A country-cluster analysis of the distribution and promotion infrastructure in Central and Eastern Europe

International Business Review 10 (2001) 517–549 www.elsevier.com/locate/ibusrev

A country-cluster analysis of the distribution and promotion infrastructure in Central and Eastern Europe Lalita A. Manrai a

a,*

, Ajay K. Manrai a, Dana-Nicoleta Lascu

b

College of Business and Economics, University of Delaware, Newark, DE 19716-2710, USA b University of Richmond, Richmond, USA

Abstract A country-cluster scheme is developed in this paper classifying 18 countries of Central and Eastern Europe in terms of their overall attractiveness for international marketing. These 18 countries include Albania, Belarus, Bosnia–Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Poland, Romania, Serbia–Montenegro, Slovakia, Slovenia and Ukraine. When companies examine and evaluate the potential countries for international marketing opportunity, they not only look at the demand potential of the country but also the logistics of marketing operations in the country. While all 4 Ps of marketing are regulated by the government, the availability of infrastructure for efficient distribution and promotion of products is a critical consideration for selection of a country. This is so because compared to the other 2 Ps of marketing mix, i.e. product and price decisions, the success of distribution (place) and promotion decisions is relatively more out of the control of marketers, being tied to the availability of infrastructure. Accordingly, this country-cluster scheme is developed in two stages. First, selected demographic and economic indicators are analyzed to asses the overall market potential and economic strength of the country. Next, several factors related to distribution and promotion of goods in these countries are examined in detail. Finally, the two sets of classification schemes above are combined to develop a two-dimensional country-cluster matrix (demographic–economic as the first dimension and distribution–promotion as the second dimension). The aggregate analysis reveals three country clusters. Cluster 1, the most promising group of countries (attractive on both dimensions) includes Czech Republic, Hungary, Poland, Romania, Slovakia and Ukraine. Cluster 3, the least promising group of countries (attractive on neither dimension) includes Albania, Bosnia– Herzegovina, Macedonia and Serbia–Montenegro. Cluster 2 includes countries which are either

* Corresponding author. Tel.: +1-302-831-1775; fax: +1-302-831-4196. E-mail address: [email protected] (L.A. Manrai). 0969-5931/01/$ - see front matter  2001 Elsevier Science Ltd. All rights reserved. PII: S 0 9 6 9 - 5 9 3 1 ( 0 1 ) 0 0 0 3 1 - 2

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moderate in terms of attractiveness on both dimensions or countries with a trade-off between two dimensions (one high, other low). Cluster 2 includes Belarus, Bulgaria, Croatia, Estonia, Latvia, Lithuania, Moldova and Slovenia. Implications for international marketing and future research directions are discussed.  2001 Elsevier Science Ltd. All rights reserved.

1. Introduction Central and Eastern Europe represents a market of 198.61 million people (1995 estimates) across 18 countries of Albania, Belarus, Bosnia–Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Poland, Romania, Serbia–Montenegro, Slovakia, Slovenia and Ukraine (US Department of Commerce classification of Central and Eastern Europe). The GDP per capita for these countries ranges from as low as US$ 900, for Macedonia, probably one of the poorest to GDP per capita of US$ 8110 for Slovenia and GDP per capita of US$ 7350 for the Czech Republic. Slovenia and Czech Republic compare quite favorably with some of the West European countries like Greece with GDP per capita of US$ 8870 or Eastern part of Germany (formerly East Germany) with GDP per capita of US$ 5950. In deciding which markets to enter, there are several other factors that need to be taken into account by the international marketer besides the size of the market and its productivity/purchasing power parity. These factors include the economic, political, legal, competitive and technological environment of the countries as well as the marketing infrastructure and support services. The international market selection, therefore, is a complex process which involves a careful analysis of all these factors, keeping in mind at the same time specific strengths and weaknesses of the company and its international marketing priorities and objectives. Each of the four elements of the marketing mix, i.e. product, price, place (distribution) and promotion are critical to the success of international operations. However successful execution of distribution and promotion decisions in particular depends heavily upon the infrastructure of the country. Thus while assessing the attractiveness of a country for international marketing, in addition to the demand potential, the marketing logistics including availability of distribution and promotion infrastructure plays a critical role in decision making. With reference to the above discussion, the research reported in this paper makes an important contribution. We develop a country-cluster scheme and classify the 18 countries mentioned above in terms of their overall attractiveness for international marketing. This country-cluster scheme is developed in two stages. In the first stage, we present an analysis of the selected demographic and economic indicators to assess the overall market potential and strength of economy and classify the 18 countries into five groups ranging from least attractive (low) to most attractive (high). Next, several factors related to the distribution and promotion of goods in these 18 countries are examined in detail. This analysis includes quantitative as well as qualitative information and is concluded with an overall classification of countries into five groups ranging from least attractive (low) to most attractive (high), taking into

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account distribution- and promotion-related considerations. Finally, the two sets of classification schemes developed above, i.e. one based on demographic and economic indicators and the other based on distribution and promotion related considerations, are combined to develop a country-cluster matrix in which three different clusters are identified based on the aggregate analysis. While the previous research in this area has pointed to the importance of studying environmental considerations in country selection decision (Hisey & Caves, 1985; Lee, 1996), to the best of our knowledge, no study has conducted an aggregate analysis looking at all 18 Central and Eastern European countries simultaneously. Further, the distribution and promotional issues are specifically integrated into our country-cluster analysis, and, as such, this contribution of our research is new and also has very useful managerial implications for the marketing of goods in these countries. The research reported in this paper thus provides a comparative assessment of 18 countries in terms of their attractiveness for international marketing as well as country specific insights into demographic–economic potential and distribution– promotion infrastructure. This paper is divided into five sections. In Section 2, we analyze selected demographic and economic indicators for the 18 countries and classify the countries into five groups ranging from least attractive to most attractive. Next, in Section 3, we discuss in detail distribution- and promotion-related issues for the 18 countries and report quantitative statistics as well as qualitative data. Section 3 is concluded with another classification of the 18 countries into five groups ranging from least attractive to most attractive. Section 4 combines the two classification schemes to develop an overall country-cluster matrix in which three different country clusters are identified. Finally, Section 5 discusses the country clusters developed in this paper and limitations of the research and directions/plans for future research are identified. The data for this research was collected from a variety of published secondary data sources. These sources are identified at respective places in the text as well as given as footnotes at the bottom of the tables. The methodology for aggregation of data, and for classification of countries into different groups is discussed separately for respective sections.

2. Country overview: demographics and economy In this section, selected demographic and economic indicators for the 18 countries are analyzed using quantitative statistics as well as qualitative information. These indicators were selected to assess the demand potential as well as its stability. For demographic indicators, population size was used as a measure of demand potential. For assessing the stability of demand, three different economic indicators were used, i.e. GDP per capita measuring the economic productivity, unemployment rate measuring the income stability, and inflation rate measuring the price stability. This analysis is concluded with a classification of the 18 countries into five groups capturing the degree of attractiveness of the country for international marketing opportunities.

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2.1. Demographic indicators 2.1.1. Population: market size Countrywide information on the capital, area (in sq. km), population (in million) and literacy rate (%) was compiled from sources on the Internet, such as trade directories. This information is summarized in Table 1. With the exception of Albania, the countries are quite comparable on literacy rate (96–100%). The country population ranges from as low as 1.63 million for Estonia to as high as 51.87 million for the Ukraine (July 1995 estimates). Based on the distribution of these population statistics, the market size of the 18 countries was classified into five categories given in Table 2A, as follows: small (⬍5 million), small–medium (5–10 million), medium (10–20 million), medium–large (20–30 million) and large (⬎30 million). Accordingly, nine out of 18 countries are classified as small countries, i.e. Albania, Bosnia– Herzegovina, Croatia, Estonia, Latvia, Lithuania, Macedonia, Moldova, and Slovenia. Next, the two countries classified as small–medium include Bulgaria and Slovakia, and four countries classified as medium include Belarus, the Czech Republic, Hungary and Serbia–Montenegro. Romania was classified as medium–large country and the two large countries as per this classification scheme are Poland and Ukraine. 2.2. Economic indicators Two types of economic indicators were examined, i.e. the overall productivity of the economy as measured by the GDP per capita (US$) and overall stability of the economy as measured by the unemployment (%) indicative of income stability and inflation (%) indicative of price stability. 2.2.1. GDP per capita: economy productivity GDP per capita was computed by dividing the total GDP (1994 estimates) by population. These statistics were also compiled from Internet. This information is also summarized in Table 1. Based on the distribution of these statistics, classification schemes (Table 2) were developed as follows: GDP per capita reflects the productivity of the economy and the 18 countries were classified into five categories of low (⬍1500 US$), low–medium (1500–3000 US$), medium (3000–4500 US$), medium–high (4500–6500 US$), and high (⬎6500 US$). The GDP statistics on Bosnia–Herzegovina are not available but other available information indicates that the economic situation in Bosnia–Herzegovina is very similar to Macedonia. Accordingly Bosnia–Herzegovina was classified as a low GDP per capita country. The other three low GDP per capita countries included Albania, Macedonia and Serbia–Montenegro. The three low–medium GDP per capita countries included Croatia, Moldova and Romania. The four countries included in the medium GDP per capita category included Bulgaria, Latvia, Lithuania and Ukraine. Five countries were included in the medium–high GDP per capita category, i.e. Belarus, Estonia, Hungary, Poland and Slovakia. The last category of high GDP per capita included two countries, i.e. Czech Republic and Slovenia.

