Project Management Institute

Attitude-based strategic negotiation for conflict management in construction projects

Keith W. Hipel, University of Waterloo, Waterloo, Ontario, Canada

Tarek Hegazy, University of Waterloo, Waterloo, Ontario, Canada

Abstract

An innovative negotiation methodology for managing conflicts in construction projects is presented in this paper where multiple decision makers are involved. The proposed negotiation methodology has a unique ability to consider the attitudes of the decision makers, which is an important psychological factor in the negotiations that take place in various stages of a construction project. The methodology is developed at the strategic level of decision making in which the graph model for conflict resolution (GMCR) is employed in assisting decision makers, such as project managers, to achieve the best strategic decision, given the competing interests and attitudes of the decision makers. A real-life case study is used to illustrate how the proposed methodology can be conveniently applied in practice and to demonstrate the importance and the benefits of incorporating the attitudes of multiple decision makers into the negotiation process in order to better identify the most feasible resolutions. The proposed negotiation methodology has been implemented in a negotiation decision support system that assists project managers in tackling real-world controversies, particularly in complex disputes that occur in construction projects.

Keywords: Construction projects, attitudes, negotiation, strategic decision, conflict management

Introduction

The construction industry is one of the largest industries in the world, with members who are expert in planning, design, construction, operation, and administration. Construction projects have become increasingly complex, where the parties involved often have conflicting objectives. For example, the owner would like a project to be inexpensive and completed quickly, while the contractor wants large and income-generating projects with few time restrictions.

In the highly competitive multi-party environment of construction, disputes can arise for many reasons, such as the complexity and magnitude of the work, the lack of coordination among the contracting parties, poorly prepared and/or executed contract documents, inadequate planning, financial issues, and disagreements about the methods of resolving on-the-spot, site-related problems. Any one of these factors can derail a project and lead to complicated litigation or arbitration, increased costs, and a breakdown in the communication and relationships among parties (Harmon, 2003). Therefore, the successful delivery of a project requires their full collaboration so that the time, costs, resources, and objectives of a project can be coordinated.

Among many alternative dispute resolution tactics, such as negotiation and mediation, negotiation has gained popularity as a method to remedy the shortcomings of litigation. Not only are the costs and times of court claims avoided, but also the involved parties have more control over the negotiation outcomes in a less hostile environment.

Although negotiation has been a daily routine for construction project managers, it is the subject of little research or education (Dudziak and Hendrickson, 1988). Construction project managers seem to learn negotiating skills only through experience and observation (Smith, 1992). Therefore, practical negotiation methodologies and support tools may be useful for the construction industry in enabling project managers to handle negotiations more productively.

The goal of this research is to present an attitude-based negotiation methodology for managing complex conflicts in construction projects. In other words, the primary objective is to investigate how the attitudes of multiple decision makers (e.g., project managers) can influence the outcome of construction negotiations. To achieve this goal, the graph model for conflict resolution technique is used to model the interactive decision-making at the strategic level. This technique has been extensively explained by Hipel, Hegazy, and Yousefi, (2009); Fraser and Hipel, (1984); Hipel (2009a); and Hipel (2009b). Also, the use of the graph model technique in the construction industry has been explained by Yousefi, Hipel, and Hegazy (2008), and Kassab, Hipel, and Hegazy (2006).

This article is organized as follows: Section 2 presents the development of the negotiation methodology using GMCR; followed by Section 3 which provides discussions about the resulting negotiation outcomes. Finally, the proposed negotiation decision support system (NDSS) is presented in Section 4.

