Authors - Payel Das, Siri Kethineedi Abstract - This study explores the elements of consumer resistance to sustainable marketing with an integrated theoretical approach adopting cognitive dissonance theory, institutional theory, and theory of planned behaviour. Although awareness of sustainability is increasing, consumers frequently do not accept sustainable products because of psychological discomfort, institutional barriers, and perceived behavioural limits. Using interpretive structural modelling (ISM), this study elucidates the hierarchy relationships among the main barriers, such as greenwashing, lack of transparency, price sensitivity, norm conformity, and instantaneous gratification. The most impactful of these drivers were identified as greenwashing and transparency deficits, both of which contribute to distrust and ultimately erode consumer confidence. Weak regulations and social norms that perpetuate these problems are demonstrated by Institutional Theory, while price premiums and limited access reduce perceived behavioural control and are described in the theory of planned behaviour. This study proposes a multi-tiered effort for policymakers and businesses to address resistance. Transparency will be enforced through independent certifications and stringent sustainability standards regulated by the regulatory frameworks. To regain consumer trust, companies must embrace true sustainability and communicate honestly. Price premiums can also be lowered through innovation, subsidies, and supply chain efficiencies to help play a role in them become more affordable. Understanding these barriers allows businesses to understand how they can build consumer trust, policymakers to enact effective regulations, and society as a whole to begin moving toward more sustainable consumption habits.
Authors - Payel Das, Sonali Bolisetty, Digumarthi Iswarya Abstract - This study seeks to identify the success enablers of omnichannel retailing by using Interpretive Structural Modeling (ISM) for building a hierarchical framework. From findings in a consumer survey with 108 consumers and expert evaluations, the research uncovers user enablers such as technological infrastructure, data analytics capability, personalization, mobile optimization, and seamless integration. The study is based on Service-Dominant Logic (SDL) and the Technology Acceptance Model (TAM) to investigate theory around foundational, operational, and experiential issues that result in customer engagement and brand loyalty. The findings underscore the critical importance of strong technological infrastructure and the use of real-time data in helping with friction reduction between digital and physical touchpoints. Using AI-powered analytics, it can improve personalization, which affects perceived system usefulness and thus, customer satisfaction. In addition, the study emphasizes the need for brand consistency and proper employee training to provide trouble-free service experiences. We also explore privacy and security concerns and their impact on consumer trust and omnichannel adoption. To policymakers, this research calls for prescriptive regulations that will protect data privacy and grow the space of technological innovation. For practitioners, it provides actionable insights to maximize omnichannel universality, improve customer pursuits, and develop sustainable total brand loyalty. In doing so, with the introduction of SDL and TAM, the study contributes to theoretical knowledge and proposes a comprehensive framework for the businesses who are dealing with the complexities of omnichannel retailing.
Authors - Ketki Kshrisagar, Chinmay Kalbhor, Sudarshan Chitte, Atharva Chivate, Pragati Chopade, Sanika Chougule Abstract - This paper describes the design and implementation of an automated control system for grain storage temperature and humidity. Operations begin using a microcontroller, Arduino Uno, and DHT11 or thermocouple sensors, for real-time environmental conditions, whereas the temperature and humidity are controlled through a Peltier module and a USB spray humidifier, to give the ideal storage conditions. Another complementing feature is an I2C LCD, which visualizes real-time parameters for the users locally to monitor environmental conditions. Besides, the system also includes a Blynk app, which allows the users to monitor and control it through a phone interface from a remote location. The main function of this is to act as a standalone and inexpensive system, which is primarily aimed at reducing grain spoilage and ensuring quality. Test results have confirmed that it was able to provide applicable environmental control for various storage scenarios
Wednesday August 26, 2026 3:30pm - 5:30pm IST Virtual Room BGOA, India
Authors - Fathima Mariya A K, Sarath S, Jyothisha J Nair, Sunitha E V Abstract - Thermal images often hide mixed signals, making accurate analysis challenging. However, segmentation and analysis are significantly compromised with the task of mixed pixels (a pixel containing the signals from several endmember sources). This study proposes a hybrid approach combining gradient-based thresholding (80 percentile and 85 percentile) and different clustering techniques (K-Means, Variational Bayesian GMM, Dirichlet Process GMM and Constrained GMM) to boost precision in mixed pixel identification. Results show that the gradient threshold has a positive effect on detection error (20.77 percentile), closely matching the values of K-Means (20.82 percentile) and Constrained GMM (20.69 percentile). The deviation from those methods to VBGMM and DP GMM is more moderate by 13.60 percentile. This study confirms the usefulness of an integrated approach for a more accurate interpretation of thermal images. Deep learning and multi-spectral will be researched to boost segmentation accuracy in the future.
