Mohammad Dalvi Esfahani

TL;DR: The findings indicate that focusing on recommendation quality may be insufficient and higher levels of adoption of the recommendations can be achieved when several trust-building factors are considered, and that general site quality contributes to the development of trust.

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.

TL;DR: In this paper, a systematic literature review on the relationship between environmental sustainability, information technology, and information systems under the terms of Green IT and Green IS has been presented, with the aim of understating better the research field, categorizing the studies and identifying some research opportunities and gaps for future research.

TL;DR: This research proposes a new recommendation method using Classification and Regression Tree (CART) and Expectation Maximization (EM) for accuracy improvement of multi-criteria recommender systems and applies Principal Component Analysis (PCA) for dimensionality reduction.

TL;DR: A comprehensive framework of the individual factors that influence organizational decision-makers to adopt Green information systems IS is proposed, based on a review of psychological theories and empirical studies on Green IS and technology adoption.