FIREWALL CORTAFUEGOS

This section attempts to describe the following sub-objective of RQ3:

Visualize prominent Research focus areas (RFAs) in the field of energy fuels and their

association with prominent authors working in these RFAs.

Among several ways in which knowledge of a field could be represented, co-word network analysis is one of the most common methods. In co-word network analysis, prominent keywords (or frequently used words) are extracted and two keywords form a connection if they have appeared in the same paper. Here a 2-mode method is presented, which not only maps prominent knowledge areas in the field of energy fuels but also maps the most active researchers in those areas. In a 1-mode network, the vertices refer to same set of entities (i.e., author-author), whereas in a 2-mode network they refer to different set of entities (i.e. institution-author) (Borgatti, 2009). 2-mode networks effectively depict ‘macro-micro’ social structures. Visualization of 2-mode data shows how individuals are ‘nested’ in larger structures (Hanneman & Riddle, 2005). This type of author-RFA is similar to other affiliation networks such as a club affiliations or social gatherings (Faust, 1997). Here, our attempt is to present this information through a clutter-free graphical representation, which also conveys maximum meaning.

‘Generic keywords’ are common words mentioned by the authors in the keyword list that support the main research focus area (‘non-generic’ keyword) of the paper. For example, in Figure 4.3.5, one paper mentions the following three keywords – Biomass, Sustainable process and Energy business. Here ‘Sustainable process’ and ‘Energy Business’ are supporting the main research area, ‘Biomass’. In the same light, generic keywords, for example, ‘sustainable’, ‘fuel’ and ‘energy’ were excluded as we are interested in

148 identifying focus areas within energy fuels. Non-generic key words are taken based on the number of occurrences in the ‘original keyword’ field.

Biomass; Sustainable process; Energy business

Figure 4.3.5: Example of inclusion and exclusion of words taking keywords of a paper as an example.

These words are represented in original keywords with several variations, and those variations have been included while calculating the total number of occurrences. To differentiate it with academic field or sub-fields, These words are named as Research Focus areas (RFA). Once the words representing a focus area of both datasets were extracted, prominent authors were chosen based on the number of times they had used these keywords in their papers. Table 4.3.7 gives details of the top focus areas, top word variations and prominent authors in those focus areas of both Turkey and Malaysia. Seven of the nine areas—Biodiesel, Solar, Biomass, Hydrogen, fuel-cell, waste and thermal— are common in both Malaysia and Turkey.

Generic words, hence excluded Non-generic word,

Table 4.3.7: Research Focus Areas (RFAs) and prominent researchers of the two countries

Field Some prominent key word variations Occurrences Prominent Researchers

MALAYSIA

Biodiesel Biodiesel,Palm biodiesel, Biodiesel engine, Biodiesel feedstocks,Biodiesel refining

82 Lee, KT (20), Masjuki, HH (14), Tan, KT (9) , Fazal, MA (9), Mohamed, AR (9), Haseeb, ASMA (9)

Palm Palm Oil, Palm oil mill effluent, Oil palm, Sludge palm oil, Oil palm fruit press fiber (FPF)

72 Lee, KT (12), Mohamed, AR (9), Bhatia, S (9), Masjuki, HH (8), Hameed, BH (6), Abdullah, N (5)

Solar Solar,solar energy,double-pass solar collector,solar fraction,V- groove solar collector, solar photovoltaic

55 Sopian, K (37), Sulaiman, MY (19), Alghoul, MA. (19), Zaharim, A (16), Ruslan, MH (13)

Carbon Activated carbon, Carbon, Carbon dioxide, Carbon dioxide hydrate, Carbon sequestration

42 Hameed, BH (7), Foo, DCY (5), Tan, RR (5), Foo, KY (4) Biomass Biomass, Biomass concentration, Lignocellulosic

biomass,Biomass conversion technology, Palm oil biomass

37 Lee, KT (5),Saidur, R (4),Mekhilef, S (4)

Hydrogen Biohydrogen, Hydrogen production, Hydrogen, Hydrogen production, Hydrogen purification

37 Abbas, HF (7), Hassan, MA (6), Daud, WMAW (6)

Thermal Thermal, Photovoltaic thermal (PVT), Thermal resistance, multifunctional solar thermal collector, Hydrothermal

29 Sopian, K (12) , Ruslan, MH (10), Saidur, R (6)

Waste Waste cooking oil, Oil palm wastes, Municipal solid waste (MSW), agricultural waste

21 Lee, KT (3)

Fuel Cell Fuel cell, Direct methanol fuel cell, Solid oxide fuel cell, Direct borohydride fuel cell