Authors - Rashmi S. Bhumbare, Pallavi S. Gaikwad, Anjali M. Gutte, Araju M. Shaikh, Gayatri K. Chaudhari Abstract - In this paper, ensuring secure, transparent, and tamper-proof elections is a critical challenge in modern democratic processes. Traditional voting systems, including paper ballots and electronic voting machines (EVMs), suffer from issues such as fraud, lack of transparency, and centralized control. This project presents a Blockchain-Based Voting System, implemented as an Android application using Java/XML, with SHA- 256 encryption ensuring vote security and Firebase Realtime Database handling user authentication and data management. The system leverages blockchain technology to record votes in an immutable and decentralized ledger, preventing manipulation and unauthorized access. The implementation includes secure voter authentication, encrypted vote submission, blockchain-based integrity verification, and real-time result compilation. This approach eliminates traditional vulnerabilities such as vote tampering, duplicate voting, and unauthorized system access. Furthermore, the decentralized nature of blockchain ensures transparency, allowing voters to independently verify their votes while maintaining anonymity.
Authors - Beena B.M, Devika Madhusoodanan, Nithin Sagar, Vismaya R, Hridyalakshmi Santhosh Abstract - Energy conservation in cloud data centers remains one of the biggest research challenges today. Energy efficiency has become an important concern in the management of contemporary data centers due to the rapidly growing computational needs and the environmental impact of power consumption. This study examines various power management techniques, including Dynamic Voltage and Frequency Scaling (DVFS), Dynamic Power Management (DPM), and Adaptive Voltage Scaling (AVS), to optimize CPU power consumption. Using frequency data from historical and current CPU usage, these algorithms control CPU frequency settings and assess their impact on energy consumption and performance. The results indicate that DVFS reduces power consumption by 25-30%, DPM achieves energy savings of 28-35%, and AVS provides savings of 35-40% by dynamically adjusting both voltage and frequency. A performance matrix evaluates the power savings and utilization efficiency of these strategies to determine the most suitable approach. AVS was found to be 5-10% more energy efficient than DVFS and DPM, demonstrating its advantage in real-world applications. Furthermore, AVS exhibited the highest precision (96%) to adapt to workload fluctuations, compared to 95% for DVFS and 92% for DPM. This study focuses on adaptive power management and provides key findings on algorithmic solutions for energy efficiency in software-defined cloud infrastructures. The findings contribute to reducing data center energy consumption while maintaining performance, aligning with the UN Sustainable Development Goals by promoting sustainable and eco-friendly cloud operations.
Authors - Ajay Menon, Anjali Sivan, Navya S, Sandhya G, Astha Santhosh T Abstract - The micro, small and medium enterprise sector plays a crucial role in Kerala’s rural economy and makes a substantial contribution to socio-economic development and job creation. This study explores business continuity intentions among women-led micro enterprises in rural Kerala, using thematic analysis of in-depth interviews with six units from agro-processing, dairy and fisheries sectors. Drawing insights from qualitative data, this study uses the Theory of Planned Behaviour (TPB) to show that continuity intentions are strongly influenced by perceived behavioural control, strong family support, and positive attitudes. However, institutional inefficiencies and financial limitations create significant obstacles. This study also introduces ‘Team-led resilience’ and ‘Gendered leadership dynamics’ as critical factors, highlighting collaborative support and autonomous female leadership. These findings highlight the importance of financial literacy, access to credit, and supportive government policies, which will also help to expand the traditional TPB framework, emphasizing the importance of social and financial resilience.
