«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

The Saaty Rating Scale

Intensity of importance Definition Explanation

1 Equal importance Two factors contribute equally to the objective

3 Somewhat moreimportant

Experience and judgment slightly favor one over the other

5 Much moreimportant

Experience and judgment strongly favor one over the other

7 Very much moreimportant

Experience and judgment very strongly favor one over the other. Its importance is demonstrated in practice.

9 Absolutely moreimportant.

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

2,4,6,8 Intermediatevalues

When compromise is needed

Comparative Judgment

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 judjementPairwise comparisons of the alternatives with respect

to the criterion “Employment rate %”

Pairwise comparisons of the criteria

ConclusionSynthesis 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!!!