A city-level investigation of the determinants of import trade in
China
By: Xueli Han Student number: 10824235
Data: 29 June 2015
MSc Business Administration: International management Final Version Master Thesis
Supervisor: Dr. Niccolò Pisani Second supervisor: Dr. Lori DiVito
STATEMENT OF ORIGINALITY
This document is written by Student Xueli Han who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
ABTRACT
Extensive research has conducted about specific determinants of trade. In this field the determinants of imports is relatively unexplored. Recent findings suggest that environmental, organizational and managerial factors have main impacts on imports trade at firm-level and country-level. This thesis examines the determinants of imports at city-level by introducing multi-level assessment. Specifically, this thesis certifies the effect of GDP, the volume of export, and inward foreign direct investment (FDI) of a city on its imports performance. Moreover, the moderating effect of the level of education and R&D on the relationship between predictors and imports performance is studied in this thesis. Using a sample of 295, including government-published 291 prefecture-level cities and 4 municipalities, the findings suggest all of determinants have positive effects on the volume of imports in a city. A city with an importing focus could either increase GDP, the volume of exports, and inward FDI or enhance level of education and R&D to an even greater level since the findings suggest that moderators boost the positive relationship between independent factors and imports performance.
Keywords: determinants of imports trade; GDP; the volume of exports; inward FDI;
TABLE OF CONTENT
1. INTRODUTION ... 6
2. LITERATURE REVIEW ... 9
2.1 China as an empirical setting ... 15
2.2 Research gap ... 17
3. THEORETICAL FRAMEWORK ... 18
3.1 The growth of GDP ... 18
3.2 The volume of exports... 20
3.3 Inward FDI ... 22
3.4 Moderating factors ... 23
3.4.1 The moderating role of level of education ... 23
3.4.2 The moderating role of investment in R&D... 25
4. METHODOLOGY ... 28
4.1 Sample and data collection... 28
4.2 Measures... 29
4.2.1 Dependent variable... 29
4.2.2 Independent variable ... 29
4.2.3 Moderating variable ... 30
4.2.4 Control variable... 31
4.3 Statistical analysis and results ... 32
5. DISCUSSION ... 39
5.1 Academic relevance ... 39
5.2 Policy implication ... 41
5.3 Limitations and suggestions for future research ... 42
6. CONCLUSION... 44
ACKNOWLEDGEMENT ... 46
LIST OF FIGURE
Figure 1. Conceptual model ... 27
LIST OF TABLES Table 1. Articles addressed in import-related areas ... 11
Table 2. Import-related articles focused on China ... 16
Table 3. Distribution of prefecture-level cities in China... 29
Table 4. Descriptive statistics: means, standard deviation and correlations ... 36
Table 5. Regression results... 37
1. INTRODUTION
During the last decade, the increasing speed of globalization has been forcing economic actors to engage in international trade to facilitate economic growth. According to the World Trade Report (2014, p. 18) published by World Trade Organization (WTO), even though the growth in world merchandise trade remained at 2.2 percent in 2013, the average increases of world merchandise trade during 1993 and 2013 reached 5.3 percent annually which is much higher than annual growth of GDP (only 3 percent). It refers to a striking growth in international exchange (IE), which simultaneously involves export and import (Liang & Parkhe, 1997).
Recent articles review that importing plays increasingly important strategic role in many organizations (Knudsen & Servais, 2007). Importing has its distinguished characteristics. Unlike export, the issues of national security, which in some cases are responsible for sacrificing serious benefits for the domestic economy, should be involved when purchasing goods from a specific country or region, (Aykol, Palihawadana & Leonidou, 2013; Moon, 2000). Despite its vital nature, as opposed to well-developed field of exporting, importing has received comparatively little attention by academic scholars and practitioners (Aykol, Palihawadana & Leonidou, 2013; Ghymn, Liesch & Mattsson, 1999). In the international business field, import demand is identified mainly from three variables: (1) buyer characteristics, such as buyer’s demographics; (2) supplier features, including supplier company features; (3) perceived product attributes, particularly quality, price, features, prestige, brand name
(Zhang at el., 2013).
Several researchers, for instance, Ghymn, Liesch and Mattsson (1998) and Leonidou (1999), seem to provide a useful framework for analyzing international purchasing behavior. However, the limited literature on the subject has often been described as too fragmented and too disjointed to gain any clear trends and guidelines (Aykol, Palihawadana & Leonidou, 2013; Ghymn & Jaffe, 2004). Although several insightful conclusions have been made in the past to review and assess this stream of research (e.g. Liang & Parkhe, 1997; Quintens, Pauwels & Matthyssens, 2006), they still have been relatively limited in both scope and depth. In specific, even though the great number of the import-related research centered on external/internal determinants of importing, the level of economic actors investigated has almost focused on firms and countries. Besides, geographic area should not only focus on American or European countries, but be extended to involve important emerging countries, such as China, Russia, and India (Aykol, Palihawadana & Leonidou, 2013). Especially, China has long been regarded as a cheap export-base, in which intermediate products are manufactured to be sent all over the world. Consequently, Chinese exports have attracted predominant interest from scholars and politicians. Nonetheless, Chinese imports have been comparatively ignored in business academic literature even though the import volume is similar to export volume during recent years (Zhang at el., 2013).
Drawing on the insights elaborated by Aykol, Palihawadana and Leonidou (2013), this paper will focus on import trade at the level in China. Using
city-level investigation, this thesis will propose the determinants contributing to Chinese cities’ importing performance. In particular, this paper aims to provide the answer to following research question: What triggers Chinese cities to source abroad?
This article contributes to international business discipline in a number of ways: Firstly, this thesis enriches existing theory by introducing multi-level assessment of the city-level determinants of imports in an emerging country. It also extends the scope of import-related researches by focusing on city-level import activity, which could extend the scope of the extant literature on the level of economic actors. Besides theoretical implications, in terms of the empirical context, this study focuses on China, one of the most important emerging countries that could offer initial framework of city-level import activities in emerging countries.
The remainder of the article consists of four sections. Section 2 provides a brief literature review to pave the way to the following part. Section 3 develops hypotheses to illustrate the research question and section 4 presents methodology of research study. Next, the study findings are reported and discussed based on the existing knowledge in the field. Finally, in section 5, full conclusions are drawn and the managerial and policy implications are examined, and the limitations of the study are identified.
