Graduation Thesis

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Dual Masters Award in Advanced International Business

Management

Academic Intake 2013/15

Graduation Thesis

MNCs’ Modes of Entry into the Bottom of Pyramid Markets:

Fully-Control or Shared-Control?

Supervisors

Emmalinde Roelofse (Newcastle University) Bartjan Pennink (University of Groningen)

Author

Yang Cui (B3054507 / S2647664)

Submitting Date 08 December 2014

Word Count

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Abstract

This study discusses the modes of entry strategy for MNCs to get access to the bottom of pyramid markets. We use China, one of the most popular bottoms of pyramid markets, as an example. In all, we collected 854 deals of modes of entry by MNCs into the mainland Chinese market. We have observed that instead of the popular shared control modes a decade ago since the economic reform in 1980s, the propensity of pursuing full control modes by the MNCs has been increasing and is now the major type of modes of entry strategy. Then we estimated a multiple linear probability model and a logit model to explore what the major determinants are for modes of entry strategy and to what extent each determinant contributes to the propensity of preferring full control.

This research suggests that transaction costs tend to be the most important determinants for MNCs choosing full control modes or shared control modes into the bottom of pyramid markets. More specifically, larger cultural distance between host country and home country, higher economic distance between host country and home country and less similar market dynamism or economic conditions would lead to more uncertainties and higher risks for MNCs. As a result, MNCs tend to be more reliant on local firms and are less willing to confront with risks of full control modes. The higher the transaction costs, the more motivated the MNCs would be to choose shared control modes of entry.

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Acknowledgement

I would like to convey my gratitude to both my supervisors, without whose help on research and patient guidance for problem I was confronted with, I could have not determined on a more specific topic of research or explored the in depth knowledge of the research.

Also I would like to show acknowledgments to my genuine friends, Elizabeth Lee, Lynn Chou and Will Wang, without whose help, the data collection could not have been comprehensive enough.

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1. Introduction

This chapter introduces the importance of researching on modes of entry strategy for MNCs, different types of modes of entry and China as one of the most attractive bottom of pyramid market worldwide.

As the markets of the top of the pyramid saturates, the bottom of pyramid markets which have huge growth potential could be the next focus of MNCs’ strategy.

The main research question is that what the major determinants of modes of entry into bottom of pyramid markets are. We would like to know whether transaction costs are the main factors determining modes of entry types of MNCs. In addition, we would like to know to what extent each determinant contributes to the propensity of pursuing full control. Here, we use China, one of the most popular bottoms of pyramid markets, as an example.

For those MNCs that did have operations within emerging markets were more pursuing labour cost advantage instead of pursuing equity controls or returns of capital investments. There are a lot of ways to enter the emerging markets from Greenfield to local partnership to contractual licence. However Sun (1999) found out that particularly for China, there have been two major modes of entry, one was wholly owned acquisition and the other was by setting up joint venture, since the economic reform and market liberalisation in 1980s.

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equity control group. So here we examine cross border acquisition as full control modes and joint venture as shared control modes.

From literature reviews, researchers have found that transaction costs are the major and most important factors to determine modes of entry.

Thus, this study discusses the modes of entry strategy for MNCs to get access to the bottom of pyramid markets, particularly into Chinese markets. In all, we collected 854 deals of modes of entry by MNCs into the mainland Chinese market. We have observed that instead of the popular shared control modes a decade ago since the economic reform in 1980s, the propensity of pursuing full control modes by the MNCs has been increasing and is now the major type of modes of entry strategy. Then we estimated a multiple linear probability model and a logit model to explore what the major determinants are for modes of entry strategy and to what extent each determinant contributes to the propensity of preferring full control.

We suggests that transaction costs tend to be the most important determinants for MNCs choosing full control modes or shared control modes into the bottom of pyramid markets. More specifically, larger cultural distance between host country and home country, higher economic distance between host country and home country and less similar market dynamism or economic conditions would lead to more uncertainties and higher risks for MNCs. As a result, MNCs tend to be more reliant on local firms and are less willing to confront with risks of full control modes. The higher the transaction costs, the more motivated the MNCs would be to choose shared control modes of entry.

