THE ANALYTICAL HIERARCHY PROCESS (AHP) APPROACH

TO MODELLING CORPORATE CLIMATE CHANGE

RESPONSE

Muriel Chinoda and Jan Kruger

School of Business Leadership, University of South Africa, Pretoria, South Africa

Keywords: Climate Change Strategy, Multi-criteria Decision Making, Analytical Hierarchy Process (AHP), Climate

Change Risks, Climate Change Opportunities, Climate Change Response.

Abstract: The heightened risks and opportunities posed by climate change call for increased attention by business

executives to employ creative and rigorous methodology in generating strategic response options. Because

climate change is influenced by an assortment of multiple and interdependent variables, the search for

solutions to this complex challenge ought to be a multi-dimensional trade-off seamlessly integrated into

corporate strategy. Analytical hierarchy process (AHP)’s ability to hierarchically structure complexity into

homogeneous clusters of factors renders it as an appropriate decision support tool allowing for the

interconnectedness of climate change systems, the constraints in time, knowledge and computational

abilities that humans face. This paper presents a conceptual view of the approach, exploring key aspects of

how AHP assists in deriving a climate change model for businesses.

1 INTRODUCTION

Strategic pressures created by pushes towards

sustainable business practices, environmental

activism, threats of pledges, laws and regulations

being enacted around the world to curb greenhouse

gas emissions, and rising demands by consumers for

more environmentally friendly products and services

(Shove, 2005), mandate an input into corporate

strategic planning. The impacts, risks and

opportunities for businesses imply that CEOs can no

longer afford to pursue strategies geared towards the

single objective of shareholder wealth maximisation

(Steuer & Na, 2003). Business constraints in terms

of resources, capabilities and time, call for well-

thought-through strategies that will maximise the

opportunities for a business, while minimising the

risks, threats and vulnerabilities (Raymond &

Brown, 2011). Thus businesses have to come up

with the “best-balanced-choice” responses to climate

change. AHP lends itself well to solving such a

complex problem requiring structuring,

measurement and synthesis.

This paper is organised into five major sections.

Section 2 explores the suitability of the analytical

hierarchy process as a multi-criteria decision making

methodology for business’ response to climate

change. Section 3 describes the climate change

challenge, with particular emphasis on the risks and

opportunities it presents to businesses. In section 4

the concept of a climate change response ladder is

introduced, culminating in the formulation of the

corporate climate change response problem using

AHP. Particular emphasis is placed on the

hierarchal, progressive nature of climate change

inculcation into corporate strategy. Section 5

presents a highlight of future work and draws some

conclusions.

2 ANALYTICAL HIERARCHY

PROCESS (AHP)

First developed by Saaty (1980), AHP is a multi-

criteria decision-making methodology based on

carefully structured mathematical set of matrices and

their associated eigenvectors to compare criteria or

alternatives in a pairwise mode against some

predetermined objective (Saaty, 1980, 1994). The

ability of AHP to decompose a complex problem

into a hierarchical structure of homogeneous

clusters, coupled with its ability to capture, measure

223

Chinoda M. and Kruger J..

THE ANALYTICAL HIERARCHY PROCESS (AHP) APPROACH TO MODELLING CORPORATE CLIMATE CHANGE RESPONSE.

DOI: 10.5220/0003853802230227

In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES-2012), pages 223-227

ISBN: 978-989-8425-97-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

and synthesise individual preferences of qualitative

and quantitative attributes into ratio scale weights,

make the method appropriate in establishing climate

change response priorities and subsequently

allocating resources to chosen priorities (Hwang &

Syamsuddin, 2010).

The flexibility and simplicity of the method has

been proven in practice and validated by physical

and decision experiments (Vaidya & Kumar, 2006;

Saaty, 1994) making it useful in the private and

public sectors at strategic and operational levels in

broad areas of choice decisions (Lee & Jao-Hong,

2008), prioritisation and evaluation (Hwang &

Syamsuddin, 2010; Syamsuddin & Hwang, 2009;

Chiu, et al., 2004; Handfield, 2002), resource

allocation, benchmarking (Vaidya & Kumar, 2006),

public policy (Satty, 2008), health care and strategic

planning (Meziani & Rezvani 1990; Ossadnik, 1996;

Kurttila et al.,2000). It is against this backdrop of a

diversity of applications that AHP is proposed as the

suitable multi-criteria approach to use to quantify

and rank the possible set of initiatives and activities

that a business could employ to mitigate and adapt to

climate change risks, and capitalise on available

opportunities.

3 CLIMATE CHANGE RISKS

AND OPPORTUNITIES FOR

BUSINESSES

Climate change risks cut across almost every

industry, whether directly or indirectly (Stern, 2007).

For businesses in certain industries, energy/fuel

price fluctuations and security of supply of natural

resources are posing significant challenges and risks.

The greatest liability with respect to carbon exposure

is in carbon-intensive sectors such as oil and gas,

basic resources, utilities, heavy manufacturing, etc.,

where carbon costs could be direct, or are passed

down the value chain in the form of higher prices

(IRRC Institute).

