Developing a Web-Based Tender Evaluation System Based on Fuzzy Multi-Attributes Group Decision Making for Nigerian Public Sector Tendering
Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3299917Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 221
 Ng, L. L. N., Chin, D. K. W. and Hung, P. C. K. (2007). Tendering process model (TPM) implementation for B2b integration in a web services environment. Proceedings of the 4th Annual Hawaii International Conference on System Sciences. IEEE Computer Science.
 Betts M., Black, P., Christenden, S., Dawson, E., Du, R., Duncan, W., Foo, E., Nieto, G. J. (2006). Towards secure and legal tendering. Itcon Vol II, pg. 89.
 Expert Group Meeting Report (EGMR, 2011). E-procurement: Towards transparency and efficiency in public service delivery. Department of Economic and Social Affairs, Division for Public Administration and Development Management, United Nation Headquarters, New York. 4-5 Oct. 2011. ST/ESA/PAD/SER.E/171.
 Mohemad, R., Hamdan, A., Othman, Z. A. and Noor, N. M. M. (2010). Decision support system (DSS) in construction tendering processes. International Journal of Computer Science, vol 7, iss. 2, No 1.
 Singh, D and Tiong, R. L. K (2004). A fuzzy decision framework for contractor selection. Journal of Construction Engineering Management, 131, 62.
 Wang, T., and Lin, Y (2005). Application of fuzzy group decision making method on contractor selection for information system outsourcing. Available at http://www.iceb.nccu.edu.tw/proceedings/APDSI.../DSS--14.pdf.
 Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.
 Fong, S. and Yan, Z. (2009). Design of a web-based tendering system for e-government procurement. ICEGOV2009, Nov. 10-13, 2009, Bogota, Colombia. ACM 978-1-60558-663-2/09/11.
 Padumadasa, E. U. and Rehan, S. (2009). Investigation into decision support system and multiple criteria decision making to develop a web-based tender management system. Proceedings of the International Symposium on the Analytical Hierarchy Process.
 Noor, N. M. M. and Man, M. (2010). iWDSS – Tender: Intelligent web-based decision support system for tender evaluation. Decision Support System, advances in, Book edited by: Gerdevlin, pp342.
 Noor, N. M. M. and Mohemad, R. (2010). Decision support for web-based prequalification tender management system in construction projects. Decision Support System, Book edited by: Chiang S. Jao, pp. 406.
 Procurement Procedures Manual for Public Procurement in Nigeria (2008). Bureau of Public Procurement, Federal Republic of Nigeria.
 Mangitung, D. M. (2010). Typical contractor prequalification characteristics of public procurement practices in Indonesia. Construction Building Research Conference (COBRA). Published by The Royal Institution of Chartered Surveyors.
 Hatush, Z. (1996). Contractor selection using multi attribute utility theory. A Phd thesis, University of Salford, UK.
 Jang, J. S. R. and Gulley, N. (1997). Matlab fuzzy logic toolbox: Users guide. The Mathworks, Inc. Natick.
 Hines, J. W. (1997). Fuzzy and neural approaches in engineering matlab supplement. John Wiley and Sons, New York.
 Larman C. (2011). Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Iterative Development. 3rd Edition, Pearson, New Delhi, India.
 O’Docherty, M. (2005). Object oriented analysis and design: Understanding system development with UML 2.0. Wiley.
 Martins, M.S (2006). Validation of simulation based models: A theoretical outlook. The electronic Journal of Business Research Methods, 4(1), 39-46.
 Afolabi, A., Owolabi, D., Ojelabi, R., Oyeyipo, O., & Aina, D. (2017). Development of a web-based tendering protocol for procurement of construction works in tertiary institution. Journal of Theoretical and Applied Information Technology, 95(8), 1595-1606.
 Macdonald, M. (2012). Beginning ASP.NET 4.5 in C#. Apress.