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2. Literature Review

This chapter reviewed the related research of bottom of pyramid and modes of entry strategy and summarized the theoretical backgrounds for the determinants of market entry strategy, in particularly, transactional cost framework.

2.1 The Bottom of the Pyramid Markets

As the markets of the top of the pyramid saturates, the bottom of pyramid markets which have huge growth potential could be the next focus of MNCs’ strategy.

The idea of the bottom of the pyramid was suggested by Prahalad & Hart (2002) that there are nearly 4 billion people at the base of the economic pyramid with incomes less than $3,000 in local purchasing power and living in relative poverty. Strong empirical evidence has not been found until the joint WRI/IFC1 report (Hammond, Kramer, Katz, Tran & Walker, 2007) suggested the measure for bottom of the pyramid size and scopes which were based on household income and consumption survey data. This report presented data in 8 important sectors, drawing on household surveys in 110 countries for income and a subset of 36 more for expenditures, showing that the bottom of the pyramid is a $5 trillion annual market and is tremendously unserved by business and enterprises (Katz, 2007). This addresses novel opportunities for MNCs to generate profits and pursue new sources of future growth when their traditional focus, serving the customers in the developed markets, is no longer prevailing because of markets saturation (London & Hart, 2004). Hence, moving strategy focus onto serving these customers of the bottom of the pyramid would be significantly beneficial to MNCs.

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Graph 1 bottom of the pyramid Market and Estimated bottom of the pyramid Market by Sector (Hammond, et. al, 2007)

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So, these markets have promising market size, consumers having limited disposable income but relatively high purchasing powers, rapid improvement of income level and potential sustainable advancement of demands and purchasing powers, relatively less competitive environment and also opportunities for innovation (Hoskisson, Eden, Lau & Wright, 2000).

Continents BOP population (millions) BOP share of total population (%) BOP income (millions) BOP share of total income (%) PPP US$ Africa 486 95.1 429,000 20,000 70.5 Asia 2858 83.4 3,470,000 742,000 41.7 Eastern Europe 254 63.8 458,000 135,000 36.0

Latin America &

Caribbean

360 69.9 509,000 229,000 28.2

Table 1 Bottom of the pyramid Population, Income and Market Size of 4 Continents (Hammond, et. al, 2007, pp. 120)

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However, these markets also suffer from weaker formal institutions (law enforcement, contracts), underdeveloped strategic factor markets, missing important intermediaries for doing business, instability and uncertainty projected by rapid political and economic reforms, informal institutions (inter-firm relational ties, socio-cultural clash) dominating markets, subnational diversity (unbalanced income level, consumer tastes and preferences) and also with strong government interventions in business activities (Gubbi, 2014a). In this case, it requires MNCs to develop new strategies and explore the new market conditions to succeed in doing business and earn money from these markets.

2.2 MNC Strategy: Market Entry Types

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Graph 2 Modes of Entry (Gubbi, 2014b)

Among the popular research on modes of entry, Mayer (2009) used a multi-nominal model to see how institutional factors and local resources required influence MNCs’ decisions of modes of entry (greenfield, joint venture or acquisition); Williams (2011) controlled for home country effects and set up a logistic regression model to compare the influence of cultural factors and institutional factors on entry strategy (propensity of pursuing majority stake by full ownership like greenfield and acquisition, or pursuing minority stake by shared ownership like joint venture). It was found out that when expanding into less developed economies, cultural distance becomes irrelevant and the effects of institutional quality become stronger, which implied that local institutional context is more complicated and plays bigger roles when it comes to MNCs entry to bottom of the pyramid markets.

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implies the ease of doing business and the level of transaction costs of entry. At firm level, firm size reflects the resource potential of the parent companies and the degree of internationalisation facilitates experience for expansion.