The pricing of carbon through various market

mechanisms (such as carbon tax, cap-and-trade,

border tax adjustments, etc.), coupled with the rise

of the cost of insurance to curb the physical risks of

climate change (e.g. extreme weather patterns, rising

sea levels), is increasing the cost of doing business.

Restricted access to markets due to climate-change-

related legislation (such as the European Union

Directive on Aviation) and shifts in consumer

preferences towards greener products and services,

coupled with mounting legal and regulatory

pressures and litigation as well as increasing public

and stakeholder activism (Dietz et al., 2009) is

affecting business reputations and brand equity,

posing threats to revenue, market share and the very

existence of certain businesses.

For the agile firm, however, climate change is

ushering in opportunities to drive efficiencies and

innovations, harness new revenue streams and make

new investments, thereby enhancing reputations,

gaining market share and significant competitive

advantages. This drive towards carbon reduction,

combined with a proactive management of systemic

climate risks, is defining new levels of

environmental stewardship and business

competitiveness (Van den Berg et al., 2006). New

industries that were non-existent a decade ago have

been born and are thriving, such as cleaner

technologies in energy generation, hybrid and

electric vehicles; and sub-sectors in financial

markets such as carbon trading, brokerage services,

climate exchanges or clean-energy venture

capitalism. Long-term investors, asset managers and

analysts are also beginning to integrate climate

change considerations into investment analysis and

decision-making.

It is against this background that a framework for

companies to respond to the climate change

challenges is proposed. The next section provides a

detailed account of how the AHP methodology is

applied to design a corporate climate change

response framework.

4 CORPORATE CLIMATE

CHANGE AHP ALGORITHM

In this section, a mathematical model is formulated

for the climate change response decision problem

under conditions of three overarching conflicting

objectives: environmental, social and economic

sustainability (Raymond & Brown, 2011; Steuer &

Na, 2003).

4.1 Steps in the Application of AHP in

Climate Change Response

The underlying idea is holistic, incorporation of

climate change issues into a business, beginning

with the neophyte and progressively moving towards

full integration into corporate strategy. Herbert

Simon’s (1972) intelligence, design, choice model

for decision making is used in this study. The

intelligence gathering phase is about discussions of

the problem statement among the executive team

members of a firm and experts in order to obtain an

ICORES 2012 - 1st International Conference on Operations Research and Enterprise Systems

224

enriched and consensual view of the climate change

problem. During the design phase the executive

team discusses and agrees on the overall objectives

and criteria by which alternatives will be rated. They

will also identify the clusters; sub-clusters and a list

of alternative solutions i.e. construct the AHP

hierarchy tree. This is an iterative process because

the set of objectives is often dependent on the

alternatives being considered; conversely the list of

alternatives will likely change based on the defined

set of objectives. The choice phase is dedicated to

evaluating (using a ratio scale) how well each

alternative per cluster contributes to the firm’s

agreed objectives and finding the best combination

of alternatives to mitigate the most risks and threats

posed by climate change while simultaneously

capitalising on the opportunities presented (Porter &

Reinhadart, 2007).

It is this characteristic of AHP, i.e. the ability to

measure, synthesise, order and prioritise all the

analyses from the different stakeholders using ratio

measures (Saaty, 1994), that make the methodology

indispensible in this decision problem. AHP brings

in the subjective values and preferences of the

decision makers, while utilising their varying levels

of capabilities, expert knowledge and experiences to

bring out a quantitative result that is usable in

strategic evaluations.

Step 1: Construction of the climate change response

ladder

. The first step in the construction of the

response framework is the application of the

decomposition principle to structure the climate

change response problem into a hierarchy of

homogeneous clusters, sub-clusters and sub-sub

clusters (Saaty, 1980). The executive team discusses

and identifies possible alternatives and initiatives

which are populated onto the 4 progressive clusters:

(1) Raising Awareness, (2) Adaptation and

Operational Efficiencies, (3) New Products and

Revenue Streams and (4) Fully Integrated Climate

Change Strategy.

Depending on the company’s knowledge,

experience, industry and level of climate change

astuteness, different items will be found at each of

the four (4) ladder rungs. An example of the possible

initiatives and options is provided in Figure 1. Each

item might have sub-items, for example Employee

Awareness (A1) might have sub-items which would

be labelled as A11, A12… etc, forming a tree for

each cluster. The process is continued until the

ladder is completed, that is A1.. A

, E1-E

, P1-P

and S1-S

, including the sub-levels where desired.

Following on from Kurttila et al.’s (2000) use of

AHP for SWOT analysis, it is recommended that the

number of items on each rung not exceed 10,

because any larger will make the number of pairwise

comparisons onerous.

Step 2: Pairwise Comparisons between items on each

rung of the ladder.

The next step in the construction

of the climate change response framework is to

construct pairwise comparisons of all combinations

of alternatives in a cluster relative to the parent

cluster. Team members work individually first so

that their knowledge and expertise is applied to the

process without undue influence from peers. The

individual evaluations are then combined by taking

geometric means which act as convenient starting

points for group discussions. These pairwise

comparisons are used to derive local priorities of

alternatives in a cluster or sub-cluster. A set of

questionnaires is compiled, based on the original

Saaty Rating Scale of linguistic variables (Table 1).

