International Journal of Innovation Studies
The International Journal of Innovation Studies (IJIS) is a peer-reviewed academic journal that focuses on enhancing the comprehension and application of innovation across multiple fields and disciplines. It provides a forum for researchers, scholars, practitioners, and policymakers to discuss groundbreaking research, theories, methodologies, and practical insights related to innovation. In addition to publishing high-quality research articles, IJIS also seeks to foster interdisciplinary collaboration and dialogue. By bringing together diverse perspectives and expertise, the journal aims to drive forward the frontiers of innovation studies, offering valuable contributions to both theoretical and practical advancements in the field.
EMERGING ROLE OF NEW MEDIA TECHNOLOGY IN TEACHING AND LEARNING: A LITERATURE REVIEW
New media technologies (NMTs) have profoundly impacted higher education, and have changed teaching and learning methodologies. The advantages and difficulties of NMTs in the context of education are examined in this article. The article looks at the benefits of NMTs, such as better communication, more interactivity, and easier access to information. It also covers the difficulties instructors and students have in making effective use of this technology. These difficulties include technological constraints, differences in individual learning preferences, cultural variables, and course design issues. Higher education is fast changing as a result of new media, which is becoming more and more important in how teachers and students connect and engage with the curriculum. This study examines how instructors are currently using new media, taking into account topic matter, demography, and prior teaching experience. The article highlights the complex relationship between social media and higher education. While it offers significant opportunities for enhancing teaching and learning, it also presents challenges that require careful consideration and strategic planning. By understanding the implications, higher education institutions can effectively harness the potential of social media while mitigating its risks.
New Media Technologies, Higher Education, E-Learning, Learning Styles, Educational Technology, communication, interactivity, anytime-anywhere learning, developing countries, Mass Communication
Social justice in Australia and Oceania have evolved through complex historical processes. It is shaped by Indigenous governance practices, European colonisation and struggles for equality, recognition and self-determination, the latter continue to contribute to today's disputes of Indigenous rights, welfare policy, environmental justice and regional development. Australia’s and Oceania’s Indigenous societies were diverse and maintained a range of systems of governance, law and social organisation prior to European colonisation in Australia.
CRYPTOCURRENCY INTEGRATION IN CORPORATE TREASURY ANAGEMENT: OPPORTUNITIES AND RISKS
This research paper examines the integration of cryptocurrency assets into corporate treasury management practices, analyzing both the strategic opportunities and inherent risks. As digital assets mature and gain institutional acceptance, an increasing number of corporations are considering or implementing cryptocurrency allocation strategies. This paper provides a comprehensive analysis of the current landscape, regulatory environment, operational frameworks, and risk management strategies necessary for successful cryptocurrency integration. Through case study analysis and empirical data, we demonstrate that while cryptocurrency integration presents significant opportunities for portfolio diversification and potential returns, it requires sophisticated risk management frameworks, robust governance structures, and careful consideration of regulatory compliance.
Cryptocurrency integration, Corporate treasury management, Digital assets, Risk management, Regulatory compliance
Dr.S.Dhanalakshmi, K. Anitha , Sudheer Aloori, Dr. Diganta Kumar Das, Mrs.Amesha A.R.S, Dr. D. Paul Dhinakaran
CUSTOMER PERCEPTION TOWARDS MOBILE WALLET SERVICES IN KARUR DISTRICT
The rapid proliferation of smartphones and digital payment infrastructure in India has transformed the financial transaction landscape. Mobile wallet services such as Google Pay, PhonePe, Paytm, and Amazon Pay have emerged as dominant cashless payment instruments, particularly in semi-urban and rural markets. This study investigates the perception of customers in Karur District, Tamil Nadu, towards mobile wallet services with respect to convenience, security, trust, and overall satisfaction. A structured questionnaire was administered to a sample of 384 respondents selected through stratified random sampling. Data were analysed using percentage analysis, weighted average scoring, chi-square tests, and Likert-scale analysis. The findings reveal that ease of use, cashback incentives, and speed of transactions are the primary drivers of adoption, while poor internet connectivity, transaction failures, and security concerns remain key barriers. The study offers valuable insights for service providers, policymakers, and fintech stakeholders aiming to improve mobile wallet adoption in semi-urban India.
Mobile Wallet, Digital Payment, Customer Perception, Karur District, Fintech, Cashless Economy, TAM
EFFECT OF PROJECT PLANNING ON PROJECT PERFORMANCE: A CASE OF COOKSTOVE PROJECT IN RULINDO DISTRICT, RWANDA
The general objective of this research is to find out the effect of project planning on the performance of the Cookstove Project in Rulindo District. For this study, the researcher employed both descriptive and correlational research designs. Descriptive survey research was utilized to gather information on various issues, while the correlational research design focused on exploring the relationships between the variables under study. The researcher relied on document analysis, questionnaires, and interviews in collecting data. Descriptive and inferential statistics were used to analyze data. The findings show an R value of 0.823, indicating a strong positive correlation between predictors (Monitoring and evaluation planning, resource planning, risk planning, and financial planning) and project performance in the Cookstove Project in Rulindo District. The R² value of 0.677 means that approximately 67.7% of the variance in project performance can be explained by financial planning, resource planning, risk planning, and monitoring and evaluation planning. The unstandardized coefficient for financial planning is 0.246, indicating that a one-unit increase in financial planning results in a 0.246-unit increase in project performance (β = 0.246, t = 2.558, p = 0.012). The unstandardized coefficient for resource planning is 0.248, indicating that a one-unit increase in resource planning leads to a 0.248-unit increase in project performance (β = 0.248, t = 2.982, p = 0.003). The unstandardized coefficient for risk planning is 0.151, revealing that a one-unit increase in risk planning results in a 0.151-unit increase in project performance (β = 0.151, t = 2.172, p = 0.032). Lastly, the unstandardized coefficient for M&E planning is 0.264, indicating that a one-unit increase in M&E planning correlates with a 0.264-unit increase in project performance (β = 0.264, t = 4.467, p = 0.000). The study recommended that project managers, coordinators, and field staff prioritize effective financial, resource, risk, and monitoring planning to ensure the successful implementation of the cookstove project in Rulindo District.
