Facilitating Brownfield Redevelopment Projects: Evaluation, Negotiation, and Policy

A risky project evaluation technique called the fuzzy real options analysis is developed to evaluate brownfield redevelopment projects. Other decision making techniques, such as multiple criteria analysis and conflict analysis, can be incorporated into fuzzy real options analysis to facilitate negotiations on brownfield redevelopment among decision makers (DMs). The value of managerial flexibility, which is important in negotiations and policy making for brownfield redevelopment, is overlooked when the traditional evaluation method, net present value (NPV), is employed. Findings of this thesis can be used to promote brownfield redevelopment, thereby helping to eliminate environmental threats and enhance regional sustainability. A brownfield is an abandoned or underutilized property that contains, or may contain, pollutants, hazardous substances, or contaminants from previous usage, typically industrial activity. Brownfields often occur when the local economy transits from industrial to service-oriented seeking more profit. Governments actively promote brownfield redevelopment to eliminate public health threats, help economic transition, and enhance sustainability. However, developers are reluctant to participate in brownfield redevelopment because they often regard these projects as unprofitable when using classic evaluation techniques. On the other hand, case studies show that brownfield redevelopment projects can be good business opportunities for developers. An improved evaluation method is developed in order to estimate the value of a brownfield more accurately. The main reason that makes the difference between estimates and ''actual'' values lies in the failure of the deterministic project evaluation tool to price the value of uncertainty, which leads to efforts to enhance the decision making under uncertainty. Real options modelling, which extends the ability of option pricing models in real asset evaluation, is employed in risky project evaluation because of its capacity to handle uncertainties. However, brownfield redevelopment projects contain uncertain factors that have no market price, thus violating the assumption of option pricing models for which all risks have been reflected in the market. This problem, called private risk, is addressed by incorporating fuzzy numbers into real options in this thesis, which can be called fuzzy real options. Fuzzy real options are shown to generalize the original model to deal with additional kinds of uncertainties, making them more suitable for project evaluation. A numerical technique based on hybrid variables is developed to price fuzzy real options. We proposed an extension of Least Squares Monte-Carlo simulation (LSM) that produces numerical evaluations of options. A major advantage of this methodology lies in its ability to produce results regardless of whether or not an analytic solution exists. Tests show that the generalized LSM produces similar results to the analytic valuation of fuzzy real options, when this is possible. To facilitate parameter estimation for the fuzzy real options model, another numerical method is proposed to represent the likelihood of contamination of a brownfield using fuzzy boundaries. Linguistic quantifiers and ordered weighted averaging (OWA) techniques are utilized to determine the likelihood of pollution at sample locations based on multiple environmental indicators, acting as a fuzzy deduction rule to calculate the triangle membership functions of the fuzzy parameters. Risk preferences of DMs are expressed as different ''ORness'' levels of OWA operators, which affect likelihood estimates. When the fuzzy boundaries of a brownfield are generated by interpolation of sample points, the parameters of fuzzy real options, drift rate and volatility, can be calculated as fuzzy numbers. Hence, this proposed method can act as an intermediary between DMs and the fuzzy real options models, making this model much easier to apply. The values of DMs to a brownfield can be input to the graph model for conflict resolution (GMCR) to identify possible resolutions during brownfield redevelopment negotiation among all possible states, or combinations of DMs' choices. Major redevelopment policies are studied using a brownfield redevelopment case, Ralgreen Community in Kitchener, Ontario, Canada. The fuzzy preference framework and probability-based comparison method to rank fuzzy variables are employed to integrate fuzzy real options and GMCR. Insights into this conflict and general policy suggestions are provided. A potential negotiation support system (NSS) implementing these numerical methods is discussed in the context of negotiating brownfield redevelopment projects. The NSS combines the computational modules, decision support system (DSS) prototypes, and geographic information systems (GIS), and message systems. A public-private partnership (PPP) will be enhanced through information sharing, scenario generation, and conflict analysis provided by the NSS, encouraging more efficient brownfield redevelopment and leading to greater regional sustainability. The integrated usage of fuzzy real options, OWA, and GMCR takes advantage of fuzziness and randomness, making better evaluation technique available in a multiple DMs negotiation setting. Decision techniques expand their range from decision analysis, multiple criteria analysis, to a game-theoretic approach, contributing to a big picture on decision making under uncertainty. When these methods are used to study brownfield redevelopment, we found that creating better business opportunities, such as allowing land use change to raise net income, are more important in determining equilibria than remediation cost refunding. Better redevelopment policies can be proposed to aid negotiations among stakeholders

Fuzzy investment decision support for brownfield redevelopment

Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.This dissertation focuses on decision making, investing and brownfield redevelopment. Especially on the analysis, evaluation and selection of previously used real estates suitable for commercial use. The objective of this dissertation is to design a method that facilitates the decision making process with many possible alternatives and large number of relevant parameters influencing the decision. The proposed method is based on the use of fuzzy logic, modeling, statistic analysis, cluster analysis, graph theory and sophisticated methods of information collection and processing. New method allows decision makers to process much larger amount of information and evaluate possible investment alternatives efficiently.