150 Table 4.3.7 (continued): Research Focus Areas (RFAs) and prominent researchers of the two countries

Field Some prominent key word variations Occurrences Prominent Researchers

TURKEY

Hydrogen Hydrogen, Bio-hydrogen, Hydrogen storage, Hydrogen production, hydrogen energy

185 Kargi, F (25), Dincer, I (16), Gunduz, U (12), Yucel, M,(12), Eroglu, I(11), Argun, H (10), Hepbasli, A (9), Demirbas, A (7) Solar Solar energy, solar radiation, Organic solar cells 113 Bakirci, K (5), Dincer, I (5), Ozek, N (3),Yilmaz, E (3)

Biodiesel biodiesel economy, Biodiesel production, biodiesel policy 112 Demirbas, A (20), Ilkilic, C (10), Balat, M (7), Keskin, A (6), Aydin, H (6), Saydut, A (6), Guru, M (6)

Biomass Biomass energy,Lignocellulosic biomass 106 Demirbas, A (14), Balat, M (12), Haykiri-Acma, H (9), Yaman, S (8), Demirbas, MF (6)

Thermal Geothermal energy, Thermal analysis, Thermal energy storage, Thermal efficiency

106 Dincer, I(12), Sari, A(10), Karaipekli, A(8), Hepbasli, A(7), Balta, MT(6)

Wind Wind energy, wind turbine, wind power 103 Akdag, SA(7), Guler, O(7) Coal Coal oxidation, Coal tar pitch, Turkish coals 93 Saydut, A (4), Ozdeniz, AH (4) Waste Waste oil, Olive mill wastewater, Wastewater, Waste engine oil 60 Eroglu, E (4), Yumrutas, R (4)

Next, a 2-mode network representation to identify prominent researchers in each of the RFAs in Turkey and Malaysia is carried out. By providing a 2-mode representation, I believe that our network provides a more diverse cognitive structure than is available through 1-mode knowledge domain visualizations (KDVs).

The standard representation of cognitive structure (Mane & Börner, 2004), which mostly represents connections between keywords (might also represent frequent words, research topics or fields, etc.), does not provide information on the prominent authors who are working in these research topics; prominent authors are an important part of cognitive structure, which is missed in 1-mode presentation through KDVs. In a study, Hou et al. (2008) , presented the cognitive structure of the Scientometrics journal by first drawing a word co-occurrence network and then manually partitioning the network based on the research sub-field. Hou et al. (2008) finally textually described the prominent authors working in those sub-fields. In contrast, our representation provides a multi-dimensional bird’s eye view of RFA (prominent research areas), prominent authors working in these RFA and the strength of this association (see Figure 4.3.6). These graphs are drawn considering how our eyes and brains process visual information (Kosslyn, 2006)

152 a) Malaysia

b) Turkey

Figure 4.3.6: 2-mode network diagram representing the cognitive structure of Malaysia and Turkey

In the networks of Turkey and Malaysia, it is the prominent authors in the network that connect the various focus areas. Few researchers have carried out their research in multiple focus areas. Lee, Kt of Malaysia and Dincer, I. and Demirbas, A. of Turkey are among the researchers who have carried out their research in multiple focus areas.

The overall impetus of research in both countries is in the field of renewable and sustainable energy. Palm is an important plantation in Malaysia, and palm oil is a burgeoning industry in this country. Use of palm oil for biofuel and for biomass has been studied aggressively by Malaysian researchers. Wind energy, on the other hand, has seen tremendous research interest in Turkey. Turkey has wind potential to generate 83,000 MW; however, the installed wind capacity was 3.33% of this wind potential (Bilgili & Simsek, 2012). In areas affected by ocean thermal energy and wave and tidal energy, few activities have been conducted in OIC countries (Sopian et al., 2011). The same pertains to Turkey and Malaysia. Missing in the top 9 RFAs is ‘nuclear’, an energy source with is controversial due to potential environmental hazards but has tremendous potential. Neither country has a nuclear power generation plant, but has government agencies in place to review the nuclear option. In Turkey, however, an application has been submitted

to construct the first nuclear plant at Akkuyu (http://www.world-

nuclear.org/info/Country-Profiles/Countries-T-Z/Turkey/#.UUvcWxxgenA).

4.4 Chapter conclusion

I have presented the results and analysis of the study. An attempt was made to answer the research questions, with their respective sub-objectives and sub questions. The results brought out new aspects of research collaborations in the context of Malaysia. The network approach located central authors in the research community, determined

154 the cohesiveness of various collaboration networks, and provided new propositions for analysis of research collaboration networks, among others. The key findings emerging from each of the research questions are given in the next chapter.

CHAPTER 5: CONCLUSIONS

The key findings of each of the three case studies are first delineated. Limitations of the study and its contribution to the literature are presented. Lastly, I discuss avenues for future research.