In this section descriptive statistics are presented to provide necessary information about the characteristics of the research participants and key statistics before presenting the results of hypotheses testing. First, the breakdown of the research participants by industry is presented in Table 16. Results show that the bulk of the participants are from the textile, clothing, and apparel industry (20.27%). The metal, iron-steel, and machine industry and construction equipments industry constituted 10.87% and 9.40% of participants respectively. Participants from the food and beverages industry accounted for an additional 7.13%. Other industries included consumer durables, cement, glass, and ceramic, electrical equipments, electronics, information systems, retail, automotive and automotive parts, petroleum, energy and other industries. All in all, the research covered wide variety of product related industries and none of the industries dominated the participant base, which fosters generalizability of the results at least within Turkish context and alleviate potential industry biases in the results. Moreover, industry makeup of the participant firms roughly corresponds to the sectorial makeup of top 1000 Turkish exporters (TIM 2013).
Table 16. Research Participants by Industry
Industry Frequency Raw percentage Net percentage
Consumer durables 19 7.0 4.67
Cement, glass, and ceramic 12 4.4 2.93
Electrical equipments 12 4.4 2.93
Electronics, information systems 14 5.2 3.47
Food and beverages 29 10.7 7.13
Furniture and derivatives 20 7.4 4.93
Petroleum, energy 17 6.3 4.20
Textile, clothing, apparel 82 30.4 20.27
Medical, chemical, pharmaceutical 24 8.9 5.93
Other 43 15.9 10.60
Total 405* 150* 100
* Because participants could choose more than one industry, given the realities of Turkish business environment, the number and percentage of the stated industries exceeded the number of participants, which are 270.
Table 17 shows the matrix of key international activity types of participant firms by region. This descriptive information reveals that export is the most common international involvement choice by Turkish firms and many firms are present across wide range of geographies. The statistics indicate that, despite recent expansion into African and Middle-Eastern geographies, the most important markets for Turkish firms are still European markets as stated in a recent report by Turkish exporters assembly (TIM 2013), but the coverage of European countries visibly extend beyond the European Union and includes Eastern European and Balkan countries. Furthermore, relatively strong presence in the continents of Africa and Americas indicate that geographical obstacles are not a primary hindrance to international expansion of Turkish firms. Licensing and franchising practices are primarily applied by firms in apparel, food, and retail industries and are concentrated in closer geographies.
Table 17. Research Participants by International Involvement
Region
Furthermore, the data show that significant number of Turkish firms also follows greenfield investment and/or acquisition strategies, distributed in a relatively more balanced way across geographies than licensing and franchising except Americas. This result provide empirical evidence to the notion that Turkish firms are becoming increasingly active and visible in the global business environment (Demirbag et al. 2009). Consequently, the research participants’ international activities encompass broad range of regions and activity types.
Table 18 exhibits most popular host countries, out of the 66 countries that were mentioned at least once as the most or second most host country by the 270 participating firms, for the participant firms. As expected, Germany and Russia are by far two most important countries for the research participants. Turkey and Germany have had long, sophisticated, and extensive trade and investment relationship throughout recent history. In turn, Russian and Turkish economies are highly complementary to each other and, with the facilitating role of geographical proximity and historically rich socio-cultural ties, Turkish firms appear to leverage the opportunity of doing business in Russia. Furthermore, the coverage of the list also confirms that geography and psychic distance (Johanson
& Vahlne 1977) are not likely to be primary barriers for Turkish firms’
international activities. Likewise, most important countries for the research participants roughly match with the list of Turkey’s major trade and business partners (CIA 2014). All in all, the list, which exhibits sufficient representation of Turkey’s major economic ties, reveals that countries that are important to participant firms comprise a broad range and exhibits diverse institutional characteristics.
Table 19 shows participant demographic statics of number of employees, firm annual revenue, firm age, and employment duration within the current firm of survey respondents. The distribution of number of employees and annual revenue indicates that firms of different sizes were represented fairly equally. The distribution of firm age indicates that the middle-aged firms represented the majority of the participants. Returning to number of employees, roughly half of the participants firms have less than 250 employees, giving a fair share to small and medium sized firms in the sample. Likewise, nearly half (48.9%) of the participant firms have less than TRY 100.000.000 in revenue (EUR 1 = TRY 2.88 and USD 1 = TRY 2.16 as of August, 13th 2014). On the other hand, large firms were also represented fairly within the research sample, with about 24.3% of participant firms employing more than 1000 employees and 16.7% having more than 1.000.000.000 TRY in annual revenue.
Table 18. Top 25 Host Countries as Stated by Participants Country stated as
most important Number of
times stated Country stated as
second most important Number of times stated
Table 19. Research Participants by Key Demographic Information
Firm Size
Moreover, the data on the duration of employment in the current firm for a total of 540 participant key informants, two for each firm, were gathered at the individual level rather than firm-level unlike other question in the survey. Despite relatively dynamic and flexible labor market in Turkish business environment (Arandarenko 2004), only 11.9% of the respondents reported less than two years of work experience. Though job titles were too diverse to report as a descriptive statistics, it was ensured that all participants in the final sample were competently informed about both marketing and SCM functions and operations of their firm, and their positions were typically middle and upper levels, including firm owners and partners, CEOs, CMOs, COOs, marketing directors, operations / SCM directors, export directors, heads of foreign operations, marketing managers, and operations / SCM managers. Overall, responses to the questions related to experience (measured through work duration), responsibilities, and knowledge of the participants provide confidence to the appropriateness of these participants as the key informants in this research.
Table 20 presents the correlations among the key concepts that are examined in this research. The matrix shows that most of the significant correlations are grouped within perceptual measures and archival measures respectively, but only institutional uncertainty measured through secondary data correlates with SCA that was measured through primary data collection. AC appears to correlate with three other relevant DCs at over 0.5 range, indicating slightly higher average correlation values than the other DCs. Likewise, it is interesting to notice negative significant correlation between institutional uncertainty (IUNC) and institutional distance (IDST), indicating that countries with less institutional distance to Turkey are likely to exhibit higher rates of institutional uncertainty.
Table 20. Correlations among the Focal Concepts
SCA RC INV AC IPR IDVP IDST IUNC
SCA 1 0.677** 0.434** 0.531** 0.430** 0.107 0.100 -0.129*
RC 1 0.495** 0.605** 0.498** 0.012 0.086 -0.030
INV 1 0.551** 0.368** 0.032 0.070 -0.020
AC 1 0.450** 0.073 0.100 -0.095
IPR 1 0.119 0.104 -0.152*
IDVP 1 0.607** -0.888**
IDST 1 -0.680**
ISUNC 1
Mean 5.884 5.975 5.876 5,767 5,617 4.096 1.703 4.208
SD 0.711 0.624 0.814 0.743 0.943 0.649 0.575 0.878
* Significant at p<0.05 level
** Significant at p<0.01 level