Tirane Minsk Sarajevo Sofia Zagreb Prague Tallinn Budapest Riga Vilnius Skopje Chisinau Warsaw Bucharest Belgrade Bratislava Ljubljana Kiev

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

28,750 207,600 51,233 110,910 56,538 78,703 45,100 93,030 64,100 65,200 25,333 33,700 312,680 237,500 102,350 48,845 20,296 603,700

Area (sq. km)

3.41 10.44 3.20 8.78 4.67 10.43 1.63 10.32 2.76 3.88 2.16 4.49 38.79 23.20 11.10 5.43 2.05 51.87

Population (million)

Source: Internet: Countrywise Trade Directories (1998)

Capital

Country

Table 1 Demographic and economic indicators

3.8 53.4 NA 33.7 12.4 76.5 10.4 58.8 12.3 13.5 1.9 11.9 191.1 64.7 10.0 32.8 16.0 189.2

GDP $ (billion) 1100 5130 NA 3830 2640 7350 6460 5750 4480 3500 900 2670 4920 2790 1000 6070 8110 3650

GDP/ capita ($) 18 1 NA 16 17 3 2 10 7 5 30 1 16 11 40 15 9 1

72 97 NA 98 97 99 100 99 100 98 NA 96 99 97 NA NA NA 98

Unemployment Literacy (%) (%)

16 29 NA 122 3 10 3 21 2 3 54 8 30 62 20 12 20 14

Inflation (%)

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Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

Small Medium Small Small–medium Small Medium Small Medium Small Small Small Small Large Medium–large Medium Small–medium Small Large

Population Low Medium–high NA Medium Low–medium High Medium–high Medium–high Medium Medium Low Low–medium Medium–high Low–medium Low Medium–high High Medium

GDP/Capita

(A) Based on demographic and economic indicators Country Market size Economy productivity

Table 2 Country attractiveness evaluation

Low–medium High NA Low–medium Low–medium High High Medium Medium–high Medium–high Low High Low–medium Medium Low Low–medium Medium High

Income low unemploy. Medium–high Medium NA Low High Medium–high High Medium High High Low Medium–high Low–medium Low Medium Medium–high Medium Medium–high

Prices low inflation

Economy stability based on

Low (1.5) Medium–high (3.7) Low Low–medium (2.2) Low–medium (1.9) Medium–high (4.1) Medium (3.1) Medium (3.3) Medium (2.6) Medium (2.6) Low (1.0) Low–medium (2.4) Medium–high (3.8) Medium (2.9) Low–medium (2.0) Medium (2.8) Medium (2.8) Medium (3.5) (continued on next page)

Overall evaluation (# points)

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1500–3000 14–20 30–50 1.51–2.50

⬍1500

⬎20

⬎50

ⱕ1.5

⬍5

Small–medium/low– medium 5–10

2.51–3.50

20–30

9–13

3000–4500

10–20

Medium

3.51–4.50

8–20

5–8

4500–6500

⬎4.50

⬍8

⬍8

⬎6500

Medium–large/medium– Large/high high 20–30 ⬎30

Notes: (1) Variable weights are as follows: market size: 40%; economy productivity: 30%; income stability (low unemp.): 20%; price stability (low infl.): 10%, (2) ratings imply the following points for market size, economy productivity, income stability and price stability: small/low: 1 point, small– medium/low–medium: 2 points, medium: 3 points, medium–large/medium–high: 4 points, large/high: 5 points, (3) score range for overall evaluation: 1.0–4.1 points

Market size (population in millions) Economy productivity (GDP/captia in US$) Income stability (low unemploy. in %) Price stability (low inflation in %) Overall evaluation*** (# points)

(B) Bases for evaluation/classification scheme Variable Evaluation Small/low

Table 2 (continued)

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2.2.2. Unemployment rate: income stability The next variable examined was unemployment rate. Low unemployment rate reflects that people have jobs, i.e. purchasing power, and the economy is stable. Thus the codification of this variable is reverse. The 18 countries were classified into five categories of income stability based on unemployment rates as follows: low (unemployment ⬎20%), low–medium (unemployment 14–20%), medium (unemployment 9–13%), medium–high (unemployment 5–8%), and high (unemployment ⬍5%). The countries classified as having low-income stability (high unemployment) included Macedonia and Serbia–Montenegro. Bosnia–Herzegovina is also included in this group due to the similarity of its economic situation with Macedonia. The low–medium income stability category of countries included five countries, i.e. Albania, Bulgaria, Croatia, Poland and Slovakia. Next, the three countries classified under medium income stability included Hungary, Romania and Slovenia. Two countries evaluated as medium–high in income stability were Latvia and Lithuania. Finally the group designated as high in income stability (low unemployment) included five countries, i.e. Belarus, the Czech Republic, Estonia, Moldova and the Ukraine. 2.2.3. Inflation rate: price stability Another variable used to capture the stability of economy was rate of inflation. Lower inflation rate implies price stability. Thus the codification for this variable was also reversed. The 18 countries were classified into five categories of price stability based on inflation rates as follows: low (inflation ⬎50%), low–medium (inflation 30–50%), medium (inflation 20–30%), medium–high (inflation 8–20%), and high (inflation ⬍8%). The countries classified as having low price stability (high inflation) included Bulgaria, Macedonia and Romania. Once again, Bosnia–Herzegovina is also included in this group due to the similarity of its economic situation with Macedonia. The low–medium price stability category included Poland and the medium price stability category included Belarus, Hungary, Serbia–Montenegro and Slovenia. The fourth price stability category, i.e. medium–high, included the five countries of Albania, the Czech Republic, Moldova, Slovakia and the Ukraine. Finally the countries classified as having high price stability (low inflation) included Croatia, Estonia, Latvia and Lithuania.

3. Country attractiveness evaluation (based on demographic and economic indicators) The above two classification schemes, i.e. based on demographic and economic indicators are combined to develop measures of country attractiveness. The procedure for aggregation of information was developed after extensive discussions between the three authors. To the best of our knowledge, no existing studies have addressed the issue of information aggregation, especially of this nature and magnitude. We were, therefore, required to develop our own procedure. The methodology used for aggregation of the information is as follows:

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1. The five subgroups for each of the four indicators discussed above, i.e. market size, economy productivity, income stability and price stability, are treated as ratings on a 5-point scale. Thus small/low implies 1 point, small–medium/low– medium implies 2 points, medium implies 3 points, medium–large/medium–high implies 4 points and large/high implies 5 points. 2. The four indicators are assigned weights as follows: market size — 40%, economy productivity — 30%, income stability — 20% and price stability — 10%. The rationale for these weights is derived with reference to their importance for international marketing. The basic attraction for seeking international markets is demand, thus the market size is assigned the highest weight. Economy productivity implies the labor productivity and efficiency, resources, as well as sound political and legal systems. These are also fairly important considerations for international marketers; thus this factor is assigned a weight of 30%. Finally the unemployment and inflation rates, in addition to the overall productivity of economy, also reflect its strength in terms of purchasing power and affordability of goods. While overall productivity of economy is considered to be the main indicator of the strength of economy (30% weight), these other variables reflecting the stability of the economy are assigned slightly lower weights, of 20 and 10%, respectively. 3. The country ratings on the four indicators are aggregated with the importance weights for the four indicators using a linear/expectancy value model to arrive at overall weighted evaluations given in Table 2A (individual ratings on four indicators are multiplied by their respective weights and the products added together). The weighted scores range from 1 to 4.1. Based on the distribution of overall weighted scores, five categories of overall evaluation are developed. These are: low attractiveness (score: ⬍1.5), low–medium attractiveness (score range: 1.51–2.50), medium attractiveness (score range: 2.51– 3.50), medium–high attractiveness (score range: 3.51–4.50) and high attractiveness (score: ⬎4.5). Based on these score assignments, Albania, Bosnia–Herzegovina and Macedonia are designated as low attractiveness countries. Bulgaria, Croatia, Moldova and Serbia–Montenegro are classified as low–medium attractiveness countries and Latvia, Lithuania, Slovakia and Slovenia are classified as medium attractiveness countries. The countries classified as medium–high attractiveness countries include Belarus, the Czech Republic, Estonia, Hungary, Poland, Romania and the Ukraine. None of the countries were classified under the high attractiveness category. This classification scheme compares and corroborates well with other published information on these countries. For example, the World Bank estimated that it will take $5 billion to repair the ravages of war and revive the economy of Bosnia– Herzegovina and no prospects are seen for tourist industry in this country. European Marketing Data and Statistics (1998) views Macedonia as the poorest and least developed republic in the former Yugoslavia and having severe economic problems. Albania is also seen as one of the poorest countries in Eastern Europe with average monthly wages of $100 per month. On the other hand, countries like the Czech Republic are acknowledged to have high productivity in agriculture and heavy equipment and precision manufacturing.