Wednesday August 26, 2026 3:30pm - 5:30pm IST Virtual Room BGOA, India
Authors - M. Suresh, T. A. Alka, Aswathy Sreenivasan Abstract - The main purpose of this study is to theoretically explore the evolution of trends in teaching entrepreneurship through a Bibliometric analysis. The final number of documents selected is 1375, which are analysed through the Biblioshiny package under R programming. The results show that there are technology-related and non-technology-related trends that have evolved in teaching entrepreneurship. Major trends are happening in teaching methods, learning, courses, global reach, teamwork, and the emergence of technology trends such as artificial intelligence, virtual reality, etc. Bibliometric results draw that the major themes evolved in this domain are related to innovation trends in teaching entrepreneurship for shaping entrepreneurs for tomorrow, transformation, learning culture, technology trends, academic entrepreneurship in the covid-19 pandemic, learning types, concepts, skills required, sustainability and teaching entrepreneurship, entrepreneurialism and thinking in teaching entrepreneurship. The major future research avenues are; entrepreneurial intention; effectuation; entrepreneurship, business model innovation; innovation; digital transformation, and entrepreneurial university; academic entrepreneurship; innovation. The limitations of the research are; the Scopus database is only used for the search. Only the documents in the English language and final publication stage papers were selected. The inherent drawbacks of the bibliometric methodology may influence the results. The study offers theoretical implications for future research work including Sci-Val future research topics and practical implications by offering insights to entrepreneurs, investors, researchers, academicians, policymakers, etc. The novelty and the originality of the study are underlying in the in-depth theoretical exploration through a comprehensive literature review of the past thirty years.
Authors - Ganga S, Nitharshana P, Varun Madhusoodan, Rojalin Patri Abstract - Advancement of financial technology has resulted in the emergence of automated investment solutions, such as robo-advisors. While Gen-Z investors are typically receptive to digital innovations, their adoption of robo-advisory services remains an underexplored area. This study investigates the primary factors affecting Gen-Z's inclination to use robo-advisors, applying the Technology Acceptance Model (TAM). A quantitative methodology was utilized, with data collected from 161 respondents and analyzed through multiple regression techniques. Findings indicate that trust and attitude have a significant impact on the adoption intent of robo-advisory services in investment decisions made by Gen-Z investors. The results suggest that fostering trust and shaping positive perceptions of robo-advisors are more crucial for adoption than enhancing usability. This study contributes to fintech literature and offers insights for financial institutions and policymakers aiming to increase robo-advisory adoption among young investors.
Authors - Apolinar P. Datu, Annaliza C. Sinfuego, Garry C. Bayran, Dominic T. Urgelles, Julius R. Beltran, Rossana B. Liray, Janina Odette S. Vidallon, Erwin Joel B. Layug Abstract - The rapid transition to online learning, catalyzed by the global pandemic, has necessitated a critical examination of its implications within the context of general education. This study investigates the multifaceted factors influencing the implementation, delivery, and reception of online classes in general education programs across selected higher education institutions. Employing a mixed-methods research design, quantitative data were gathered through structured surveys while qualitative insights were obtained via in-depth interviews with students and faculty members. Results indicate that technological accessibility, digital competency, instructional quality, learner motivation, and institutional support are central determinants of effective online learning. The research highlights disparities in students’ digital readiness and access to conducive learning environments, which significantly affect their academic engagement and performance. Moreover, pedagogical adaptability and the integration of interactive tools were found to be critical in maintaining student interest and participation in virtual settings. The findings underscore the necessity for higher education institutions to invest in sustainable digital infrastructures, provide continuous faculty development programs, and adopt inclusive, student-centered online learning strategies. This study contributes to the growing body of literature on e-learning by offering empirical evidence on the challenges and enablers of online education in general education curricula. It also presents actionable recommendations aimed at enhancing the quality and equity of online instruction. In doing so, the research supports the advancement of resilient and adaptive educational systems capable of meeting the evolving demands of 21st-century learners.
Wednesday August 26, 2026 3:30pm - 5:30pm IST Virtual Room BGOA, India