Development of the Negotiation Methodology

A case study is used to develop the negotiation methodology and demonstrate its advantages. The case study is a real-life brownfield redevelopment site located in Ontario, Canada. According to the definition of a brownfield site, the land (soil) is heavily contaminated and should be treated either by replacing the contaminated soil or by decontaminating the existing soil. The site in the case study had been heavily contaminated for a long period of time extending from 1919 to 2000, and complex disputes arose among the decision makers (i.e., project managers) due to the enormous remediation costs, responsibilities, risks, and uncertainties involved with brownfield redevelopment. More information about brownfield projects is provided by De Sousa (2001) and Yousefi, Hipel, Hegazy, Witmer, and Gray (2007). The involved project managers decided to conduct negotiations over time to avoid complicating the conflict further and to find the most beneficial decision at the strategic level. In order to model the project managers' negotiations and conflict resolution processes, GMCR is applied using the following stages:

Stage A: Identifying the Project Manager's and Options

Three main project managers' were identified for this real-life brownfield negotiation: (1) PO: a privately owned company that was the previous owner of the site; (2) CY: a government representative; and (3) UW: a publicly owned educational institute. The names and some details have been changed to provide complete anonymity since this study represents the authors' interpretations of the events. The involved project managers and their options are listed in Table 1. Basically, PO had two options: remediating the brownfield site slowly and remediating the site quickly. CY also has two options: providing incentives (e.g., financial assistance) for PO and UW; and taking legal action against PO. Finally, the UW's only option was to either construct a school of pharmacy in the decontaminated site or not.

Table 1: The feasible states, the project managers, their options, and preferences for the case study negotiations

Project Manager Options 18 Feasible States
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
PO 1) Slow Remediation Y Y Y Y Y Y Y Y N N N N N N N N N N
2) Fast Remediation N N N N N N N N Y Y Y Y N N N N N N
CY 3) Incentives Y N Y Y N N Y N Y N Y N Y Y Y N N Y
4) Legal Action Y N N N Y N Y Y N N N N Y Y N Y Y N
UW 5) Construction Y N Y N Y Y N N Y Y N N Y N N N Y Y
PO's Preference among States Most Preferred: 2, 3, 5, 1, 8, 10, 9, 11, 17, 14, 0, 6, 4, 7, 12, 13, 16, 15: Least Preferred
CY's Preference among States Most Preferred: 9, 8, 11, 10, 17, 14, 12, 13, 16, 15, 5, 2, 0, 4, 7, 1, 6, 3: Least Preferred
UW's Preference among States Most Preferred: 8, 17, 10, 9, 11, 12, 14, 16, 15, 13, 2, 0, 4, 5, 7, 6, 1, 3: Least Preferred

N: No (reject); Y: Yes (accept)

Stage B: Obtaining Feasible States

Each project manager can either accept (Y) or reject (N) any of its options, and since there are totally five options, the total number of decision states is 25 = 32. However, some states are infeasible and can be removed, as explained by Fraser and Hipel (1984). Once the infeasible states are removed, the remaining feasible states are labeled and listed as shown in Table 1 in which each column represents a state for which Y means “yes” and N indicates “no.”

Stage C: Ranking the Feasible States

Based on a specific project manager's preferences, the feasible states are ranked for that project manager from the most preferred state on the left to the least preferred state on the right as shown in Table 1 where ties are allowed. For example, CY most prefers state 9, in which PO completes remediation without delays and finishes the site remediation as quickly as possible, CY neither provides incentives nor takes the case to court, and finally UW constructs a school of pharmacy on the decontaminated site. Also, CY least prefers state 3 which means that PO remediates the site slowly in spite of receiving the CY's incentives and UW does not construct a school of pharmacy on the site.

Stage D: Developing the Graph Model and Reachable List

When a project manager is in a certain decision state, it is permissible to change one's mind about the same options to reach other states. The set of these achievable states is called the reachable list. In other words, the reachable list for each project manager in a certain decision state is the set of states that the particular project manager can change his or her strategies to achieve, while the strategies of all the other project managers remain fixed (Fraser and Hipel, 1984). The reachable lists for the case study are displayed in Figure 1(b). The reachable lists can be used to develop the graph model representation for the project managers. The PO's graph model, for example, is shown in Figure 1(a), representing the moves among three states 2, 8, and 17. The circles represent the states and the arrows represent the moves among the states. In order to comply with the project managers' actual moves and countermoves that take place in the case study, irreversible moves for the project managers are considered in developing the graph model. An irreversible move is a move in which a project manager can move from state a to state b but cannot move back from state b to state a (Fang, Hipel, and Kilgour, 1993). As shown in Figure 1(a), for example, PO has no move from state 2 and this situation is shown by two single-head arrows as irreversible moves to state 2. PO has however two moves from state 17 to states 2 and 8.

