Marketing analytics capability and decision-making quality: Empirical evidence from the Jordanian telecommunications sector

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Authors: amer zaid salameh alqudah, Thabet Banihani, Malek Al-Harafsheh, Hassan Shtawi, Majed Al-Rahahleh, Zeyad A. Al Momani, Abdul-Hakim Khraisat
Cited by: 1
References: 1

Abstract

This paper will explore how, as part of Orange Jordan, one of the largest telecommunication firms in the Jordanian market, the Marketing Analytics Capability (MAC) affects the Quality of Decision-Making (DMQ). Precisely, it examines the implication of the major dimensions of the marketing analytics capability such as data assimilation, analytics tools, analytical capabilities, and data-oriented culture with how organisational analytics usage is a moderating aspect to the quality of managerial decision-making. A stratified random sample of managerial and operational levels was chosen on the full-time employees of Orange Jordan which were asked to respond to a structured questionnaire. Data gathering was done between August and November 2024 and it was analyzed through partial least squares structural equation modeling (PLS-SEM). The empirical evidence shows that marketing analytics capability positively and significantly affects the quality of decision making. Nevertheless, the modifying impact of the analytics use was also identified to be of no significance. The study is also part of the growing literature on analytics-based marketing since it presents empirical data on an emergent market setting. Practically, the results are important to telecommunications managers since they highlight the need to intensify marketing analytics ability to improve decision-making performance. These endeavors aid the creation of more sustainable marketing approaches by way of better resource allocation based on data, better organizational learning, and strategizing, therefore, adding to the larger aims of sustainable development connected to innovation, digital infrastructure, and responsible organizational approaches.

Fields of Study & Subjects

Big Data and Business Intelligence Customer churn and segmentation Organizational and Employee Performance

Publication details

Journal / source
International Journal of Data and Network Science
Publisher
Growing Science
Volume
10
Issue
3
Pages
1117–1126
Publication date
1 January 2026
Language
EN