The evolving role of artificial intelligence in marketing: A review and research agenda

B Vlačić, L Corbo, SC e Silva, M Dabić - Journal of business research, 2021 - Elsevier
An increasing amount of research on Intelligent Systems/Artificial Intelligence (AI) in
marketing has shown that AI is capable of mimicking humans and performing activities in an …

A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting

H Song, RTR Qiu, J Park - Annals of tourism research, 2019 - Elsevier
This study reviews 211 key papers published between 1968 and 2018, for a better
understanding of how the methods of tourism demand forecasting have evolved over time …

The impact of COVID-19 on tourism sector in India

S Jaipuria, R Parida, P Ray - Tourism Recreation Research, 2021 - Taylor & Francis
ABSTRACT The novel coronavirus (COVID-19), which is one of its kind of humanitarian
disasters, has affected people and businesses worldwide, triggering a global economic …

Forecasting tourist arrivals with machine learning and internet search index

S Sun, Y Wei, KL Tsui, S Wang - Tourism Management, 2019 - Elsevier
Previous studies have shown that online data, such as search engine queries, is a new
source of data that can be used to forecast tourism demand. In this study, we propose a …

Artificial intelligence and big data in tourism: a systematic literature review

D Samara, I Magnisalis, V Peristeras - Journal of Hospitality and …, 2020 - emerald.com
Artificial intelligence and big data in tourism: a systematic literature review | Emerald Insight
Books and journals Case studies Expert Briefings Open Access Publish with us Advanced …

Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions

G Srivastava, S Bag - Benchmarking: An International Journal, 2024 - emerald.com
Purpose Data-driven marketing is replacing conventional marketing strategies. The modern
marketing strategy is based on insights derived from customer behavior information …

Bayesian BILSTM approach for tourism demand forecasting

A Kulshrestha, V Krishnaswamy, M Sharma - Annals of tourism research, 2020 - Elsevier
The tourism sector, with its perishable nature of products, requires precise estimation of
demand. To this effect, we propose a deep learning methodology, namely Bayesian …

New developments in tourism and hotel demand modeling and forecasting

DC Wu, H Song, S Shen - International Journal of Contemporary …, 2017 - emerald.com
Purpose The purpose of this paper is to review recent studies published from 2007 to 2015
on tourism and hotel demand modeling and forecasting with a view to identifying the …

Tourism demand forecasting with time series imaging: A deep learning model

JW Bi, H Li, ZP Fan - Annals of tourism Research, 2021 - Elsevier
To leverage computer vision technology to improve the accuracy of tourism demand
forecasting, a model based on deep learning with time series imaging is proposed. The …

Tourism forecasting: A review of methodological developments over the last decade

EX Jiao, JL Chen - Tourism Economics, 2019 - journals.sagepub.com
This study reviewed 72 studies in tourism demand forecasting during the period from 2008
to 2017. Forecasting models are reviewed in three categories: econometric, time series and …