«Investment scenarios and regional factors in
the solar energy sector»
Dr. Nikolaos Apostolopoulos
The Macrojournals /MacroTrends Conference: New
York 2015
December 28-29th, 2015
Research purpose
• The present research concentrates on the regional
factors that determine entrepreneurship on the sector of
renewable energy resources, and more precisely, on
solar energy.
• The study amalgamates qualitative and quantitative data
in order to develop a framework that merges regional
factors and renewable energy entrepreneurship by
applying AHP. The aim is to rank regions in terms of
entrepreneurship in the field of competitiveness. In order
to attain this goal, regional macroeconomic, energy and
environmental data are integrated.
Locality matters
• Despite the fact that environmental change is examined at supra
national level, its effect is chiefly regional or local, and that is why
regions are challenged to perform an essential role (Galarraga et al,
2011).
• Nijkamp (2011) mentions that transnational forums and panels
cannot provide convincing solutions and directions; therefore,
sustainable regions and cities are now at the epicenter.
• The noteworthy part of territorial influence is stressed in numerous
inquiries as its upgraded part can conduce to the intricating issue of
the interrelatedness between ecological and economic procedures
(Quaas et al., 2007, Salvati and Zitti, 2008).
• Regions, and especially the rural ones, can attract investments on
renewable energy enterprises by exploiting their comparative
advantages (OECD, 2012).
3. Regional factors, investment attractiveness and solar energy
entrepreneurship: An Analytic Hierarchy Process approach.
 Banks (Haghighi et al., 2010; Seçme et al., 2009)
 Business (Schniederjans and Garvin, 1997; Saaty et al., 2003;
Kearns, 2004)
 Strategy selection (Chen and Wang, 2010; Li and Li, 2009; Limam
et al 2009; Wu and al., 2009)
 Supplier selection (Labib, 2011; Wang and al Wu, 2010; Wang and
Yang, 2009)
 Firms competence evaluation (Amiri et al., 2009)
 Marketing (Radasch and Kwak, 1998; Kwak et al., 2005)
 Environment (Malczewski et al., 1997; Kurttila et al., 2000;
Masozera et al., 2006)
 Sustainability evaluation (Su at al., 2010)
 Energy selection (Kahraman and Kaya, 2010)
AHP methodology
• 1. Decomposition, solving a complex problem into
simpler elements, and then create a hierarchy of goals,
criteria and alternatives.
• 2. Comparative Judgment, assessing the relative
importance of the two pairs of elements.
• 3. Synthesis of Priority is the selection of priority based
on pairwise comparisons
• 4. Consistency test, tests consistency for each
comparison matrix.
Decomposition
Comparative Judgment
The Saaty Rating Scale
Intensity of
importance
Definition
Explanation
1
Equal importance Two factors contribute equally to the objective
3
Somewhat more
important
Experience and judgment slightly favor one over
the other
5
Much more
important
Experience and judgment strongly favor one
over the other
7
Very much more
important
Experience and judgment very strongly favor
one over the other. Its importance is
demonstrated in practice.
9
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
Synthesis of Priority
• Assuming n elements of a hierarchy C1,…Cn, the purpose is to estimate
the relative weight of Ci with respect to Cj. The aij symbolizes the
number that represents the comparison of Ci with Cj. All the aij compose
a square matrix A=(aij) of order n. When the matrix holds that aij = 1/aji,
for i ≠ j, and aii = 1, then this matrix has the reciprocity characteristic.
• Suppose A is a consistency matrix, weights Wi and judgments aij create
a relation of the form: Wi/Wj= aij (for i, j= 1,2…..n)
• In order the judgments to be consistent and hold the exact values of
wi/wj, the vector w should satisfy the:
Aw= λmaxw for λmax ≥ n, Where λmax is the largest or principal
eigenvalue.
Synthesis of priorities
• When all paired comparisons of the elements are applied, the vector
of priorities, w=[w1,w2, . . . ,wn], can be estimated through the
eigenvector calculation. There are many ways to get an
approximation of the eigenvector. One way to obtain a solution is:
• 1st step: square the matrix or raise it to a power
• 2nd step: sum the rows
• 3rd step: normalize to obtain the vector
• The aforementioned process stops when the elements of the vector
w=(w1,w2…,wn) have no or small difference between the nth power
and the (n+1) power.
Consistency test
• After calculating the eigenvector, we must obtain the eigenvalue
λmax in order to estimate the consistency.
• According to Saaty (1990) the λmax is calculated if we multiply the
priority vector with the summing result of each column of the
matrix. λmax should be λmax ≥ n. Any price of λmax less than n
means that we have made an unacceptable estimation.
• The measurement of the inconsistency is calculated through the
consistency index:
• CI=(λmax-n)/(n-1)
Consistency test
In order to calculate the consistency ratio, we compare the CI with the
appropriate number from the average random consistency index table, which
is presented by Saaty. As Saaty mentions, the table is produced by a large
sample of reciprocal matrices.
In the case that the Consistency Ratio=CI/RI is less than 0,10, the matrix
is consistent and the judgments are acceptable. In the opposite case,
if CR > 0.1, there is a hint that the judgments are not reliable.
However, if the CR is slightly above 0,1, the comparisons could
sometimes get accepted. For CR above 0,9 the comparisons are fully
unreliable.
AHP hierarchy in regional competitiveness in solar
energy entrepreneurship
Decompose the problem
Porter’s Diamond Analysis
Porter, M.E. (1990), The Competitive Advantage of Nations, Macmillan, London.
Porter, M.E. (1998), Competitive Advantage: Creating and Sustaining Superior Performance,
Free Press, New York.
Comparative judjement
Pairwise comparisons of the alternatives with respect
to the criterion “Employment rate %”
Pairwise comparisons of the criteria
Conclusion
Synthesis of priorities
Incosistency index: 0,01
Synthesis of priorities
Criteria and alternatives performance
Expert Choice‘s sensitivity analysis (10 scenarios)
General conclusions
• Firstly, the AHP is applied for the first time in this
manner, not only in terms of the pairwise
comparisons with actual measurements, but also
in relation to the selection of the criteria.
• It is also the first time the regions are ranked in
this way
• The strong impact of regional factors is
highlighted
• It has practical applicability as it could be utilized
as a navigator by business managers and policy
makers
Future research
• It would be scientifically interesting to address this issue by
adopting a cross-national approach making comparisons
among regions of different nations. By using data at
European level a rank of the European regions could be
formed in relation to solar energy entrepreneurship.
Furthermore, it would be interesting if eco-industries
employed similar approaches, for instance, in the recycling
industry or waste management, as they have attracted
great research and investment interest in the last years.
Thank you!!!