ASTM E1765-98
(Practice)Standard Practice for Applying Analytical Hierarchy Process (AHP) to Multiattribute Decision Analysis of Investments Related to Buildings and Building Systems
Standard Practice for Applying Analytical Hierarchy Process (AHP) to Multiattribute Decision Analysis of Investments Related to Buildings and Building Systems
SCOPE
1.1 This practice presents a procedure for calculating and interpreting AHP scores of a project's total overall desirability when making building-related capital investment decisions.
1.2 In addition to monetary benefits and costs, the procedure allows for the consideration of characteristics or attributes which decision makers regard as important, but which are not readily expressed in monetary terms. Examples of such attributes that pertain to the selection of a building alternative (and its surroundings) are location/ accessibility, site security, maintainability, quality of the sound and visual environment, and image to the public and occupants.
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Standards Content (Sample)
NOTICE: This standard has either been superseded and replaced by a new version or discontinued.
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Designation: E 1765 – 98 An American National Standard
Standard Practice for
Applying Analytical Hierarchy Process (AHP) to
Multiattribute Decision Analysis of Investments Related to
Buildings and Building Systems
This standard is issued under the fixed designation E 1765; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (e) indicates an editorial change since the last revision or reapproval.
INTRODUCTION
The analytical hierarchy process (AHP) is one of a set of multi-attribute decision analysis (MADA)
methods that considers nonmonetary attributes (qualitative and quantitative) in addition to common
economic evaluation measures (such as life-cycle costing or net benefits) when evaluating project
alternatives. Building-related decisions depend in part on how competing options perform with respect
to nonmonetary attributes. This practice complements existing ASTM standards on building
economics by incorporating the existing economic/monetary measures of worth described in those
standards into a more comprehensive standard method of evaluation that includes nonmonetary
(quantitative and nonquantitative) benefits and costs. The AHP is the MADA method described in this
practice. It has three significant strengths: an efficient attribute weighting process of pairwise
comparisons; hierarchical descriptions of attributes, which keep the number of pairwise comparisons
manageable; and available software to facilitate its use.
1. Scope E 631 Terminology of Building Constructions
E 833 Terminology of Building Economics
1.1 This practice presents a procedure for calculating and
E 917 Practice for Measuring Life-Cycle Costs of Buildings
interpreting AHP scores of a project’s total overall desirability
3 and Building Systems
when making building-related capital investment decisions.
E 964 Practice for Measuring Benefit-to-Cost and Savings-
1.2 In addition to monetary benefits and costs, the procedure
to-Investment Ratios for Buildings and Building Systems
allows for the consideration of characteristics or attributes
E 1057 Practice for Measuring Internal Rate of Return and
which decision makers regard as important, but which are not
Adjusted Internal Rate of Return for Investments in Build-
readily expressed in monetary terms. Examples of such at-
ings and Building Systems
tributes that pertain to the selection of a building alternative
E 1074 Practice for Measuring Net Benefits for Investments
(and its surroundings) are location/accessibility, site security,
in Buildings and Building Systems
maintainability, quality of the sound and visual environment,
E 1121 Practice for Measuring Payback for Investments in
and image to the public and occupants.
Buildings and Building Systems
2. Referenced Documents E 1334 Practice for Rating the Serviceability of a Building
or Building-Related Facility
2.1 ASTM Standards:
E 1480 Terminology of Facility Management (Building-
Related)
E 1557 Classification for Building Elements and Related
This practice is under the jurisdiction of ASTM Committee E-6 on Performance
Sitework—UNIFORMAT II
of Buildings and is the direct responsibility of Subcommittee E06.81 on Building
Economics. E 1660 Classification for the Serviceability of an Office
Current edition approved April 10, 1998. Published August 1998. Originally
Facility for Support for Office Work
published as E 1765 – 95. Last previous edition E 1765 – 95.
2 E 1661 Classification for the Serviceability of an Office
For an extensive overview of MADA methods and a detailed treatment of how
to apply two MADA methods (one of which is AHP) to building-related decisions, Facility for Meetings and Group Effectiveness
see Norris, G. A., and Marshall, H. E., Multiattribute Decision Analysis: Recom-
E 1662 Classification for the Serviceability of an Office
mended Method for Evaluating Buildings and Building Systems, National Institute
Facility for Sound and Visual Environment
of Standards and Technology, 1995.
E 1663 Classification for the Serviceability of an Office
This practice presents a stand-alone procedure for performing an AHP analysis.
