独创性
潮流效应
旅游
结构方程建模
动态能力
分析
大数据
业务
营销
验证性因素分析
供应链管理
供应链
资源(消歧)
计算机科学
数据科学
心理学
定性研究
数据挖掘
社会学
社会心理学
机器学习
政治学
法学
服务(商务)
社会科学
计算机网络
作者
Yuvika Gupta,Farheen Khan,Anil Kumar,Sunil Luthra,Maciel M. Queiroz
出处
期刊:The International Journal of Logistics Management
[Emerald (MCB UP)]
日期:2023-09-07
标识
DOI:10.1108/ijlm-03-2022-0125
摘要
Purpose With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line. Design/methodology/approach Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance. Findings The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role. Research limitations/implications This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs. Originality/value The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.
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