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The comparison of two indices could shed light on potentially unknown information.

One example is given in Figure 3-81, which Dowell (2007), from Howe Robinson, created at the end of 2007. The graph represents two indices (the BDI and the Howe Robinson Index) on the same scales. And illustrates that the demand for containers had declined by 33 percent, while the demand for dry bulk products had increased by 420 percent at the end of 2007. As the graph shows, the two indices were moving in parallel for a period of time until the middle of 2006, when the container index started to fall and the dry index started to rise.

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Figure 3-81 Comparison between the BDI and the Howe Robinson Container index Source: Dowell (2007)

An explanation of the reaction of the two indices since 2007, as illustrated in Figure 3-81, is attempted herein. The supply of raw products used mostly by developing countries, such as China, for the production of new products, had increased by 420 percent. The most probable cause was that the suppliers were affected by the preceding

‘good’ four years where the demand for goods in developed economies increased according to the Howe Robinson Container Index. This had a logical consequence for the suppliers to increase their volumes of production without recognising or

appreciating the fact that the demand for goods of developed economies fell once at the end of 2005 and, for second time, at the end of 2007. So, the oversupply of goods to the market, combined with the bad performance of the USA economy in 2008 with a corresponding lowering of demand, led the global economy into recession. This clearly affected all of the economic indicators, as well as the BDI with its significant decline since 2008. However, this decline was not only as a result of the oversupply of the market with bulk commodities, but also due to the oversupply of vessels. Consequently, a second large fall of the index was noticed during the summer of 2010, even though the signs were that the economy had returned to positive growth rates (by 3.9 percent in 2010 and by 3.3 percent in 2011) in comparison with the -3.05 percent in 2009

(UNCTADstat 2011a; The World Bank 2011). Figure 3-82 illustrates how the BDI and the world economy were affected by the ‘Great Trade Collapse’ and how GDP rates were changing for both emerging and developing countries, and that the BDI was moving generally in parallel. The same parallel impression can be taken from Figure 3-83, whereby the BDI is compared with the World Trade volumes.

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Figure 3-82 Baltic Dry Index against GDP growth of selected countries and regions (1980-2015)

Source: N. Contzias Shipping Consultants (2011)

Figure 3-83 BDI against World Trade volume (2003-2010) Source: N. Contzias Shipping Consultants (2011)

As discussed so far, various indices exist in the maritime transport sector with each having a different role and function. In order to understand the validity of the indices existing in the maritime transport sector, a content analysis was undertaken.

159 3.4 Content Analysis⁸

A content analysis was undertaken to enhance knowledge about where and how often the identified indices are used in the maritime transport sector. This information has helped this research realise the validity of the indices studied. Through that realisation, only the valid indices were retained for the next step, which involves their

understanding and interpretation.

By adopting the method of content analysis, all of the indices mentioned in 10 journals and reports can be captured. A total of 10 maritime publications were chosen because of the need to cover a broad range of views and to check the usage of the various indices across the maritime transport sector. The perspectives of ship-owners, ship managers and the shipping industry were obtained by analysing the following publications:

Fairplay, Seatrade, Ship Management International, R.S. Platou monthly report, Lloyd’s List (Daily Newspaper) and Lloyd’s Shipping Economist. A public policy and trade perspective was captured through an examination of the UN quarterly publication UNCTAD Transport Newsletter. Finally, academia/research areas were covered by including the journals Maritime Policy and Management, Maritime Economics and Logistics and the Journal of Transport, Economics and Policy. The results of the content analysis are reported in Table 0-6 (Appendix C).

Content analysis is a highly useful research method for transport studies, as it is possible to generate quantified data from non-quantified sources (Rodrigue et al. 2009). This method has not only been applied to transport studies but also to logistics for example, those of Ellinger et al. (2003) and Spens and Kovacs (2006). Additionally, it is an approach whereby the researcher is able to conduct an analysis of the documents and texts (which may be printed or visualised) that attempt to quantify a specified content material in terms of predetermined named categories; moreover, it takes place in a systematic and repeatable manner. A definition of content analysis is provided by Krippendorff (2004 p.18): “Content analysis is a research technique for making

replicable and valid inferences from text (or other meaningful matter) to the contents of their use”. Furthermore, it is a flexible method that can be applied to a variety of media.

In other words, it is not a research method aimed at analysing documents and texts;

rather, it generates data from them. Even so, it is commonly treated as a research

8 The findings from this section have been published by the researcher in the following peer-reviewed publication: Karamperidis, S., Jackson, E. and Mangan, J. (2013). The Use of Indices in the Maritime Transport Sector. Maritime Policy & Management, [e-pub ahead of print].