The relationship between the graph model and reachable list

Figure 1: The relationship between the graph model and reachable list

Stage E: Representing Attitude

This research represents a major expansion of GMCR: Combining attitudes within the paradigm of GMCR furnishes a flexible analytical tool which reflects how the project managers' attitudes may change the strategic outcomes of a negotiation. Attitude was initially defined by Inohara, Hipel, and Walker (2007) and is expanded and represented in this research in a matrix format or so-called attitude case. Table 2 shows an attitude case which represents the attitudes among three project managers: i, j, and k; where each cell entry in the table can take on a value of +, 0, or – to represent a positive, neutral, or negative attitude, respectively. As an example shown in Table 2, the project managers i, j, and k have positive attitudes (+) towards themselves since eii = + and ejj = +, ekk = + and have neutral attitudes towards one another (e.g., eij = 0, eji = 0, eik = 0); where: e represents attitude and eij, for example, represents the attitude of project manager i towards project manager j.

Table 2: One attitude case

Project Manager i j k
i + 0 0
j 0 + 0
k 0 0 +

Stage F: Determining the Most Relevant Attitude Cases

The project managers' attitudes shown in Table 2 represent one possible attitude case. With respect to the case study negotiations having three project managers involved, an attitude case is a 3 × 3 matrix in which each cell of the matrix can be +, –, or 0, representing positive, negative, or neutral attitudes of the project managers, respectively. Therefore, the total number of the attitudes of the project managers towards themselves and one another becomes 39, in which 3 represents the three types of attitude and 9 represents the number of cells in a 3 × 3 matrix. The total number of attitudes cases thus equals 39 = 19,683. However, many of these attitude cases are infeasible and can be removed. The process of removing infeasible attitude cases is explained by Yousefi (2009). Upon eliminating the infeasible attitude cases, the most relevant feasible attitude cases are determined with respect to the case study negotiation. Figure 2 displays the four most relevant attitude cases identified according to the background of this real-life negotiation.

Four identified attitude cases for the case study negotiations

Figure 2: Four identified attitude cases for the case study negotiations

Stage G: Performing Attitude-Based Stability Analysis

The interactive decision-making analysis, defined within the structure of GMCR, can be carried out, and the attitude-based solution concepts defined in Table 3 can be applied to the conflict in order to obtain equilibrium states or possible solutions for the conflict with respect to each of the four attitude cases. The attitude-based stability analysis is carried out using a tableau which facilitates the systematic modeling and analysis of the moves and countermoves by the project managers to reach possible resolution for the conflict being analyzed. Figure 3 displays a tableau which is used to carry out the attitude-based stability analysis for attitude case 3, for example, represented in Figure 2. More details about the stability analysis tableau are provided by Fraser and Hipel (1984). It should be noted that the tableau used in the conventional GMCR was expanded to include the attitude-based stability analysis.

Table 3: Solution concepts for conflict resolution

Solution Concepts Descriptions
Nash Stability (NASH) Moving to a different state brings no benefit to the project manager.
General Metarationality (GMR) Moving to a more preferred state may trigger an opponent's countermove with less benefit to the focal project manager, even if the countermove is less preferred for the opponent.
Symmetric Metarationality (SMR) Moving to a more preferred state may trigger an opponent's countermove to harm the project manager, even if the countermove is self-harmful to the opponent. The focal project manager has the chance to counter-respond.
Sequential Stability (SEQ) Moving to a more preferred state may trigger an opponent's countermove to improve the opponent's positions where self-harmful countermoves are not considered.
Limited move stability (Lh) The project manager acts optimally within a defined number of action/countermove cycles (h state transitions).
Non-myopic Stability (NM) Same as limited move stability but for infinite state transitions.
Stability tableau for attitude case 3

