Browsing by Author "Saha, P."

Now showing 1 - 6 of 6

An Exploration of Trust as an Antecedent of Unified Payment Interface Usage: A SEM-Neural Network Approach
(IGI Global, 2022) Saha, P.; Kiran, K.B.
The introduction of UPI has revolutionized the Indian banking system, and since then, dynamics of the payment ecosystem has noted a major transformation. UPI has proved to be a boon in the pandemic situation by facilitating contactless and remote transactions. Thus, it is crucial to study user acceptance of payments using UPI and factors influencing its usage. The present paper extended UTAUT3 (Unified Theory of Acceptance and Use of Technology) with an additional construct called 'trust'. Studies on behavioral intention are not rare. But behavioral intention towards UPI usage is not yet explored. What makes this study unique is its attempt to use both SEM and neural network to analyze data. It will guide future researchers to pursue technology adoption studies using this multi-method technique. The novelty also resides in the fact that trust, the newly added construct, has proved to be the most important antecedent of behavioral intention towards UPI usage. © © 2022, IGI Global.
Artificial Bee Colony (ABC) based variable density sampling scheme for CS-MRI
(2017) Jagadish, A.K.; Goswami, S.; Saha, P.; Chakrabarty, S.; Rajgopal, K.
The self-sustained dynamics of the bee population in nature is a result of their hierarchical working culture, efficient organizing skills and unique highly developed foraging ability, which enables them to interact effectively among each other as well as with their environment. In this paper, a novel algorithm utilizing the bee's swarm intelligence, and its heuristics based on quality and quantity of food sources (nectars) is proposed to generate a variable density sampling (VDS) scheme for compressive sampling (CS) based fast MRI data acquisition. The algorithm uses the scout-bees for global random selection process which is further fine-tuned by employed and onlooker-bees who forage locally in the neighborhood giving prime importance to points possessing high fitness values (or high energy) usually located around the center of fc-space. The algorithm introduces the concept of searching for the high quality food sources in annular regions, called as bins, of varying widths. Retrospective CS-MRI simulations show that the proposed fc-ABC based VDS scheme performs significantly better than other sampling schemes. � 2016 IEEE.
Artificial Bee Colony (ABC) based variable density sampling scheme for CS-MRI
(Institute of Electrical and Electronics Engineers Inc., 2017) Jagadish, A.K.; Goswami, S.; Saha, P.; Chakrabarty, S.; Rajgopal, K.
The self-sustained dynamics of the bee population in nature is a result of their hierarchical working culture, efficient organizing skills and unique highly developed foraging ability, which enables them to interact effectively among each other as well as with their environment. In this paper, a novel algorithm utilizing the bee's swarm intelligence, and its heuristics based on quality and quantity of food sources (nectars) is proposed to generate a variable density sampling (VDS) scheme for compressive sampling (CS) based fast MRI data acquisition. The algorithm uses the scout-bees for global random selection process which is further fine-tuned by employed and onlooker-bees who forage locally in the neighborhood giving prime importance to points possessing high fitness values (or high energy) usually located around the center of fc-space. The algorithm introduces the concept of searching for the high quality food sources in annular regions, called as bins, of varying widths. Retrospective CS-MRI simulations show that the proposed fc-ABC based VDS scheme performs significantly better than other sampling schemes. Â© 2016 IEEE.
Assessing the predictors of intention to use unified payment interface: the role of age and gender as moderators
(Inderscience Publishers, 2025) Saha, P.; Kiran, K.B.
Discovering significant predictors of behavioural intention towards unified payment interface (UPI) usage is crucial because UPI is an exemplary digital innovation and UPI enabled payments are preferred by both payer and payee. The present study extended UTAUT3 with an additional construct called word of mouth content (WOMC) and verified its influence on the intention of UPI users. The study also examines whether age and gender moderate the association between WOMC and intention. Data were collected using consumer intercept survey and analysed with structural equation modelling. The moderating effects were examined using multi-group analysis. The results state that performance expectancy, social influence, habit, personal innovativeness and WOMC are significant predictors of the intention of UPI users and the relationship between WOMC and intention differs across gender but not across age. This study is the first of its kind to carry out empirical research on the adoption of UPI in an emerging economy like India. © © 2025 Inderscience Enterprises Ltd.
Dense Sense: a novel approach utilizing electron density augmented machine learning paradigm to understand the complex odour landscape
(Royal Society of Chemistry, 2025) Saha, P.; Sharma, M.; Balaji, S.; Barsainyan, A.A.; Kumar, R.; Steuber, V.; Schmuker, M.
Olfaction is a complex process where multiple nasal receptors interact to detect specific odorant molecules. Elucidating structure–activity-relationships for odorants and their receptors remains difficult since crystallization of the odor receptors is an extremely difficult process. Therefore, ligand-based approaches that leverage machine learning remain the state of the art for predicting odorant properties for molecules, such as the graph neural network approach used by Lee et al. In this paper we explored how information from quantum mechanics (QM) could synergistically improve the results obtained with the graph neural network. Our findings underscore the possibility of this methodology in predicting odor perception directly from QM data, offering a novel approach in the machine learning space to understand olfaction. This journal is © The Royal Society of Chemistry, 2025
What insisted baby boomers adopt unified payment interface as a payment mechanism?: an exploration of drivers of behavioral intention
(Emerald Publishing, 2022) Saha, P.; Kiran, K.B.
Purpose: The unified payment interface (UPI) is in its early stages of adoption for baby boomers. This study explores the factors affecting the behavioral intention of baby boomers to adopt UPI. UTAUT was adopted as theoretical lens of the study and extended with ubiquity, privacy risk and perceived security. The impact of an external factor – effect of COVID-19 was also examined in this study. Design/methodology/approach: A consumer intercept survey was used to collect data from baby boomers via a self-administered structured questionnaire. Structural equation modeling was used to establish the relationships among latent variables. Further, using bootstrap re-sampling technique, the role of perceived security as a mediator between risk, ubiquity and behavioral intention was examined. Findings: The study confirmed that COVID-19 was the most influential external factor for baby boomers to adopt UPI, followed by performance expectancy, social influence, ubiquity, effort expectancy and perceived security. Apropos of UPI adoption by baby boomers, privacy risk negatively influenced perceived security, whereas perceived security fully mediated the relationship between risk, ubiquity and behavioral intention. Research limitations/implications: The study focused only on baby boomers and their intention to adopt UPI. Hence the results cannot be generalized to all age groups and are specific to the cohort. Originality/value: The present study aims to establish research findings on predicting antecedents of adopting a newly introduced payment mechanism and an exemplary Indian digital innovation, UPI, by baby boomers. This study is first to empirically explore intention of baby boomers toward adoption of UPI. © 2022, Emerald Publishing Limited.