Supplier selection with rank reversal in public tenders

For supplier selection in the public sector, the Weighted Sum Model is often used in combination with relative scoring methods that allow rank reversal. With rank reversal we refer to a changed order in the ranking of bids leading to a new winner, after removing or adding a non-optimal bid that does not win the original tender. In practice, an important reason indicated by practitioners for using methods that allow rank reversal is that it would rarely occur in practice. Based on an analysis of 303 Dutch public tenders, this research shows this is not true. In about 1 out of 5 the tenders, rank reversal occurs after adding non-optimal fictional bids to tenders that do not have quality thresholds. After removing bids, the rate is about 1 out of 40 if a curved relative scoring method is used. In addition, the research shows that rank reversal rates increase when (i) there is no quality threshold, (ii) the number of bids increases, (iii) bid price variance increases, and (iv) price weights are not very low or high. We argue that relative scoring methods that allow rank reversal should not be used in public procurement, or otherwise only in exceptional cases, as it conflicts with public procurement principles and leads to reduced overall bid value.     

A multi-criteria expert decision system for investment decisions: The case of commercial real estate investments in China

Consistent with the rapid growth of the Chinese economy and its commercial real estate (CRE) market, evaluating CRE investments in China is becoming an important application area where a multi-criteria expert decision system can make a significant contribution. We used a multi-criteria expert decision system to evaluate ten actual CRE investments in China. Based on thirty-one industry experts, we identified key decision factors to consider when evaluating different CRE investment projects and determined their importance weights. We then evaluated whether or not the ten CRE investment projects were considered to be successful, taking into account the unique characteristics of each CRE investment project. We finally compared the evaluations for the ten cases with their actual performance using four different performance indicators. The results showed that the evaluations had at least 87.5% accuracy across four different performance indicators. As probably one of the first systematic and in-depth scholarly studies to evaluate CRE investment projects in China, this study contributes to a better understanding of such evaluations and helps CRE investors evaluate CRE investment projects in a more informed fashion.     

Bayesian portfolio selection using a multifactor model

This article develops a new portfolio selection method using Bayesian theory. The proposed method accounts for the uncertainties in estimation parameters and the model specification itself, both of which are ignored by the standard mean-variance method. The critical issue in constructing an appropriate predictive distribution for asset returns is evaluating the goodness of individual factors and models. This problem is investigated from a statistical point of view; we propose using the Bayesian predictive information criterion. Two Bayesian methods and the standard mean-variance method are compared through Monte Carlo simulations and in a real financial data set. The Bayesian methods perform very well compared to the standard mean-variance method.     

Performance improvement decision aid systems (PIDAS) in retailing organizations using data envelopment analysis

This paper investigates the usefulness of Data Envelopment Analysis (DEA) models to aid decision making in multi-level retail organizations. It is argued that market efficiency is a key performance measurement dimension in retail organizations. The paper proposes three variants of market efficency that correspond to different tiers of management in a multi-level setting. The disentanglement of market efficiency will lead to the development of the Performance Improvement Decision Aid System (PIDAS) which seeks to classify units on clusters of different performance profile. The method is illustrated using data from a restaurant chain in the UK.     

Decision making framework for tender evaluation and contractor selection in public organizations with risk considerations

Selecting the best construction contractor plays a critical role in the success of any construction project. Moreover, in the public sector, the traditional lowest bid method is still broadly used and contracts are often awarded based on the lowest price. However, this method has been criticized by many researchers because even if it might guarantee the lowest cost for a project, it does not guarantee the maximum value in terms of time and quality. More particularly, the risk exposure during the tendering process is usually very high and the success of the construction project is strongly related to managing this risk in an appropriate way. Therefore, the selection of the most appropriate contractor should be based on a set of criteria such as technical capability, financial stability, risk, safety, etc., in addition to cost in order to avoid problems that may happen after the contract is awarded. This study aims therefore to develop a decision making framework (DMF) to assist the public organizations in selecting the most appropriate construction contractor(s). The proposed DMF uses a combination of multi-criteria decision making (MCDM) tools and fuzzy logic theory and consists of three stages. In the first stage, data envelopment analysis (DEA) is used to reduce the number of contractors, based on multiple criteria, such that only efficient contractors are considered. In the second stage, the risk factors that are related to each efficient contractor are identified and assessed using a fuzzy logic based approach. Finally, in the third stage, a bi-objective mixed integer linear programming (MILP) model is developed to select the best contractor(s) based on cost and risk and to determine the optimal quantity of work to be assigned to each selected contractor. Indeed, the proposed approach considers the multiple award contract case in which more than one contractor can be selected to share the amount of work to be performed. We assume that prior to using the proposed DMF, a pre-qualification study is conducted using multiple criteria chosen by the public organization, and only pre-qualified contractors are included in the first stage of the proposed DMF. Moreover, a case study inspired from the contractor selection process in a public organization in the United Arab Emirates (UAE) is used to show the effectiveness of the proposed approach.     

Portfolio selection methodology for a nuclear project

It is difficult to evaluate complex, publicly sensitive nuclear project proposals. Scientists, subject matter experts, politicians, and citizens often differ on scope, budget, time, and quality priorities. There are numerous qualitative factors and quantitative variables. Experts could widely disagree on criteria or neglect to discriminate between seemingly identical alternatives. An ineffective portfolio selection method could lead to safety problems, budget overruns, or outright project failures. This case study develops and examines a mixed‐method, integrated qualitative and quantitative portfolio selection model, applied to a “tritium extraction facility” project concept.     

Assessment of brownfield redevelopment opportunities using a multi-tiered approach: A case in Italy

The objectives and implementation of environmental remediation and regeneration of brownfield sites have evolved over the years. Today, the intertwining of environmental, economic, and social issues related to the reuse of these sites is more apparent than in previous years; thus, the interconnectedness of these issues is now more considered in the remediation and regeneration of brownfield sites. The implications of environmental remediation and regeneration activities have broadened, leading to different and often contrasting interests among the stakeholders involved in these activities. In this study, we analyzed the role of private and public stakeholders in the remediation and regeneration of a brownfield site in Porto Marghera, Italy (Venice). We also examined the influence of the brownfield's site-specific features on its own remediation and regeneration. By adopting a multi-tiered approach, including, first, a desktop analysis and, second, in-depth interviews and a multi-criteria decision analysis, we identified factors that, if present or improved, could enhance the attractiveness of the area to developers and foster the site's redevelopment.