General Introduction

Background

For generations, the construction industry has been challenged to deliver various services to the population. The current global housing crisis, especially in developing countries (Akinwumi et al., 2015) makes this challenge even more imperative requiring urgent actions.

Similar to most developing countries, the increase in population has led to an acute demand for housing. Despite the current global economic downturn, Cameroon construction industry for example accounted for 3.4% of Gross domestic product (GDP) in 2011 (African Economic Outlook, 2012). Its importance justifies why the Cameroon government promptly intervened with strategies to minimize the impacts of the global economic recession. Some measures include reducing construction material prices (Nkama, 2009) and encouraging international investors to explore Cameroon’s construction market (Khan and Baye, 2008). In particular, China is one of the countries that has been investing in the Cameroon construction industry (Khan and Baye, 2008).

Despite huge investments from the Cameroon government and foreign investors in the construction industry, demand for housing still far outstrips supply. This has led to the emergence of informal practices, where progressive refurbishment and regeneration have been carried out by individuals in most cities to render their houses usable (Fombe, 2012). In both the formal and informal sectors of Cameroon, housing delivery is a major challenge and is further exacerbated by many other issues related to construction project management. Studies about how to improve the understanding of key aspects of construction project management are scarce. Louzolo-Kimbembé and Pettang (2006) reported the lack of efficient cost planning techniques. (Abanda, et al., 2011) and (Manjia, et al., 2010) reported the lack of labour cost estimating tools. Recently, (Fombe & Ntani, 2012) argued for the necessity to deal with huge amount of waste being generated from construction projects. The afore-mentioned weaknesses have already been dealt with in developed countries, although considerable progress is still being made. This progress in improving construction delivery efficiency and productivity has largely been due to the use of decision support systems. There are a multiplicity of such systems including, artificial neural network, fuzzy logic, case-based reasoning, ontology knowledge based systems, etc. The advent of computers has facilitated the implementation of these systems. Although, there has been recent efforts by different researchers (Louzolo-Kimbembé & Pettang, 2006; Abanda, et al., 2011; Manjia, et al., 2010; Fombe & Ntani, 2012) to address various aspects of construction project management using decision support systems in Cameroon, a wider and an in-depth knowledge of the applications of such systems in that country is schetchy.

This publication provides an overview of different decision support systems applied in construction in developing countries with focus on Cameroon. Specifically, the publication covers the following:

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  Background and importance of construction industry in developing countries;

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  Establishmenmt of the different challenges faced by the construction industry;

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  Identification of the different decision support systems applicable in improving efficiency in the delivery of building construction projects;

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  Development of a decision support system that can enhance decision-making in the deliverying of construction projects in developing countries.

Organisation Of This Book

The book consists of 11 chapters. The structure and order of writing of the chapters is presented in Figure 1 and the content of each chapter is briefly described.