Figure 3: Stability tableau for attitude case 3

As shown in Figure 3, the tableau consists of the attitude case, each project manager's state ranking, project managers' moves from one state to another adjacent state, stability types, and equilibrium results in an organized format. The attitude-based stability analysis helps by achieving two objectives: (1) determining the project manager's possible moves from each state in the project manager's state ranking according to the project manager's attitude; and (2) determining the stability of each state for each project manager using the solution concepts defined in Table 3. The achievement of the two objectives is discussed in the following paragraphs.

In order to determine the project manager's possible moves from each state, below a given state in the project manager's state ranking, the possible moves of the project managers are determined according to the attitudes shown above the tableau in Figure 3. For example, the possible moves from state 12, circled in Figure 3, are determined for the project managers. According to the reachable list of PO in Figure 1(b), PO has possible unilateral moves from state 12 to state 0. To determine whether PO can use its only possible move or not, the PO's attitude towards itself, CY, and UW is concurrently considered. PO's moves from state 12 should benefit itself (because PO has a positive attitude towards itself), at the same time, lower CY's position (because PO has a negative attitude towards CY), and improve UW position (because PO has a positive attitude toward UW). If PO moves from state 12 to state 0, although PO's position is improved and CY's position is lowered, moving from state 12 to state 0 will also lower UW's position within its own state ranking. Thus, this move contradicts PO's attitude toward UW and as a result, PO cannot use its possible move and state 0, below state 12, is crossed as shown in Figure 3.

With respect to UW's possible moves from state 12 circled in Figure 3, UW's attitude towards itself, PO, and CY should be concurrently considered. Because UW has a negative attitude towards PO and CY, and a positive attitude towards itself in this attitude case, UW only considers the possible moves that improve its own position and lower the other project managers' position. As shown in the UW's state ranking in Figure 3, UW has no possible move from state 12.

With respect to the CY's possible moves from state 12, CY has a positive attitude toward itself and a neutral attitude toward the other project managers. Therefore, CY's possible moves should only benefit itself. Among two possible moves (i.e., 16 and 17) from state 12, CY has a possible move only to state 17, which is more preferred to state 12.

In order to determine the stability of each state for each project manager, the two solution concepts defined in Table 3 are used: attitude-based Nash (RNASH) and attitude-based sequentially sanctioned (RSEQ). In both stabilities, self-harmful moves and countermoves are not considered and thus, the two solution concepts are more suitable for this case study. The stability of state 12, for example, is assessed for the project managers.

According to the definition of Nash stability (Table 3), state 12 is Nash stable for UW because UW has no unilateral move from state 12, and “RNASH” is marked below state 12 in the UW's state ranking. Assessing the stability of 12 for PO, it can be seen that PO has also no move from state 12 and a “RNASH” is marked below state 12 in the PO's state ranking (Figure 3). The stability of state 12 for CY is now assessed. If CY moves from state 12 to state 17, PO and UW cannot countermove because PO and UW have no move from state 17. Thus, CY can unilaterally move from state 12 to state 17 and as a result, state 12 is unstable for CY and a “u” is marked below state 12 in the CY's state ranking. It should be mentioned that the same procedure is carried out to determine the stability of all the remaining states for each of the project managers (Figure 3).

Discussion of the Results

The attitude-based stability analysis carried out for attitude case 3 has also been executed for the remaining three attitude cases and the results are summarized in Table 4. As shown, because of the changes in the attitudes of the project managers, four different sets of equilibrium states were obtained, corresponding to the four different attitude cases. The equilibrium states involved in each attitude case represent possible strategic solutions for the multilateral negotiations. The four sets of resulting outcomes are now evaluated in the following paragraphs in order to determine the best strategic decision.