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European Marketing Data and Statistics (1998) sources state that private sector’s share of GDP for the Czech Republic is the highest in Eastern Europe (70%) and that the country has already reached the standard of advanced industrial economies in terms of systems of trade and foreign exchange. Estonia is viewed as one of the most prosperous Soviet republics and has successfully attracted joint ventures with western companies. Foreign direct investment in Estonia was estimated at $70 million in 1996. Estonia also has close ties with Scandinavian countries, which represent attractive markets for its products, as well as sources for capital and technological know how (European Marketing Data and Statistics, 1998). Poland’s economy has done very well despite difficulties of transition. The private sector has been extremely productive, accounting for 55% of GDP despite the fact that a substantial proportion of the industry is still controlled by state. Thus the classification scheme developed and presented in Table 2 is considered a fair representation of demographic and economic situation in Central and Eastern Europe. Next, we examine several distribution and promotion related issues in these 18 Central and Eastern Europe countries.

4. Distribution and promotion infrastructure In this section, we discuss the distribution and promotion infrastructure of the 18 countries and conclude with a classification of the 18 countries into five groups capturing the ease or difficulty of marketing products in these countries. 4.1. Distribution infrastructure The variables used to evaluate the distribution infrastructure include the efficiency of the transportation system and the degree of privatization and development of retailing sector. 4.1.1. Transportation efficiency The efficiency of the transportation system is determined by computing the amount of freight carried/per unit by the four different sectors of transportation, i.e. roadways, railways, merchant ships and airlines. Table 3 summarizes the length of roadways and railways in kilometers (km) and the number of merchant ships and number of airports for the 18 countries. These statistics are compiled from the Internet, mostly trade directories. Next in Table 4, we provide statistics on freight carried by roadways in million ton-km (European Marketing Data and Statistics, 1998), freight carried by railways in million ton-km (European Marketing Data and Statistics, 1998), freight carried by merchant ships (Lloyd’s Register of Shipping, Fleet Statistics, 1997) and freight carried by airlines (International Civil Aviation Organization Statistics, 1997). Next, we compute the amount of freight carried ‘per unit’ of transportation to determine the efficiency of each of these four transportation systems. This is summarized in Table 5 in items of tons for roadways and railways, tons/ship for merchant ships and million ton-km/airport for airlines.

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Table 3 Transportation availability Country

Roadways (km)

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

18,450 98,200 21,168 36,932 27,368 55,890 30,300 158,711 59,500 44,200 10,591 20,000 367,000 461,880 46,019 17,650 14,726 273,700

Railways (km)

543 5570 1021 4294 2699 9434 1030 7785 2400 2010 922 1150 25,528 11,365 3960 3660 1201 23,350

Merchant ships (#s) 11 NA None 109 35 14 65 10 85 44 None None 152 238 37 2 17 379

Airports (#s) 11 118 27 355 76 116 22 78 50 96 16 26 134 156 54 37 14 706

Source: Internet: Countrywise Trade Directories (1998)

The distribution of statistics for the efficiency of each of these four transportation sectors was examined to develop a classification scheme. This classification scheme is summarized in Table 6. Where the efficiency could not be computed due to missing information on amount of freight carried, the classification is done based on the transportation availability only (Table 4 information). Finally overall efficiency of the transportation system was determined by averaging the efficiency of the four transportation sectors. The rating distributions and countries classified under the five categories of low, low–medium, medium, medium–high, and high for each of the four transportation sectors, as well as the overall classification, is discussed next. Roadways efficiency was classified as follows: low (⬍20,000 tons), low–medium (20,000–50,000 tons), medium (50,000–100,000 tons), medium–high (100,000– 200,000 tons) and high (⬎200,000 tons). The four countries with low roadways efficiency included Albania, Bosnia–Herzegovina, Hungary and Serbia–Montenegro. The low–medium roadways efficiency category included three countries, i.e. Croatia, Latvia, and Romania and medium roadways efficiency category included four countries, i.e. Belarus, Estonia, Moldova and the Ukraine. The four countries classified as medium–high in roadways efficiency were Lithuania, Macedonia, Poland and Slovenia and the high roadways efficiency category of countries were Bulgaria, the Czech Republic and Slovakia. Railways efficiency was classified as follows: low (⬍1 million tons), low–medium (1–4 million tons), medium (4–10 million tons), medium–high (10–20 million tons)

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Table 4 Freight carried Country

Roadways (million ton-km)a

Railways (million ton-km)a

Merchant ships (000 tons)b

Airlines (million ton-km)c

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

80 9539 NA 9510 575 20,684 1549 723 1700* 5160 1178 1121 71,600 19,748 NA 5148 1740 23,100

NA NA NA 7018* 1438 21,425 3829** 7143 9772** 7369 NA 4612** 68,390** 23,473** NA 11,216 NA NA

63 NA NA 1103 298 228* 454 45 639 388 NA NA 2151 2263 NA 19 1 3788

2 NA NA 33 3 23 NA 27 1 1 1* 2 62 24 NA NA 3 19

Note: *1993 estimates, ** 1994 estimates, otherwise 1995 estimates a b c

European Marketing Data and Statistics (1998). Lloyd’s Register of Shipping, Fleet Statistics (1997). International Civil Aviation Organization Statistics (1997).

and high (⬎20 million tons). The six countries classified under the low railways efficiency category included Albania, Bosnia–Herzegovina, Croatia, Hungary, Macedonia and Slovenia. The low–medium railways efficiency category included six countries, i.e. Belarus, Bulgaria, Czech Republic, Estonia, Lithuania and Serbia– Montenegro. Latvia and Moldova were classified as medium railways efficiency countries. None of the countries fitted the classification under medium–high category. Finally, the four countries of Poland, Romania, Slovakia and Ukraine were classified as high railways efficiency countries. As regards the efficiency of the merchant ships, the following classification scheme was used: low (⬍3000 tons/ship), low–medium (3000–6000 tons/ship), medium (6000–9000 tons/ship), medium–high (9000–12,000 tons/ship) and high (⬎12,000 tons/ship). The six countries classified under the low merchant ships efficiency category included Belarus, Bosnia–Herzegovina, Macedonia, Moldova, Serbia–Montenegro and Slovenia. The low–medium merchant ships efficiency category included Albania and Hungary. Croatia, Estonia, Latvia, and Lithuania were classified under the medium merchant ships efficiency category. The medium–high merchant ships efficiency group included four countries of Bulgaria, Romania, Slovakia and the Ukraine. The two countries classified under the high merchant ship efficiency group were the Czech Republic and Poland.

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Table 5 Transportation efficiency Country

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

Roadways (tons*)

4336 97,138 NA 257,500 21,010 370,084 51,122 4555 28,571 116,742 111,227 56,050 195,095 42,756 NA 291,671 118,158 84,399

Railways (tons*)

Merchant ships (tons/ship)

NA NA NA 1,634,373 532,790 2,271,041 3,717,476 917,534 4,071,667 3,666,169 NA 4,010,435 26,790,191 20,653,762 NA 30,644,809 NA NA

5730 NA NA 10,120 8510 16,290 6980 4500 7520 8820 NA NA 14,150 9510 NA 9500 60 9990

Airlines (million tons-km/airport) 181,818 NA NA 92,958 39,474 198,276 NA 346,154 20,000 10,417 62,500 76,923 462,687 153,846 NA NA 214,286 26,912