Project Planning, Resource Planning, Risk Planning, Financial Planning, Monitoring and Evaluation Planning, Performance of the Cookstove Project
Dushimimana Marcel, Dushimimana Jean de Dieu
BEYOND STRUCTURE: MIRROR IMAGE THEORY AS METAPHOR FOR HEALING IN AMY TAN’S THE BONESETTER’S DAUGHTER
Through the lens of mirror image theory, this article reads Amy Tan’s The Bonesetter’s Daughter (2001) to consider how reflection is conceived as a metaphor for healing in intergenerational trauma and diasporic identity. Tan employs mirror figuratively, not just as a structural device, but as transfigurative tool for the narrative building, character and symbolic development. In examining the divided text, concurrent but independent mother-daughter narratives, and repeated motifs of bones, ghosts and translation within it, this essay argues that healing is realized through the term mirror recognition—the imaginative awareness of an ancestral trauma which crosses cultural and generational barriers. Through such a perspective, Tan’s novel demonstrates that the process of reflection helps to bring together past and present, East and West, so that cultural unity comes into being.
Amy Tan; Mirror Image Theory; Mother–Daughter Relationship; Chinese American Literature; Cultural Reflection
AI-POWERED RECRUITMENT: BALANCING EFFICIENCY WITH BIAS PREVENTION
Artificial Intelligence has rapidly transformed recruitment practices, promising unprecedented efficiency in candidate sourcing, screening, and selection. However, the deployment of AI systems in hiring has raised critical concerns about algorithmic bias, fairness, and the potential perpetuation of historical discrimination. This research examines the current state of AI-powered recruitment, analyzing both its efficiency gains and bias risks through empirical data, case studies, and comparative analysis. The findings reveal that while AI can significantly reduce time-to-hire and improve candidate quality when properly implemented, organizations must adopt rigorous bias detection and mitigation strategies to ensure equitable hiring outcomes. This paper provides evidence-based recommendations for HR professionals seeking to leverage AI's benefits while maintaining ethical recruitment standards.
Artificial Intelligence; Recruitment; Algorithmic bias; HR technology; Talent acquisition; Machine learning; Hiring automation; Diversity and inclusion; Predictive analytics; Ethical AI
Dr.B.Bhavya, Priyadharshini . P, Aluri Persis Rebeccah, Dr Linda Mary Simon , Ms.Jijitha.B , Dr. D. Paul Dhinakaran
GENDER REPRESENTATION IN CAR ADVERTISING: IMPLICATIONS FOR WOMEN’S EMPOWERMENT AND CONSUMER BEHAVIOR
Gender representation in advertising shapes societal norms, consumer perceptions, and purchasing behavior. This study examines gender portrayal in car advertising with emphasis on the underrepresentation of women and its implications for empowerment and consumer decision-making. Positioned within the discourse on social transformation, sustainability, and inclusive development, the research highlights that advertising narratives can either reinforce traditional stereotypes or promote progressive gender roles. The study adopts a quantitative approach using data collected from consumers through a structured questionnaire. A sample of respondents was analyzed with descriptive and inferential statistical tools. Techniques including percentage analysis, chi-square tests, and regression analysis were employed to examine the relationship between gender portrayal in automobile advertisements and consumer attitudes and purchasing intentions. The analysis explored how representation patterns influence brand perception, emotional connection, and trust among male and female consumers. Findings reveal that car advertisements remain predominantly male-centric, with women often portrayed in passive or secondary roles. This imbalance significantly affects brand perception, trust, and purchase intention, particularly among women consumers who feel underrepresented and disconnected from advertising messages. The results demonstrate that inclusive and balanced portrayals generate positive consumer responses and strengthen brand credibility. The study emphasizes the importance of equitable gender representation as part of responsible and sustainable marketing. Promoting empowering depictions of women in advertising can enhance visibility, participation, and consumer engagement while contributing to social change. The research offers empirical insights supporting gender-sensitive communication strategies and demonstrates their value in creating ethical, socially responsible, and future-oriented marketing practices aligned with global goals.