1. LITERATURE REVIEW
The pioneering work of Smith (1776) offers the foundations to research on importing. After then, several well-known scholars contributed to a better understanding of import activities at the micro-business level. For instance, Heckscher (1950) demonstrates the effects of foreign trade on distribution and income and Vernon (1966) unveils international trade in the product life-cycle. In the early 1960s, O’Connell and Benson (1963) release the first business-oriented article on importing. In the 1970s, although firms in Japan and other Eastern economies increased sourcing from abroad because of the economic recession in Western countries (Kotabe & Omura, 1989), strikingly few scholars wrote on importing. Since 1980s, Corporations in the developed economies began to transfer their production facilities to low-cost regions, mainly to Asia (Roberts & Fuller, 2010), which facilitated the growing volume of import among Asian countries in order to support their producing. Furthermore, it also enhanced diversities of the scope of import-related topics (Aykol, Palihawadana & Leonidou, 2013). To some extent, it is ranging from the most advanced thematic area, external/internal determinants of importing (Katsikeas, 1998; Knudsen & Servais, 2007; Karande, Ha & Singhapakdi, 2008), to the least developed thematic area, miscellaneous issues, such as global sourcing of services (Kotabe & Murray, 2004).
In 1990s, crucial changes in the global business environment positively influenced import activities and thus triggered the interest of an increasing number of
business scholars in the international business field (Aykol, Palihawadana & Leonidou, 2013). These changes involve declining trade barriers, the intensification of competition, and the tendency to regard imports as an important way to gain competitive advantages (Kotabe & Murray, 2004). Liang and Parkhe (1997) develop an integrative framework that involves exporters and importers in a dyadic exchange relationship by drawing on the organizational buyer ’s behavior (OBB). They define OBB as ‘the decision process by which formal organizations establish the need for imported products and services, identify and evaluate alternative global suppliers, select a supplier located in another country and manage the IE relationship (Liang & Parkhe, 1997, p. 498). In addition, Ohlin (1993) proposes the first set of factor endowments of importing activities.
Due to the emergence of a new breed of international competitors from emerging markets, like China, India, Brazil, and Russia, critical developments in interest of researchers in studying importing activities occurred during 2000s (Aykol, Palihawadana & Leonidou, 2013). The most possible reason is that the movement of manufacturing capacity from western countries to emerging markets, which requires importing great number of raw materials among emerging markets (Herreias & Orts, 2011).
According to the review of Aykol, Palihawadana and Leonidou (2013), the bulk of the import-related research activity over fifty-year period investigated focused on four main areas (See Table 1): a) external/internal determinants of importing (e.g. Katsikeas, 1998), addressing the critical role of both exogenous and endogenous
factors in determining import performance; b) factors facilitating/inhibiting importing (e.g. Liang & Parkhe, 1997), stressing the role of import motives and barriers in determining import process; c) importer-exporter relationships (e.g. Lee et al., 2004), illustrating the increasing important role of the relationships with exporter suppliers in achieving business success; d) strategic aspects of importing, emphasizing strategic factors, such as government mechanism, in achieving higher import performance in international markets.
Table 1. Articles addressed in import-related areas
Year Author Main topic
External/internal determinants of importing
1988 Katsikeas Product characteristics, competitive pricing and relation capabilities are the key factors
2000 Quester, Dzever & Chetty
Country-of-origin information does result in different importing decisions among managers
2001 Skarmeas & Katsikeas
Interdependence magnitude and asymmetry, transaction-specific investments, relationalism, and trust influence importer’s performance
2004 Ghymn & Jaffe The motivation of external elements in importing behavior
2007 Knudsen & Swrvais
Influence of organizational factors in importing intensity
2008 Karande, Ha & Singhapakdi
Firm size, product type, and experience in importing intensity
2009 Kasiskeas, Skarmeas & Bello
The effects of environmental factors in importing intensity
2013 Aykol,
Palihawadana & Leonidou
The determinants can be divided in to environmental, organizational and managerial effects
Factors facilitating/inhibiting importing
1997 Liang & Parkhe Competitive pressure and unavailability at home market facilitates importing activity
1998 Fawcett & Scully Unfavorable exchange rates and political variables inhibits import performance
1999 Leonidou Lack of logistics support and dependable suppliers are important internal barrier
2005 Quintens, Pauwels & Matthyssens,
Cost pressure, lack of domestic suppliers and competitors play significant role in sourcing abroad 2013 Aykol,
Palihawadana & Leonidou
Import barriers result mainly from external or internal forces
Importer-exporter relationship
2004 Ghymn & Jaffe The ability of providing high quality products and stability of supply strengthen the relationship between importer and exporter
2007 Knudsen & Servaisn
Importance of close cooperation between in internationalization configurations
Strategic aspects of importing 2004 Chryssochioidia
& Theoharakis
Product technology sophistication, product and service quality and importer strategic objectives are important for the attainment of competitive advantage
a) External/internal determinants of importing
In relation to the determinant of importing activity, Katsikeas (1998) argues that product characteristics, competitive pricing and relation capabilities are key factors influencing import activities. However, patterns of motivation are significantly different between regular importers. Among developing countries, income and the exchange rate have substantial impacts on imports (Bahmani-Oskooee, 1984). Besides, the motivation to import may result from internal operational needs and external elements (Ghymn & Jaffe, 2004), like customer preference purchase o f domestic versus import brands. Moreover, Skarmeas and Katsikeas (2001) identify four kinds of variables, such as interdependence magnitude and asymmetry, transaction-specific investments, relationalism, and trust, which contribute to high-performance importers.
In general, determinants of importing encompass external and internal aspects. More specifically, it can be divided into environmental, organizational and managerial effects on import behavior (Aykol, Palihawadana & Leonidou, 2013). First, in addressing particular question of why certain corporations are actively engaged in international purchasing activities while others not, several researchers (e.g. Kasiskeas, Skarmeas & Bello, 2009) in the field have focused on the environmental factors triggering importing activities. Environmental factors include uncertainty, culture and other market characteristics (Kasiskeas, Skarmeas & Bello, 2009). Second, the role of organizational factors has received comparatively more attention in importing literature. Organizational factors involve firm size, product type, and
experience in importing intensity (Karande, Ha & Singhapakdi, 2008; Knudsen & Servais, 2007). Third, previous studies on importing activity did not pay much attention to managerial effects. They concentrated partly on cultural background and country-of-origin perceptions (Aykol, Palihawadana & Leonidou, 2013). Quester, Dzever and Chetty (2000) demonstrate that country-of-origin information does result in managers’ different perceptions of product quality and thus influences decisions on importing activities.