Table 4: Stability analyses results

Attitude Case Resulting Equilibrium States (Possible Negotiation Outcomes)
1 10, 11
2 0, 1, 3, 4, 6, 7
3 7, 9, 11, 14, 17
4 2, 8, 9

Attitude Case 1

Figure 2 displays a scenario in which the project managers have positive attitudes towards themselves and neutral attitudes towards other project managers. The stability analysis was carried out, and outcomes (i.e., equilibrium states) 10 and 11 resulted for this case. Outcome 10 is more preferred to outcome 11 for PO and UW. Also, outcome 11 is more preferred to outcome 10 for CY. Outcome 10 means that PO quickly cleans up the property, UW refuses to construct a school of pharmacy on the decontaminated site, and CY does not take legal action against PO and provides incentives for both PO and UW. Outcome 11 means that PO cleans up the land quickly, CY neither takes legal action nor provides incentives, and UW does not construct a school of pharmacy on the site. It should be mentioned that the meaning of the feasible states can be interpreted using Table 1.

Attitude Case 2

This case represents the most hostile attitude scenario in which the project managers have negative attitudes towards the other project managers. The resulting outcomes include 0, 1, 3, 4, 6, and 7, which are the least preferred outcomes in comparison with the outcomes of the attitude case 1. In other words, considering the project managers' state rankings, the resulting outcomes have been shifted substantially to the right side of the state ranking for each project manager. For example, outcome 3 is the least preferred state in the state rankings of CY and UW (Table 1). Moreover, outcomes 0, 4, 6, and 7 include a situation in which CY takes legal action, the least preferred action for all of the project managers. It can be concluded that when the project managers involved in the strategic negotiations possess a negative attitude towards one another, the resulting outcomes represent the least beneficial decisions for the project managers.

Attitude Case 3

The stability analysis for this case has been carried out in the previous section and the results were discussed and shown in Figure 3. This attitude case represents a situation in which the attitudes of the project managers towards one another are not reciprocal. For example, PO has a negative attitude towards CY; whereas CY has a neutral attitude towards PO, as shown in Figure 3. In addition, when UW has a negative attitude towards the others, PO and CY have positive and neutral attitudes towards UW, respectively. The resulting set of possible solutions for Case 3 consists of outcomes 7, 9, 11, 14, and 17. According to the project managers' state rankings, some of the outcomes are less preferred and some are more preferred so that no single outcome is the most beneficial for all project managers. It can be concluded from this attitude case that due to the inconsistency in the attitudes of the project managers towards one another, a less coherent set of outcomes is obtained, and as a result, some outcomes are shifted to the left side (more preferred) and some outcomes are shifted to the right (less preferred) of the project managers' state rankings. In this case, it is very hard for an analyst (e.g., a mediator) to provide a single mutually beneficial solution for the project managers involved in the negotiations.

Attitude Case 4

This represents the most cooperative attitude scenario in which the project managers have a positive attitude towards the other project managers. The stability analysis for case 5 results in a set of outcomes 2, 8, and 9. This set is shifted to the far left side of the project managers' state rankings and is therefore more preferred by the project managers. Outcome 8, for example, is the most preferred outcome for UW, the second most preferred outcome for CY, and the fifth most preferred outcome for PO. As defined in Table 1, outcome 8 means that PO cleans up the land fast, CY does not take legal action against PO and provides incentives for PO and UW, and UW constructs a school of pharmacy on the decontaminated site. It can be concluded that, in multilateral brownfield negotiations, when the project managers possess positive attitudes towards one another, more beneficial outcomes result and the project managers have a better opportunity to agree on one outcome at the strategic level and then continue with detailed negotiations at the tactical level.

