Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
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This Author published in this journals
All Journal JABM JOURNAL of ACCOUNTING - BUSINESS & MANAGEMENT International Journal of Tourism and Hospitality in Asia Pasific
Chelliah, Shankar
Unknown Affiliation
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Other

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Grab Marketing Strategy, Research & Development Widyatama, Gabriel Willy; Chelliah, Shankar; Kai, Yang; Yingxing, Yang; Tien, Yee Chew; Mey, Wee Choo; Sin, Liem Gai
International Journal of Tourism and Hospitality in Asia Pasific Vol 3, No 2 (2020): June 2020
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (195.013 KB) | DOI: 10.32535/ijthap.v3i2.827

Abstract

Grab is a Singapore-based company providing transportation applications available in six countries in Southeast Asia. It utilizes smartphone cloud-based technology to provide ride-hailing and logistics services, food delivery, and courier service. This study proposes to determine and analyze the problems that exist in the Grab company. One of the problems in a company is a competition between companies. One of the competitors is GO-JEK. This research is expected to provide solutions to problems that exist within the company. How to stand out from competitors, attract more customers and drivers, and various training courses for drivers? What should the company decide on the price? In different countries, how should companies operate under different government policies?
Big Data in Tourism: A Bibliometric Analysis (2014-2024) Huang, Xiaoxu; Chelliah, Shankar
Journal of Accounting, Business and Management (JABM) Vol 32 No 1 (2024): Special Issue
Publisher : STIE Malangkucecwara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31966/jabminternational.v32i1.1454

Abstract

The emergence of big data and its related technologies has brought about novel economic models, industry phenomena, and relational networks, instigating revolutionary changes with significant value for tourism sustainability. This study conducts a bibliometric analysis of 212 articles (2014-2024) on big data in tourism from the Web of Science (WoS) Core Collection database, aiming to create a knowledge map based on big data in tourism. This study utilizes VOSviewer software to carry out citation analysis, co-citation analysis, co-authorship analysis, and keyword co-occurrence analysis, revealing trends in publications, national contributions, influential journals and authors, author collaborations, as well as the conceptual structure and research trends in the field of big data in tourism. The findings indicate a concentration of research in seven areas: machine learning, social network analysis, sustainability, tourism demand forecasting, artificial intelligence, smart tourism, and text mining techniques. The research has focused on emerging hot topics since 2022, including destination image, COVID-19, topic modeling, and urban tourism. This study maps the knowledge of big data in tourism, elucidates the academic evolution in this field, and offers future research directions for scholars in the domain.
Co-Authors Huang, Xiaoxu Mey, Wee Choo Sin, Liem Gai Tien, Yee Chew Widyatama, Gabriel Willy Yang Kai Yingxing, Yang