Abstract
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.
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.
| Original language | English |
|---|---|
| Pages (from-to) | 649-679 |
| Number of pages | 31 |
| Journal | International Journal of Logistics Management |
| Volume | 35 |
| Issue number | 2 |
| Early online date | 7 Sept 2023 |
| DOIs | |
| Publication status | Published - 13 Feb 2024 |
Keywords
- Big data analytics capability
- Dynamic capabilities
- Firm performance
- Resource-based view
- Tourism supply chains
ASJC Scopus subject areas
- Business and International Management
- Transportation
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