Note: *freight carried million ton-km÷km of roadways/railways

Airline efficiency categories were as follows: low (⬍50 million-km/airport), low– medium (50–150 million-km/airport), medium (150–250 million-km/airport), medium–high (250–350 million-km/airport) and high (⬎350 million-km/airport). The low airlines efficiency group included six countries, i.e. Bosnia–Herzegovina, Croatia, Estonia, Latvia, Lithuania and the Ukraine. The low–medium airlines efficiency group included four countries, i.e. Bulgaria, Macedonia, Moldova and Slovakia. Albania, Belarus, the Czech Republic, Serbia–Montenegro, and Slovenia were classified as medium airlines efficiency countries and Hungary and Romania were classified as medium–high airlines efficiency countries. The only country that fitted the high airlines efficiency classification was Poland. The overall efficiency of the transportation system was determined by combining the ratings of the countries for each of the four transportation sectors in equal (25%) weights. For each of the four sectors, a rating of low implied 1 point, low–medium implied 2 points, medium implied 3 points, medium–high implied 4 points and high implied 5 points. Combining the ratings in equal weights, the overall weighted scores ranged from 1.0 to 4.75. Based on the distribution of these weighted scores, the overall efficiency of the transportation system is categorized as follows: low (⬍1.5 points.), low–medium (1.51–2.5 points.), medium (2.51–3.5 points.), medium–high (3.51–4.5 points.), and high (⬎4.5 points.). Bosnia–Herzegovina is classified as low in overall transportation efficiency. Nine countries are classified as medium in overall transportation

Roadways

Low Medium Low High Low–medium High Medium Low Low–medium Medium–high Medium–high Medium Medium–high Low–medium Low High Medium–high Medium

Country

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

Table 6 Transportation efficiency classification

Low Low–medium Low Low–medium Low Low–medium Low–medium Low Medium Low–medium Low Medium High High Low–medium High Low High

Railways Low–medium Low Low Medium–high Medium High Medium Low–medium Medium Medium Low Low High Medium–high Low Medium–high Low Medium–high

Merchant ships Medium Medium Low Low–medium Low Medium Low Medium–high Low Low Low–medium Low–medium High Medium–high Medium Low–medium Medium Low

Airlines

(continued on next page)

Low–medium (1.75) Low–medium (2.25) Low (1.0) Medium (3.25) Low–medium (1.75) Medium–high (3.75) Low–medium (2.25) Low–medium (2.00) Low–medium (2.25) Medium (2.50) Low–medium (2.00) Low–medium (2.25) High (4.75) Medium–high (3.75) Low–medium (1.75) Medium–high (4.00) Medium (2.25) Medium (2.25)

Overall

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Roadways

Medium 50,000–100,000 4–10 6000–9000 150–250

2.51–3.50

1–4 3000–6000 50–150

1.51–2.50

Merchant ships

Low–medium 20,000–50,000

Railways

3.51–4.50

250–350

9000–12,000

10–20

Medium–high 100,000–200,000

Airlines

⬎4.50

⬎350

⬎12,000

⬎20

High ⬎200,000

Overall

b

For Bosnia–Herzegovina and Serbia–Montenegro, the classification is based on length of roadways only. For Albania, Belarus, Bosnia–Herzegovina, Macedonia, Serbia–Montenegro, Slovenia and Ukraine, the classification is based on the length of railways only. c Bosnia–Herzegovina, Macedonia and Moldova have no merchant ships — thus classified as low. For Serbia–Montenegro, the classification is based on number of merchant ships only. For Belarus, no data is available, assumed low. d For Belarus, Bosnia–Herzegovina, Estonia, Serbia–Montenegro and Slovakia, the classification is based on the number of airports only. e Overall transportation efficiency determined by averaging (25% weights each) efficiency for roadways, railways, merchant ships and airlines. The ratings imply the following points for the efficiency of roadways, railways, merchant ships and airlines: low: 1 point, low–medium: 2 points, medium: 3 points, medium–high: 4 points, high: 5 points. Overall efficiency score range: 1.00–4.75.

a

Bases for classification scheme Variable Classification Low Roadways efficiency ⬍20,000 (tons)a Railways efficiency ⬍1 (million tons)b Merchant shipping ⬍3000 efficiency (tons/ship)c Airlines efficiency ⬍50 (million tonkm/airport)d Overall transportation ⱕ1.50 efficiency (points)e

Country

Table 6 (continued) L.A. Manrai et al. / International Business Review 10 (2001) 517–549 531

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efficiency; these include Albania, Belarus, Croatia, Estonia, Hungary, Latvia, Macedonia, Moldova, and Serbia–Montenegro. The medium categorization for overall transportation efficiency is given to Bulgaria, Lithuania, Slovenia and Ukraine. The medium–high overall transportation efficiency category included Czech Republic, Romania and Slovakia and overall the only country falling into the high overall transportation efficiency category was Poland. 4.1.2. Degree of privatization and development of retail sector For comparing the 18 countries in terms of degree of privatization and development of retail sector, a variety of information will be used, i.e. foreign direct investment, governmental efforts, retail sales level, number and type of retailers, etc. Internet trade directories are used for information sources mostly for large countries. We will first present the information countrywise and then conclude with an overall evaluation of the 18 countries into 5 groups capturing the degree of privatization and development of the retailing sector. The retailing sector in Albania, particularly in the capital city of Tirane and the port-city of Durres is doing quite well. This is attributed mainly due to the large scale foreign aid and remittances from friends and relatives abroad combined with a speedy privatization (Lowenberg, 1994). Foreign investment in Albanian oil and gas exploration sector is estimated at $150 million and this has given boost to the local economy in recent years. Belarus, the next country on the other hand has attracted only minimal direct foreign investment and the economy continues to be mainly agricultural (European Marketing Data and Statistics, 1998). The economy of Bosnia–Herzegovina also relies almost exclusively on agriculture, but much land is under dispute. Thus the retailing sector in these two countries, i.e. Belarus and Bosnia–Herzegovina is considered to be minimally developed. Bulgarian economy lags behind the other East-European countries in attracting foreign direct investment. Most production units and warehouses are still owned by the state and the former state-run monopolies manage production, distribution and transportation companies (Vanden Bloomen & Puranov, 1994). The total retail sales in Bulgaria in 1996 were estimated at $5.7 billion, amounting to about $648 per capita. Croatia is doing better compared to other regions of the former Yugoslavia. Roads and factories are being rapidly rebuilt and it has great ambitions for tourism (European Marketing Data and Statistics, 1998). The total retail sales in Croatia in 1996 were estimated at $5.0 billion; amounting to $1042 per capita. The Czech Republic has one of the most promising economies in Central and Eastern Europe. There is rapid development of private distribution systems and the private entrepreneurs are rebuilding distribution systems from scratch which, in part, is necessitated by the developments in the retail sector. It is estimated that the Czech Republic will have a distribution structure similar to that of Germany by the end of this century (Bryne & Jozefowski, 1994). Retail organizations are mostly managed by the private sector. The economy is characterized by a large number of smallscale retailers, few large department stores and chain grocery stores. Many US firms have developed their own distribution as well as ties with local firms. Foreign compa-

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nies like Levi Strauss, Benetton, Elizabeth Arden, etc are building up large scale retailing operations, but still for the most part, the economy is dominated by small scale retailing. The total retail sales in Czech Republic in the year 1996 were estimated at $20.6 billion amounting to a per capita sales of $2005. Estonia, the smallest of the Baltic republics was the first to declare independence in summer 1992 (European Marketing Data and Statistics, 1998). Today it is five years ahead of many other Eastern European countries. The port of Helsinki is the major transit port to Estonia (Kauhanen, 1993). However, in addition to the poor state of its infrastructure, security is another important consideration in this country. Small shipments could take up to a week to reach their destination by truck, the pilferage is high — even whole trucks are stolen — and motor carrier companies use older trucks to avoid being a target for theft or hijacking (Trunick, 1993). Hungary exhibits similar patterns as the Czech Republic, although, overall, its economy and thus the distribution systems and retailing sector are less developed. State owned distribution systems are being replaced by privately owned distribution systems. The economy is characterized mostly by small scale, family run operations, although, in the recent times, many large-scale foreign retailers have made inroads into Hungarian market place (Internet: Countrywise Trade Directories, 1998). These include Baumax (Germany), Cora (France), Humanic (Austria), Ikea (Sweden), La Strada (Italy), Marks & Spenser (UK), Metro (Germany), Michelfeit (Austria), Penny Market (UK) and Tesco (UK). Fotex, a local Hungarian company has diversified operations into a variety of retail sectors such as household appliances, consumer electronics, cosmetics, furniture, etc. The total retail sales in Hungary in 1996 were estimated at $13.3 billion, amounting to a per capita sales of $1289. Latvia and Lithuania are relatively smaller countries. However, reforms and privatization are being implemented in these countries with EU standards in mind. The total retail sales in these countries in the year 1996 were of the order of $2.3 billion and $2.1 billion, respectively. This amounts to $899 and $570 per capita. No specific information on the development of the retailing sector in Macedonia and Moldova is available. Considering that Macedonia is one of the poorest countries in this group, the development of the retail sector there is considered to be low. Moldova’s situation is considered quite comparable, perhaps a bit less developed than its neighbor Romania which is discussed next, after Poland. Poland is one of the most developed economy in this group of countries in many ways. Apart from a large population base of 39 million, Poland has a highly developed retail sector, with a total of 529,000 outlets, amounting to 14 stores per 1000 inhabitants (McQuaid, 1995). Competition, however, is fierce, and while brand recognition is important, a western brand has to compete for market share with hundreds of local brands that have flooded the market place. The retailing operations are mostly small scale although few foreign retailers like Ikea, Macro and Office Depot have established themselves successfully in the Polish market place. Small, ‘Mom & Pop’ stores have virtually cropped up everywhere in the last five years. While most stores sell a limited variety of products, their product-mix is scrambled across a variety of product categories, i.e. a small store may be selling food products and housewares, whereas another may be selling food products, books/stationery and