Gender Representation, Car Advertising, Women’s Empowerment, Consumer Behavior, Statistical Analysis
"INDIGENOUS WOMEN IN THE CHITTAGONG HILL TRACTS: A STUDY ON GENDER-BASED VIOLENCE"
The Chittagong Hill Tracts (CHT) of Bangladesh occupies a geopolitically significant position due to its borders with India and Myanmar, its natural resources, and its complex historical and political contexts. For decades, Indigenous Peoples of the CHT have struggled for self-determination, land rights, and survival, but successive state policies—marked by militarisation, Bengali settler transmigration, and systemic discrimination—have produced widespread violence, displacement, and marginalization. The 1997 CHT Peace Accord formally ended over two decades of armed conflict, yet key provisions, including demilitarisation, land dispute resolution, and rehabilitation of displaced peoples, remain largely unimplemented. Women and girls, excluded from peace negotiations, continue to face gendered impacts of conflict, including sexual violence, abduction, and impunity for perpetrators. The failure of the state to address communal violence and ensure justice has eroded trust in formal legal systems. As a result, many Indigenous communities, despite support from NGOs, continue to rely on traditional justice mechanisms, which are perceived as more accessible and culturally familiar, though increasingly contested by Indigenous women’s rights activists.Drawing on primary data collected through field observations, structured surveys of 100 respondents, three focus group discussions, and in-depth interviews with ten experts, alongside secondary sources, the research highlights both the persistence of impunity in formal legal systems and the contested reliance on traditional justice mechanisms. Findings reveal the resilience of indigenous women and communities, while underscoring the urgent need for state accountability, implementation of peace accord provisions, and gender-sensitive policies. The study contributes to broader debates on indigenous rights, peacebuilding, and gender justice.
Gender based Violence (GVB), Traditional justice, Indigenous women, gender justice
COMPETENCY MAPPING: CONNECTING ORGANIZATIONAL OBJECTIVES WITH EMPLOYEE DEVELOPMENT AND STRATEGY DRIVEN HR FUNCTIONS – A CASE STUDY IN DFPCL.
In today’s arising innovative business world, companies are increasingly focusing on human resource for organization’s development with respect of using Competency mapping so that they can compete in rapidly changing environment. Competency mapping and assessment has not only gained paramount importance in organization but also helps an individual to give the perceptivity of competency skills like attributes, workspace skills, applied and core knowledge skills that will help the individual to retain any job. It’s vital to keep the competency up-to-date, as this study gives the insight of enforcing latest tools and methodologies of competency mapping in an organizations. Every person has unique talents, which may contain both strong and weak points, competence mapping will enable them to enhance their skills that they might not be aware of where they need to make improvements. It’s a cross functional integration that helps an individual to perform the job efficiently and effectively. In the current scenario HR people struggle with unlimited difficulties in finding a skilled person which can match the work demands of the organization. HR seeks to continuously analyze the competencies that different people will need in order to do the tasks that have been given to them effectively and to offer chances for these employees to enhance these competences in order to position them for future jobs within the organization. As a result, here an effort has been made to examine how a person and an organization are connected by competency mapping. The concept of “competency” originated in the 1970s when David McClelland introduced it as an alternative to traditional intelligence testing, arguing that competency is a better predictor of job performance. His ideas laid the foundation for competency mapping, where skills, behaviors, and attributes necessary for success in specific roles are identified. Over time, competency mapping has evolved into a strategic tool for managing talent. It is now used to align employee abilities with organizational goals, encompassing recruitment, performance management, and career development. As competency mapping evolved, it became closely tied to training and development. Initially, training was a reactive process to fill skill gaps. Today, it is a proactive, ongoing initiative aimed at enhancing the specific competencies identified through mapping. Training programs are now customized to address both technical and behavioral competencies, ensuring employees are not only able to perform their current roles effectively but also prepared for future challenges. This study aims to conduct a comprehensive analysis of competency mapping and training & development practices at a Petrochemicals Corporation Limited. It will explore the significance of competency mapping, evaluate the existing framework for identifying essential competencies, and analyze how these results are integrated into HR processes such as recruitment and performance management. Additionally, the study will assess the effectiveness of training and development practices in addressing competency gaps and identify best practices and areas for improvement. Ultimately, the research seeks to provide valuable insights that enhance employee performance and satisfaction while supporting the organizational goals. The study provides valuable insights for HR professionals and organizational leaders, offering practical suggestions to improve competency mapping practices.
Dr. Aditi Banerjee, Dr. Sapna Suri, Dr. Sanjay Kumar Taurani, Dr. J. Varaprasad Reddy
PUBLIC SECTOR GOVERNANCE AND SERVICE DELIVERY EFFICIENCY: A STUDY OF ADMINISTRATIVE REFORMS IN DEVELOPING NATIONS
Governance in the public sector is important in determining the performance of service delivery in the developing countries. This is irrespective of the fact that there is little empirical data on whether governance gains are being converted to efficiency gains that can be measured despite the massive administrative reforms introduced within the last twenty years. This paper will analyses how the quality of governance influences the efficiency of the service delivery in 52 developing nations between 2000 and 2023. The study uses panel fixed-effects and system GMM estimators to deal with endogeneity and country-specific heterogeneity using the governance indicators provided by the World Bank and the service outcome data provided by the United Nations. The higher the quality of governance, the more efficient delivery is. Control of corruption and regulatory quality have the most positive impacts in terms of governance dimensions. More so, the governance- efficiency relationship is mediated by administrative reform projects in part, especially in developing economies with middle incomes. The results have an implication in the literature as they represent current cross-country panel evidence of the governance service delivery nexus. The policy implications are strengthening the institution and enforcing anti-corruption and implementing sustained reforms to enhance the performance of the public sector in developing countries.
Public Sector Governance; Administrative Reforms; Efficiency of Service Delivery; Developing Nations; Panel Data Analysis; Institutional Quality; Public Administration.