Using the linguistic variable measurements to

demonstrate the effect of each alternative on

corporate objectives, decision makers are presented

with a series of pairwise comparison questions of the

format, “How important is alternative E1 relative to

alternative E3? (… based on some objective, e.g. the

risks, threats and vulnerabilities to the business, or

the strengths to capitalise on the opportunities). The

choice options are based on the 5 linguistic variables

“equally important”, “somewhat more important”,

“much more important”, “very much more

important”, or “absolutely more important”. The

sum of all the criteria beneath a given parent item on

each cluster of the ladder must equal one (1). Its

global priority shows its relative importance within

the overall ladder.

Step 3: Ranking the pairwise comparisons by

calculating the Eigenvalues.

The relative importance

of one alternative over another is computed using

eigenvectors in a matrix of the form:

A = (a

) = 

⋯

⋮⋱⋮

⋯



(1)

where in the matrix, the element a

= 1/a

and when

i = j, a

= 1. The value of w

ranges from 1 to 9 and

1/1 indicates “equally important”, while 9/1

indicates “absolutely more important”, as shown in

Table 1. If the judgments made by decision makers

are inconsistent, matrix A will yield some

inconsistencies which are generally acceptable

(Saaty, 1980, 1994). The Eigenvalue method of Eq.

2 is used to resolve the problem.

(A- λ

max

I)q=0 (2)

where λ

max

is the largest Eigenvector of the matrix

THE ANALYTICAL HIERARCHY PROCESS (AHP) APPROACH TO MODELLING CORPORATE CLIMATE

CHANGE RESPONSE

225

A; q is the correct Eigenvector (i.e. the estimation of

the relative priorities); and I is the identity matrix.

Each Eigenvector sums up to 1 to obtain the

priorities.

Step 4: Pairwise comparisons are made between the

four ladder rungs.

The last step is the synthesis of

priorities (known as hierarchic composition). The

team chooses the factors with the highest local

optima from each cluster as cluster representatives.

The four are then compared and their relative

priorities are determined using the Saaty Table and

another pairwise comparison process as in Step 2.

The production of an analytic evaluation of the

possible options within each cluster (local optima)

and the combinations to give the best overall optima

are the key advantages of using AHP.

5 CONCLUSIONS

The tree structure used to formulate an AHP

problem provides a clear, organised and logical view

of the climate response problem making it The tree

structure used to formulate an AHP problem

provides a clear, organised and logical view of the

climate response problem making it easy for

decision makers to visualise and analyse the problem

systematically at each level. The framework

proposed in this paper allows for the evaluation of

both qualitative and quantitative factors, thereby

combining sophistication and realism to solve a

practical challenge faced by businesses. While

judgments can be very subjective, ratio scale

measures of subjective importance and preferences

are essential for rational decision making and

resource allocation especially for an issue as

strategic as climate change response.

The rest of the study will focus on understanding

the rationality-irrationality dichotomy of business

executives in choosing between diverse and often

conflicting strategic options for responding to

climate change. A case study research design using

the mixed-method strategy of inquiry is employed.

By conducting a comparative case study, it will be

interesting to see the similarities and differences of

strategic choices for two companies in different

industries, in the same jurisdiction, confronting

similar macroeconomic fundamentals.

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APPENDIX:

Table 1: Saaty Linguistic Variables.

Intensity of Importance Definition Explanation

Equally important Two factors contribute equally to the objective.

Somewhat more

important

Experience and judgement slightly favours one over the other.

Much more important Experience and judgement strongly favours one over the other.

Very much more

importance

Experience and judgement very strongly favours one over the other. Its

importance is demonstrated in practice.

Absolutely more

important

The evidence favouring one over the other is of the highest possible validity.

2, 4, 6, 8

Intermediate values When compromise is needed

Figure 1: Climate Change Response Ladder.

Raising

Awareness

Employee awareness

(A1)

Understanding

GHG/CO

(A2)

CR in annual reports

(A3)

Community outreach

(NPO/NGO)(A4)

……..

Adaptation &

Operational

Efficiencies

Energy efficiency (E1)

Material efficiency (E2)

Redesigning operations

(E3)

Employee travel (E4)

Waste management

(E5)

Redundant data (E6)

……

New Products &

Revenue

Streams

Green characteristic

product marketing (P1)

Product redesign (new

revenues) (P2)

Supply chain

partnerships (e.g.

purchase local goods &

services) (P3)

Integrated Lifecycle

management (design &

production) (P4)

……..

Integrating CC

into corporate

strategy

Emissions reduction

programmes (S1)

Green technology & new

investment opportunities

(S2)

Carbon credits &

emissions trading (S3)

Investor (S4)

Promote lifelong

learning & continuous

improvement (S5)

Advocacy & industry

leadership (S6)

……….

Investment Appraisal, Project management, Change management, Leadership

THE ANALYTICAL HIERARCHY PROCESS (AHP) APPROACH TO MODELLING CORPORATE CLIMATE

CHANGE RESPONSE

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