Application of value—focused thinking on the environmental selection of wall structures

Abstract

The decision of selecting building structures with respect to the environmental demand is an issue commonly addressed in environmental management. In this paper, the importance of considering the decision analysis technique value-focused thinking in the environmental selection of wall structures is investigated. In this context, a qualitative value model is developed in which the external and internal environmental factors are considered. The model is applied on a case study in which a decision should be made on three categories of exterior wall structures: wood, masonry and concrete. It is found that the wall structure made of wood is the most compatible option with respect to the external and internal environmental requirements of building structures.

Introduction

In most decision situations regarding the environmental management of building structures, there may appear some uncertainties about what consequences might result from any chosen alternative Moreover, there is more than one party who is interested in the consequences of a decision or in the process by which the decision is made. Such parties, whether they are individuals, groups, or organizations are referred to as stakeholders. In decision situations involving different stakeholders, the creation of alternatives on a systematic basis is of major interest. This systematic basis should be based on the values of stakeholders, since their values are the reason for their interest in the decision. Consequently, there will be a ‘specific need’ for analyzing the decision at a certain stage of the environmental assessment of buildings. Keeney (1992) investigated the general environmental decision problem; however, he did not develop a specific decision model for the environmental management of buildings. Cole, 1993, Cole, 1994 discussed the assessment of the environmental impact of buildings and derived models for auditing buildings based on understanding the problem and defining the environmental criteria required for establishing sustainable green buildings. Kohler, 1995, Kohler, 1997, Kohler et al., 1998 has considered the importance of life cycle assessment (LCA) of building materials as an essential factor in planning and designing sustainable buildings. Similar contributions were made by d'Epinay, 1997, Shiers and Howard, 1997. For the case of comparing different building materials, the Canadian Wood Council (CWC) (2002) as well as the Swedeish Institute for Wood Technology Research (Trätek) (1999) have published several studies based mainly on the results of LCA and field data. Most of these studies have focused on implementing the results of LCA as a decision tool. Such implementation, however, is not free from disadvantages that are inherent in the LCA. For instance, the different methodologies, definitions, and limitations used in the LCA will make it rather complicated and unpractical to generalize the results and the obtained decision. In addition, these studies focused mainly on the external environmental factors only such as energy and resources whereas a little attention, sometimes, is paid to the internal environmental factors, which can also be important in the final assessment.

On the other hand, the value-focused thinking (VFT) as a well-known decision tool tackles these problems and studies different environmental and even non-environmental values and makes them react with each other to produce the suitable outcome. Hassan (2003) employed the VFT as a decision technique for the environmental management of building structures. However, his model did not consider the internal environmental factors, which can be important for a complete analysis of the decision.

Cole (1999) studied the key aspects in the environmental assessment methods, particularly the green building tool (GBTool) and showed that there is a difference between the green assessment method and sustainable assessments. There is a big potential that the GBTool can enhance the results obtained from a systematic decision analysis like the VFT as it provides an insight on the criteria used in the environmental assessment of buildings.

This paper is devoted to the case of applying the VFT approach as a decision analysis tool for the environmental selection of wall structures. In this context, a qualitative value model is developed in which the results of LCA are taken into consideration. The model takes into account the internal and external environmental criteria and is applied on a case study where a decision should be made on three types of wall structures: wood, masonry and concrete.

VFT is a well-established decision technique. This technique is suitable for the decision analysis concerning problems, which occurs frequently in the field of environmental management of buildings. The feasibility of applying the VFT, in this context, comes from the fact that the environmental values of buildings represent the most important part in any environmental decision and the VFT is by definition a systematic method for studying and analyzing these values. In order to analyze the decision problem, the approach of VFT implies the quantification of objectives with a multi criteria value model, or as it is more commonly called, multi-attribute utility functions. Keeney (1992) has shown argues that VFT expands options and improves the likelihood of selecting the optimal outcome as decision-makers can use the values as a guide for alternate generation. For the reader who is not acquainted with the VFT, a brief outline is presented.

The well-known concept of utility function constitutes the main core of VFT. A multi-attribute utility function can structure complex environmental decision problems by taking into account several objectives at the same time. This can assist the decision maker to formulate goals, weight them and making them operational. The mathematical implication on the utility function is presented as follows.

Let x₁,x₂,…,x_n be attributes that have utility independent of each other u₁,u₂,…,u_n are the utility functions over x₁,x₂,…,x_n, respectively, and k₁,k₂,…,k_n are their weighting factors, where n is the corresponding number of the variable. The following equation is the basis of calculating the performance of a system provided an additive utility function, e.g. the total weighting factors are equal unity, is considered,

$$\text{u(x}{}_1\text{,x}{}_2\text{,…,x}{}_{\mathrm{n}}\text{)=k}{}_1\text{u}{}_1\text{(x}{}_1\text{)+k}{}_2\text{u}{}_2\text{(x}{}_2\text{)+···+k}{}_{\mathrm{n}}\text{u}{}_{\mathrm{n}}\text{(x}{}_{\mathrm{n}}\text{)}$$

The mathematical justification of this equation is based on the logical theory of probability and it is fully derived and proved, see for example Fishburn (1970). It is worth noting that the value of utility of a criterion ranges between zero and one, e.g. if an option in the decision table possesses the highest score of a desired criterion then its utility will be assigned one, otherwise when another option possesses the lowest score of the same criterion, its utility will be zero.

Decision table is a matrix that comprises the recognized options (decision alternative) and the criteria stated in the value model for the objective hierarchy, as will be discussed later on. The decision-maker then will have to score each criterion for each option according to a defined scale and calculate the utility values; the scores are the resulting values of the criteria when a decision is implemented. The weights (usually totalling 100%) express the importance of the criteria and reflect the decision-maker's subjective values (preferences). This does not mean that all values are weighted equally, just that each is used to evaluate options. Consequently, the decision can be established with view of the calculated performance using Eq. (1). The decision analysis steps and choosing a set of criteria are further detailed in Keeney (1992).

The risk analysis provides the decision-maker with a systematic insight on the potential consequences of the decision as well as it controls the likelihood of obtaining the right decision.

The general shape of the utility function is totally determined by the risk attitude. Classes of risk-averse, risk-neutral and risk seeking utility functions, see Raiffa, 1968, Keeney, 1992:

$$\text{u(x)=a+b(−e}{}^{\mathrm{-cx}}\text{),}$$

$$\text{u(x)=a+b(cx),}$$

$$\text{u(x)=a+b(e}{}^{\mathrm{cx}}\text{),}$$

respectively, where a and b are constants to insure that u is scaled from zero to one and c is positive for increasing utility function and negative for decreasing ones The parameter c is computed when the certainty equivalent of 50/50 lottery is known by using a recursive algorithm; for the linear case, the parameter c indicates the degree of the assessee's risk aversion. And can be set to +1 or −1 for the increasing and decreasing cases, respectively.

For the decision problems of environmental management of buildings, the scenarios of risk analysis are suggested to be worked out into four different ways as follow:

• Applying the risk attitudes on one important (actual) criterion and compare the final results of performances with each other.

• Applying the risk attitudes on all the criteria under concern and compare results.

• Applying risk attitudes with different subjective middle value (SMV) for different criteria under study. The SMV is defined here as the value between the worst and best performance of a criterion according to the risk attitude. For risk neutral, risk averse and risk seeking attitudes, it lies in the middle, near the worst, and near the best, respectively.

• A combination of the points (a), (b) and (c) above.