Ali Ahani
Griffith University
30 Papers
51 Citations
Ali Ahani is an academic researcher from Griffith University. The author has contributed to research in topics: Computer science & Market segmentation. The author has an hindex of 13, co-authored 22 publications. Previous affiliations of Ali Ahani include Universiti Teknologi Malaysia.
Chat about Author
Papers
Market segmentation and travel choice prediction in Spa hotels through TripAdvisor’s online reviews
TL;DR: Findings confirm that the proposed hybrid machine learning methods can be implemented as an incremental recommendation agent for spa hotel/resort segmentation through effectively utilizing ‘big data’ procured from online social media contexts.
237
Forecasting social CRM adoption in SMEs: A combined SEM-neural network method
TL;DR: The study finds that compatibility, information capture, IT/IS knowledge of employee, top management support, information sharing, competitive pressure, cost, relative advantage, and customer pressure are the most important factors influencing social CRM adoption.
226
Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels
Ali Ahani,Mehrbakhsh Nilashi,Elaheh Yadegaridehkordi,Louis Sanzogni,A. Rashid Tarik,Kathy Knox,Sarminah Samad,Othman Ibrahim +7 more
TL;DR: In this article, the authors identify the important factors for hotel selection based on previous travelers' reviews on TripAdvisor and develop a new method for the use of Multi-Criteria Decision-Making (MCDM) and soft computing approaches.
213
Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach
Elaheh Yadegaridehkordi,Mehdi Hourmand,Mehrbakhsh Nilashi,Mehrbakhsh Nilashi,Liyana Shuib,Ali Ahani,Ali Ahani,Othman Ibrahim +7 more
TL;DR: In this paper, a study aimed to identify and rank the significant factors influencing adoption of big data and in turn to predict the influence of big Data adoption on manufacturing companies' performance using a hybrid approach of decision-making trial and evaluation laboratory (DEMATEL)- adaptive neuro-fuzzy inference systems (ANFIS).
145
Preference learning for eco-friendly hotels recommendation: A multi-criteria collaborative filtering approach
Mehrbakhsh Nilashi,Ali Ahani,Ali Ahani,Mohammad Dalvi Esfahani,Elaheh Yadegaridehkordi,Sarminah Samad,Othman Ibrahim,Nurfadhlina Mohd Sharef,Elnaz Akbari +8 more
TL;DR: A new soft computing method is developed with the aid of machine learning techniques in order to find the best matching eco-friendly hotels based on the several quality factors in TripAdvisor to improve the scalability of prediction from the large number of users' ratings.
128