Strategic decision modeling in Brownfield redevelopment

De ruimtelijke planning en het herstructureringsproces van bedrijventerreinen zijn onlangs aan enkele belangrijke veranderingen onderhevig geweest. Ten eerste is de omvang van de ruimtelijke herstructureringsprojecten toegenomen. Ten tweede zijn de traditionele lineaire planningsprocessen vervangen door publiek-private samenwerkingen waarbinnen de rollen en de onderlinge afhankelijkheid van ontwikkelaars en overheidsorganen gewijzigd zijn. Binnen deze nieuwe kaders is de herstructurering van brownfields veelal problematisch; er treden veel conflicten op tijdens planprocessen. In dit onderzoek wordt beargumenteerd dat het gebrek aan consensus onder betrokken stakeholders een belangrijke oorzaak is van de optredende stagnatie binnen brownfield herstructureringsprocessen. Het uiteindelijke doel van dit onderzoek is het voorspellen en analyseren van het optreden van conflicten in herstructureringsprocessen, alsmede het doen van aanbevelingen over optimale publiek-private samenwerkingsovereenkomsten voor de herstructurering van brownfields. Om dit doel te verwezenlijken is er een onderzoekskader opgesteld, welke is gericht op het specificeren en analyseren van: (1) de attributen van een brownfield; (2) de voorkeuren van de groepen van actoren; en (3) de kenmerken in het onderhandelingsproces tussen de twee groepen van actoren. Voor het verzamelen van noodzakelijke data zijn er twee online enquêtes gehouden. In beide gevallen waren de geënquêteerden experts binnen een specifieke tak van gebiedsontwikkeling. Voor dit onderzoek zijn verschillende methoden gebruikt. Ten eerste is de Fuzzy Delphi methode gebruikt om brownfield attributen te structureren en te prioriteren. Stated Choice experimenten verschaffen vervolgens het inzicht in de individuele voorkeuren van verschillende actor-groepen. Deze resulterende nutsfuncties zijn uiteindelijk gebruikt als de input voor de analyse van multi-actor besluitvorming, waarvoor de methode Game Theory is gebruikt. De resultaten van het besluitvormingsproces hangen niet alleen af van een individuele keuze maar ze bevatten ook de invloed van de keuzes van een tegenspeler. Het vinden van mogelijke consensusrijke strategieën in de onderhandelingen over de herstructurering van brownfields is het doel van deze laatste stap. Tot op heden is er weinig onderzoek verricht naar de ontwikkeling van besluitvormingsmodellen waarin systematisch de kenmerken van de brownfieldterreinen en de herstructureringsplannen verbonden wordt met het gedrag van de betrokken actoren; een dergelijke verbinding kan inzicht geven in mogelijke bronnen van conflicten. Dit onderzoek draagt bij aan de ontwikkeling van modellen waarin de interactie tussen verschillende actoren binnen een complex probleemgebied wordt geanalyseerd. De resultaten van dit onderzoek ondersteunen besluitvormers en procesmanagers bij het vinden van een optimale overeenkomst in de publiek-private onderhandelingen omtrent de herstructurering van brownfields

Decision Making of Environmental Engineers on Project Selection

Some environmental engineers do not understand how to perceive profitable opportunities in redeveloping the large number of contaminated brownfield sites in New Jersey. The purpose of this qualitative exploratory case study was to find effective decision-making strategies that help environmental engineers acquire profitable environmental redevelopment projects. The target population consisted of 4 environmental engineers in an environmental organization in Camden County, New Jersey who possessed proven decision-making strategies that helped them acquire profitable environmental redevelopment projects in the past 5 years. The conceptual framework for this study was the multiple criteria decision method (MCDM). Semistructured interviews were conducted with the engineers, and company documents were additional sources of data gathered. Triangulation and member checking were used to ensure the trustworthiness of interpretations. Five themes emerged from the analyses relating to strategies for an MCDM assessment in project management, a go/no-go assessment in project selections, education and training, ethics as an organizational value, and project management. These findings may lead to social change in Camden County, New Jersey community organizations, such as schools, daycare centers, and local businesses, which may benefit from the knowledge and safety recommendations of remediation decision making. Furthermore, these findings may provide opportunities for environment organizations to teach and train stakeholders on environmental processes while providing profitable opportunities to shareholders through sustainable practices

A critical review of decision support systems for brownfield redevelopment

Over the past two decades, many decision support systems (DSSs) have been developed to support decision makers and facilitate the planning and redevelopment process of brownfields. Existing systems are however often siloed in their approach and do not fully capture the complexity of brownfield sites from a sustainable development point of view. This critical review provides an insight into the development and implementation of DSSs, published and emerging, together with assessment of their strengths, limitations and opportunities for future integration. Brownfields DSS applications include: remediation technology selection; and land use planning; and risk assessment. The results of this review lead the authors to identify four opportunities to improve brownfield DSSs: (i) increased use of qualitative socioeconomic criteria, particularly costs and economic variables, (ii) decision-support during the early stages of brownfield redevelopment, (iii) the integration of predictive modelling methods, and (iv) improvements of user interfaces and modern web-based functionalities

Decision support system for Brownfield Site Sustainable Regeneration.

