The Impact of Statistical Data Analytics on Decision Making Process in Hotels

Document Type : Original Article

Authors

1 Hotel Management Dep., Faculty of Tourism and Hotels, Minia University, Minia, Egypt

2 Hotel Management Department, Faculty of Tourism and Hotels, Minia University.

3 Hotel Management Department, Faculty of Tourism and Hotels, Minia University

Abstract

Understanding the role of statistical data analytics in enhancing the effectiveness of hotel decision making is a vital to improve operational performance and enhance customer satisfaction. Although previous studies have focused on explaining statistical data analytics, there is a lack in these studies that have focused on exploring the impact of statistical data analytics on decision making in the Egyptian hospitality contexts. Therefore, this research intends to uncover the impact of statistical data analytics dimensions (analytical skills, data quality, domain knowledge, big data, and tool sophistication) on the decision making process in hotels. The research methodology is analytical; the population consists of managers and employees from four- and five-star hotels in Hurghada and Sharm El-Sheikh, and the sample is randomly stratified. As a result, the researchers obtained data from 405 respondents. SPSS V. 22 was used to analyze the data and test the research hypotheses. The findings indicate that each dimension of statistical data analytics (analytical skills, data quality, domain knowledge, big data, and tool sophistication) has a statistically significant positive impact on the decision making process in hotels. The research recommends that hotels prioritize developing analytical skills through targeted training programs. This investment in human capital enables employees to interpret complex data and derive actionable insights, ultimately leading to better decision making. Moreover, this research contributes to filling the research gap in previous studies by investigating statistical data analytics and providing important practical implications for the hospitality sector.

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