In addition, an ASTM software product for performing AHP analyses has been Facility for Typical Office Information Technology
developed to support and facilitate use of this practice. User’s Guide to AHP/Expert
Choice for ASTM Building Evaluation, MNL 29, ASTM, 1998.
Annual Book of ASTM Standards, Vol 04.11.
Copyright © ASTM, 100 Barr Harbor Drive, West Conshohocken, PA 19428-2959, United States.
NOTICE: This standard has either been superseded and replaced by a new version or discontinued.
Contact ASTM International (www.astm.org) for the latest information.
E 1765
E 1664 Classification for the Serviceability of an Office 4. Significance and Use
Facility for Layout and Building Factors
4.1 The AHP method allows you to generate a single
E 1665 Classification for the Serviceability of an Office
measure of desirability for project alternatives with respect to
Facility for Facility Protection
multiple attributes (qualitative and quantitative). By contrast,
E 1666 Classification for the Serviceability of an Office
life-cycle cost (Practice E 917), net savings (Practice E 1074),
Facility for Work Outside Normal Hours or Conditions
savings-to-investment ratio (Practice E 964), internal rate-of-
E 1667 Classification for the Serviceability of an Office
return (Practice E 1057), and payback (Practice E 1121) meth-
Facility for Image to Public and Occupants
ods all require you to put a monetary value on benefits and
E 1668 Classification for the Serviceability of an Office
costs in order to include them in a measure of project worth.
Facility for Amenities to Attract and Retain Staff
4.2 Use AHP to evaluate a finite and generally small set of
E 1669 Classification for the Serviceability of an Office
discrete and predetermined options or alternatives. Specific
Facility for Location, Access, and Wayfinding
AHP applications are ranking and choosing among alterna-
E 1670 Classification for the Serviceability of an Office
tives. For example, rank alternative building locations with
Facility for Management of Operations and Maintenance
AHP to see how they measure up to one another, or use AHP
E 1671 Classification for the Serviceability of an Office
to choose among building materials to see which is best for
Facility for Cleanliness
your application.
E 1679 Practice for Setting the Requirements for the Ser-
4.3 Use AHP if no single alternative exhibits the most
viceability of a Building or Building-Related Facility
preferred available value or performance for all attributes. This
E 1692 Classification for the Serviceability of an Office
is often the result of an underlying trade-off relationship among
Facility for Change and Churn by Occupants
attributes. An example is the trade-off between low desired
E 1693 Classification for the Serviceability of an Office
energy costs and large glass window areas (which may raise
Facility for Protection of Occupant Assets
heating and cooling costs while lowering lighting costs).
E 1694 Classification for the Serviceability of an Office
4.4 Use AHP to evaluate alternatives whose attributes are
Facility for Special Facilities and Technologies
not all measurable in the same units. Also use AHP when
E 1700 Classification for the Serviceability of an Office
performance relative to some or all of the attributes is
Facility for Structure and Building Envelope
impractical, impossible, or too costly to measure. For example,
E 1701 Classification for the Serviceability of an Office
while life-cycle costs are directly measured in monetary units,
Facility for Manageability
the number and size of offices are measured in other units, and
2.2 ASTM Adjuncts:
the public image of a building may not be practically measur-
Computer Program and User’s Guide to Building Mainte-
able in any unit. To help you choose among candidate buildings
nance, Repair, and Replacement Database for Life-Cycle
with these diverse attributes, use AHP to evaluate your
Cost Analysis, Adjunct to Practices E 917, E 964, E 1057,
alternatives.
E 1074, and E 1121.
4.5 Potential users of AHP include architects, developers,
2.3 ASTM Software Product:
owners, or lessors of buildings, real estate professionals
AHP/Expert Choice for ASTM Building Evaluation, Soft-
(commercial and residential), facility managers, building ma-
ware to Support Practice E 1765.
terial manufacturers, and agencies managing building portfo-
lios.
