Adoption of AI-integrated CRM system by Indian industry: from security and privacy perspective. (16th July 2020)

• Record Type: Journal Article
• Authors: Chatterjee, Sheshadri; Ghosh, Soumya Kanti; Chaudhuri, Ranjan; Chaudhuri, Sumana
• Is Part Of: Information and computer security. Volume 29:Number 1(2021)
• Page Start: 1
• Page End: 24
• Publication Date: 2020-07-16
• Subjects: CRM -- India -- Privacy -- Security -- Artificial intelligence; Computer security -- Management -- Periodicals; Computer networks -- Security measures -- Periodicals; Data protection -- Management -- Periodicals; 658.47
• DOI: 10.1108/ICS-02-2019-0029
• Languages: English
• ISSNs: 2056-4961

Abstract

Abstract : Purpose: The purpose of this study is to make an attempt to identify the factors responsible for the adoption of an artificial intelligence (AI)-integrated customer relationship management (CRM) system in Indian organizations with a special focus on security and privacy issues. Design/methodology/approach: This study was conducted for the identification of factors responsible for the adoption of the AI-integrated CRM system in Indian organizations focusing attention on security and privacy perspective. For this, the adoption theories and models have been studied. The literature available in this context has also been studied with a focus on security and privacy issues. After the initial study, few hypotheses have been formulated and a conceptual model has been developed. These hypotheses were validated with the help of statistical tools by conducting sample survey with 324 usable responses against 36 questionnaires. Findings: The results of this study highlight that of the eight hypotheses conceptually formulated, one hypothesis was not supported as is evident from the application of statistical analysis. This is the influence of perceived ease of use on attitude of the stakeholders intending to use the AI-integrated CRM system in Indian organizations. The results also transpire that the model so provided has achieved 87% explanative power. Research limitations/implications: The model so provided has taken the help of the technological acceptance model. It has also used the issues circumscribing menace of security and privacy vulnerabilities. Consideration of the technological acceptance model and aspects of issues of security and privacy has enriched the model rendering its explanative power to 87%. Practical implications: The model is simple. Practitioners can execute this model without having any complexity. The policymakers could also get inputs from the model, as it has focused specially on security and privacy issues that could help to enhance the trust of the potential users. Originality/value: Not many studies are found covering the adoption of the AI-integrated CRM system by Indian organizations with a special focus on security and privacy aspects. In this light, this study is a novel attempt.