POSTHUMAN EXISTENCE IN ARTIFICIAL WORLDS: SPACE, TECHNOLOGY, AND IDENTITY IN PASSENGERS
The spacecraft Avalon in Passengers (2016) is examined in this paper as a technologically mediated setting that creates posthuman subjectivity by fusing corporate infrastructures, automated systems, and artificial intelligence with human life. Based on N. Katherine Hayles' posthumanist theory, the study contends that rather than autonomous individual action, the movie depicts human identity as being formed through informational processes, technological mediation, and distributed cognition. Through algorithmic governance, automated service networks, and hibernation technologies, the Avalon functions as an enclosed artificial environment where human bodies are converted into data-regulated entities, obfuscating the distinction between humans and machines.The study illustrates how subjectivity arises within a system of technical regulation that reconfigures embodiment and agency by examining the ship's architecture, service infrastructures, corporate control over time, biological processes, and social interaction. Stratified forms of posthuman existence are created by automated surroundings and hierarchical spatial architecture, where corporate control and computational authority influence identity. Thus, the Avalon is shown in the movie as a posthuman lifeworld where survival, embodiment, and consciousness are all created by technology.In the final stages, Passengers shows how closed technical systems alter human experience by substituting digitally distributed forms of agency for liberal humanism ideas of autonomy. By highlighting the moral and political ramifications of technologically controlled living in late capitalism space imaginaries, the research presents the movie as a critical investigation of posthuman existence in artificial worlds.
Hibernation technologies, subjectivity, posthuman and spatial architecture.
Dr. K.R.. Shiva Shankaran, Dr. Praveen Kumar and Dr.Shalini Infanta
GENDERED VULNERABILITY TO DEPRESSION AMONG WOMEN LIVING WITH DIABETES IN INDIA: A BIO-PSYCHO-SOCIAL REVIEW
Diabetes mellitus is a big public health problem in India, and it is becoming more and more linked to serious mental health problems, especially depression. Women with diabetes are more likely than men to be depressed. This is because of biological, psychological, and social factors that are shaped by female experiences and structural inequalities. Using a bio-psycho-social approach, this review looks at how women with diabetes in India are more or less likely to become depressed based on their gender. The study is based on an analysis of 25 peer-reviewed research papers from reputable scientific databases published between 2020 and 2025. The results show that biological factors like changes in hormones, the severity of the disease, and complications linked to diabetes make people more likely to become depressed. Poor mental health outcomes are also caused by psychological factors such as stress, emotional burden, and low self-efficacy linked to diabetes. Social factors, especially gender roles, caregiving duties, limited freedom, and limited access to health care, make women much more vulnerable. Depression also makes it harder to control blood sugar levels and makes it less likely that people will follow their treatment plans. The review shows that there are important gaps in combining mental health services with diabetes care, and it stresses the need for bio-psychosocial treatments that take gender into account. To help depressed women with diabetes, we need healthcare methods that are all-encompassing and take into account both medical and socio-cultural factors.
Diabetes, Depression, Women, Gender, Bio-psycho-social, Mental health, India
Dr. Chitra N, Dr.S.Sasikala Alias Annamalai
ATMOSPHERES OF ANXIETY: AFFECTIVE ECOLOGIES IN THE OVERSTORY
This paper focuses on Richard Powers' The Overstory to investigate the emotive aspects of climate fiction. Drawing on affect theory, namely the writings of Sara Ahmed, Timothy Morton, and Brian Massumi, the study investigate how the novel creates a sense of communal ecological consciousness through wonder, grief, anxiety, and connectivity. Powers frames environmental catastrophe as an emotive event that circulates among human and nonhuman bodies, rather than merely presenting climate change as a scientific or political crisis. The study explores the ways in which arboreal metaphors, polyphonic structure, and narrative style contribute to an embodied feeling of environmental precarity. The paper makes the case that The Overstory uses affect to subvert anthropocentric perception and promote ecological relationality through qualitative textual analysis based on affect theory and ecocriticism. The story reorients readers' emotional ties and broadens their empathy beyond humans by emphasizing trees as communicative and agentic beings. In the end, this study shows that climate fiction functions as affective education as well as speculative narrative, transforming readers' perceptions of the planetary problem and fostering fresh approaches to ecological awareness.
Anthropocene; Ecological Consciousness; Affect Theory; Climate Fiction; Ecocriticism
MEMES AS MICRO-NARRATIVES: CODE-SWITCHING, EMOTIONAL RESONANCE, AND THE DEFAMILIARIZATION OF REALITY
Memes are the best way to talk to each other in the digital age. They are short stories that use a few words and pictures to explain complex social and cultural ideas. Memes are often seen as funny, but they are actually short stories that look into identity, behaviour, and how people express their feelings in online social settings. This paper examines memes as culturally nuanced communicative phenomena through the theoretical lenses of Mikhail Bakhtin, Roland Barthes, Jean Baudrillard, Russian Formalist concepts of defamiliarization, and posthuman theory. The research asserts that memes operate through precise code-switching, behavioural amplification, and emotionally impactful narratives, facilitating a transition from singular organic realities to complex interpretive coexistence. Memes alter perceptions of social issues and transform contemporary storytelling by rendering mundane events peculiar.