b) Factors facilitating/inhibiting importing
In relation to factors facilitating or inhibiting import performance, they are classified in three broad areas: Attitudes, motives/stimuli, and import barriers/problems (Aykol, Palihawadana & Leonidou, 2013). Among them, attitudes toward importing were gained the least attention by researchers, except sporadic research on country-of-origin effects on importing which are mentioned earlier (e.g., Quester, Dzever & Chetty, 2000; Anderson & Chao, 2003). Motives/stimuli to import occupy a significant proportion of research and barriers/problems relating to the development of the importing process also account for comparatively significant part of import-related research. In terms of import stimuli, researchers have paid great deal of attention on cost pressure, lack of domestic suppliers and competitors gaining an advantage from sourcing abroad (Liang & Pakhe, 1997; Quintens, Pauwels & Matthyssens, 2005). Specifically, organizational buyers are more likely to import after recognizing need, which results from competitive pressure and unavailability at home market (Liang & Parkhe, 1997). Import barriers result mainly from external or
internal forces (Aykol, Palihawadana & Leonidou, 2013). As for external barrier, unfavorable exchange rates and political variables play the most significant role in deterring import performance (Fawcett & Scully, 1998). On the other hand, lack of logistics support and dependable suppliers plays the most phenomenal role among internal barrier (Fawcett & Scully, 1998; Leonidou, 1999).
c) Importer-exporter relationships
With the thrust of research focusing on interaction between international purchasers and suppliers (Aykol, Palihawadana & Leonidou, 2013), importer-exporter relationships are continuously the dominant area of import-related research. In specific, several researchers (e.g. Barnes et al, 2010; Bianchi & Saleh, 2010; Skarmeas et al., 2008; Knudsen & Servaisn, 2007) focus on the role of trust, power, dependence and communication between buyers and sellers in international market. Knudsen and Servaisn (2007) argue the importance of close cooperation between the firm and the international partners explaining differences in internationalization configurations by focusing on the international purchasing behavior of small- and medium-sized industrial firms in Denmark. The second most proliferated field refers to the criteria for selecting suppliers (Aykol, Palihawadana & Leonidou, 2013). Ghymn & Jaffe (2004) unveil that ability of a vendor to provide high quality products and stability of supply are most significant factors in the selection decision process.
d) Strategic aspects of importing
A relatively great amount of research concentrates on strategic aspects of importing (Aykol, Palihawadana & Leonidou, 2013). The field of performance
implications of import strategy is most broadly discussed topic (e.g. Chryssochoidis & Theoharakis, 2004), followed by sourcing resources and governance mechanisms in importing (e.g. Enderwick, 2009).
2.1 China as an empirical setting
Several studies have examined importing behavior in China (See Table 2). Imports are a significant engine of growth because of the appreciation of Chinese currency (Herrerias & Orts, 2011). According to Herrerias & Orts (2011), machinery equipment and intermediate products, which are cheaper and easier to improve efficiency and productivity by implementing in the production process, account for the majority of imports in China. Mummalaneni, Dubas and Chao (1996) illustrate that Chinese purchasing managers frequently consider attributes like on-time delivery, quality, price/cost target, long-term relationship with purchasing organization as selection criteria. Recently, Xie, Peng and Zhao (2013) provide the influence of market-focused selection and relation-focused selection on supplier performance by collecting data from 208 Chinese manufacturers. Moreover, Kasiskeas, Skarmeas and Bello (2009) emphasize that psychic distance negatively influences the relationship quality, which could furthermore influence supplier selection.
Especially, in case of the determinants of China’s imports, a study uncovers relatively comprehensive analysis of the determinants of import demand in China. By analyzing China’s import demand empirically, Tang (2003) reveals that the volume of imports is, to some extent, resulted from domestic activity and relative prices.
According to Zhang et al. (2013), Chinese import market is predominantly featured by quality competition, which means quality plays phenomenal role in industries. Another important determinant is price, especially in industries where quality and product differences are relatively small. Moreover, among categories of expenditures, private consumption expenditure is key driver in Chinese import market (Zhang et al., 2013). Additionally, other variables, including the currency exchange rate, tariffs, also have crucial impacts on import demand (Zhang et al., 2013). A couple of studies also put efforts on specific industries, such as energy. Zhao and Wu (2007) indicate that several factors, including domestic oil production, industrial production, and expansion of the transport sector, have crucial effects on imports by researching Chinese oil import market. Similarly, Sun, Qi and Jia (2010) illustrate that the income and crude oil price, the reform in exchange rate, and economic growth are important and large force to enhance the oil import in China.
Table 2. Import-related articles focused on China Year Author Main topic
1996 Mummalaneni, Dubas & Chao
Attributes like on-time delivery, quality, price/cost target, long-term relationship with purchasing organization are critical selection criteria among Chinese managers
2003 Tang The volume of imports responses to domestic activity and relative prices
2009 Kasiskeas, Skarmeas & Bello
Psychic distance is negatively influence supplier selection.
2009 Herrerias & Orts Machinery equipment and intermediate products, account for the majority of imports in China. 2010 Sun, Qi & Jia Similar to Zhao and Wu, Several key factors are
important and large force to enhance the oil import in China.
2013 Xie, Peng & Zhao Influence of market-focused selection and relation-focused selection on supplier performance
2013 Zhang et al. Quality price, expenditures, exchange rate, tariffs, private consumption expenditure is key driver in Chinese import market
2.2 Research gap
Despite several investigations related to importing, there is still room to expand research into new domains. In terms of economic actor, extant research almost investigates in firm-level and level. Hence, besides firm-level and country-level, the intermediary country-level, city-level should also receive more attention; In terms of geographic scope of import-related research, the most popular regions investigated are North America, mainly the USA, and Europe, mainly the UK. Recently, other geographic areas, including Asia and Latin America, are growing rapidly, therefore, should be gained increasing number of researches. Extant researches mainly concentrated on the relationship between exporter and importer and the selection of international suppliers (Aykol, Palihawadana & Leonidou, 2013), however, other thematic regions on import, such as the determinant driving import activity warrants further attention. Moreover, as mentioned above, a couple of studies focused on Chinese importing activity emphasizes on specific industries, mainly energy. Given these empirical considerations, the purpose of this paper is to improve our understanding of the Chinese import market by investigating the key determinants of Chinese imports at city-level. A number of contributions can be derived from this stream of research. Briefly, this study will introduce multi-level assessment and augment the scope of economic actor for import-related research by adding city-level. It also expands geographic scope of import-related research by investigating China.