2.3 Chinese Market

As Chapter 2.1 pointed out, China is one of the most attractive bottoms of pyramid markets with high future growth potential. However, it lacks in research on the determinants that influence how MNCs choose to enter this market. According to the research from 1990s, there have been three popular modes of entry, wholly owned foreign entities, cooperative entities and joint ventures. Among them, the shared control modes, joint ventures, have been the most favoured way for foreign companies since 1980s. (Hu & Chen, 1993; Sun, 1999; Townsend, 2009)

However, it has been decades since the Chinese economic reform and open up policy were introduced in 1980s. The market has been witnessing dramatically changes with the liberalisation of the economy and fully control modes of entry has gradually become a more preferred way to get access to the market.

Hence, it would interest to explore whether the influence of different determinants for modes of entry has changed. And also which one is the major determinant now for MNCs. Understanding this would make contribute to helping MNCs to choose more adequate modes of entry into this market according to their own conditions.

2.4 Theoretical Background: Transaction Costs

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The transaction costs theory has been broadly brought into discussion to explain MNCs’ modes of entry. Anderson (2003), Hennart (1991) and Williams (2003) have been arguing that transaction costs are the major and most important determinants to explain MNCs’ modes of entry. This chapter would adopt the primary factors in transaction costs framework as the graph shows.

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2.4.1 Cultural Distance between Home Country and Host Country

Cultural distance, which is the difference between the cultural orientation of the home country and the target country, is among the factors that can contribute to the uncertainty related to entering a new market (Kogut & Singh, 1988; Schroath, Hu & Chen, 1993; Sun, 1999).

The closer the culture background the home country and host country has, the less trouble understanding the business environment of this market the MNC has. Closer cultural links provide MNCs with more advantages in language, the way of doing business, ethical sense and other basic understandings that help them to deal with local authorities more efficiently, to set up new business more easily and to make use of the local resource endowments in a more effective way.

Their better knowledge tends to reduce their reliance on local partners, existing establishments and networks. Thus, MNCs embrace with higher willingness in choosing full-control modes of entry if they are less culturally distant from the host country.

For those MNCs share less close cultural lies with this bottom of pyramid market than countries in group one and group two. These firms in group three tackle more disadvantages in understanding the way of doing business and suffer more conflicts in managing business and making decisions. Their disadvantageous conditions make them relatively more reliant on local firms and existing local operations. They suffer higher transactional costs in dealing with this unfamiliar business environment. Hence, we develop the hypothesis for cultural distance as below.

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H1alt: The greater the cultural distance between home country and host country, the more likely the MNC would prefer to choose full-control modes of entry into a bottom of pyramid market rather than shared-control way.

2.4.2 Economic Distance between Home Country and Host Country

The difference in economic conditions of host country and home country forms barriers for markets entry as well. Similar developing levels of economic conditions imply similar market dynamism. MNCs feel more familiar to do business in a market when they share similar market dynamism.

Generally, firms from more developed markets have already gained mature knowledge and experience dealing with customers in more developed market; since the customer behaviours are similar and it is easier for them to operate under familiar market dynamism and even dealing with existing supply chains. On the contrary, the less developed bottom of pyramid market is relatively novel to MNCs from developed world. There are not only concerns about whether their past successful experience in more developed markets would work effectively, but also fears of being confronted with high uncertainties and risks. This makes MNCs more reluctant to bear the costs of failing the investments.

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Hence, we develop the hypothesis of economic distance between home country and host country as follows.

H2a: The larger the economic distance between home country and host country, the higher the likelihood that the MNC would choose shared-control modes of entry into a bottom of pyramid market than full-control type.

H2alt: The larger the economic distance between home country and host country, the higher the likelihood that the MNC would choose full-control modes of entry into a bottom of pyramid market than shared-control type.

2.4.3 Local Economic Development Conditions of the Host Country

Apart from country level factors, regional specific conditions can act as a determinant for modes of entry as well. Different level of local economic development not only contributes to market attractiveness but also is associated with the level of uncertainty and risks in this region.

Local economic development conditions can be reflected from various perspectives. Higher local economic development of a certain region implies better economic conditions of this market. It is associated with stronger resource endowments of this region, such as higher population level, higher population growth, higher density of important industries, more human capital, higher infrastructure investment and more balanced industrial structure. It also implies better market conditions, such as better established transportation system, higher goods turnover rate and better connections to other regions. Market of higher local economic development would be able to facilitate MNCs’ economic activities.