The work described in this thesis concerns the development of a Brownfield Site Sustainable Regeneration - Decision Support System (BSSR-DSS). The project aims to develop a pilot system that can provide information and alternatives for sustainable brownfield regeneration as a platform to make decisions in this context. One of the main characteristics of the BSSR-DSS is its ability to process the input data (related to site characteristics), run simulations and assess/evaluate different scenarios in order to obtain the most sustainable solution. The process input data for the BSSR-DSS relates to a wide range of sustainability indicators that have been developed in the European Project "RESCUE - Regeneration of European Sites in Cities and Urban Environments". The system involves the elaboration of methods and approaches using innovative mathematical techniques such as Artificial Neural Networks and Fuzzy Logic to analyze and evaluate the input data (site characteristics and sustainability indicators) to produce a significant output. The literature review undertaken confirmed that no current system integrating the two above mathematical techniques has been implemented to date. The system is also linked to a Geographic Information System (GIS) called MAPINFO. This allows extensive information searches to be undertaken that can be site specific, and the information displayed on a map

Safety Risk Management of LEED Building Construction : A BIM based Approach

Green buildings have been gaining popularity in the construction industry due to their low impact on the environment. Green buildings are aimed at creating energy-efficient, healthy, and environment-friendly buildings. However, OSHA records show that about 48% more accidents occur in green building construction as compared to traditional construction methods. Compromising the workers\u27 health and safety questions the true sustainability of the building. Green buildings have been a popular strategy in institutional sustainability agendas. Globally, LEED is the most popular green buildings rating system. Statistics show that an increasing number of construction projects intend to obtain the LEED certification in the next decade. However, elevated worker health and safety risks have been gradually becoming a concern while pursuing LEED credits. However, there exists a limited study comparing the safety hazards occurring in conventional construction practices and green construction practices.This research explores the major safety risks associated with LEED-certified building construction. Failure Mode Effect, Analysis (FMEA) is used to determine the safety risk associated with each LEED credit. LEED credits were ranked based on safety performance. Safety score and incremental cost of LEED credits were used to identify the optimal credit combination for LEED gold certification that reduces the safety risk and minimizes the cost. Bayesian Belief Networks (BBN) was used to analyze the impact of project factors on safety risk. This analysis identified how the risk level of LEED credits changes based on project parameters. Safety risks identified from FMEA and BBN were used to develop Building Information Modelling (BIM)-based solutions to improve worker safety. The outcomes of this research will address the challenges of LEED construction and inform the construction industry in enhancing the health and safety of construction workers with state-of-the-art technolog

Generating a New Evaluating System for Regional Scale Redevelopment Effectiveness of Brownfields in Waterloo Region Using a Multi-Criteria Analysis Mechanism

Brownfield redevelopment has been a popular topic as part of the contemporary planning literature. Encouraging brownfields’ redevelopment and improving the redevelopment effectiveness and efficiency have been two of the top concerns for planners. Redevelopments with various purposes can benefit the region in different ways. It is not necessary that redeveloping into the most common purpose would make the greatest contribution to the region. A region-wide redevelopment projects’ effectiveness evaluation will help planners have a better understanding of the region’s current situation in terms of brownfield redevelopment. This research aims to integrate a multi-criteria analysis method with brownfield redevelopment effectiveness evaluation, with the intention of suggesting improvements to brownfield redevelopment resource allocation and enlightening regional land use efficiency. During the first phase of this study, a database was generated for previously redeveloped brownfields within Waterloo Region to fill in the informational gap of region-wide redevelopment projects. During the second phase, criteria were selected that can represent redevelopments’ influences, and a multi-criteria analysis technique was used to generate a region-wide effectiveness evaluation model. The redevelopment projects in Waterloo Region have been assessed by this evaluation model. This study not only creates an information database for redeveloped brownfields in Waterloo Region, but also provides an effectiveness ranking for previous redevelopment projects and identifies the best and worst performing projects. Based on the effectiveness evaluation, the region’s performance in terms of brownfield redevelopment can also be analyzed. Waterloo Region has planning tools and policies available to provide legal and technical advice for potential developers of brownfield sites. At the same time, different levels of financial supports, such as grants and tax incentive programs, are also available in Waterloo Region. However, a lack of monitoring and evaluation of programs after redevelopments is Waterloo Region’s shortcoming. In terms of brownfield redevelopment, efficiently allocating supportive resources would be the key for the region’s next step. The region-wide brownfield repurposing activities’ effectiveness evaluation could be a start that draws attention to development of efficient brownfield redevelopment resources allocation tools in the future