A Systematic Review of Application of Big Data Analytics in Tourism Sector

2019 ◽  
Vol 16 (5) ◽  
pp. 1832-1838
Author(s):  
N Padmaja ◽  
T Sudha
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Tourism Sector

Managing supply chain resources with Big Data Analytics: a systematic review

2017 ◽  
Vol 21 (3) ◽  
pp. 177-200 ◽  
Author(s):  
Marcelo Werneck Barbosa ◽  
Alberto de la Calle Vicente ◽  
Marcelo Bronzo Ladeira ◽  
Marcos Paulo Valadares de Oliveira
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Big Data Analytics and Firm Performance: A Systematic Review

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 226 ◽  
Author(s):  
Parisa Maroufkhani ◽  
Ralf Wagner ◽  
Wan Khairuzzaman Wan Ismail ◽  
Mas Bambang Baroto ◽  
Mohammad Nourani
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Firm Performance ◽  
Empirical Research ◽  
Data Analytics ◽  
Web Of Science ◽  
Big Data Analytics ◽  
Future Research ◽  
Science Index ◽  
The Web

The literature on big data analytics and firm performance is still fragmented and lacking in attempts to integrate the current studies’ results. This study aims to provide a systematic review of contributions related to big data analytics and firm performance. The authors assess papers listed in the Web of Science index. This study identifies the factors that may influence the adoption of big data analytics in various parts of an organization and categorizes the diverse types of performance that big data analytics can address. Directions for future research are developed from the results. This systematic review proposes to create avenues for both conceptual and empirical research streams by emphasizing the importance of big data analytics in improving firm performance. In addition, this review offers both scholars and practitioners an increased understanding of the link between big data analytics and firm performance.

A Framework for Effective Data Analytics for Tourism Sector

2022 ◽  
pp. 483-496
Author(s):  
Sapna Sinha ◽  
Vishal Bhatnagar ◽  
Abhay Bansal
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
It Infrastructure ◽  
Technological Revolution ◽  
Competitive Edge ◽  
Tourism Sector ◽  
Tools And Techniques ◽  
The Way

From BRICS nations, India is the second largest tourism market after China in Asia. Technological revolution has added new dimensions to the way technologies being used in all the sectors. Also, the use of electronic gadgets leaves trail of data, which is very huge in size, this data (Big Data) is exploited by every sector for providing better services and gaining competitive edge. This trend grabbed the attention of researchers and industry for development of more optimized tools and techniques. There are many general frameworks proposed by industry and researchers for implementation of Big Data in industry but, there is no framework proposed for tourism sector. In this paper, the authors propose unified IT infrastructure framework named as tAdvisor for effective data analytics using Big Data Analytics approach for increasing productivity in tourism sector. Various challenges and issues related with the implementation of Big Data Analytics is also discussed in the paper.

A Framework for Effective Data Analytics for Tourism Sector

2017 ◽  
Vol 9 (4) ◽  
pp. 92-104 ◽  
Author(s):  
Sapna Sinha ◽  
Vishal Bhatnagar ◽  
Abhay Bansal
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
It Infrastructure ◽  
Technological Revolution ◽  
Competitive Edge ◽  
Tourism Sector ◽  
Tools And Techniques ◽  
The Way

From BRICS nations, India is the second largest tourism market after China in Asia. Technological revolution has added new dimensions to the way technologies being used in all the sectors. Also, the use of electronic gadgets leaves trail of data, which is very huge in size, this data (Big Data) is exploited by every sector for providing better services and gaining competitive edge. This trend grabbed the attention of researchers and industry for development of more optimized tools and techniques. There are many general frameworks proposed by industry and researchers for implementation of Big Data in industry but, there is no framework proposed for tourism sector. In this paper, the authors propose unified IT infrastructure framework named as tAdvisor for effective data analytics using Big Data Analytics approach for increasing productivity in tourism sector. Various challenges and issues related with the implementation of Big Data Analytics is also discussed in the paper.

The emerging big data analytics and IoT in supply chain management: a systematic review

2018 ◽  
Vol 25 (2) ◽  
pp. 141-156 ◽  
Author(s):  
Arun Aryal ◽  
Ying Liao ◽  
Prasnna Nattuthurai ◽  
Bo Li
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Research Approach ◽  
Network Systems ◽  
Content Type ◽  
And Performance ◽  
Over Time

Purpose The purpose of this study is to provide insights into the way in which understanding and implementation of disruptive technology, specifically big data analytics and the Internet of Things (IoT), have changed over time. The study also examines the ways in which research in supply chain and related fields differ when responding to and managing disruptive change. Design/methodology/approach This study follows a four-step systematic review process, consisting of literature collection, descriptive analysis, category selection and material evaluation. For the last stage of evaluating relevant issues and trends in the literature, the latent semantic analysis method was adopted using Leximancer, which allows more rapid, reliable and consistent content analysis. Findings The empirical analysis identified key research trends in big data analytics and IoT divided over two time-periods, in which research demonstrated steady growth by 2015 and the rapid growth was shown afterwards. The key finding of this review is that the main interest in recent big data is toward overlapping customer service, support and supply chain network, systems and performance. Major research themes in IoT moved from general supply chain and business information management to more specific context including supply chain design, model and performance. Originality/value In addition to providing more awareness of this research approach, the authors seek to identify important trends in disruptive technologies research over time.

Sign in / Sign up

Export Citation Format

Share Document