Available big data have proliferated rapidly in the last decade and continue to grow in popularity. The existing new data sources such as Online Social Networks (OSNs) and Internet of Things (IoT) influence many digital aspects in-order to shape/reshape normal life of people and other related parties such as businesses, stockholders etc. Urban mobility is one of the considerable impacted domains, where many applications and services have been provided by implicating user activities and other city information. This paper aims to provide a comprehensive view on the influence of various sources of data in the users' trips. To this end, at first we review relevant studies and available services that are designed to facilitate travelers' life as well as we identify the existing gaps in this domain. Next we propose a framework iTrip, which aims to utilize data from different data sources as input and then, recommend/provide advance services to various type of customers. The outcome of this framework will provide a set of summarized recommendations, predictions, decisions, and plans to be used in decision-making for long/short distance transportation mechanisms. In addition, as a future direction of this study a set of ideas and topics is provided