First Advisor

Timothy Anderson

Term of Graduation

Summer 2020

Date of Publication


Document Type


Degree Name

Doctor of Philosophy (Ph.D.) in Technology Management


Engineering and Technology Management




Wireless communication systems -- Management, Benchmarking (Management), Decision making, Cell phone services industry -- Libya -- Case studies



Physical Description

1 online resource (xv, 309 pages)


Most tools and models of performance and quality of service management are generic and do not solve complex technical systems. The critical components of the system need such tools to assess their efficiency to make a better decision about them. One of the primary objectives in the service systems is to improve the ability of efficiency, effectiveness, and sustainability of critical assets. One of the challenges with improving critical assets is the amount of major capital spending needed to upgrade a technology infrastructure with a high obsolescence rate. This along with usage and reliability issues, makes evaluating mobile cells to enhance the Quality of Services (QoS) more difficult.

This research bridges engineering and management by using a robust and objective management tool for benchmarking mobile Base Transceiver Station's (BTS) efficiency with the important radio Key Performance Indicators (KPIs) for evaluating technical efficiency. The objective of this research is to assess the cellular performance and BTS efficiency by demonstrating a robust model that is derived from multiple KPIs based on technical and financial aspects. This novel research provides a comprehensive multidimensional model for tuning the BTS's parameters, which can lead to developing a standard global mobile network KPI. The model measures the efficiency of BTSs and offers a reference set for inefficient BTSs to improve their efficiency. This creates tuning guidelines for the network optimization engineers to improve inefficient BTSs by comparing their configurations with efficient BTSs to achieve a high level of network optimization. Thus, the benchmarking classifies the BTSs into four categories using a performance matrix, and this analysis helps the decision-makers to focus on the right area, and to identify the most critical BTSs based on best practices.

The first part of the research includes a literature review, highlights of the problem statement, research motivation, and the research focus. Data Envelopment Analysis (DEA) is employed as the main methodology to build the evaluating model, and to identify a robust multi-dimensional benchmarking model using resources allocated as inputs and multi-outputs of KPIs. The expert judgments were also used to validate the model and the results. The second stage of the model uses the principles of the Boston Consulting group's product portfolio matrix (BCG matrix) as a performance matrix approach to provide target-setting strategies. Also, the statistical and regression analyses are adopted to extract useful insights, which helps the implementation of the enhancements. The real data from a local mobile operator in North Africa is used as a case study.

Besides the analysis and the assessment of the BTS's efficiency, a set of recommendations is provided to improve the inefficient BTSs. Moreover, the set of references from the best practice point of view for the inefficient BTSs are defined. These results give network engineers specific suggestions to improve the inefficient BTSs based on tuning parameters of best practices for peers. Finally, the scope of further research is provided along with some opportunities to enhance the model for new technology and other aspects of application areas as well as the future steps to validate the results in a real network.


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