Quality 4.0 and Big Data Marketing: A Systematic Literature Review

Adnan Raouf, Raad and Ali Ismael, Omar Ali Ismael (2025) Quality 4.0 and Big Data Marketing: A Systematic Literature Review. In: THE 5TH INTERNATIONAL SCIENTIFIC CONFERENCE ON ADMINISTRATIVE AND FINANCIAL SCIENCES (CIC-ISCAFS'2025), 29-30/January/2025, Cihan University-Erbil.

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Abstract

This paper explores the logical relationships between
two new concepts, Quality 4.0 and Big Data-driven Marketing.
The review of literature provides a view of the theoretical
underpinning and implementation of Quality 4.0 and big data
driven marketing. Research questions will concentrate on the
dependency relationship between Quality 4.0 and big data
marketing and the problems faced in carrying them out jointly.
Quality 4.0 integration and big data marketing bring encouraging relationships, e.g., using predictive analytics for enhancing quality and personalizing the customers’ experiences. Real-time data from Quality 4.0 Systems would provide actionable insights into marketing strategies meant for personalization, enhancing customer satisfaction, as well as enhancing operational efficiency. Nonetheless, there are still problems relating to general data governance, privacy-related issues, and the general context of an enabling environment. The Big Data-driven marketing
restructuring in Quality 4.0 conveys actionable information that is applied to improve product quality and engage customers through data-driven decision making. In theory, it broadens the base of intersection between quality management and marketing with emerging technologies embedded in a new model for company
strategy. And finally, it opens the way for further research into whether and how innovation is related to quality management in different industry settings. This study adds to the literature by exploring the intersection between Quality 4.0 and big data-based marketing and shedding light on ways of using digital technologies not only for quality enhancement but also in the backdrop of marketing. The paper presents a novel framework based on confluence between these two domains by underlining their shared potential for fostering organizational innovation. The study recommends further research on both topics.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Quality 4.0, Big Data, Data-driven Marketing, Predictive Analytics, Industry 4.0.
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
H Social Sciences > HG Finance
H Social Sciences > HJ Public Finance
Divisions: Conferences > CIC-ISCAFS
Depositing User: ePrints Depositor
Date Deposited: 20 May 2025 11:21
Last Modified: 20 May 2025 11:21
URI: https://eprints.cihanuniversity.edu.iq/id/eprint/3528

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