Browsing by Author "Palima Pandey"

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Analytical modeling of perceived authenticity in AI assistants: application of PLS-predict algorithm and importance-performance map analysis
(Emerald Publishing, 2025) Palima Pandey; Alok Kumar Rai
Purpose: The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship. Design/methodology/approach: Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map. Findings: A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension. Practical implications: The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies. Originality/value: The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map. © 2024, Emerald Publishing Limited.
Consumer adoption in technological context: Conceptualization, scale development& validation
(School of Management Sciences, 2021) Palima Pandey; Alok Kumar Rai
Consumer adoption’ is a rich concept, which is far beyond merely purchase of a product. Literature presents different psychological as well as behavioural components of adoption however, there have been found a lack of integration between them and consensus is yet to emerge regarding the concrete blend of its constituents. The study dealt with the conceptualisation of the term ‘consumer adoption’ in technological context. The construct was operationalized and consequently, an empirically tested comprehensive scale of ‘technology adoption’ was developed. The initial phase of the scale development process comprised of item generation, refinement, pre-testing and exploratory factor analysis while the advanced stage incorporated confirmatory factor analysis. The scale was validated on the basis of systematic authentication of measurement and structural model. The study resulted into construction of a nine-item scale of ‘technology adoption’ comprising three factors namely ‘acceptance’, full-scale usage’ and embracement’. Further, the resultant factors served the basis for development of an ‘operational definition’ of adoption. © 2021, School of Management Sciences. All rights reserved.
Consumer Adoption of AI-powered Virtual Assistants (AIVA): An Integrated Model Based on the SEM–ANN Approach
(Sage Publications India Pvt. Ltd, 2023) Palima Pandey; Alok Kumar Rai
Artificial intelligence (AI) has lured consumers to orchestrate their routine activities relying on such technologies. Though AI-powered virtual assistants (AIVAs) have gained traction among service providers, these are still lagging on the demand front. This study intends to develop an ‘AIVA adoption model’ delineated under a holistic framework based on structural equation modelling and deep neural network incorporating multilayer perceptron algorithm. The sensitivity analysis designated ‘effort expectancy’ as the most dominant antecedent of AIVA adoption, followed by ‘perceived innovativeness’. While ‘perceived risk’ held high relevance, the tech users were equally concerned about the performance of AIVA in conjunction with its anthropomorphic response; however, they gave the least consideration to subjective norms. The parallel mediation analysis revealed that the adopters preferred transactional relationships with AIVA more than the communal one, while the simultaneous application of both the perspectives better generates loyal customers. The moderation analysis unveiled that the uncanny valley paradigm could not always be supportive, especially in the context of AIVA. The developed model may serve the basis to generate as well as sustain adoption and loyalty of the specified technology. © 2023 Fortune Institute of International Business.