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method because of its characteristic approach to analysis (Bryman 2008). One disadvantage, however, is that its quality depends on the quality of the sources being examined (Bryman 2008). Therefore, a broad range of high quality journals and reports which are applicable to the maritime transport sector was examined.

Within the logistics literature, content analysis has been used to inform: 1) literature reviews (Defee and Stank 2005); and 2) analyse interviews and other empirical data (Fawcett et al. 2006). Results from the content analysis involve fundamental model development, which are considered instructions for subsequent practice, and recognition of barriers to collaborative practices (Dinwoodie et al. 2010).

Millward (1995) presents three main types of content analysis:

 Quantitative content analysis (NCA). NCA is used for the identification of statistical frequencies of particular categories of characteristics which are present in a message. These frequencies may then be ranked or otherwise manipulated statistically.

 Qualitative content analysis (LCA). LCA is used to inquire the meaning hidden within a body of content, and to supply a detailed outline of the social reality, with the use of categories based on the research questions to code segments of text.

 Structural content analysis (SCA). SCA represents the relationship that exists between elements of a text. That representation is taking place through specific rules that report the relationships among response categories.

The differences between the various types of content analysis are connected to the level whereby the researcher interprets the meaning of a message, and not only to count the actual content of the data. In this research effort, NCA was deemed most appropriate method in terms of stated objectives. By using this type of content analysis, statistical frequencies of particular ‘key’ words were found within the examined publications.

Simple frequency analysis of the key words was conducted using Microsoft Excel 2007;

key words were then ranked according to frequency of occurrence. The sample comprised the 10 aforementioned publications for the period October 2008 to September 2010. Five key words were deemed appropriate for use in the subsequent content analysis. The first three key words were chosen to detect the word index and its derivatives. The final two were selected because they are linked specifically to the

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maritime transport. The key words for the research were: index, indices, measurement, cost and connectivity.

With the use of NCA, the content of the publications was visually scanned for the key words. Some data access problems were experienced due to the lack of availability of some titles during the chosen period, and which covered the post-economic crisis period (or ‘Great Trade Collapse’), as the IMF named the economic crisis of 2008 (Hellenic Shipping News Worldwide 2011a). The time period for which each journal was available and examined is presented in detail in Table 3-20.

162 Publication Title/

Frequency

Number and information for every journal examined, and problems - limitations that appeared during the content analysis

Fairplay / (weekly) October 2008 until September 2010, 101 issues.

Seatrade / (bi - monthly)

November 2009 until October 2010, 6 issues.

Ship Management International / (bi - monthly)

September / October 2008 until July / August 2010, 12 issues.

Journal of Maritime Policy and Management / (bi - monthly)

December 2008 until September 2010, 12 issues.

Journal of Maritime Economics and Logistics / (quarterly)

December 2008 until September 2010, 8 issues.

Journal of Transport, Economics and Policy / (four - month)

September 2008 until May 2010, 6 issues.

R.S. Platou Monthly Report / (monthly)

October 2008 until September 2010, 24 issues.

UNCTAD Transport Newsletter / (quarterly)

4th quarter 2008 until 3rd quarter 2010, 7 reports.

Lloyd’s List / (daily)

Daily newspaper (released Monday to Friday). One issue per month picked at random, total 24 issues examined. October 2008 until September 2010.

Lloyd’s Shipping Economist / (monthly)

January 2010 until September 2010, 9 reports.

Note: Some of the selected publications have regular features which report on specific indices (e.g. shifts in the BDI are reported each day in the market section of Lloyd’s List). Where this was the case, such indices were only counted once, not every time they appeared.

Table 3-20 Journal title and data availability for the content analysis

The results of the top 18 indices found during the NCA are demonstrated in Table 3-7, in comparison with the complete table of the 109 in total indices found from content analysis conducted, which is given in Appendix C.

163 Sampling

Sampling is a method that links to the content analysis and applies to the research aims.

This is useful because sampling helps to draw conclusions from a selected record (little part) taken from a population, known as the sampling frame (Collis and Hussey 2009).

A sample is an unbiased subset that represents a larger population. A population is a body of people or a collection of items under consideration for statistical purposes (Collis and Hussey 2009). As a result, one can draw conclusions that represent the whole population by examining only a small proportion. For that reason, a sampling method was applied, in conjunction with the content analysis, as mentioned above; this selected method is called the cluster sampling method. The cluster sampling method makes a random selection from a sampling frame listing groups of units rather than individual units (Collis and Hussey 2009). This method allows the selection of individuals belonging to selected groups. More information on the existing sampling techniques is provided in Section 4.6.