3. Summary of Practice
5. Procedure
3.1 This practice helps you identify a MADA application,
describe the elements that make up a MADA problem, and
5.1 To carry out a MADA analysis using AHP, follow this
recognize the three types of problems that MADA can address:
procedure:
screening alternatives, ranking alternatives, and choosing a
5.1.1 Identify the elements of your problem to confirm that
final “best” alternative.
a MADA analysis is appropriate (see 5.2),
3.2 A comprehensive list of selected attributes (monetary
5.1.2 Determine the goal or objective of the analysis, select
and nonmonetary) for evaluating building decisions provides a
the attributes on the basis of which you plan to choose an
pick list for customizing an AHP model that best fits your
alternative, arrange the attributes in a hierarchy, identify the
building-related decision. Three types of building decisions to
attribute sets in the hierarchy, identify the leaf attributes in the
which the list applies are choosing among buildings, choosing
hierarchy, and identify alternatives to consider (see 5.3),
among building components, and choosing among building
5.1.3 Construct a decision matrix summarizing available
materials. Examples of these typical building-related decisions
data on the performance of each alternative with respect to
are provided.
each leaf attribute (see 5.4),
3.3 A case illustration of a building choice decision shows
5.1.4 Compare in pairwise fashion each alternative against
how to structure a problem in a hierarchical fashion, describe
every other alternative as to how much better one is than the
the attributes of each alternative in a decision matrix, compute
other with respect to each leaf attribute (see 5.5),
attribute weights, check for consistency in pairwise compari-
5.1.5 Make pairwise comparisons, starting from the bottom
sons, and develop the final desirability scores of each alterna-
of the hierarchy, of the relative importance of each attribute in
tive.
3.4 A description of the applications and limitations of the
Paragraphs 5.1-5.4 are common to many MADA methods. Paragraphs 5.5-5.7
AHP method concludes this practice. pertain specifically to the AHP method.
NOTICE: This standard has either been superseded and replaced by a new version or discontinued.
Contact ASTM International (www.astm.org) for the latest information.
E 1765
a given set with respect to the attribute or goal immediately analyst define the “attributes” and building “alternatives” for
above that set in the hierarchy (see 5.6), and the MADA analysis.
5.3.1.3 Attributes selected for the hierarchy, displayed in
5.1.6 Compute the final overall desirability score for each
Fig. 1, are occupancy availability (within 18 months); infor-
alternative (see 5.7).
mation technology (available telecommunications and com-
5.2 Confirm that a MADA analysis is appropriate. Three
puter support infrastructure); economics (life-cycle costs of
elements are typically common to MADA problems.
alternative buildings, owned or leased); and location (how
5.2.1 MADA problems involve analysis of a finite and
convenient to capitol building). The analyst works with the
generally small set of discrete and predetermined options or
decision maker to make sure that all significant needs of the
alternatives. They do not involve the design of a “best”
decision maker are covered by the hierarchy of attributes.
alternative from among a theoretically infinite set of possible
5.3.2 Fig. 2 covers attribute sets and leaf attributes.
designs where the decision maker considers trade-offs among
5.3.2.1 A set of attributes refers to a complete group of
interacting continuous decision variables. Selecting a replace-
attributes in the hierarchy which is located under another
ment HVAC system for an existing building is a MADA
attribute or under the problem goal. There are four separate sets
problem. In contrast, the integrated design and sizing of a
of attributes in the hierarchy displayed in Fig. 2. Each set is
future building and its HVAC system is not a MADA problem.
enclosed by dashed lines.
5.2.2 In MADA problems, no single alternative is dominant,
5.3.2.2 A leaf attribute is an attribute which has no attributes
that is, no alternative exhibits the most preferred value or
below it in the hierarchy. The eleven leaf attributes present in
performance for all attributes. If one alternative is dominant, a
the hierarchy in Fig. 2 are shaded.
MADA analysis is not needed. You simply choose that alter-
5.4 Construct a decision matrix with data on the perfor-
native. The lack of a dominant alternative is often the result of
mance of each alternative with respect to each leaf attribute.
an underlying trade-off relationship among attributes. An
5.4.1 Characterize your MADA problem with a decision
example is the trade-off between proximity to the central
matrix similar to Table 1. The decision matrix indicates both
business district for convenient meetings with business clients
the set of alternatives and the set of leaf attributes being
and the desire for a suburban location that is convenient for
considered in a given problem, and it summarizes the “raw”
commuting to residential neighborhoods and relatively free of
data available to the decision maker at the start of the analysis.
street crime.
A decision matrix has a row corresponding to each alternative
being considered and a column corresponding to each leaf
5.2.3 The attributes in a MADA problem are not all mea-
attribute being considered. Each element of the matrix contains
surable in the same units. Some attributes may be either
the available information about that row’s alternative with
impractical, impossible, or too costly to measure at all. For
respect to that column’s attribute. Put quantitative data in the
example, in an office building, energy costs are measurable in
decision matrix if available; use nonquantitative data other-
life-cycle cost terms. But the architectural statement of the
wise.
building may not be practically measurable in any unit. If all
5.4.2 T
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