Universiti Teknologi Malaysia Institutional Repository

Business intelligence dashboard for driver performance in fleet management

Khalid, A. S. and Hassan, N. S. and Abu Bakar Razak, N. A. and Baharuden, A. F. (2020) Business intelligence dashboard for driver performance in fleet management. In: 11th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2020, 10-12 Jan 2020, Osaka, Japan.

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Official URL: http://dx.doi.org/10.1145/3377571.3377642

Abstract

Transportation is at the center of logistics as it represents the physical movement of materials between points in a supply chain. The problem involve in the transportation industry is fleet management. Fleet management is the broad topic that involve vehicles maintenance, operation capacity, driver selection and so on. This project focus on performance of the driver in fleet management. Imbalance driver contribution in fleet management decline the productivity of the organization especially in transportation industry. Each driver should be evaluated and analysed on their productivity and contribution towards the organization based on their performance. The aim of this project is to identify the factors influencing driver performance in logistic transportation and provide business intelligence dashboard for visualize driver performance for organization in their decision making. One transportation industry has been selected for the case study relying on business intelligence framework and tools for the development of dashboard. As the finding of this project, a conceptual model representing factors influencing driver performance is proposed. A dashboard was developed to provide business insight and help the organization in decision making based on the conceptual model proposed. The dashboard comprises of four main components which are summary, delivery, driver profile and driver behaviour. The dashboard was evaluated with respondents who involved in fleet management.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:business intelligence, driver performance, fleet management
Subjects:T Technology > T Technology (General)
Divisions:Advanced Informatics School
ID Code:93309
Deposited By: Narimah Nawil
Deposited On:19 Nov 2021 03:15
Last Modified:19 Nov 2021 03:15

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