Neural Computing and Applications, Journal Year: 2022, Volume and Issue: 34(16), P. 13867 - 13881
Published: April 12, 2022
Language: Английский
Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 72, P. 103269 - 103269
Published: Jan. 18, 2023
Language: Английский
Citations
21
Benchmarking An International Journal, Journal Year: 2024, Volume and Issue: unknown
Published: March 28, 2024
Purpose This study aims to explore the challenges faced by tourism and hospitality industry following COVID-19 pandemic propose effective strategies for recovery resilience of this sector. Design/methodology/approach The analysed encountered post-pandemic identified key overcoming these challenges. utilised modified Delphi method finalise employed Best-Worst Method (BWM) rank Additionally, solution are ranked using Criteria Importance Through Intercriteria Correlation (CRITIC) method. Findings significant industry, highlighting lack health hygiene facilities as foremost concern, followed increased operational costs. Moreover, it revealed that attracting millennial travellers emerged top priority strategy mitigate impact on industry. Originality/value research contributes understanding in wake pandemic. It offers valuable insights into practical recovery. findings provide beneficial recommendations policymakers aiming revive support industries.
Language: Английский
Citations
8
IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 93273 - 93288
Published: Jan. 1, 2022
Even though machine learning (ML) applications are not novel, they have gained popularity partly due to the advance in computing processing. This study explores adoption of ML methods marketing through a bibliographic review period 2008–2022. In this period, has grown significantly. growth been quite heterogeneous, varying from use classical such as artificial neural networks hybrid that combine different techniques improve results. Generally, maturity and increasing specialization type problems solved were observed. Strikingly, types used solve vary wildly, including deep learning, supervised reinforcement unsupervised methods. Finally, we found main with related consumer behavior, recommender systems, forecasting, segmentation, text analysis—content analysis.
Language: Английский
Citations
25
Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 81, P. 104011 - 104011
Published: July 29, 2024
Language: Английский
Citations
5
Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 81, P. 103895 - 103895
Published: July 30, 2024
Language: Английский
Citations
5
Journal of Retailing and Consumer Services, Journal Year: 2022, Volume and Issue: 68, P. 103063 - 103063
Published: June 20, 2022
Language: Английский
Citations
21
Current Issues in Tourism, Journal Year: 2023, Volume and Issue: 27(3), P. 396 - 412
Published: Jan. 10, 2023
This work presents a longitudinal analysis of hotel customer satisfaction, making comparison between pre- and post-pandemic situations, as well detailed the evolution satisfaction throughout different phases COVID-19 crisis. To this end, we used representative microdata from more than 405,000 online reviews 802 Venetian accommodation facilities. Data were retrieved Booking.com platform cover 2018–2021 period. Results point to systematic reduction although negative effect is non-linear over time. In fact, magnitude varies according severity phase (acute vs. transitional periods) on replication number type (first versus second wave), displaying some adaptation effects. The paper contributes literature sustained crises, with an empirical application one most popular tourist destinations. Our results suggest that managers should respond critical situations taking care their customers' identifying needs depending crises' phases.
Language: Английский
Citations
12
Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 116, P. 535 - 547
Published: Jan. 7, 2025
Language: Английский
Citations
0
PeerJ Computer Science, Journal Year: 2025, Volume and Issue: 11, P. e2669 - e2669
Published: Feb. 19, 2025
Companies that deliver food (food delivery services, or FDS) try to use customer feedback identify aspects where the experience could be improved. Consumer on purchasing and receiving goods via online platforms is a crucial tool for learning about company's performance. Many English-language studies have been conducted sentiment analysis (SA). Arabic becoming one of most extensively written languages World Wide Web, but because its morphological grammatical difficulty as well lack openly accessible resources SA, like dictionaries datasets, there has not much research done language. Using manually annotated FDS dataset, current study conducts extensive using reviews related include Modern Standard dialectal Arabic. It does this by utilizing word embedding models, deep techniques, natural language processing extract subjective opinions, determine polarity, recognize customers' feelings in domain. Convolutional neural network (CNN), bidirectional long short-term memory recurrent (BiLSTM), an LSTM-CNN hybrid model were among approaches classification we evaluated. In addition, article investigated different effective stemming techniques. dataset corpus gathered from Talabat.com, trained evaluated our suggested models. Our best accuracy was approximately 84% multiclass 92.5% binary FDS. To verify proposed approach suitable analyzing human perceptions diversified domains, designed carried out excessive experiments other existing datasets. The highest obtained multi-classification 88.9% Hotels Arabic-Reviews Dataset (HARD) 97.2% same dataset.
Language: Английский
Citations
0
Tourism and Hospitality, Journal Year: 2025, Volume and Issue: 6(2), P. 51 - 51
Published: March 24, 2025
The COVID-19 pandemic altered the holiday plans of many people. Whether it was due to travel bans or fear contracting infection, people modified, among other aspects, their chosen destination, transport, accommodations, length stay, and activities be undertaken during stay. In this context, we aim disentangle effect these changes on tourist satisfaction. Previous research effects tourism sector has studied shrinkage demand, in behaviour adaptation processes supply side. Nonetheless, few works have analysed tourists’ plans. Two main hypotheses been put forward. First, tourists might dissatisfied given that they could not attain expectations. contrast, second hypothesis suggests those individuals who changed more satisfied because diminished perceived risk contagion. We used data drawn from a survey (N = 2009) visited Costa Daurada, very popular Mediterranean coastal destination just after end Spanish lockdown. Then, statistically significant differences satisfaction levels between groups did are assessed by means Kruskal–Wallis Wilcoxon Rank Sum tests. Results signal were when had modified initial Indeed, overall visitors switched Daurada slightly lower, difference significant, compared ones planning there beginning. Satisfaction significantly lower for case rest items (transportation, accommodation, activities). On contrary, activities, apparently contributed mitigate perception led better experience. also suggest willing adapt new situation order renounce holidays. terms implications management stakeholders, conclusion is continuous cooperation mutual trust key adapting turbulent environments which becomes central.
Language: Английский
Citations
0