Evaluation of LPI Values of Transition Economies Countries With a Grey MCDM Model

Evaluation of LPI Values of Transition Economies Countries With a Grey MCDM Model

Alptekin Ulutaş (Sivas Cumhuriyet University, Turkey) and Çağatay Karaköy (Sivas Cumhuriyet University, Turkey)
DOI: 10.4018/978-1-7998-5077-9.ch024

Abstract

This study has three objectives. First, there are many publications in the literature on the countries of transition economies. However, there are few publications in the literature on the logistics performance of countries of transition economies. This study analyses the logistics performance of countries of transition economies to fill this research gap. Second, only a few studies on LPI considered the period in calculating LPI values. This study considers the period in LPI calculation by using grey MCDM methods to fill this research gap. Third, this study proposes a new integrated grey MCDM model consisting of grey SWARA and grey MOORA. Both grey methods are more practical compared to other grey methods. Both methods were preferred in this study as they have simpler and less processing steps than other grey MCDM methods. According to the results of grey SWARA, the most important criterion is determined as “Infrastructure” (I) criterion. According to the results of grey MOORA, the country with the best logistics performance has been identified as “Serbia.”
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Introduction

Since the end of the 20th century in the world; important changes have started to take place in terms of economy, politics, culture and geographical borders. The most important of these is the fall of the Berlin Wall at the end of 1989 and the unification of East Germany and West Germany. After this event, at the end of 1991, the Soviet Union was completely disintegrated, and in 1993 and after, Yugoslavia and Czechoslovakia were disintegrated. While these events took place on the world agenda, they initiated a process that would lead to permanent changes in the world economy and politics. In the context of the collapse of the Eastern Bloc and new developments, countries that have started the transition to a market economy have a large geographical area and population. Especially after the 1990s, the changes were not limited to the geography of the Soviet Union. The Central and Eastern European countries, which had to adopt the socialist system after World War II and took the central planning economic system as a role model, started to make radical changes in the social and economic field. It has become possible to examine the countries entering the transition economies as qualifying as transition to the market economy or transformation countries.

Transition economies are studied in different groups because their countries are located in different regions and geographies. Transition economy countries can be listed as follows; EU countries (Bulgaria, Czech Republic, Croatia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia), Southeast Europe Countries (Albania, Bosnia-Herzegovina, Kosovo, Montenegro, Macedonia, Serbia), Community of Independent States (Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan), East Asia Countries (Cambodia, China, Lao P.D.R., Mongolia, Vietnam) (IMF, 2000; Bulut, 2019).

Key Terms in this Chapter

Grey SWARA: This method is the combination of grey numbers and the SWARA method.

Transition Economies: It is a definition used in the literature for the countries that are in the process of transition from the planned economic system to the free market economy with the dissolution of the Soviet Union.

MCDM: Methods that enable multiple alternatives to be evaluated based on multiple criteria.

SWARA: This method starts with the ranking of the criteria by experts and it enables experts to obtain the weight of the criteria.

Grey MOORA: This method is the combination of grey numbers and the MOORA method.

Grey Numbers: Generally, grey numbers are expressed with two numbers (lowest and highest).

MOORA: The method that usually starts with vector normalization and is used to sort the alternatives.

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