2. THEORETICAL FRAMEWORK
As mentioned above, the determinants identified before can be divided into three different perspectives specifically: environmental, organizational, and managerial factors (Aykol, Palihawadana & Leonidou, 2013). Most researchers investigate environmental and managerial factors in deductive and qualitative analysis. In contrast, by using inductive and quantitative analysis, this thesis will focus on multi-level determinants and suggest a useful framework to contextualize the factors influencing Chinese city’s imports activity. GDP is the most popular factors for scholars who investigate in import-related region. Although imports and exports are regarded as two separate activities, recent researches figured out there is a complex relationship between them. In particular, there is a one way complementary causal link from the growth of China’s exports to imports. Inward foreign direct investment (FDI) is also considered to generate the volume of imports, especially in labor-intensive countries, like China. As for moderators, investment in R&D and education level will be taken into account.
3.1 The growth of GDP
GDP is defined by Organization for Economic Co-operation and Development (OECD) as ‘an aggregate measure of production equal to sum of gross values added of all resident institutional units engaged in production’. GDP can be determined by three approaches, i.e., production, income, and expenditure approaches (OECD, 2002). Previous researchers investigated the influence of GDP on importing activity
by focusing on the aspects of income and expenditure. Braymen and Lam (2013) highlight that income distributions have crucial impacts on import patterns at country-level. More specifically, households with similar income levels tend to have similar consumption patterns. Furthermore, by investigating the import demand in France, Italy, Netherlands, the UK, and the US, Tsionas and Christopoulos (2004) conclude that relative incomes have significant effects on both long-run import demand functions and the short-run dynamics of import demand. In China’s case, a rise in national income will contribute to an increase in import demand (Zhang et al., 2013). In other words, the increasing income of residents creates needs for goods and services and thus triggers imports surpassing part between the needs and domestic supply.
From the expenditure approach’s perspective, several studies discompose the GDP to several kinds of expenditure in order to investigate the framework of imports activity in-depth (e.g. Nayaran & Nayaran, 2005; Alias & Cheng, 2000). Alias and Cheong (2000) find that the component of final demand expenditure is important determinant of import demand, particularly in the long-run (Alias & Cheong, 2000). Similarly, Narayan and Narayan (2005) also demonstrate growth in expenditures on consumption, investment and exports will facilitate higher demand for imports and expenditure on exports has the biggest correlation with imports. It means high expenditure on consumption supports an organization’s importing behavior.
Also abundant researches reveal that the growth of the whole GDP significantly and positively affects the importing activity. Katsikeas and Kaleka
(1999) highlight macroeconomic forces account for relatively predominant part in stimulating an organization to engage in imports market. In Pakistan’s case, all components of final expenditure influence significantly and positively import demand (Chani, Pervaiz & Chaudhary, 2011). In other words, to some extent, increase in economic growth will result in higher import. In the case of China, Adams and Shachmurove (2008) conclude that although the impact of economic growth is less than what is expected, continued growth of GDP enables China to import increasing quantities of energy from world market. Tcha and Wright (1999) also find that GDP growth rate affects iron ore trade between China and Australia. All in all, the growth of GDP provides financial condition for city to support importing. Thus,
Hypothesis 1: GDP is positively related to import trade volume at the city-level.
3.2 The volume of exports
Although there is not a significant link between imports and exports as a result of increased domestic production capabilities which is attributed to large FDI inflows, there still exists complex link between them. A stable and long-run relationship between imports and exports exists in France, Germany, Italy, Sweden, the UK and USA (Irandoust & Ericsson, 2004). Similarly, in the research of Afzal (2008), although macroeconomic policies affect adequately long-run equilibrium between imports and exports, the tendency of imports and exports move together in
the long run.
Moreover, there are a few articles explaining causality between exports and imports. Firstly, Mohamed, Saafi and Farhat (2014) figure out a simultaneous cause and effect between imports and exports in the case of a developing country, Tunisia. On the same vein, a long run equilibrium relationship between exports and imports is also found in the case of Pakistan and, furthermore, there exists bidirectional causality between imports and exports (Mukhtar & Rasheed, 2010), which means that the exports and imports trigger each other simultaneously. In the case of China, based on the panel analysis for China and 19 home countries/regions, Liu, Wang and Wei (2001) indicate a procedure of development for China: there is a one -way complementary causal link form the growth of China’s exports to imports. Specifically, more exports contribute to more imports (Liu, Wang & Wei, 2001). China’s processing trade pattern is as follows: China’s vast factories, particularly coastal factories, purchase semi-finished products from Western and other part of Asia and assemble them into final goods to sell abroad (Cui & Syed, 2007). It refers that exporting and importing are the activities in the same processing line rather than independent two nodes. Cash flow from exports is likely to support sustainable imports activity. Therefore,
Hypothesis 2: Export trade volume is positively related to import trade volume at the city-level.
3.3 Inward FDI
In 2013, China still leads Asia-Pacific in FDI with a dominant 34.73% market share (fdiIntelligence, 2014). Researchers and practitioners have paid great attention on the relationship between FDI and imports. For instance, de Mello and Fukasaku (2000) argue that there is a positive linkage between imports and FDI inflows from the research in some of the Latin America and Southeast Asian countries. Similarly, Liu, Wang and Wei (2001) indicate that, even though the influence is not striking, the growth of FDI positively affects imports. Furthermore, especially for developing countries, the synergy from the interaction of the inward FDI and imports are critical in R&D spillovers (Yang & Cheng, 2008).
Due to the main topic, this paper will focus on the causality, not the whole linkage, between inward FDI and imports. In the case of Spain, inward FDI plays a significant role in promoting imports in the research of Alguacil and Orts (2003). In other words, the growth of inward FDI generates the growth of import volume. Whaheed and Jawaid (2010) reveal that unidirectional causality from inward FDI to aggregate imports exists in Pakistan, which means they affect each other simultaneously. There are also several empirical studies in the case of China. Firstly, Zhang and Li (2007) estimate a positive effect of inward FDI on total trade volume of China from 1980 to 2004. Thereafter, Dong and Jun (2010) emphasize the important role of R&D investment on steady China’s economic growth. Besides, Xiao (2009) confirms that inward FDI has positive impacts on both exports and imports in China, and more specifically, from China’s view, the more inward FDI will trigger more
imports. Therefore,
Hypothesis 3: Inward FDI is positively related to import trade volume at the city-level.