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In this case, more liberal market makes MNCs more secure of pursuing higher equity control and more comfortable choosing full control modes of entry.

Hence, we develop the hypothesis of economic conditions is as below.

H3a: The higher the local economic development of the region, the more liberal the market is, then the higher the propensity that the MNC would choose full-control modes of entry than shared-control type.

H3alt: The higher the local economic development of the region, the higher the likelihood that the MNC would choose shared-control modes of entry into a bottom of pyramid market than full-control type.

2.4.4 Government Policy of the Host Country

More friendly the government policy towards foreign investment, the more motivated the MNCs to choose full control modes of entry.

More friendly government’s policy firstly provides guarantee of beneficial regulations where MNCs may have economic rewards for conducting a certain type of modes of entry. In addition, MNCs may have more flexible rights in deciding investment decision, business operations and managerial structure under a certain type of modes which the government supports.

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market attractiveness in particularly offer higher tax motivations to foreign companies. Special Economic Zones are introduced in 1979 as one step of the economic reform to attract foreign investments, to improve the economic development and technology advancement with more friendly taxation discounts to MNCs. As Waxin (2004), summarized that economic incentives to engage in business with China may be divided into two types: government tax incentives and incentives closely associated with areas having established industrial systems and a developed economic infrastructure.

Special Economic Zones since 1997 has been the most important policy for attracting foreign investment. Outside the Special Economic Zones, MNCs could receive substantial inducement of taxation to the type of shared control (joint venture). This shows that along with basic income tax rate for joint ventures (30%, there is a local surtax, levied by the local authorities (10% of tax), which in sum drives the tax rate for a MNC to 33%. On the contrary, within the Special Economic Zones, the tax rate of MNC would be reduced to 15%. (Ni, 2014)

There are in total 7 Special Economic Zones so far in Mainland China, including special exporting zones since 1997 (later in 1980 changed to special economic zones, not only for exporting incentives), which are Shenzhen, Shantou and Zhuhai (Guangdong Province) and Xiamen (Fujian Province); Hainan since 1988; and Kashgar and Khorgas (Xinjiang Uyghur Autonomous Region) since 2010.

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Hence, we develop the hypothesis for government policy as follows.

H4a: The more friendly the government policy towards foreign investment, the higher the likelihood that MNCs are more willing to perform fully-control modes of entry into a bottom of pyramid market than shared-control modes. H4alt: The more friendly the government policy towards foreign investment, the higher the propensity that MNCs choosing shared-control modes of entry into a bottom of pyramid market than full-control modes.

2.4.5 Research and Development Intensity

In particular for manufacturing industries, the higher the research and development intensity of its activity, the higher its technology level would be. The higher the technology level of the firm’s economic activity is, the more reluctant it would be to choose shared control modes especially into a bottom of pyramid market. It would be a huge opportunity cost if they perform shared control modes in a market with low institutional quality, where the patent rights are less clear and the behaviour of mimic by competitors is extremely high.

Hence, we develop the hypothesis for research and development intensity in manufacturing industries as follows.

H5a: MNCs that are of higher research and development intensity are more willing to perform fully-control modes of entry into a bottom of pyramid market than shared-control modes.

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3. Methodology

This chapter introduces the model to estimate the propensity, data collection and testing the models’ goodness of fit.

3.1 Modes of Entry Model

In order to investigate the determinants that influence MNCs’ propensity of choosing full control modes into a bottom of pyramid market as China, we need to test whether each determinant suggested by the transaction cost framework is statistically significant and to estimate to what extent each determinant impacts modes of entry of MNCs.

Here in this empirical research, the ‘Limited Dependent Variable Models’ (Brooks, 2008) will be employed to explore the pattern of MNCs’ modes of entry into the market of China. We would like to see how the propensity of pursuing fully-controlled modes of entry varies due to different determinants.

We use dummy variables to define the two most popular modes of entry into the market of China by foreign companies, the fully-control modes of entry, cross-border acquisition, as value 1, while the shared-control modes of entry, joint-venture, as value 0. The binary value 1 and 0 shadow a zero to one range where the propensity of MNC pursuing full-control entry modes lies.