Memes, micro-narratives, code switching, defamiliarization, digital culture, and posthuman communication
ARTIFICIAL INTELLIGENCE DRIVEN CUSTOMER ENGAGEMENT IN ONLINE RETAIL
The integration of artificial intelligence (AI) into e-commerce has profoundly transformed consumer engagement methods; nonetheless, its total impact on the customer experience remains complex and multifaceted. This study employs a quantitative research methodology to examine the fundamental factors that affect customer perceptions of AI-driven engagement and its effect on satisfaction. A structured online survey was administered to a cohort of 300 seasoned internet users. Exploratory Factor Analysis (EFA) of 25 Likert-scale statements identified a robust four-factor structure: Perceived Value & Personalization (PVP), Privacy & Transparency Apprehension (PTA), Relational Decoupling (RD), and Service Efficiency & Reliability (SER), collectively accounting for 58.4% of the total variance. A multivariate regression analysis indicated that all four variables were significant predictors of overall customer satisfaction (R² = .506, p < .001). Specifically, PVP (β = .398) and SER (β = .311) had positive influences, but PTA (β = -.242) and RD (β = -.187) shown large negative effects. Additionally, a mediation analysis indicated that Relational Decoupling partially mediates the adverse relationship between privacy concerns and satisfaction (indirect effect: 0.10, 95% CI [0.05, 0.16]). The findings suggest that although AI's functional benefits are strong motivators for happiness, ethical and relational issues significantly diminish their impact. This research provides a validated paradigm for online retail, emphasizing that an effective AI approach must achieve a balance of technological efficiency, clear data regulations, and human-centered design to foster trust and enduring loyalty.
Artificial Intelligence, Customer Engagement, Online Retail, Personalization, Privacy Concerns, Mediation Analysis, Customer Satisfaction, Factor Analysis.
IMPACT OF MINDFULNESS-BASED STRESS REDUCTION (MBSR) THERAPY INTERVENTION ON RAJAS, TAMAS AND PSYCHOLOGICAL WELL-BEING AMONG UNIVERSITY TEACHERS: ROLE OF STRESS COPING AND WORK ENGAGEMENT
University teachers frequently experience occupational stress due to workload, role conflict, publication demands, student management, and administrative responsibilities. Prolonged stress adversely affects psychological well-being and may increase Rajasic (restlessness, achievement pressure) and Tamasic (inertia, withdrawal) tendencies as explained in Triguna theory. The present study assessed the effectiveness of Mindfulness-Based Stress Reduction (MBSR) as a therapy intervention in enhancing psychological well-being among university teachers by reducing Rajas and Tamas and improving adaptive coping and work engagement. A quasi-experimental pre-test post-test control group design was employed. A total sample of 100 university teachers from Bihar state universities was selected through purposive sampling and divided into experimental group (n=50) and control group (n=50). MBSR intervention was conducted for 8 weeks. Tools used were Vedic Personality Inventory (Wolf, 1998), Brief COPE (Carver, 1997), Utrecht Work Engagement Scale (Schaufeli & Bakker, 2004), and Ryff’s Psychological Well-being Scale (Ryff, 1989). Findings revealed significant improvement in psychological well-being, adaptive coping and work engagement and a significant reduction in Rajas and Tamas in the experimental group compared to the control group. The study supports the therapeutic value of mindfulness intervention for teacher well-being promotion.
Mindfulness therapy, Triguna (Rajas-Tamas), Psychological well-being
A CRITICAL ANALYSIS OF THE DISTRICT LEGAL SERVICES AUTHORITY IN GOALPARA'S (DLSA) COMPOSITION, IMPLEMENTATION, PROCEDURES AND EFFICACY UNDER THE LEGAL SERVICES AUTHORITY ACT, 1987
The present study deals with the composition of District Legal Services Authorities, the eligibility criteria, the services provided by the District Legal Services Authorities, Legal Aid Counsels at Goalpara District, Assam Para Legal volunteers, Legal Aid clinics, introduction of new scheme of legal Aid Defense Counsel system, structure of District Legal Services Authorities, its staffs, panel lawyers, Legal aid clinics, legal literacy clubs, para legal volunteers etc. within Goalpara District of Assam.
District, Legal, Services, Authorities, lawyers.
ANALYSIS OF AI APPLICATIONS IN ENHANCING CUSTOMER EXPERIENCE IN MARKETING
The advent of reality is a new innovation force in the marketing sector that aims to change the customer experience, levels of satisfaction, and customer loyalty ecosystem. This paper discusses the way in which AIs can be leveraged to help increase customer satisfaction with a special emphasis on such tools as conversational agents, predictive analytics, and personalised recommendations. A sample size of 200 targeted participants was used to conduct the sampling in which the organised questionnaires were employed and a 5-point Likert scale. ANOVA, chi-square tests, and correlation tests found out the necessary hypotheses. The research has revealed that the satisfaction of customers is greatly enhanced when driven by artificial intelligence as evident in the ORF of the increasing levels of customer satisfaction that ranged between 3.0 to 4.7 respectively at varying degrees of personalisation. The impact of chatbots on customer loyalty has been so astounding since customer loyalty ratings had increased to 4.5 following the frequency of using it as opposed to 2.5. Predictive analytics presented a significant positive relation (r = 0.76, p < 0.001) with customer retention, and it is the sign that the model can be applied in the marketing strategy based on looking in the future. The robotics that have been artificially enhanced have been seen to have a steady customer satisfaction among various demographics, although the younger participants showed slightly better accumulation of benefits. It pays attention to the importance of the artificial intelligence that may be utilized to enhance marketing strategies, establish a stronger relationship with clients, and remain market leaders. However, it emphasizes the necessity to focus more on data strategies and openness to build trust and facilitate the role of AI in marketing.
Artificial intelligence, marketing, customer experience, customer satisfaction, predictive analytics, personalization, loyalty.
