Abstract
This paper tests the meta-analysis based unified theory of acceptance and use of technology (meta-UTAUT) model to predict the behavioral intentions of organizational users and their use behavior to artificial intelligence (AI) integrated customer relationship management (CRM) systems. Data was collected from 315 organizational users in India. The hypotheses draw on the theoretical underpinnings which have been statistically validated. Results show that CRM quality and satisfaction significantly influences an organization’s employees attitudes and intentions to use AI integrated CRM systems. The compatibility of CRM systems has, however, a limited impact on employees attitudes. The findings, which are aligned with the extended UTAUT model, provide useful insights into organizations and decision-makers for designing AI integrated CRM systems.
Highlights
Customer Relationship Management (CRM) is considered an effective tool by organizations to identify their best customers
This paper argues that since organizations are likely to adopt Artificial Intelligence (AI) integrated CRM system the question of society influencing the employees of organizations and voluntariness of the employees is redundant
Data collected from 315 usable responses as per the five-point Likert scale was analyzed by the Partial Least Square-Structural Equation Modelling (PLS-Structural Equation Modelling (SEM)) approach
Summary
Customer Relationship Management (CRM) is considered an effective tool by organizations to identify their best customers. To analyze the use behavior of employees to AI integrated CRM system, their attitudes and intentions must be aligned to support using the system because their intentions and attitudes predict use behavior (Chatterjee et al, 2020; Dwivedi et al, 2017; Gupta et al, 2019b) This suggests that the factors impacting the attitudes and intentions of users to AI integrated CRM systems need to be identified. For AI to be employed, it is important that an organizations’ employees responsible for analyzing customers data make diligent use of AI integrated CRM system Such systems support organizations to accurately analyze the likes, habits, dislikes of the customers (Chatterjee et al, 2019; Sharma & Sharma, 2019). A study examining the uptake of mobile learning by university students highlighted that satisfaction is an important predictor of behavioral intention for adopting information science and information technology (Kabra et al, 2017)
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