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candy. Thus there are no identifiable patterns of merchandise mix, leading to logistical complexities in distribution. Shelf space is limited and competition is high. A recent study by McQuaid (1995) identified four options for companies entering the Polish market. First, ‘cash rich’ companies can afford to manage their own direct distribution. This is best suited for products like snacks and soft drinks, where logistical problems and the heavy cost of merchandising require tight control by the producer. Second, companies using ‘sell to many’ strategy work through any wholesaler who is able to meet minimum requirements, with generally a large number (200– 400) of such wholesalers. Third, companies ‘striving to strike a balance’ between cost, control and coverage, a preferred distribution is fast becoming the most popular option. Finally, producers can also work through exclusive sales agreement with a number of regional distributors. In order to decide which of these distribution strategies will work the best, Western companies are increasingly using third party logistics companies for help in handling this complex distribution system (Hope, 1996). The total retail sales in Poland in the year 1996 were estimated at $47.7 billion amounting to per capita retail sales of $1235. Romania could easily become one of the busiest transportation hubs in Central and Eastern Europe due to its strategic location. It is one of the eastern most countries of the European continent and is located on the Black Sea, thus well connected to Western Europe, the Middle East and Asia. Yet its infrastructure and transportation equipment are inadequate and outdated (Crawford & Curry, 1997). In the recent years, however, there has been a steady growth in the development of the retail sector, particularly services industries. Recently, for example, the German trading group Metro International AG opened the first of its planned chain of wholesale markets at the outskirts of Bucharest (Wall Street Journal, 1996). Most of the local firms are small and medium size with limited financial resources. To address limitations imposed by this trait, Proctor and Gamble, Romania is developing ways to reduce its distribution costs, particularly van transportation costs, to its network of lower volume retailers (Interbrands Team Report, 1995). Recent reforms and improvements in legislation are geared toward attracting foreign investment. The best prospects are for companies in electrical power, computer, hardware and software and consumer goods (Crawford & Curry, 1997). The total retail sales in 1996 in Romania were of the order of $6.6 billion amounting to $290 per capita. Serbia and Montenegero’s economy shows relatively very little promise with unemployment rates of 40–50% and average wages of only about $125 per month. In Montenegero, smuggling is a favorite activity and this country aspires to develop a tax haven or off-shore banking rival to Cyprus (European Marketing Data and Statistics, 1998). The next country in this list, Slovakia, shows promise in the retail sector. As many as 98% of the retail shops are privatized and the most developed area is the capital city of Bratislava and its surroundings. Until recently, K-Mart and Ikea were the only major large-scale retailers, however Billa, an Austrian retail chain, is about to start operations in Slovakia. The Czech department store Kotva is also expected to soon develop a network of outlets in Slovakia. The overall retailing industry in Slovakia is still fragmented, with the top five retail companies owning only 5.2% of market share. Retail sales have been growing in the recent years, with

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total retail sales in 1996 being estimated at $8.8 billion, amounting to $1651 per capita. It is expected that the distribution patterns in Slovakia will soon resemble those in Western countries (Cialdella, 1997). Slovenia is the richest country of the former Yugoslavia and has best chance of closing gaps on living standards in Eastern Europe. Tight monetary and fiscal policy has kept inflation under control and GDP and per capita income have recorded growth in the last few years. The last country on this list, i.e. the Ukraine, is the largest in terms of population and area and has the second largest overall GDP after Poland as noted earlier. However, the GDP per capita of this country is quite low as compared to that of several other smaller countries in the list. The Ukraine has undergone an economic crisis in the 1990s and desperately needs economic reforms and outside investment. Ukraine has been called ‘Central Europe’s Ugly Duckling’. It only attracted about $200 million in foreign capital compared to the Czech Republic and Hungary, which attracted foreign capital of $750 million each in 1994. But the recent trends have been promising and the ugly duckling may turn into a beautiful swan in next decade or so. Inflation in the Ukraine has been brought down to 14% recently, compared to 10,000% in 1993, and unemployment is practically non-existent. No specific information on the development of retail sector is available. However, in view of the severe economic crises that this country has gone through in the 1990s, the development of the retail sector is not expected to be significant at present, though it has promise for the future. Based on the above discussion of the degree of privatization and development of the retail sector, it is concluded that the countries of Poland and the Czech Republic have the most developed retail sector and are rated high. On the other hand, the countries of Bosnia–Herzegovina, Macedonia and Serbia–Montenegro are evaluated as having the least developed retailing sector and are rated as low. The countries that seem to have some, although very limited, development of the retailing sector, and thus are rated low–medium, include Albania, Belarus, Bulgaria, Estonia and Slovenia. The countries which are not as promising as Poland and the Czech Republic, but seem to be fairly well developed in terms of retailing operations, include Hungary, Romania and Slovakia. These three countries are labeled as medium–high in retail sector development. The remaining five countries classified under the medium retail sector development category include Croatia, Latvia, Lithuania, Moldova, and the Ukraine. These ratings are summarized in Table 11. 4.2. Promotion infrastructure The variables used to evaluate the promotion infrastructure include the availability of the advertising media and the development of the advertising industry. 4.2.1. Circulation of newspapers and radios/TV’s owned The availability of advertising media is determined by computing the circulation of newspapers and number of radio and TV sets per 1000 people in the country. Table 7 summarizes the number of newspapers, circulation of newspapers (in 000), number of radio stations, number of radio sets in use (in 000), number of TV stations,

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Table 7 Advertising media availability Country

Newspapers #

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

4 10 2 54 9 24 15 46 8 NA NA 5 84 5 NA 35 6 NA

Radio Circulation (1000) 135 NA NA 552 494 3084 243 2345 344 NA NA NA 5697 1219 NA 1831 NA NA

Television

# Stations

# Radio sets # Stations (1000)

# TV sets (1000)

18 NA 11 35 22 NA NA 47 NA 39 8 NA 54 17 35 NA 11 NA

515 2900 800 4000 1174 6500 720 6350 1710 1435 390 3000 16,900 4680 2015 3030 370 41,800

255 2300 1012 3200 2138 4920 565 4360 1200 1430 355 1200 11,800 4600 1930 2530 330 17,520

9 NA 6 29 12 NA 5 41 NA 7 5 NA 40 13 18 NA 7 NA

European Marketing Data and Statistics (1998) and Internet: Countrywise Trade Directories (1998)

and number of TV sets in use (in 000). This information was compiled from European Marketing Data and Statistics (1998) Internet: Countrywise Trade Directories (1998). Next, the availability of advertising media per 1000 was computed using the population statistics reported earlier in Table 1. This information on advertising media availability per 1000 is summarized in Table 8. The distribution of statistics for the advertising media availability for each of the three media, i.e. newspapers, radios, and TV’s was examined to develop a classification scheme. This information is summarized in Table 9. Where the availability could not be computed due to missing information, for example, on the circulation of newspapers, the classification was done based on the number of newspapers. When information on both the number of newspapers and circulation was missing, other qualitative information was used for classification. The ratings distributions and the countries classified under the five categories of low, low–medium, medium, medium– high and high for each of the three advertising media as well as the overall classification are discussed next. Newspaper circulation was classified as follows: low (⬍100 per 1000 people), low–medium (100–150 per 1000 people), medium (150–200 per 1000 people), medium–high (200–300 per 1000 people) and high (⬎300 per 1000 people). Based on this classification scheme, eight countries were classified under the low category.