According to Chapter 2, the major determinants for probability of choosing full-control modes are cultural distance between home country and host country (H1), economic distance between home country and host country (H2), local economic development conditions of the host country (H3), government policy of the host country (H4) and research and development intensity (H5).

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0 1 2

3 4 5

Modes of Entry= (Culture Dis tan ce) (Economic Dis tan ce)

(Local Economic Development) (Government Policy) (R & D Intensity) 1, if cross border acquisition

Modes of Entry 0, if jo int venture                 Equation 1 MOE of MNCs

We will adopt different forms of limited dependent models including linear probability model, the logit model and the probit model. Generally, linear relation is the simplest way to denote relation between variables (Woodridge, 2003). As Brooks (2008) summarized, the linear probability model where the dependent variable is a 0-1 dummy, is based on the assumption that the possibility of an event happening is linearly related to a basket of independent variables; however, two facts that linear probability may not be adequate to explain cannot be ignored: the process of its truncation would result in too many observations whose estimated probabilities are exactly one or zero (the boundaries) and it is not plausible that a firm would definitely choose either full-control modes of entry into a bottom of pyramid market or shared-control method.

Hence, other more specified models are also constructed where a function that effectively transformed the regression equation so that the estimated values of the dependent variable could be restrained within interval of (0, 1). Separately, the logistic model uses a cumulative logistic function and probit model employs a cumulative normal distribution (Brooks, 2008) and their forms are in the equations below. z z z 0 1 2 3 4 5 e 1 F(z) 1 e 1 e

z=Modes of Entry= (Culture Dis tan ce) (Economic Dis tan ce)

(Local Economic Development) (Government Policy) (R & D Intensity) 

 

 

    

      

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2 1 z ( ) 2 0 1 2 3 4 5 1 F(z) e 2

z=Modes of Entry= (Culture Dis tan ce) (Economic Dis tan ce)

(Local Economic Development) (Government Policy) (R & D Intensity)                 

Equation 3 Probit Model of Modes of Entry

Using the limited dependent models above, we could have a relatively more fitted regression model that could estimate foreign company’s’ propensity of pursuing full-control modes of entry into a bottom of pyramid market.

3.2 Data Collection

3.2.1 Dependent Variable

As the most popular two types of entry modes are this research’s main focus, information about full-control modes (cross-border acquisition) and shared-control modes (joint venture) into the market of China by foreign firms have been collected. 76,466 recorded deals of merges & acquisitions targeting at the market of China from 1997 to 2014 have been selected from the giant Database of Bureau van Dijk--Global M&A Deals Analysis (BvD--Zephyr)2. The database of Zephyr is one of the most informative sources for M&A deals and M&A research internationally. It updates the deals M&A, initial public offerings (IPO), planned initial public offerings, institutional investors purchase (IBO), management buy outs (MBO), share buyback, leveraged buyout (LBO), reverse takeover, venture capital (VC) and joint venture (JV) deals happening daily world-wide. So far, it has collected more than 1,000,000 deals dating back to the year 1997, cross all industries and covering all continents including Asian-Pacific region and mainland China.

2_{BvD- Zephyr is a comprehensive database of global M&A deals and rumours with integrated}

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After standardizing the data of all 76,466 deals targeting at mainland China, we only selected the ones that accommodate to the following requirements.

(1) Deals that are of these two categories, cross-border acquisition (full-control modes of entry) and joint venture (shared-control modes of entry);

(2) Acquirers of other countries from outside mainland China (excluding all domestic deals between Chinese acquirers and Chinese targets);

(3) Announced and successfully completed deals (excluding announced deals, assumed completed deals, pending deals, pending awaiting regulatory approval, pending awaiting shareholder approval, postponed deals, rumour, expired rumours, withdrawn rumours and withdrawn deals);

(4) Deals with information of acquirers’ country of origin;

(5) Deals with information of acquirers’ names, target names, target cities, target primary US SIC Code (standard industrial codes of the United States);

The sample size of this research was then narrowed down to 854 deals, including 631 cross-border acquisitions and 223 joint ventures. Here, we coded the entries as value 1 for full-control modes (cross-border acquisition) and value 0 for shared-control modes (joint venture).

