The role of marketing information systems in the production of knowledge institutions in the collective transport companies

لحول سامية; مقاوسي صليحة; عقاري زكرياء

لحول سامية
مقاوسي صليحة
عقاري زكرياء

Keywords: intelligent transportation systems, marketing information systems, knowledge, mass transport enterprises.

Abstract

This research aims to highlight the contribution of marketing information systems in the production of knowledge institutions of mass transit. This is done based on the sub-systems in the field of transport, namely: sources for obtaining information (such as systems global positioning GPS, systems Site Automatic vehicle AVL, traffic control and parking vehicles Smart APC Smart Cards CAP) and decision support systems marketing (such as systems planning timeline and GIS SIG), in addition to marketing research and passenger information systems. And confirmed the findings of the research contribution marketing information systems in the production of knowledge institutions mass transport through the interaction of subsystems her, where the system starts to extract the information produced from databases daily operations (APC, AVL, GPS, CAP) and Data Acquisition Systems marketing (records and reports internal marketing research, marketing intelligence). And then transferred the information recorded to the management centers extract, transform and load (ETL) data through wireless communication or downloaded periodically recordings on organizational databases.
And use the information stored in databases interactively as a data warehouse in the institutions of collective transport with GIS SIG and time planning systems.
These interactions take place by the marketing decision support systems with a data warehouse using data analysis techniques (treatment Inquiry, immediate and analytical processing on data mining). The series is produced by using a drilling technique knowledge on marketing data related to the performance and operation of fleet vehicles institutions and improve mass transit service and client relationship. This knowledge is in: real-time information to users of mass transit, bus priority at traffic signals, demand management, wait times in attitudes, predict arrival times, create a route, the behavior of users of mass transit, adhere to the timetable planned.