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Table 8 Advertising media availability per 1000 Country

Albania Belarus Bos–Herz Bulgaria Croatia Czech Rep Estonia Hungary Latvia Lithuania Macedonia Moldova Poland Romania Serb–Mont Slovakia Slovenia Ukraine

Newspaper circl. (per 1000) 39.59 NA NA 62.87 105.78 295.69 149.08 227.23 124.64 NA NA NA 146.87 52.54 NA 337.20 NA NA

# Radio sets (per 1000)

# TV sets (per 1000)

151.03 277.78 250.00 455.58 251.39 623.20 441.72 615.31 619.57 369.84 180.56 668.15 435.68 201.72 181.53 558.01 180.49 805.86

74.78 220.31 316.25 364.46 457.82 471.72 346.63 422.48 434.78 368.56 164.35 267.26 304.20 198.28 173.87 469.93 160.98 337.77

These included Albania, Bosnia–Herzegovina, Bulgaria, Macedonia, Moldova, Romania, Serbia–Montenegro and Slovenia. Six countries were classified as having low– medium circulation of newspapers and these included Belarus, Croatia, Estonia, Latvia, Lithuania and Poland. None of the countries fitted the classification under the medium circulation group. The countries classified as medium–high group included the Czech Republic, Hungary and the Ukraine. Finally, the only country classified as having high newspapers circulation was Slovakia. Availability of radio sets was classified as follows: low (⬍200 per 1000 people), low–medium (200–400 per 1000 people), medium (400–600 per 1000 people), medium–high (600–800 per 1000 people) and high (⬎800 per 1000 people). Based on this classification scheme, four countries were classified in the low category. These included Albania, Macedonia, Serbia–Montenegro and Slovenia. Five countries were classified under the low–medium category, i.e. Belarus, Bosnia–Herzegovina, Croatia, Lithuania and Romania. The medium category included four countries, i.e. Bulgaria, Estonia, Poland and Slovakia. The medium–high category included four countries, i.e. the Czech Republic, Hungary, Latvia and Moldova and the only country classified under the high category was the Ukraine. As regards the availability of TV sets, the classification scheme was as follows: low (⬍100 per 1000 people), low–medium (100–200 per 1000 people), medium (200–300 per 1000 people), medium–high (300–400 per 1000 people) and high (⬎400 per 100 people). Based on this classification scheme, Albania was categorized as low. The low–medium category included four countries, i.e. Macedonia, Romania, Serbia–Montenegro and Slovenia. The medium category included two countries, i.e.

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Table 9 Evaluation of advertising media availability per 1000 Country

Newspapers circulation

# Radio sets

# TV sets

Overall

Albania Belarus

Low Low–medium

Low Low–medium

Low Medium

Bos–Herz

Low

Low–medium

Medium–high

Bulgaria Croatia Czech Rep

Low Low–medium Medium–high

Medium Low–medium Medium–high

Medium–high High High

Estonia Hungary

Low–medium Medium–high

Medium Medium–high

Medium–high High

Latvia

Low–medium

Medium–high

High

Lithuania Macedonia Moldova Poland Romania

Low–medium Low Low Low–medium Low

Low–medium Low Medium–high Medium Low–medium

Medium–high Low–medium Medium Medium–high Low–medium

Serb–Mont Slovakia Slovenia Ukraine

Low High Low Medium–high

Low Medium Low High

Low–medium High Low–medium Medium–high

Low (1.00) Low–medium (2.33) Low–medium (2.33) Medium (2.67) Medium (3.00) Medium–high (4.33) Medium (3.00) Medium–high (4.33) Medium–high (3.67) Medium (2.67) Low (1.33) Medium (2.67) Medium (3.00) Low–medium (1.67) Low (1.33) High (4.67) Low (1.33) Medium–high (4.33)

Low–medium 100–150

Medium 150–200

Medium–high 200–300

High ⬎300

200–400

400–600

600–800

⬎800

100–200 1.51–2.50

200–300 2.51–3.50

300–400 3.51–4.50

⬎400 ⬎4.50

Bases for classification scheme Variable Classification Low Newspapers ⬍100 circulationa (per 1000) Radios (per ⬍200 1000) TVs (per 1000) ⬍100 Overall ⱕ1.50 advertising media availabilityb (points)

a For Belarus, Bosnia–Herzegovina, Moldova and Slovenia, the classification is based on number of newspapers. For Lithuania, Macedonia, Serbia–Montenegro and Ukraine, the classification is based on other qualitative information. b Overall advertising media availability determined by averaging (33 1/3% weights each) statistics for newspaper circulation per 1000 and number of radios and TVs per 1000. The ratings imply the following points for newspaper, radios and TVs availability: low: 1 point, low–medium: 2 points, medium: 3 points, medium–high: 4 points, high: 5 points. Overall availability score range: 1.00–4.67.

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Belarus and Moldova. Six countries were classified under the medium–high category and these included Bosnia–Herzegovina, Bulgaria, Estonia, Lithuania, Poland and the Ukraine. The high category included five countries, i.e. Croatia, the Czech Republic, Hungary, Latvia and Slovakia. The overall availability of the advertising media was determined by combining the ratings of the countries for each of the three individual media in equal (33 1/3%) weights. For each of the three individual media, a rating of low implied 1 point, low–medium implied 2 points, medium implied 3 points, medium–high implied 4 points and high implied 5 points. Combining the ratings in equal weights, the overall weighted scores ranged from 1.00 to 4.67. Based on the distribution of these weighted scores, the overall availability of advertising media is categorized as follows: low (⬍1.5 points), low–medium (1.51– 2.50 points), medium (2.51–3.50 points), medium–high (3.51–4.50 points) and high (⬎4.50 points). Based on this classification scheme, four countries were classified under the low category. These included Albania, Macedonia, Serbia–Montenegro and Slovenia. Three countries were classified as low–medium, i.e. Belarus, Bosnia– Herzegovina and Romania. The medium category included six countries, i.e. Bulgaria, Croatia, Estonia, Lithuania, Moldova and Poland. The medium–high category included four countries, i.e. the Czech Republic, Hungary, Latvia and the Ukraine. Finally, only Slovakia fitted the classification under the high category. 4.2.2. Development of advertising industry and acceptance of advertising For comparing the 18 countries in terms of development of advertising industry and acceptance of advertising, a variety of information sources will be used, i.e. number of advertising agencies available in each country (compiled from Standard Directory of Advertising Agencies, 1998), major advertising laws and regulations, advertising expenditures by media, consumers’ attitude toward advertising, etc. We will first present the information countrywise and then conclude with an overall evaluation of the 18 countries into five groups, capturing the degree of advertising industry development and acceptance of advertising. An overall listing of advertising agencies in these 18 countries is provided in Table 10. No information is available on the number of advertising agencies or advertising expenditure by media in Albania. Going by other developments in general in Albania, the advertising industry in this country is considered to be one of the least developed. In Belarus, the next country on the list, the only advertising agency noted was Bates Primary Saatchi & Saatchi. No information is available on the development of advertising industry in Bosnia–Herzegovina either. Once again based on the development status in general of this country, the advertising industry is considered to be one of the least developed. Bulgaria has at least 11 different advertising agencies tested in the capital city of Sofia, as detailed in Table 10. TV seems to be the most popular media of advertising, attracting as much as 61% of the advertising expenditure. This is followed by print (23%), radio (12%) and others including outdoor (4%). In Bulgaria, two major types of foreign advertisers on TV are the manufacturers of tobacco products and alcoholic beverages. Compared to this, the local companies advertising their products in Bulga-

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Table 10 Advertising agencies in Central and Eastern Europe Albania NA Belarus: Minsk Bates Primary Saatchi & Saatchi Bosnia–Herzgovina NA Bulgaria: Sofia-11 Nos. Champions Leo Burnett Advertising DDB

Estonia: Tallinn-7 Nos. Poland: Warsaw-25 Nos. Artmiks Lts. Ammirati Puris Linta Bates Adell Saatchi & Saatchi Advertising Bates Adell Saatchi & Saatchi Hill & Knowlton Eesti AS Inorek and Grey Kontuur-Leo Burnett Estonia Zavod

BBDO Warsaw

Slovakia: Bratislava-8 Nos. Creo Young & Rubicam DDB Bratislava

Bates Saatchi & Saatchi Biuro Reklamy

Foote, Cone & Belding Grey & Soria

Leo Burnett Warsaw

Istropolitana/DMB & B Mark/BBDO

Burson-Marsteller Conquest Europe

Grafitti/BBDO

Hungary: Budapest-25 Corporate Profiles Nos. DDB Ammirati Puris Lintas DMB & B Warsaw

Grey Sofia

BBDO Budapest

International Media Concepts/DMB7B Interpartners Bulgaria Leo Burnett Advertising

Bates Saatchi & Saatchi Advertising Bates Saatchi & Saatchi Leo Burnett Budapest

Ogilvy & Mather Sofia PBI Advertising Ltd.