3.2.2 Independent Variables

In line with the hypotheses we would like to test in Chapter 2, the explanatory variables related to each hypothesis are as follows.

(1) Cultural distance between home country and host country (H1);

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Schroath, Hu & Chen, 1993; Sun, 1999).

Group one includes firms from Hong Kong, Macao and Taiwan. They share the closest social culture bonds with mainland China. They have less trouble understanding the business environment of this market. Their advantages in language, cultural backgrounds, communication methods, the way of doing business, ethical sense, traditions in company structures, decision makings and other similarities help them to deal with local authorities more efficiently, to set up new business more easily and to make use of the local resource endowments in a more effective way. Their better knowledge in operating in this bottom of pyramid market makes them less reliant on local partners, existing establishments and networks. Thus, MNCs in this group embrace with higher willingness in choosing full-control modes of entry.

Group two includes all Asian Neighbouring Countries of China, such as Japan, South Korea, Singapore, Philippines, Malaysia and Thailand. The countries in this group have similar cultural backgrounds. Historically, these neighbouring countries have developed closed ties due to the relative advantage of geographic proximity. Their past experience equips them with easier understanding about the business environment of mainland China. They are relatively less uncomfortable to fully control either from managerial perspective or setting up networks with other businesses.

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Among all three groups, firms of group three have the greatest cultural distance between this bottom of pyramid market and their home markets, firms of group two have the medium level of cultural distance while group one’s companies have less disadvantages in the distance of cultural links. Hence, in line with H1, MNCs of group three are more willing to choose shared modes of entry, while companies of group one show higher propensity of pursuing full-control and group one firms tend to contribute more to joint venture entries to this market. (2) Economic distance between home country and host country (H2);

The difference in economic conditions of host country and home country forms barriers for markets entry as well. Similar developing levels of economic conditions imply similar market dynamism. MNCs feel more comfortable to do business in a market which has similar economic conditions. Firms from more developed markets have already acquired mature knowledge and experience dealing with customers in more developed market; however the less developed bottom of pyramid market is relatively new to them. There are also concerns about whether their past successful experience in more developed markets would work effectively. The higher the economic distance between host country and home country, the more different the market dynamism it is between the two, which makes firms from developed countries more reliant on local firms when entering a bottom of pyramid market. Hence, they are more comfortable choosing shared-control modes of entry, setting up joint ventures or even bidding and working with government’s projects. (Townsend, Yeniyurt & Talay, 2009)

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(3) Local economic development conditions of the host country (H3);

According to different local economic development conditions (H3), we categorize the targets into three regions, the Eastern Coastal area of China, the Middle zone of China and the Western zone of China (MLR of P.R. China, 2014; Ni, 2014). Graph below shows the segmentation according to local economic development.

Graph 4 The Three Economic Areas of P. R .China (Source: Ni, 2014, pp. 18)

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transportation. Also they have been developed and used as important region for manufacturing and agriculture industries since China’s open up policy and economic reform in 1980s led by Xiaoping Deng. This region has been the most developed area of China and has relatively higher economic growth. It has the better establishments and infrastructure, technology and education advantage and high internationalisation level. The higher local economic development level has more liberal business environment where MNCs find more comfortable to choose fully-control modes of entry because of lower uncertainty and less risks of doing business. Just as Sun (1999) proved that higher local economic development is positively correlated with the establishments of fully-control ventures.

The middle area of China includes Heilongjiang Province, Jilin Province, Inner Mongolia, Shanxi Province, Anhui Province, Jiangxi Province, Henan Province, Hubei Province and Hunan Province, in all 9 provinces of China. It has more resource endowments but less advantageous position and lower economic development. Although it has been acting as ‘connection’ to the coastal area and western area of China, the market is less liberal than coastal area. Due to higher uncertainty and more risks of doing business, MNCs would be less willing to choose wholly owned acquisitions as entry modes.