Dr Alyas Ahmed, Dr Rohit Bhagat, Dr. Pallavi Bhagat
NEUROARCHITECTURE-BASED ASSESSMENT OF COGNITIVE AND EMOTIONAL RESPONSES TO BIOPHILIC INTERIOR ENVIRONMENTS USING EEG-INFORMED SPATIAL MODELING
This study quantitatively investigates the influence of biophilic interior environments on human cognitive and emotional responses by integrating neuroarchitecture principles, EEG-based neural analytics, and data-driven spatial modeling. A total of 60 participants (30 females, 30 males; mean age = 27.4 years) were exposed to three controlled interior settings: high-biophilic (Level-3), moderate-biophilic (Level-2), and non-biophilic control. Brain activity was recorded using a 32-channel EEG system with a 500 Hz sampling rate across all sessions. A spectral analysis indicated that, in the Level-3 biophilic condition, alpha-band power (8-12 Hz) increased by 34-41% at electrode sites O1/O2, indicating deeper states of relaxation and greater attentional stability. On the other hand, beta-band activity, reflecting cognitive workload (13-30 Hz), was reduced by 18% relative to the control environment. Emotional ratings using EEG-derived frontal asymmetry (F3/F4) showed a 27% leftward shift, reflecting more positive affective states. Performance on a reaction-time task of spatial working memory also improved by 22% in the high-biophilic setting. These results confirm that neurocognitive benefits can be induced through the use of biophilic interior design elements, while the EEG-informed spatial model developed herein lays the foundation for a predictive framework for optimizing interior environments based on real-time neural responses.
Neuroarchitecture, Biophilic Design, EEG (Electroencephalography), Cognitive Response, Emotional Response, Spatial Modeling, Alpha and Beta Brain Waves, Human–Environment Interaction, Interior Environmental Psychology, Neurocognitive Performance
Sara Zarnegarzadeshirazi, Mohammadmehdi Soroush
ANALYSIS OF PRODUCT AND PROCESS INNOVATION IN IMPROVING COMPANY PERFORMANCE (CASE STUDY ON LEATHER CRAFT INDUSTRY IN GARUT)
This research analyses how product innovation and process innovation affect the rate of performance of small and medium enterprises (SMEs) in Garut, West Java, Indonesia, leather craft industry. The study used a survey method to collect data from 62 SMEs using structured questionnaires measured on a Likert scale, and analysed using Minitab 21. According to descriptive results, the mean of process innovation (mean = 30.87) and product innovation (mean = 32.55) has a moderate level of performance. The SME performance stands at relatively low to medium (mean = 7.35). Multiregression analysis shows that product innovation (b = 0.104; p = 0.011) and process innovation (b = 0.145; p < 0.001) have both a positive and significant impact on the performance of SMEs. The model describes the performance variance of 71.94 (Adjusted R2 = 0.719). The results support the claim that enhancing innovation efforts, especially process innovation, is essential in enhancing profitability, absorption of labour, and business continuity amongst SMEs dealing with leather craft.
Innovation process, innovative product, corporate performance, Performance SME, Profitably UKM.s
“FOSTERING WORKPLACE VITALITY: EXPLORING THE UNDERLYING DRIVERS OF EMPLOYEE SUCCESS IN CONTEMPORARY ORGANISATIONS”
Motivation plays a vital role in shaping employee’s attitudes, enhancing productivity and driving organisational success. This study focuses on the influence of motivational strategies on employee job satisfaction and workplace performance among Information Technology (IT) professionals. The convenience sampling method was used for this study to collect data from 150 respondents working in the IT sector in Chennai city. A structured questionnaire with three sub sections along with the socioeconomic profile was disseminated to each respondent through google form link. The study used statistical instruments such as Simple Percentage Analysis, Descriptive Statistics, Regression, Correlation and Chi-Square to analyze the data. The results indicate that there is significant positive influence of Motivational Strategies on Job Satisfaction and Workplace Performance. The study highlights the importance for organisations to continually assess and refine their motivational approaches to sustain their employees for making the organisation reach higher profits and achieve its goal. The study also provides pathway for future research and suggestions for the management for making improvements in adopting various motivational strategies.
Motivation, Vitality, Strategies, Performance, Rewards, Success
Dr. R. Rangarajan, Dr. A.S Kalyana Kumar, Smita Singh .V
ASSESSING THE IMPACT OF EMPLOYEE SATISFACTION ON LOYALTY IN THE GARMENT SECTOR.A STUDY OF BANGALORE - BASED INDUSTRIES.
This study investigates the factors influencing employee satisfaction and its effect on loyalty within the garment industries in Bangalore. Primary data was collected using a structured questionnaire with a 5-point rating scale from employees in five key areas—Bagalur, Yelahanka, Yeswanthapura, Electronic City, and Peenya—yielding 530 responses, with 430 valid samples used for analysis. Descriptive statistics indicated moderate to high levels of satisfaction and loyalty among respondents. Correlation analysis revealed strong positive associations among employee satisfaction, organizational commitment, and retention intent, with coefficients ranging from 0.62 to 0.68. Further, regression analysis showed that employee satisfaction significantly predicts employee loyalty (B = 0.45, p < 0.001), along with organizational commitment (B = 0.35, p < 0.001) and retention intent (B = 0.30, p < 0.001), with the model explaining 62% of the variance in loyalty. A review of relevant literature on working conditions in Bangalore’s garment factories provided additional secondary insights to contextualize the findings. Overall, the results underscore the critical role of employee satisfaction in driving loyalty and highlight the potential benefits of targeted human resource interventions for enhancing organizational performance in the garment sector in Bangalore.
Employee satisfaction, garment industries, organizational commitment, loyalty.