3.4 Moderating factors
3.4.1 The moderating role of level of education
The level of education, particularly the quality of education, also gained great deal of interest from researchers in the region of GDP. In general, Hanushek and Womanm (2007) find that the quality of education indeed matters for economic growth. More specifically, the quality of education has a beneficial impact on GDP per capita, and the effect is more significant in countries with more stable institutions (Faruq & Taylor, 2011). The impacts of different level stage of education, primary, middle, and tertiary education, on economic growth are also different. Afzal et al. (2011) find that general higher education generates economic growth more significantly than other levels of education in Pakistan. In details, the level of higher education, including university education and professional education, can be considered as the higher level of labor force which creates more economic growth. The percentile of adult population with tertiary education enhances the growth of GDP in most countries of EU (Sterlacchini, 2008).
However, the significance of impact of education quality on economic growth is varied country by country. The returns of investment on education on economic
growth in Sri Lanka are positive but less significant than in other developing countries (Ganegodage & Rambaldi, 2011). In the case of China, based on provincial data from 1978-2005, Li and Huang (2008) reveal that education has positive and significant effects on economic growth. Furthermore, Zhu et al. (2008) conceptualize the human capital as one production factors and identify that, although there is the large growth gap in productivity across China, there exits economic contribution rate of education in every city. Similarly, by evaluating Jiangsu and Liaoning provinces, Shindo (2010) examines the greater educational subsidies in government triggers the higher economic growth, which is resulted from advanced human capital caused by high level of education.
In terms of the effect of education on exports and inward FDI, despite few numbers of articles supporting the relationship; there indeed exists a significant relationship between them. As Chinese economic develops steadily in a rapid growth rate, more and more foreign students come to China for further study. According to Zhou (2009), Chinese universities increasingly collaborate with foreign institutions and it triggers more education exports. Recently, Chao Jr (2013) also indicates that China has embarked on its offshore branch campuses. For instance, Zhejiang University set up UK branch campus and Xiamen University established Malaysia campus. In conclusion, higher level of education enables Chinese university to export education to other countries.
The complementarity between the quality of education and inward FDI enables inward FDI to have a positive effect on GDP, which further influence the
volume of imports (Wang & Wong, 2011). Recently, Lin (2011) finds that labor quality measured by education level has critical impacts on the inward FDI, especially technology-intensive FDI. However, similar to the impact on GDP, it is uneven across industries and provinces. Specifically, labor quality plays more important role in attracting FDI in coastal provinces and cities, such as Tianjin, Shanghai (Lin, 2011). In conclude,
Hypothesis 4: Level of education at the city-level positively moderates the relationships hypothesized in H1, H2, and H3.
3.4.2 The moderating role of investment in R&D
Nowadays, technological change is a crucial factor in facilitating economic growth. Therefore, firms, countries and even cities are gradually putting priority on the investment in R&D. Consequently, several researches (e.g. Pessoa, 2010) indicate that R&D has positive effects on economic growth, the volume of exports and inward FDI. In terms of the positive impacts of R&D on economic growth, it is varied by country and country, but in a positive way (Pessoa, 2010). Specifically, in the case of the U.S., increased knowledge by R&D has significant economic benefits (Mansfield, 1972). By focusing on European regions, Sterlacchini (2008) finds that the impact of R&D on economic growth is only striking among a high per capita GDP, developed countries. However, Li, Hu and Zhang (2010) analyze empirically that R&D
investment influence positively the economic growth by investigating Hebei Province in China. Consequently, investment on R&D is likely to generate economic growth, which further triggers the volume of imports.
As for the impact of R&D on the volume of exports, the interdependent link between R&D activity and exports is well acknowledged by great number of investigations (e.g. Harris & Li, 2010). In general, the intensity of R&D expenditure, especially public R&D expenditure, triggers the export of medium and high-tech products in EU region (Sandu & Ciocanel, 2014). There is a strong relationship between R&D and exports in Irish firms and British firms (Girma, Gorg & Hanley, 2008), so is in Germany (Roper & Love, 2002). Among researches investigating the Asian region, R&D expenditure has positive relationship with the volume of exports in the case of Japan where government relies more on internal research efforts (Ito & Pucik 1993). During the past few decades, Chinese cities tend to put priority on internal R&D performance, hence, the outcome of Ito and Pucik (1993) can be adapted to current Chinese cities. Moreover, the effects of R&D are striking and positive on both export propensity and growth in Chinese manufacturing firms (Zhao & Li, 1997). Recently, Wei and Liu (2006) come to conclusion that inter-industry productivity spillovers exist from R&D to exports. Accordingly, the investment on R&D could positively affect the volume of export, which further positively influences the volume of imports.
In relation to the impacts of the investment of R&D on inward FDI, they are positively related and reinforce each other (Lin & Yeh, 2005). Even though a positive
correlation between the R&D and FDI inflows fails in Japanese case (Beladi & Firoozi, 2008), FDI inflow and investment in R&D are complementary in nature (Sasidharan & Kathuria, 2011). In the case of Chinese manufacturing sector, there also exists positive spillover from R&D to the presence of FDI (Wei &Liu, 2006). Consequently, it can be concluded that investment on R&D generates FDI inflows, which further triggers importing activity.
All in all, here comes the fourth hypothesis,
Hypothesis 4: Investment on R&D at the city-level positively moderates the relationships hypothesized in H1, H2, and H3.
The previously discussed hypotheses result in the conceptual model as shown in Figure 1.
3. METHODOLOGY
The next section discusses the methodology of this research. It will illustrate precisely how the research question is intended to be tackled and will explain the choice of method in the light of this question with several moderators. Firstly, the dataset and selection are discussed. Thereafter, a discussion of the methods that are used will follow together with the research design. The research design demonstrates the structure of research. Specifically, it explains how research is conducted and how it is analyzed (Van der Velde, Jansen & Anderson, 2004). Lastly, it concludes with an explanation of the analyses.
4.1 Sample and data collection
This study will use a panel research design to examine the city-level determinants of imports in China. The reason why use China as follows: First, China has experienced rapid economic growth and has become one of the most typical emerging markets that attract interests from researchers. For imports activity, China has gradually lowered barriers for foreign exporters and encourages local importers to source abroad. Most importantly, every Chinese city has its own characteristics which enable research to come up with comparable and comprehensive outcomes. In order to achieve the research objective, that is, to investigate city-level drivers of import trade in china, this thesis uses the prefecture-level cities and municiplities published by Chinese government. So far, Chinese government has published 291 prefecture-level cities and 4 municipalities, they are scattered over the whole China, including
coastal cities and inland cities ( See Table 3.) However, we can just collect sufficient data for 272 cities.
