Natural logarithm transformation for predicting procurement time of PPP projects in Nigeria. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Ahmed, Abdullahi Baba; Musonda, I.; Pretorius, JH
• Editors: Hamasha, Mohammad
• Is Part Of: Cogent engineering. Volume 6:Issue 1(2019)
• Publication Date: 2019-01-01
• Subjects: natural logarithm transformation -- procurement time -- public private partnerships -- multiple regression model; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2019.1571147
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Traditional method of procurement has been in practice over a considerable period and is still the most common type of public infrastructure procurement. The major alternative to it is the Public–Private Partnerships (PPP). PPP focuses on goods or service delivery by means of partnership between two partners (private and public) to come together and share risks and rewards. However, PPP is criticized of being too costly, having a lengthy procurement period, etc. Nigeria, among other Sub-Sahara African countries, has the longest procurement time. This article, therefore, attempts to use secondary data from the World Bank to model and predict the procurement time of PPP projects in Nigeria using Natural Logarithm Transformation approach. A mathematical model that estimates the procurement time of PPP projects in Nigeria is developed using multiple regression analysis. Minitab Software version 18 was used. The model was validated and tested and was found to fall within the predetermined benchmark of ± 10% of what is obtainable in Nigeria. Using the model, procurement time of PPP projects in Nigeria was found to be 646 calendar days. A study from the World Bank on PPP procurement's benchmarking indicates that Nigeria can procure a PPP project in 660 calendar days. From the calculated amount, it is possible to procure PPP projects in Nigeria within 646 calendar days showing a difference of 2%. A total of 646 days is too long, thus indicating a need for immediate improvement for maximum benefits.