Mohammed Wanous

To bid or not to bid: a parametric solution

One of the most important decisions that has to be made by construction companies/contractors is whether or not to bid for a new project when an invitation has been received. It would be of great help if a structured model could be developed that deals systematically with different bidding situations. A simple parametric solution for the ‘;bid/no bid’ decision is reported in this paper. This solution is based on the findings of six semi-structured interviews and a formal questionnaire through which 38 factors that affect the bid/no bid decision were identified and ranked according to their importance to contractors operating in Syria. Only the most influential factors were considered in the development process. The model was optimized using data about 162 real bidding situations. Then the optimized model was tested using another 20 real projects. It proved 85% accurate in simulating the actual decisions. Although, the proposed model is based on data from the Syrian construction industry it could be modified very easily to suit other countries.

A neural network bid/no bid model: the case for contractors in Syria

Despite the crucial importance of the ‘bid/no bid’ decision in the construction industry, it has been given little attention by researchers. This paper describes the development and testing of a novel bid/no bid model using the artificial neural network (ANN) technique. A back‐propagation network consisting of an input buffer with 18 input nodes, two hidden layers and one output node was developed. This model is based on the findings of a formal questionnaire through which key factors that affect the ‘bid/no bid’ decision were identified and ranked according to their importance to contractors operating in Syria. Data on 157 real‐life bidding situations in Syria were used in training. The model was tested on another 20 new projects. The model wrongly predicted the actual bid/no bid decision only in two projects (10%) of the test sample. This demonstrates a high accuracy of the proposed model and the viability of neural network as a powerful tool for modelling the bid/no bid decision‐making process. The model offers a simple and easy‐to‐use tool to help contractors consider the most influential bidding variables and to improve the consistency of the bid/no bid decision‐making process. Although the model is based on data from the Syrian construction industry, the methodology would suggest a much broader geographical applicability of the ANN technique on bid/no bid decisions.

Developing Countries and ICT Initiatives: Lessons Learnt from Jordan’s Experience

Many developing countries have started major Information Communication Technologies (ICT) initiatives including e‐Government, e‐Learning, e‐Health, and other schemes that are designed to boost the adoption of ICT based applications within public and private sectors as well as creating a knowledge society. The main aims of these initiatives is to be ready to undertake major reform programmes in order to achieve the social and economic development that ICT is believed to deliver. The Hashemite Kingdom of Jordan commenced major ICT programmes in 1999. Eight years on most of the e‐Initiatives that have been implemented have not met their intended objectives. This paper will review Jordans ICT transformation over the past decade identifying critical factors that might be behind the countrys lack of progress with its transformation. This might prove useful for other developing countries undertaking similar ICT initiatives.

Assessment for learning and skills development: the case of large classes

It is widely accepted that assessment has a great influence on the quality of learning. Assessment can be a powerful tool for improving students’ learning and motivation. It also helps in developing a positive and supportive learning environment. The present paper briefly outlines the original assessment arrangements for a cross-department programme at the University of Bristol, Faculty of Engineering before describing the process of reviewing these arrangements and designing a more developmental teaching, learning and assessment framework. The programme is called Professional Studies (PS) and has become compulsory for all six branches of Engineering taught at Bristol. The total Engineering undergraduate population of around 800 students attends the PS course every year. PS is crucial for Engineering degrees to be accredited by the respective professional bodies, such as I. Mech. E., Inst. Civil Eng. and Inst. Aero. Eng. In addition to teaching professional awareness, the PS course seeks to develop a range of transferable personal skills, which are highly sought after by employers. This dual objective has played a key part in shaping the way the PS course teaching, learning and assessment strategy has been developed. Over three years, input from students, academic staff across the six Engineering departments, the Engineering Council UK, external examiners and prospective employers, has helped to adapt the course to optimize the effectiveness of the learning outcomes and to control the heavy demand associated with large classes on teaching and assessment resources. Finally, a brief evaluation of the new method is provided with possible further improvements.

Understanding national e-government: the role of central government

E-government generally refers to the implementation of information and communications technology to change the structures and processes of government organisations aiming at performance improvement. Many governments worldwide invested heavily in national e-government. However, e-government is a recent, multidisciplinary topic that involves various stakeholders. There are different types of e-government and e-government itself is dynamic with an evolving nature. This led to the lack of clear understanding of managerial practices surrounding the role of the central government in its deployment and development. This paper presents a generic framework for explaining e-government focusing on the role of the state throughout its deployment.

Reviewing existing methods for evaluating e-government websites

Investigating e-government and examining its development has become an evolving research area in the information systems field. Much of the existing research on e-government has used the internet to examine government websites. The use of the internet has been recommended by e-government scholars as a method to evaluate e-government development. However there is no agreement as to what is the best method to examine use of the internet in order to evaluate e-government. In addition there is no universal instrument used to perform data collection and analysis. This research paper will resolve some of the existing ambiguity surrounding this area.

A Neural Network Mark-up Estimation Model for Syrian Contractors

One of the most important decisions that have to be made by construction contractors is how much to mark-up the estimated cost of a new project. The main objectives of this paper are to model the relationship between mark-up estimation and the key factors affecting it and to compare the application of regression analysis and neural network techniques on the mark-up decision making process in order to find which technique is more reliable in terms of accuracy and robustness. The most influential mark-up factors were identified through a formal questionnaire survey conducted among Syrian contractors. Subsequently, data on one hundred and eleven real-life bidding situations was collected from Syria. Ninety-six of these projects were used to develop linear, non-linear regression and neural network mark-up models. The remaining fifteen projects were randomly held-back for validating the developed models. The neural network model proved to be robust and more accurate than the regression models. Although this study was carried out in the context of the Syrian construction industry, the methodology and the findings have much broader geographical applicability.