Table 3. Distribution of prefecture-level cities in China
4.2 Measures
4.2.1 Dependent variable
The dependent variable in this thesis is imports. The import of a city is divided into foreign trade imports and domestic trade imports. Foreign trade imports includes imports from abroad while domestic trade imports contains imports from other cities in the same country. In order to capture the level of international imports for every city, this thesis relies on the total volume of foreign trade imports as the dependent variable.
4.2.2 Independent variable
The independent variables used in this thesis are GDP, volume of foreign exports, and inflow FDI. As mentioned above, GDP indeed plays an important role in boosting the volume of imports. And the value of GDP is easily searched in official documents; therefore, it is reasonable to take GDP into account as an independent
Region Frequency Percentage
North China 33 11.19 Northeast China 34 11.52 East China 78 26.44 Mid China 42 14.24 South China 39 13.22 Southwest China 37 12.54 Northwest China 32 10.85 Total 295 100
variable. Besides, there exists long-run equilibrium between imports and exports. In other words, they are closely connected. Although more researches identify imports affect exports, there are still several articles (e.g. Liu et al., 2001) arguing that exports also affects imports. This thesis relies on the total volume of foreign trade exports as another independent variable. As for inflow FDI, it has gained increasingly much attention from scholars. There are three kinds of figures demonstrating inflow FDI, i.e., number of contracts for FDI, contracted FDI capital, and FDI actually absorbed by cities. In order to examine the actual effects of FDI on imports, this thesis focuses on the FDI actually absorbed by cities. Hence, the final independent variable of this thesis uses foreign direct investment actually absorbed as the proxy.
4.2.3 Moderating variable
In order to investigate further in the relationship between GDP, exports, and inflow FDI and imports, this thesis identifies two moderating variables that influence this relationship in different ways.
The level of education is the first moderating variable. As mentioned above, among different stages of education, the higher/tertiary education has the most significant impacts on the growth of GDP, exports, and inflow FDI. The educational background of labor capital is the main factor to trigger this relationship. Consequently, this thesis centers on the percentage of students enrolled in higher education, rather than the percentage of regular institutions, as the proxy.
articles, to some extent, the level of R&D promotes the economic growth (e.g. Sterlacchini, 2008), exports activity (e.g. Sandu & Ciocanel, 2014), and the volume of inflow FDI (e.g. Wei &Liu, 2006). The extent to which a city has a high level of R&D is measured by the expenditures on R&D.
4.2.4 Control variable
The first control variable is population, which is common control variable and connected to city performance. This thesis captures year-end resident population as the proxy for population as the most proportion of financial activities is caused from people who currently live in the city.
Diversity of needs from gender is controlled by city gender variable since gender is a good predictor of behavioral diversity (Cannella Jr, Park & Lee, 2008), including purchase behavior which obviously influences imports. Hence, the percentage of male population is the second control variable.
Whether the city focuses on primary industry also influences city imports activity. Primary industry collects natural resources and the secondary industry uses these materials to manufacture things that people use. Accordingly, primary industry provides the resources and materials necessary for almost the whole economic system. Therefore, the third control variable is the proportion of primary industry which is defined as GDP primary industry divided by gross domestic product.
The final control variable is the number of tourists. Tourists also need commodities, which means it can also contribute to the volume of imports, especially
in cities where purchase most of necessities to meet the requirement generated by people (Wagner, 2007).
4.3 Statistical analysis and results
The descriptive statistics and correlations between variable are presented in Table 4. The variables are tested for multicollinearity by assessing the correlations between all predictor variables. The point of interest here is whether any of the correlations have a value above .7 which indicates the probability of problematic constructs as multicollinearity can exists when there are high levels of correlation between variables (Pallant, 2011). As seen in Table 4, after testing for multicollineary and evaluating the bivariate correlations, all variables are retained as they have value below .7.
Based on the descriptive statistics, the mean value of the dependent variable is 106.37 million dollar and the deviation is significant (512.78 million dollar). There are also high levels of deviation among predictor variables. Hence, it is suitable to capture these factors as independent variables. Besides, there is comparatively low gap in percentage of primary industry. Most of Chinese cities still focus on primary industry and have low level of education (14.63% with standard deviation 9.06% and 15.19% with 13.51% respectively).
Hypothesis 1, 2, and 3 are tested by a multiple linear regression analysis in order to determine the direct relationship between independent variables and dependent variables. As the dependent variable has continuous values and it is
assumed a linear relationship between the dependent and predictor variables, the Ordinary Least Squares (OLS) is most suitable model. The first step is clarifying the effects of control variables on the dependent variable. Hence, in the first model only control variables were introduced. Thereafter, all independent variable was introduced with control variables to identify to see which independent variable is most significant when controlling for the others. The following six models assess the effect of each moderator on each hypothesis under control variables. Consequently, this thesis runs a total of eight models. In the first model tests the effects of control varaibles. Model 2 assesses the first, second, and third hypotheses and indicates the relative significance of independent variables by introducing the whole independent and control variables. For testing the effect of each moderator variables on the first three hypotheses, regression process was used by computing the interaction between independent and each moderator. Therefore, model 3-5 assess the fourth hypothesis and 6-8 assess the final hypothesis in control of four control variables.
When analyzing results, there are three points of interest that needed to focus. The significance (p-value) describes whether results are reliable or not and thus determine whether hypotheses are supported. The beta (b) indicates the coefficient level which accounts for the change in dependent variable when independent variables change. It also signifies the direction of the change. The last one is 𝑅2 which
describes the goodness of fit of the model.
The results of the regression analysis indicate that not all of the variables have explanatory effect because not all of their significances are below .05 which is the
benchmark for the efficiency of models. Hypothesis 1 argues that GDP is positively related to the volume of imports as the coefficient of GDP is significant (b=.801, p=.003). Hence, hypothesis 1 is supported even though the coefficient is low. The volume of exports is also positively related to the volume of imports. The coefficient of the volume of exports is significant (b=.589, p=.038). Therefore, the positive effects of the volume of exports on the volume of imports are strongly supported. Model 2 also brings a support on hypothesis 3. Inward FDI does have positive impacts on imports. All in all, GDP has the most significant impacts on importing activities at city-level in China.