The Best Strategic Decision

The previous discussion indicates that the analysis of different attitude cases results in different negotiation outcomes. Therefore, the attitudes of the project managers can significantly influence the final outcomes of the strategic negotiations. Furthermore, the results of stability analyses for the previously mentioned attitude cases indicate that the resulting outcomes in attitude case 4 are more hostile for all project managers and may therefore be less preferred. On the other hand, the resulting outcomes in attitude case 5 are more beneficial for the project managers and may therefore be more preferred.

The overall result indicates that the equilibrium state 8 has the highest preference among the project managers involved and, therefore, equilibrium state 8 is suggested to the involved project managers as the most beneficial decision option at the strategic level for the real-life brownfield negotiation. Equilibrium state 8 represents a situation in which PO looks after remediating the land quickly, CY does not take legal action and provides incentives for PO and UW, and UW constructs a school of pharmacy on the decontaminated site. This strategic outcome was mutually agreed upon by the project managers involved in the actual case study negotiations.

Negotiation Decision Support System

The strategic negotiation methodology developed in the previous sections has been implemented into a negotiation decision support system (NDSS) as a working prototype that can provide project managers with automated, speedy, and more accurate decision results. The NDSS was implemented with the use of a spreadsheet program. Figure 4 shows the main screen of the proposed NDSS.

The NDSS main menu screen

Figure 4: The NDSS main menu screen

The proposed NDSS has been basically developed as a workbook that contains several worksheets, including a main screen with a simple interface as shown in Figure 4. The appropriate buttons have been designed for the interface in order to activate the step-by-step procedures which are similar to the stages explained in Section 2.

The interface automates all of the computations involved in the NDSS and allows the user (e.g., a project manager) to interact with the prototype, to enter the appropriate input data, to navigate through the worksheets, and finally, to obtain the best strategic decision quickly and accurately. The proposed NDSS conveniently takes the attitudes of the project managers into account and provides project managers with attitude-based negotiation outcomes. The NDSS also has a potential capability of further development to incorporate a tactical negotiation methodology into the strategic negotiation methodology presented in this paper.

Conclusions

An attitude-based negotiation methodology is presented for employment in multilateral negotiations, particularly for those taken place in construction projects. The graph model for conflict resolution (GMCR), as a flexible analytical technique, was used to develop the negotiation methodology at the strategic level. To demonstrate the advantages of the proposed methodology, a real-life negotiation case study was used and the resulting negotiation outcomes corresponding to the various attitude scenarios were discussed. Subsequently, the most beneficial strategic decision was proposed to the project managers involved in the real-life negotiation case study. Once the negotiation methodology was developed, a negotiation decision support system was designed by implementing the proposed methodology into the system.

The simplified negotiation decision support system can provide construction project managers with the negotiation results when attitudes are taken into account. The proposed negotiation system may improve conventional negotiation systems by proposing better negotiation outcomes. Therefore, the importance of this research lies in proposing a strategic negotiation support that helps construction project managers involved in complex negotiations determine which attitudes are needed in order to guide the negotiations to more preferable outcomes and prevent attitudes that can result in unwanted consequences for all participants concerned.

References

De Sousa, C. (2001). Contaminated sites: The Canadian situation in an international context. Journal of Environmental Management, 62, 131–154.

Dudziak, W., and Hendrickson, C. (1988). Simulation game for contract negotiations. Journal of Management in Engineering, 4(2), 113–121.

Fang, L., Hipel, K. W., and Kilgour, D. M. (1993). Interactive Decision Making: The Graph Model for Conflict Resolution, New York: Wiley.

Fraser, N. M., and Hipel, K. W. (1984). Conflict analysis: models and resolutions, New York: North Holland.

Harmon, K. M. J. (2003). Resolution of construction disputes: a review of current methodologies. Leadership Management Engineering, 3(4), 187–201.

Hipel, K. W. (Eds). (2009a). Conflict resolution, Vol. 1. Oxford: Eolss, United Kingdom.

Hipel, K. W. (Eds). (2009b). Conflict resolution, Vol. 2, Oxford: Eolss, United Kingdom.

