the trajectory of their businesses. It offered a valuable examination of the nuanced decisions marketers encounter as they strive for both profitability and customer-centric products. Complexity academic level: The case study is relevant to the marketing discipline. All undergraduate and postgraduate-level marketing courses in higher education institutions can use this case study. It can also be used in integrated marketing communication or digital marketing classes. It can be used further in the hospitality and management fields. Also, online courses in marketing can include this case study. 2024, Emerald Publishing Limited. -
Impact of moral and exchange capital on media favourability of financial companies in India
Purpose The purpose of this study is to illuminate the influence of institutional and transactional corporate social responsibility (CSR) on media sentiments in financial companies in India. This study is conducted to understand how different CSR strategies impact media perceptions, influencing the reputation and public image of financial companies in India. Design/methodology/approach This study examines the data of 56 National Stock Exchange-listed financial companies for eight years of data from 20142015 to 20212022. Panel data regression were used to analyse the data; fixed and random effect models were chosen based on the Hausman test results. Findings Financial companies moral and exchange capital negatively impact the medias favourability of financial companies in India. Diagnostic tests like autocorrelation and heteroscedasticity are also conducted to check the effectiveness of research models. Originality/value Although prior research has examined the effect of CSR on media sentiments, little is known about the impact of moral capital and exchange capital on media favourability of financial companies in India. 2025 Emerald Publishing Limited -
Does salesperson-brand personality congruence impact perceived service quality of the salesperson? A study of small retailers in emerging markets
Purpose: Based on the theoretical lenses of social identity theory (SIT), this research study analyses the dyadic relationship of congruence between salesperson and brand personality. By exploring the salesperson-brand personality congruence, this study proposes to measure the impact of this congruence on the retailers perception of salespersons perceived service quality performance (SalesPerf). Design/methodology/approach: The study is structured around collecting data from small retailers through an offline survey. In this study, linear associations between the various elements of the theoretical model are determined using covariance-based Structural Equation Modeling (CB-SEM). Findings: The analysis of results suggest that a retailer's perception of the salesperson's brand personality congruence positively influences the salesperson's perceived service quality. However, the retailer's satisfaction with the brand does not moderate the relationship between the retailer's perception of the salesperson's brand personality congruence and the salesperson's perceived service quality. Originality/value: This research fills the void in contemporary research by adopting a novel strategy to examine the perception of retailers toward the dyadic relationship between salesperson-brand congruence (SBPC) and salesperson's perceived service quality (PSQ). The study further enriches the existing literature by measuring the moderating role of retailer's satisfaction with the brand (SAT) on the retailer's perception of the salesperson's brand congruence (SBPC) and salesperson's perceived service quality (PSQ). 2025, Emerald Publishing Limited. -
Green apparel and Generation Zs purchase intention: the moderating role of eWOM
Purpose This paper aims to examine the relationships among attitude, subjective norm (SN), perceived behavioral control (PBC), perceived novelty (PN), consumer confidence (CC) and Generation Zs (Gen Zs) green apparel purchase intention (PI), and also test the moderating role of electronic word-of-mouth (eWOM). Methodology The quantitative study used structural equation modeling and Hayes PROCESS macro to analyze a survey sample of 512 Gen Z consumers. Findings The key findings indicate that attitude, SN, PBC, PN and CC significantly influence Gen Z consumers green apparel PI. Furthermore, eWOM moderated the relationship between CC and Gen Z consumers green apparel PI. Originality Although previous studies have examined the influence of attitude, SN and PBC on green product PI, the expanded framework with the proposed possible relationships is novel. This research sheds light on the effect of PN and CC on Gen Z consumers green apparel purchases. Furthermore, this study extends the green apparel literature by investigating the moderating impact of eWOM. 2026 Smriti Mathur, Alok Tewari, Avinash K. Shrivastava and Preeti Sharma.