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AI-ENHANCED VOCABULARY TOOLS AND THEIR IMPACT ON ACADEMIC WRITING DEVELOPMENT AMONG EFL COLLEGE STUDENTS
This research paper examines how AI vocabulary tools affect the academic writing skills of EFL college students. The research design combines quantitative and qualitative methods to evaluate writing assessment results, vocabulary quiz outcomes, and student feedback before and after the intervention. The intervention employs adaptive AI systems which provide immediate lexical suggestions and domain-specific customization combined with metalinguistic explanations for authentic coursework and self-directed learning activities. The research shows significant progress in three main areas, which cover both lexical variety and exact word choice, cohesive structure, and student engagement through customized tools and teamwork capabilities. Research indicates that students need AI tools together with human instructor guidance to develop critical thinking skills while avoiding excessive dependence on technology. The study examines three main obstacles to digital transformation, which consist of digital literacy deficits, unbalanced technology and digital resource availability, and ethical problems that need ongoing support and proper regulatory frameworks. The study reveals implications for curriculum development, which supports the use of AI-enhanced language learning tools throughout language skills and subject areas, while identifying research directions for studying AI tool retention, scalability, and cultural adaptability.
Artificial Intelligence (AI), AI-powered vocabulary tools, EFL academic writing, Lexical diversity, Automated writing feedback, Language learning technology
FEDERATED LSTM FRAMEWORK FOR REAL-TIME INSULIN PREDICTION USING EDGE-TO-CLOUD CGM INTEGRATION
Background: Effective diabetes management relies heavily on timely and accurate insulin prediction, particularly with the increased use of Continuous Glucose Monitoring (CGM) systems. However, conventional centralized machine learning (ML) approaches often require the transfer of sensitive health data to remote servers, raising concerns about patient privacy, high communication overhead, and limited adaptability to individual glucose patterns. Problem: Existing prediction models struggle to balance personalization, privacy, and computational efficiency. Centralized learning lacks scalability and exposes raw data, while traditional models like decision trees or statistical regressors fail to capture the temporal complexity inherent in CGM data. Methods: This study proposes a federated learning (FL) framework for real-time insulin prediction, utilizing Raspberry Pi devices as edge nodes for local data processing and model training. Each client trains a lightweight Long Short-Term Memory (LSTM) model on individual CGM sequences. The cloud server aggregates model weights using a secure federated averaging algorithm, avoiding raw data transfer and enabling decentralized model optimization. Results: The proposed federated LSTM approach was evaluated using simulated multi-client CGM datasets and compared against baseline models: centralized LSTM and decision tree. Results demonstrate superior performance by the federated model, achieving higher accuracy (91.4%), F1-score (90.0%), and lower mean squared error (3.75), while maintaining communication efficiency and strong personalization across clients. Conclusion: This work demonstrates the feasibility of deploying a scalable, privacy-preserving, and accurate insulin prediction system using federated deep learning (DL) and edge computing. The proposed architecture supports real-time glucose monitoring and personalized insulin management, offering a practical solution for decentralized digital healthcare.
Federated Learning; LSTM; Insulin Prediction; Edge Computing; Continuous Glucose Monitoring (CGM); Privacy-Preserving Healthcare
Prabaharan J, Dr.S.Kevin Andrews, Dr.P.S.Rajakumar
FROM CLICKS TO CLASSROOMS: THE ROLE OF INNOVATIVE SOCIAL MEDIA STRATEGIES IN SHAPING HIGHER EDUCATION CHOICES
In an era where students engage with universities through screens before ever visiting campus, social media has become more than a marketing tool and it is a space where perceptions, trust, and decisions are formed. This research investigates how innovative social media strategies influence both student engagement and the process of selecting higher education institutions. The study is based on a selected sample of 164 students from diverse programs, where Multiple Linear Regression (MLR) was applied to test whether interactive content, immersive storytelling, and stakeholder feedback predict cognitive engagement and knowledge-sharing behaviours. The results of this research revealed a significant positive relationship, with interactive content emerging as the strongest predictor of student engagement. Then, Structural Equation Modelling (SEM) was used to explore a more comprehensive framework, examining how trust, transparency, and content credibility mediate the connection between social media strategies and institutional choice. The SEM results showed good model fit (CFI = 0.95, RMSEA = 0.058), confirming that these mediating factors play a crucial role in transforming social media interactions into concrete enrolment decisions. The findings emphasize the need for higher education institutions to communicate authentically, provide credible information, and create opportunities for students to contribute and see real feedback reflected online. The study contributes to the existing literature by integrating engagement theory with decision-making models, offering a dual-pathway approach that can guide universities in designing social media strategies that are not just visible but meaningful in shaping student perceptions, strengthening institutional trust, and thereby supporting informed educational choices.
Social media strategies, student decision-making; student engagement, higher education choice
EXPLAINABLE MACHINE LEARNING FOR DYNAMIC PRICING IN FAST-CHANGING RETAIL ENVIRONMENTS
Dynamic pricing has become a critical strategy in fast-changing retail environments where demand patterns, customer behavior, and competitive conditions evolve rapidly. While machine learning models have shown strong performance in optimizing prices, their lack of transparency limits trust, adoption, and regulatory compliance in real-world retail applications. This paper proposes an explainable machine learning framework for dynamic pricing that balances predictive accuracy with interpretability. The approach integrates advanced pricing models with explainability techniques to reveal how key factors such as demand fluctuations, inventory levels, customer sensitivity, and competitor pricing influence price decisions. By providing human-understandable explanations alongside price recommendations, the framework enables retailers to make informed, accountable, and adaptive pricing decisions in real time. The model is designed to operate effectively in volatile retail settings, including online marketplaces and omnichannel platforms, where rapid changes require continuous learning and justification of pricing actions. Experimental evaluations demonstrate that the proposed explainable approach achieves competitive revenue performance while significantly improving transparency and decision confidence compared to black-box models. The findings highlight the importance of explainable machine learning in bridging the gap between algorithmic efficiency and managerial trust, supporting ethical, compliant, and sustainable dynamic pricing practices in modern retail ecosystems.