Burson-Marsteller DDB

Foote, Cone & Belding GGK Warsaw Grey Waszawa

S Team Saatchi & Saatchi Advertising Spot Advertising Sofia

DMB & B Budapest

ITI McCann-Erickson

E/B/D-Interpartners Budapest KFT EURO RSCG

Oglivy & Mather

Croatia: Zagreb-5 Nos. BBDO Zagreb Grey Zagreb McCann- Erickson

S Team Bates Saatchi & Saatchi

Fokusz Marketing Kommunikacio KFT Foote, Cone & Belding KFT GGK Budapest

Grey Budapest

E/B/D/Interpartners Warszawa Eisner Strategic Communications EURO RSCG

Oglivy One Worldwide F.F.R./ARIP The Rowland Company The Rowland Company Saatchi & Saatchi Advertising

McCann Erickson Bratislava Ogilvy & Mather s.r.o. Slovenia: Ljubljana-10 Nos. Formitas Grey Ljubljana Luna Mayer & Company McCann-Erickson S Team Bates Saatchi & Saatchi Advertising Studio Marketing Vision Factory Productions Votan Leo Burnett Ukraine: Kiev-4 Nos. Leo Burnett Kyiv Burson Marsteller/International NIS DMB & B LLC/Kiev (continued on next page)

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Table 10 (continued) S Team Saatchi & Saatchi Advertising Czech Republic: Prague-25 Nos. ARK Communications Adverta

Hill & Knowlton Hungary Hoffmann, Kossler, Baticz (HKB) Bozell McCann-Erickson Budapest NAP-TV

Ammirati Puris Lintas

Ogilvy & Mather

Avant Bozzell

Partners J. Walter Thompson Budapest The Rowland Company Scholtz & Friends Budapest The Network

Bates Saatchi & Saatchi Advertising Bates SSA Czech Republic Bates SSA Czech Republic/Slovakia Leo Burnett Advertising

Ceska Reklamni/TBWA

Wunderman Cato Johnson Young & Rubicam Hungary Latvia

DDB A.S.

NA

DMB & B Prague

Lithuania

EURO RSCG Foote, Cone & Belding

NA Macedonia:Skopje-2 Nos. S Team Bates Saatchi & Saatchi Advertising Balkans SMS Saatchi & Saatchi Moldova

Burson-Marsteller

GCI Praha

Hill & Knowlton Prague J. Walter Thompson/ARK Communications Mark/BBDO McCann-Erickson Prague

NA

Scholtz & Friends Warszawa The Network Wunderman Caro Johnson Young & Rubicam Poland Romania: Bucharest12 Nos. B V McCann Erickson Romania Bates Saatchi & Saatchi Leo Burnett & Target Centrade Saatchi & Saatchi Advertising Graffitti/BBDO Grey Bucuresti Monopoly International S.A. OFC/DMB & B Bucharest Oglivy & Mather Bucharest Scala JWT Advertising The Network Young & Rubicam Bucharest Serbia–Montenegro: Belgrade-3 Nos. The Network Ogilvy & Mather Belgrade SMS Bates Saatchi & Saatchi

Ogilvy & Mather Ogilvy & Mather Focus Scholtz & Friends Praha The Network Wunderman Cato Johnson Young & Rubicam Prague Source: Standard Directory of Advertising Agencies (1998)

Provid/BBDO

541

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ria mostly represent the service sector (East European Markets, 1996). Croatia, the next country of the list has five different advertising agencies listed in the capital city of Zagreb, as detailed in Table 10. The advertising industry in the Czech Republic seems to be quite well developed, with as many as 25 different advertising agencies listed in the capital city of Prague. Advertising is a fast growing business and all forms of media are used, i.e. TV, radio, print, public transport, outdoor, etc. Print media seems to be the most popular, attracting as much as 45% of the advertising expenditure. This is followed by TV (36%), outdoor and others (12%) and radio (7%). Consumers and firms place high value on effectiveness of advertising. Although considerable amount of advertising expenditure is devoted to consumer packaged goods, price is a more dominant attribute in product choice than brand recognition. Estonia has seven different advertising agencies listed in the capital city of Tallinn, as detailed in Table 10. Print media is clearly preferred over other forms of advertising, attracting as much as 64% of the advertising expenditure. This is followed by TV (23%), outdoor (8%) and radio (5%). The advertising industry in Hungary also seems to be quite well developed. As many as 25 different advertising agencies are listed in the capital city of Budapest, as detailed in Table 10. Print media is slightly more popular (45% of advertising expenditure) as compared to TV (39% of advertising expenditure). The share of radio and outdoor and other media is 9% and 7%, respectively. TV advertising is gaining popularity. It is predicted that TV will gain a few percentage points from print advertising in the near future (Csonka, 1997). Billboard advertising and advertising in the kiosks is quite popular, targeted primarily at youth and the rising middle class. The competition faced by Western brands is quite intense because consumer loyalty for Hungarian-made products is quite high and also due to the fact that price is a dominant factor in choice and purchase decisions. Advertising laws prohibit advertising that is misleading or which disparages competition. Recent regulations prohibit advertising tobacco and alcohol within 200 meters of a school or health care institution (MTI Econews, 1997). No information is available on number of advertising agencies in Latvia. Some information exists, however, on the popularity of different media. Print media seems to be the most popular, attracting as much as 52% of all advertising expenditure. This is followed by TV (35%), outdoor and others (9%) and radio (4%). For middle and lower class consumers, price matters the most in their purchase decision. Lithuania shows similar advertising expenditure patterns as Latvia. Print is the most popular advertising medium, attracting 47% of all advertising expenditure. This is followed by TV (34%), radio (13%) and outdoor and others (6%). The advertising agencies listed in the capital city of Skopje in Macedonia included Bates Saatchi & Saatchi Advertising Balkans and SMS Saatchi & Saatchi. Considering the overall status of Macedonia’s economy, the development of advertising in this country is estimated to be low. No information on the status of advertising industry in Moldova is available. Going by the other general information and characteristics, Moldova is likely to have a somewhat lower level of developments compared to its neighbor Romania, which is discussed later.

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Poland is also one of the countries with perhaps the most developed advertising industry. As many as 25 different advertising agencies operate in the capital city of Warsaw, as detailed in Table 10. While information on the break up of advertising expenditure by media is not available for Poland, it appears that TV is the most popular media. The television networks now include many private TV channels and cable networks which are planning to introduce home shopping channels. While other direct marketing and advertising approaches such as the internet and direct mail are increasing in popularity, most Poles prefer to buy goods in person. The proliferation of TV’s is high, as well as that of print media, due to the high literacy rates in Poland. Yet another popular media in Poland is special event advertising. Heavy promotion and advertising of beer is done at rock concerts, sporting events, etc. This is primarily targeted at the youth segment (Swiatkiewicz, 1997). Romania has 12 different advertising agencies listed in the capital city of Bucharest, as detailed in Table 10. TV is extremely popular, accounting for 71% of all advertising expenditure, followed by print advertising (17%), radio (8%) and outdoor and others (4%). Romanian TV includes two state owned national networks, i.e. TVR1 with 100% reach and TVR2 with 40% reach. In addition to these state owned national networks, there are several other state-owned local networks, several privately owned TV networks and cable news network (CNN). The developments in TV networks in Romania in part are attributed to Adrian Sarbu who was the media adviser to the first post-communist government in Romania and helped to draft rules to open the television market. Since these rules became law in 1992, over 100 cable, satellite and conventional television broadcast licenses have been issued, about 40 of which are in active use. Over three million Romanian households, nearly half the total, now subscribe to cable television, making Romanians comparable to consumers in Germany and Belgium (The Economist, 1996). The overall size of the television advertising industry in Romania is estimated at $25 million (East European Markets, 1996). Radio networks include three state owned AM networks geared primarily toward popular youth culture. Other FM stations have a broader audience. The reach of print advertising is also likely to be high with over 60% of the population reading at least one newspaper a day. Other popular forms of advertising include movies and billboards. Overall the advertising industry in Romania is considered to be quite well developed. Three advertising agencies were listed in the capital city of Belgrade for Serbia and Montenegro. Considering the overall status of the economy of this country, the development of the advertising industry is considered to be low. With regards to the next country on the list, i.e. Slovakia, eight different advertising agencies were listed in the capital city of Bratislava, as detailed in Table 10. Print media accounted for 42% share of all advertising expenditure, followed closely by TV at 39%. Outdoor and other media accounted for 10% and radio accounted for 9%. Use of billboards is significant especially in large cities and along the highways. Another popular venue for advertising is the use of posters which are found in all public places. Slovenia shows very similar characteristics to Slovakia. Ten different advertising agencies were listed in the capital city of Ljubljana, as detailed in Table 10. Similar to Slovakia, the share of print advertising was a dominant 44%, followed closely by

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TV at 36%. The share of radio advertising and outdoor advertising was 16 and 4%, respectively. Ukraine has four different advertising agencies listed in the capital city of Kiev. These include Leo Burnett Kiev, Burson Marstiller/International MIS, DMB & B LLC/Kiev and Provid/BBDO. No other information on promotion is available. Based on the information discussed above, it is concluded that the Czech Republic, Hungary, Poland and Romania have the most developed advertising industry and are rated high. On the other hand, the seven countries of Albania, Belarus, Bosnia– Herzegovina, Latvia, Lithuania, Macedonia and Serbia–Montenegro seem to have low levels of advertising industry development and are consequently classified as low. The four countries of Bulgaria, Estonia, Slovakia and Slovenia seem to have about average level of advertising industry developments and these are classified as medium. Although no specific information is available on Moldova, it is also classified into the medium group based on comparison of its economy in general with Romania. The two countries of Croatia and the Ukraine are classified into low– medium category and no country is designated as medium–high in advertising industry development. These ratings are summarized in Table 11.