Hipel, K. W., Hegazy, T., and Yousefi, S. (2009). Combined strategic and tactical negotiation methodology for resolving complex brownfield conflicts. Accepted for publication in the Brazilian Journal of Operational Research, Special Issue of Pesquisa Operational on Soft OR and Complex Societal Problems, Accepted for Publication on February 28th 2010.

Inohara, T., Hipel, K. W., and Walker, S. (2007). Conflict analysis approaches for investigating attitudes and misperceptions in the war of 1812. Journal of Systems Science and Systems Engineering, 16(2), 1–21.

Kassab, M., Hipel, K. W., and Hegazy, T. (2006). Conflict resolution in construction disputes using the graph model. Journal of Construction Engineering and Management, 132(10), 1043–1052.

Smith, M. L. (1992). Planning your negotiation. Journal of Management in Engineering, 8(3), 254–260.

Yousefi, S. (2009), Attitude-based strategic and tactical negotiations for conflict resolution in construction, PhD Dissertation, Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, Ontario, Canada.

Yousefi, S., Hipel, K. W., and Hegazy, T. (2008). An attitude-based negotiation methodology for the management of construction disputes. Accepted for publication in the American Society for Civil Engineering (ASCE) Journal of Management in Engineering. Accepted for publication on March 20, 2009.

Yousefi, S., Hipel, K. W., Hegazy, T., Witmer, J. A., and Gray, P. (2007). Negotiation characteristics in brownfield redevelopment projects. Invited paper published in the special session on Conflict and Risk Analysis in Systems Management in the Proceedings of the 2007 IEEE International Conference on Systems, Man, and Cybernetics, held in The Delta Centre-Ville, Montreal, Quebec, Canada, October 7-10, 2007, pp 1866–1871.

BIOS:

Saied Yousefi, has more than 16 years of working experience, educational background, and academic studies in the construction industry. He is currently a postdoctoral fellow at the University of Waterloo where he received his PhD in decision-making management from the Department of Systems Design Engineering in 2009. He also received his MASc in construction project management from the Department of Civil Engineering at the University of Waterloo in 2004. Before pursuing his postgraduate studies in Canada, Dr. Yousefi worked as a project engineer for seven years (1994 – 2001) at the site of the Karun 3 project in Iran, one of the most complicated dams and hydroelectric underground powerhouses in the world. His valuable site experience motivated him to continue his education in the area of “forensic project management for heavy construction projects.”

Keith W. Hipel, is University Professor of Systems Design Engineering and Coordinator of the Conflict Analysis Group at the University of Waterloo in Canada. He is Senior Fellow at the Centre for International Governance Innovation and former Vice President of the Canadian Academy of Sciences. His major research interests are the development of conflict resolution, multiple objective decision making and time series analysis techniques from a systems thinking perspective with applications in water resources management, hydrology, environmental engineering and sustainable development. Dr. Hipel has received widespread recognition for his interdisciplinary research in systems engineering via Fellow designations from IEEE, Royal Society of Canada, International Council on Systems Engineering, Canadian Academy of Engineering, Engineering Institute of Canada, and American Water Resources Association. He is the recipient of the Norbert Wiener Award from the IEEE Systems, Man, and Cybernetics Society and Docteur Honoris Causa from École Centrale de Lille in France.

Tarek Hegazy, is Professor of Construction Management at the University of Waterloo. His research focuses on Computational project management and infrastructure asset management. Dr. Hegazy is the sole author of the textbook “Computer-Based Construction Project Management” published by prentice Hall in 2002, in addition to over 150 technical publications. In 2004, Dr. Hegazy has been acknowledged as one of the world's top five contributing authors to ASCE construction research. He has consulted and advised a number of contractors and government organizations in Canada and collaborates with many universities worldwide.

This material has been reproduced with the permission of the copyright owner. Unauthorized reproduction of this material is strictly prohibited. For permission to reproduce this material, please contact PMI or any listed author.

© 2010 Project Management Institute

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