New project are implemented to replace old ones for the purposes of improving efficiency in service delivery and production depending on whether the project lies in service or production industry. For these case, a project for implementing an electronic toll collection system for a high-speed overpass extension in one of the most congested highways linking rural provinces and a city with 12 million people. The project was aimed at easing congestion, improving the quality of transport services, lower cost of operating vehicles, and address the issue of loss of revenue collected as result of corruption experienced in the manual toll collection system. For the efficiency and effectiveness of the project to be determined three years after implementation, the stakeholders need to be consulted, questioned, and the existing records before and after implementation of the project be implemented (Dietrich, D., & EMC, 2015).
Questionnaires and documents and records primary data collection techniques will be used in the study (Baesens, 2015). The stakeholders in who will be consulted in this study will include workers in the toll collection system, drivers who use the overpass, and owners of the vehicles which use the road. Questionnaires will be delivered to the drivers, vehicle owners, and workers. The questions will aim at finding out the distance and time spent in a journey before and after the project, the cost of repair and maintained of vehicles before and after the project, and the ease of operations in the toll system before and after the project. On the other hand, documents and records will be examined before and after the project to determine whether there is change in revenue collection since the project was completed. With the above mentioned information available, one is able to determine whether the project was beneficial or not.
Baesens, B. (2015). Fraud analytics using descriptive, predictive, and social network techniques: A guide to data science for fraud detection.
Dietrich, D., & EMC Education Services. (2015). Data science & big data analytics: Discovering, analyzing, visualizing and presenting data.
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