5. Country attractiveness evaluation (based on distribution and promotion infrastructure) The ratings of the 18 countries on the four factors discussed above are summarized in Table 11. These include two factors to measure the distribution infrastructure, i.e. transportation efficiency and development of retailing sector and two factors to measure the promotion infrastructure, i.e. advertising media availability and development of advertising industry. The ratings on these four factors are combined to develop measures of country attractiveness. The procedure for aggregation of the information is as follows: 1. The five subgroups for each of the four factors discussed above are treated as ratings on a 5-point scale. Thus low implies 1 point, low–medium implies 2 points, medium implies 3 points, medium–high implies 4 points and high implies 5 points. 2. The four factors are assigned importance weights as follows: transportation efficiency — 30%, development of the retailing sector — 20%, advertising media availability — 30% and development of advertising industry — 20%. The rationale for these weights is derived with reference to their importance for marketing of goods in a country. Basic distribution infrastructure (transportation) and basic promotion infrastructure (media) are assigned somewhat higher weights than other related factors in the area of distribution and promotion, i.e. retailing and advertising industry developments, respectively. 3. The country ratings on the four factors are aggregated with the importance weights for the four factors using a linear/expectancy value model to arrive at overall weighted evaluations given in Table 11 (individual ratings on the four factors are

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Table 11 Country attractiveness evaluation (based on distribution and promotion infrastructure) Country

Distribution infrastructure

Promotion infrastructure

Transportation efficiency

Retail sector development

Advtg. media availability

Advtg. industry development

Albania Belarus

Low–medium Low–medium

Low–medium Low–medium

Low Low–medium

Low Low

Bos–Herz Bulgaria Croatia

Low Medium Low–media

Low Low–medium Medium

Low–medium Medium Medium

Low Medium Low–medium

Czech Rep

Medium–high

High

Medium–high

High

Estonia

Low–medium

Low–medium

Medium

Medium

Hungary

Low–medium

Medium–high

Medium–high

High

Latvia Lithuania Macedonia Moldova Poland

Low–medium Medium Low–medium Low–medium High

Medium Medium Low Medium High

Medium–high Medium Low Medium Medium

Low Low Low Medium High

Romania

Medium–high

Medium–high

Low–medium

High

Serb–Mont Slovakia

Low–medium Medium–high

Low Medium–high

Low High

Low Medium

Slovenia

Medium

Low–medium

Low

Medium

Ukraine

Medium

Medium

Medium–high

Low–medium

Overall evaluationa

Low (1.50) Low–medium (1.80) Low (1.30) Medium (2.80) Low–medium (2.50) Medium–high (4.40) Low–medium (2.50) Medium–high (3.60) Medium (2.60) Medium (2.60) Low (1.30) Medium (2.70) Medium–high (4.40) Medium–high (3.60) Low (1.30) Medium–high (4.10) Low–medium (2.20) Medium (3.10)

a

Weights are: transportation efficiency — 30%, retail sector development — 20%, advertising media availability — 30%, advertising industry development — 20%.

multiplied by their respective weights and the products added together). The weighted scores range from 1.30 to 4.40.

6. Country-cluster matrix The two sets of country ratings, i.e. based on demographic and economic indicators as given in Table 2 and based on distribution and promotion infrastructure as given in Table 11, are combined to develop an overall matrix of country clusters as given

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in Table 12. It should be noted that in developing this matrix, precise scores are used (also given in Table 12). As can be seen from Table 12, this country-cluster analysis sort of indicates a linear relationships between demographic-economic dimension and distribution-promotion dimension and results in identification of three country clusters. Cluster 1 comprises of countries that are at least medium or higher on each of the two dimensions, i.e. demographic–economic indicators and distribution–promotion infrastructure. This cluster is labeled Medium to Medium–High (MMH) developed countries. MMH group of countries includes the Czech Republic, Hungary, Poland, Romania, Slovakia and the Ukraine. At the other extreme is Cluster 3 where most of the countries are low on both dimensions or at best low–medium. This cluster is labeled Low to Low–Medium (LLM) developed countries. LLM group of countries includes Albania, Bosnia–Herzegovina, Macedonia and Serbia–Montenegro. The middle cluster, i.e. Cluster 2, comprises of countries which are mostly low– Table 12 Country clusters (based on demographic–economic and distribution–promotion dimensions)

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medium to medium on the two dimensions. This cluster is labeled accordingly LMM. The LMM group of countries includes Belarus, Bulgaria, Croatia, Estonia, Latvia, Lithuania, Moldova and Slovenia. Further rankings of the countries within a cluster can be judged by their respective coordinates on the two dimensions, also given in Table 12.

7. Discussion and future research In this research, a country-cluster matrix was developed for 18 Central and Eastern European countries using two dimensions, i.e. demographic and economic indicators as one dimension and distribution and promotion infrastructure as the other dimension. The demographic and economic indicators reflect the overall size of the market and its economic potential, whereas the distribution and promotion infrastructure reflects the ease or difficulty of marketing goods in a country. For an international marketer, therefore, both of these considerations are important in country selection decision. Three country clusters were identified as indicated in Table 1. Cluster 1 includes countries which were rated MMH on each of the two dimensions. This is the most promising group of countries where market potential is fairly high and the distribution and promotion infrastructure is fairly well developed as well. While four out of five countries included in this group are population-wise large countries, i.e. the Czech Republic, Hungary, Poland and Romania, the fifth country included in this group, i.e. Slovakia, is a relatively smaller country. Slovakia has moved into this group on account of its fairly well-to-do economy and developments in distribution and promotion infrastructure. This suggests that the size of the market should not be the only consideration in determining the attractiveness of international markets. This point is also reinforced by the structure of Cluster 3. Cluster 3 is the least promising group of countries with country ratings being LLM. While three out of four countries included in this group are small countries, i.e. Albania, Bosnia–Herzegovina and Macedonia, the fourth country, i.e. Serbia–Montenegro, is a fairly large country. The reason why Serbia–Montenegro was classified into the least attractive group of countries is due to the poor state of its economy and minimally developed distribution and promotion infrastructure. Once again this goes to show that going by simply the size of the market is not a wise approach to evaluation of a country for international marketing. Perhaps the most interesting cluster is Cluster 2 where the trade off between the two dimensions, i.e. demographic–economic indicators and distribution–promotion infrastructure is most striking. This group of countries mostly includes those rated LMM. Within this cluster three sub-groups can be identified. The first subgroup includes Bulgaria, Moldova and Croatia, where demographics and the economy is not as promising but the developments in distribution and promotion infrastructure are reasonable. On the other hand, the second subgroup of countries characterized by relatively better demographics and economy but much less promising distribution and promotion infrastructure are Belarus, Estonia and Slovenia. The third subgroup

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comprising of Latvia and Lithuania indicates balanced developments on both dimensions. For this cluster, particularly for subgroups one and three, perhaps the best strategy would be to carefully monitor recent developments in the economy, as well as in distribution and promotion infrastructure as this cluster is still evolving and holds promise for the future. Compared to this, Cluster 1 is already promising, is relatively more stable and has immediate potential. Cluster 3 is evolving but it is likely to hold very little promise at least in the near future. In developing these country clusters, we have taken into account selected demographic and economic indicators and selected distribution and promotion related considerations. This analysis can be made more elaborate and more insightful by including other variables. For example, one of the variables certainly worth including in this analysis will be the developments related to information and communication technology as and when data is available in this area. Yet another possible expansion of this research could be longitudinal studies which will reveal patterns of shifts in country clusters. Also, averaged, multiple year measures of indicators will provide insights into the stability of these clustering patterns. Further, the analysis is done for each country as a whole, it is possible that certain sectors within the economy hold more promise than the others and such an analysis can guide the international marketing strategy at a more micro level. These are some of the issues that future research can address.

Acknowledgements The authors wish to acknowledge the research grant provided by the William Davidson Institute at the University of Michigan Business School for this research project.

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