As for the moderating variables, there are three models for effects of each moderator. The corresponding hypothesis is supported only when the interaction term coefficient is significant. According to the significances (p-value), they are all < .05, which means the effects of both moderators are supported. Accordingly, hypotheses 4 and 5 are supported. However, the coefficient of interaction is weak for both moderators. It means the level of education and R&D do influence the relationship mentioned in hypotheses 1, 2, and 3, but not strongly.
In relation to control variables, strong support for the effects on imports is found for the year-end resident population (b=.139, p=.002) and the number of tourists (b=.170, p=.000) while the percentage of male population (p=.766) and the percentage of primary industry (p=.998) do not influence the imports. In specific, the number of tourists has an influence on the imports activity and the year-end resident population also has significant impacts on the volume of imports in a city, but less
than the resident population. Interestingly, there is not significant interaction between the number of male population and the volume of imports. Similarly, whether a city is focusing on the development of primary industry does not influence the importing activity.
Table 5. Regression results
Dependent Variable: imports Controls (Model 1) H1, H2, H3 (Model 2) H4 (Model 3) H4 (Model 4) H4 (Model 5)
Control variables Beta S ig. Beta S ig Beta S ig. Beta S ig. Beta S ig.
Year-end resident p op ulation .139 .002** 1.734 .001** .227 .001** 1.486 .001** 1.196 .002** The p ercentage of male p op ulation -3.060 .766 -7.702 .573 -.142 .089 -.2.090 .101 -1.516 .688 The p ercentage of p rimary industry .042 .998 .461 .980 .015 .987 .051 .977 .059 .968 The number of tourists .170 .000** .154 .000** .569 .006** 1.529 .000** 1.375 .001**
Independent variables
GDP .801 .003** 2.020 .000** 1.066 .002** 1.820 .002**
The volume of exp orts .589 .038* 1.981 .020* .094 .032* 1.628 .022*
Inward FDI .260 .001** 1.152 .000** 1.891 .000** .421 .002**
Moderating variables
The level of education .989 .000** 1.332 .024* .580 .002**
The level of R&D
Interaction terms
GDP × The level of education .002 .000**
The volume of exp orts ×The level of education .045 .001**
Inward FDI × The level of education .021 .000**
GDP × The level of R&D
The volume of exp orts × The level of R&D Inward FDI × The level of R&D
Constant -74.545 .873 -208.608 .756 2.608 .711 166.417 .670 .495 .987
𝑹𝟐 .480 .535 .768 .689 .726
Change in 𝑹𝟐 .480 .057 .019 .005 .014
N (number of sample) 272 272 272 272 272
Table 6. Regression results-continuation
Dependent Variable: imports H5 (Model 6) H5 (Model 7) H5 (Model 8)
Control variables Beta S ig. Beta S ig. Beta S ig.
Year-end resident p op ulation .872 .001** -.828 .000** .990 .000**
The p ercentage of male p op ulation -1.322 .072 -1.479 .147 -1.724 .082
The p ercentage of p rimary industry .093 .987 .137 .876 .1190 .976
The number of tourists 1.595 .002** 1.849 .002** 1.201 -.002**
Independent variables
GDP 3.030 .000** .682 .000** .879 .002**
The volume of exp orts 1.568 .018* .352 .011* .238 .000**
Inward FDI .561 .001** .528 .001** .240 .003**
Moderating variables
The level of education
Investment on R&D 1.881 .000** 1.138 .000** 2.359 .000**
Interaction terms
GDP ×The level of education
The volume of exp orts × The level of education Inward FDI × The level of education
GDP × The level of R&D .001 .000**
The volume of exp orts × The level of R&D 0.002 .003**
Inward FDI × The level of R&D .036 .000**
Constant -116.597 .004** -204.181 .002** -142.9321 .002**
𝑹𝟐 .628 .722 .699
Change in 𝑹𝟐 .012 .018 .017
N (number of sample) 272 272 272
5. DISCUSSION
The conceptual framework and empirical findings bring useful implications regarding the determinants of imports in the city-level. While previous research has concentrated and found support mainly for the determinants and triggers for exporting activity, this thesis elaborates a comprehensive framework for the determinants for imports. Furthermore, this study has introduced multi-level assessment of the determinants of imports. All of predictors included in this thesis, i.e., GDP, the volume of exports, inward FDI, had positive effects on the importing activity in a city. Besides, all moderating variables pertaining to a city, specifically the expenditure of R&D and the level of education, were identified to have a positive moderating effect on the relationship between independent variables: GDP, the volume of exports, the inflow FDI and importing activity. In other words, the higher level of education and R&D help a city promote source abroad by triggering economic growth, exports, and inflow FDI. It means the benefits of high level of R&D and education surpass the operating cost and achieve high level of education for labor capital.
The following sub-section will discuss the academic relevance, the policy implications and the limitations and suggestions for future research in more details.
5.1 Academic relevance
Firstly, this thesis introduced multi-level assessment by investigating independent variables, i.e., GDP, the volume of exports, and inflow FDI and the
moderating role of the level of R&D and education, which are seldom used in import-related research. As mentioned above, the determinants of imports have not received great attention by scholars. Consequently, import-related literature lacks a comprehensive framework of triggers of imports. Hence, findings of this thesis offer a nuanced investigation of the factors triggering imports. Moreover, this thesis contributes to the existing literature on imports in an emerging market by shedd ing more light on the determinants of importing at city-level. As expected, the results suggest the positive role of predictors on importing activity for a city. This means that economic growth in a city triggers its importing activity. Similarly, the growth in the volume of exports and inward FDI also has positive impacts in generating importing activity. In addition, the moderating factors, the expenditure on R&D and the level of education strengthen the relationship between predictors and imports. As a result, a city that takes priority on R&D and education tends to further increase the positive effects of GDP growth, volume of export and inward FDI on import volume.
This thesis also brings support outcomes from previous studies. Existing researches show that higher GDP results in increased volume of imports (e.g. Chani, Pervaiz & Chaudhary, 2011; Katsikeas & Kaleka 1999). As shown in Katsikeas and Kaleka (1999) study, the economic growth plays predominant part in generating an economic actor to engage in international imports market. This thesis supports these outcomes. Interestingly, in the case of China, existing research mainly focuses on the effect of economic growth on imports in energy market (e.g. Adams & Shachmurove, 2008; Tcha & Wright, 1999). In relation to the effects of exports on imports, several
studies (e.g. Mukhtar & Rasheed, 2010; Liu et al., 2001) have tried to clarify the relationship between exports and imports but resulted in mixed results. My finding reinforces their finding that there is a positive effect of exports on imports, at least in China. Researchers did not pay attention on the effect of FDI on importing activity. Therefore, one of the determinants discussed in this thesis, inflow FDI, brings a new perspective in current import-related literature.