Explainable Machine Learning, Dynamic Pricing, Retail Analytics, Price Optimization, Decision Transparency, Fast-Changing Retail Environments
Mayank Atreya, Navin Chhibber, Harvendra Singh
Copyright (c) 2022 International Journal of Innovation Studies
DYNAMIC CUSTOMER PROFILING AT SCALE: CONTINUOUS SEGMENTATION FROM REAL-TIME BEHAVIORAL EVENT STREAMS
A dynamic customer profiling framework enabling continuous segmentation from real-time behavioral event streams was developed and evaluated. Traditional batch-based segmentation methods inadequately capture rapid behavioral shifts, resulting in outdated actionable intelligence. A real-time streaming architecture was implemented to ingest, process, and analyze continuous event data, enabling subsecond updates to customer profiles and segment memberships. The results demonstrated that the dynamic profiling system achieved low processing latency, high throughput efficiency, and significantly improved segmentation accuracy compared to batch models. The system effectively captured micro-behavioral variations, supported rapid transitions between segments, and provided more coherent and responsive clustering outcomes. Results confirmed continuous segmentation achieves 78% improved responsiveness and higher cluster coherence (silhouette score 0.64 vs. 0.41) compared to batch approaches, enabling real-time personalization.
Dynamic customer profiling, real-time behavioral data, continuous segmentation, streaming analytics, online machine learning, customer behavior modeling, event-driven architecture.
BRIDGING SOCIAL INTELLIGENCE AND ORGANIZATIONAL PERFORMANCE: EXAMINING THE MEDIATING ROLE OF EMPLOYEE ENGAGEMENT
In modern healthcare systems, interpersonal competence has become increasingly critical for maintaining service quality, teamwork effectiveness, and organizational sustainability. This study investigates how Social Intelligence (SI) influences Organizational Performance (OP) and evaluates the extent to which Employee Engagement (EE) mediates this relationship. Using a descriptive, cross-sectional design, data were collected from 384 healthcare professionals—including physicians, nurses, administrative staff, allied health workers, and support employees—selected through stratified random sampling. Validated scales measuring SI, EE, and OP were administered, and the responses were analyzed using SPSS and Hayes’ PROCESS Macro (Model 4). Results confirmed that SI has a positive but relatively weak direct effect on OP. EE emerged as a strong predictor of OP, demonstrating that engaged employees contribute more significantly to communication effectiveness, teamwork, service quality, and organizational growth. Mediation testing revealed that EE partially mediates the SI–OP relationship, indicating that social competencies influence performance more effectively when channelled through engagement behaviors. These findings emphasize the need for healthcare organizations to cultivate both social intelligence and engagement-supportive practices—such as meaningful job design, recognition systems, effective communication, and supportive leadership—to enhance productivity and patient-centered outcomes. The study contributes to organizational behavior literature by integrating SI, EE, and OP within a unified model relevant to healthcare environments.
Social Intelligence; Employee Engagement; Organizational Performance; Healthcare Professionals; Mediation Analysis; Workplace Behaviour; Patient-Centered Care
EXPLORING OCCUPATIONAL STRESS ACROSS INCOME CATEGORIES: A COMPARATIVE STUDY OF EMPLOYEES IN GUWAHATI CITY.
Stress is an inevitable part of modern life which affects individuals belonging to all walks of life. Stress exists in day-to-day small tasks and carries to workplace with varying complexity. Urbanization, industrial development, increasing competition and modernization in the society are contributing to increasing stress. People perceive stress when they fail to meet up to the environmental expectations and find the situation threatening or challenging. Unwaveringly, an alarming rise in psychosomatic and psychological disorders of individuals and feeling of frustration and dissatisfaction with life in general reflect the high stress being experienced by the people in the present-day world. There can be multiple reasons or causes of stress like past traumatic events, future uncertainty, increasing competition in different walks of life, role conflict etc. Employees experience moderate to high level of stress in workplace due to work deadlines, feeling of powerlessness, excessive workload, conservative company policies, composite lifestyle of people, rigorous government policies etc. Employees in both public and private sector experience stress and respond in different ways. Stress manifests in various forms of emotional disorders. (Singh and Singh 1992) found that stress gets its reflection in the form of anxiety, depression, helplessness, hopelessness and anger. The stressful people with the slightest provocation are easily induced to anger and anxiety and become unable to relax. Employees’ responses to work demands and pressures are largely influenced by their personality characteristics, and psychological and behavioural patterns, such as beliefs and values, aspiration and expectancy, need structure, attributions, locus of control, personality traits, coping skills, cognitive patterns, etc. An important personal characteristic which influences the experience of stress is “sense of control.” Control refers to the perception by the individual worker that his or her action results in expected outcomes, particularly those which are important for the workers. Sense of control has been found to have significant effect on people’s response to stress. Personality traits also play an instrumental role in building stress among employees. Traits such as perfectionism, competitiveness and agreeableness lead to more stress among teachers (Anwar S. et al. 2021)