Similarly, existing studies seldom involve moderating factors when investigating the relationship between determinants and imports. Therefore, the moderators investigated in this thesis broaden the scope of structure for import-related research.
5.2 Policy implication
The findings of the present research have important policy implications. First, when a city wants to improve the volume of imports it could promote economic growth since GDP has a positive influence on the increase of importing activity. A city with high volume of exports also results in importing activity. Besides, the high amount of inward FDI of a city enables a city to purchase abroad because inward FDI has positive impacts on imports.
Second, when a city takes decision to increase the volume of imports, it can also achieve the result by indirect ways by improving moderators. For instance, improving the expenditure on R&D could generate economic growth, increase of the exports, and inflow FDI, which further increases the volume of imports by influencing
relationship between independent variables and imports. In other words, cities can use current findings to analyze the future moves of their plan. Because there are several possible ways to strengthen the ability for sourcing abroad, it is vital for cities to choose the most suitable way according to their current situation. Specifically, if a city is willing to increase both the inward FDI and importing volume simultaneously, it can be resulted from attracting inward FDI directly and affecting R&D and the level of education. Therefore, cities should take into account all possibilities to make a best choice, which means achieve the final outcome by the least costs.
5.3 Limitations and suggestions for future research
This study has also limitations that need to be acknowledged. The predictors are all chosen by subjective factors retrieved by secondary data. Therefore, some objective factors which are line with previous researches should be considered to enrich the framework. Specifically, there are great numbers of other objective factors, such as the quality of product and the attitude of government on importing are perceived as important predictors for importing activity by previous researches. It means that future research can expand types of determinants and provide more comprehensive framework.
Moreover, this thesis focused on an emerging market, China. Although China is one of typical emerging countries, each emerging economy has its own characteristic. Hence, future research is highly recommended to investigate other emerging markets to offer more general framework of determinants of imports suits
more emerging markets.
Third, due to the nature of the secondary data gathered for some of predictors, it is difficult to find the exact number for predictors. By using proxies for the level of R&D and education, there might be disconnection between proxies and moderators. For example, the expenditure on R&D could be different from the level of R&D because of inefficient use of expenditure. Therefore, future researches should find other proxies for the level of R&D and education and alleviate the difference between proxies and predictors.
Including other moderating factors in affecting independent variables and imports could expand this study. As there are not many researches at city-level, this region should be extended by including different kinds of available variables. Future research could try to incorporate varied variables.
This thesis just included two effective control variables due to the insignificance of other two controls. Future researches are also recommended to take other control variables into consideration, such as the rate of unemployment and the government income.
6. CONCLUSION
The purpose of this thesis was to put forward to multi-level variables that trigger importing activity at city-level. In the existing literature this aspect of imports is relatively unexplored. Although there are several literatures centered on the factors which influence imports, these studies mostly focus on firm and country level. Organizations tend to take priority on exporting because it generates economic growth directly. However, importing began to receive more and more attention due to the significance of imports. Existing researches that address this topic find scattered results and show that the factors include external and internal dimensions (e.g. Ghymn & Jaffe, 2004). Thus, import markets at city-level in emerging countries should be obtained much more attention in order to give reference to organizations that are willing to invest in specific cities in emerging markets. This thesis ventured in filling this gap and investigated the determinants of imports in Chinese market at city-level. The role of organizational factors, like size, experience was investigated by several scholars (e.g. Karande, Ha & Singhapakdi, 2008; Knudsen & Swrvais, 2007). This thesis supports the effects of organizational factors by including the variable of GDP. Also by taking into account two moderating factors that could positively influence the effects of predictors, the analysis was taken a step deeper. The dataset was compiled on the prefecture-level cities from Chinese government, which covers the whole big and medium cities in China.
process regression and it was shown that the GDP, the volume of exports, and inward FDI have positive effects on the imports under control variables (year-end registered population and the number of tourists). Also this thesis indicated that two important moderators enhance the positive impacts of determinants.
The findings of this thesis have academic as well as policy implications. Firstly, the multi-level assessment was introduced by identifying determinants from different levels. Additionally, it shed light on the import market in emerging countries which play a crucial role in international markets. Adding a framework for importing behavior in Chinese city level, it provided guidelines for organizations that are going to expand business in Chinese cities. In specific, organizations could analyze a city from factors investigated in this thesis and make a decision to which city should they go abroad. In addition, this study provides Chinese cities that want to develop import market with direct and indirect options. However, this study needs to be enriched by future researches and develops into a structured and comprehensive framework of determinants for importing activity.
ACKNOWLEDGEMENT
I would like to express deepest appreciation to express my supervisor Dr. Niccolò Pisani, assistant professor of International Management at the Faculty of Economics and Business, University of Amsterdam, whose valuable comments,
REFERENCES
Afzal, M. (2008). Long-run relationship between imports and exports: Evidence from Asian countries. The Singapore Economic Review, 53(2), 261-278.
Afzal, M., Rehman, H. U., Farooq, M. S., & Sarwae, K. (2011). Education and economic growth in Pakistan: A cointegration and causality analysis. International Journal of Educational Research, 50, 321-335.
Alguacil, M.T., & Orts, V. (2003). Inward foreign direct investment and imports in Spain. International Economic Journal, 17(3), 19-38.
Alias, M. H., & Cheong T. T. (2000). Aggregate imports and expenditure components in Malaysia: A cointegration and Error correction Analysis. Institute of Southeast Asian Studies, 17(3), 257-269.
Anderson, P. H., & Chao, P. (2003). Country-of-origin effects in global industrial sourcing: Toward an integrated framework. Management International Review, 43(4), 339-360.
Aykol, B., Palihawadana, D., & Leonidou, L.C. (2013). Research on the import activities of firms 1960-2010 review, assessment, and future directions. Management international Review, 53, 215-250.
Barnes, B. R., Leonidou, L. C., Siu, N. Y. M., & Leonidou, C. N. (2010). Opportunism as the inhibiting trigger for developing long-term-oriented Western exporter-Hong Kong importer relationships. Journals of International Marketing, 18(2), 35-63.
Bahmani-Oskooee, M. (1986). Determinants of international trade flows, the case of developing countries. Journal of Development Economics, 20, 107-123.
Beladi, H., & Firoozi, F. (2008). Link between domestic R&D and inflow of FDI: A game -theoretical analysis. Pacific Economic Review, 13(2), 209-222.