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(4) Government policy of the host country (H4);

Government’s policy has the most important effects to the modes of entry decision of MNCs especially for China (Sun, 1999). In order to promote economic reform and attract more foreign investment to help with the economic development, China has been setting up ‘Special Economic Zones’ (National Committee of Literature & History of Chinese People's Political Consultative Conference, 2009). The cities in Special Economic Zones embrace with more market attractiveness in particularly offer higher tax motivations to foreign companies. Special Economic Zones are introduced in 1979 as one step of the economic reform to attract foreign investments, to improve the economic development and technology advancement with more friendly taxation discounts to MNCs. There are in total 7 Special Economic Zones so far in Mainland China, including special exporting zones since 1997 (later in 1980 changed to special economic zones, not only for exporting incentives), which are Shenzhen, Shantou and Zhuhai (Guangdong Province) and Xiamen (Fujian Province); Hainan since 1988; and Kashgar and Khorgas (Xinjiang Uyghur Autonomous Region) since 2010.

These Special Economic Zones have more attractive features for foreign investments, which are as follows (National Committee of Literature & History of CPPCC, 2009).

(a) They are usually close to important harbours which have higher convenience of goods turnovers and lower transportation costs;

(b) Open up policy would be conducted within the zones and lower custom taxation and company income taxation in order to attract foreign investments;

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system;

(d) Although the local authorities have the rights to amend the managerial regulations according to local conditions, the foreign companies in the zones have relative autonomy on their own;

(e) The optional modes of entry are restricted to certain types.

• Shared-equity entities with local firms within the zones or outside the zones where both counterparts offer investments;

• Joint ventures where local firms or authorities offer establishments, resource endowments and labour, foreign firms offer investment and the responsibilities of both counterparts are defined and bonded via contracts. After contracts expire, infrastructures belong to the Chinese counterparts. • Fully-owned equity entities, where foreign firms negotiate the locations and

running period with local governments, embrace relatively high independence of operating the entity but afford any uncertainty or risk on their own.

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In addition, Tianjin, Shanghai, Dalian, Qinhuangdao, Yantai, Qingdao, Lianyungang, Nantong, Ningbo, Wenzhou, Fuzhou, Guangzhou, Zhejiang, Beihai, Yingkou and Weihai have been pointed as coastal open cities which have more liberal policies to attract foreign investments.

(a) Foreign firms have more flexibility in construction projects;

(b) Foreign firms who bring advanced technology to update traditional Chinese firms have taxation discounts, including custom tax, imports of industrial and commercial consolidated tax and business income tax; (c) Foreign firms which bring technology that in need and are willing to set up

cooperated research and development institutions have further autonomy in allocating the investment and further discounts in taxation;

(d) Foreign firms have higher amount of foreign exchange limitation and loans in foreign exchange;

The propensity of MNCs pursuing fully-control modes of entry would be higher if the target is located in zones with beneficial policies from the government since the market in the special economic zones is more liberal for doing business.

Here, if the deals happening in the range of the 7 Special Economic Zones, 10 Experimental Zones, 2 Pilot Reform Zones or coastal open cities, are coded as value 1; otherwise, 0.

(5) Research and development intensity (H5);

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pyramid market where patent right and use of knowledge are relatively less clear, they have lower incentives to pursue shared-control modes of entry. As a result, the higher the technological contexts of the activities are, the higher the propensity of MNCs pursuing fully-control modes of entry would tend to be (Sun, 1999).

Here in this research, we apply the US SIC codes to group companies in manufacturing industries. Among all deals, there are 320 deals made by MNCs in manufacturing industries. 4 layers of technology levels are introduced according to the research and development intensity of the firm’s activity. The first 3 digits of the SIC code indicate the industry group and the first two digits indicate the major group. Suggested by the National Statistic Country Classification by the United Nations (2008) and OECD (2003) are as follows (Details are listed in Appendix 9.2).

(a) High Technology Industries;

High-Technology Industries include the specific industries with these SIC codes: Aircraft and spacecraft 353; Pharmaceuticals 2423;Office, accounting and computing machinery 30; Radio, TV and communications equipment 32 and Medical, precision and optical instruments 33. They are coded into 4.

(b) Medium High Technology Industries;

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(c) Medium Low Technology Industries;

Medium Low Technology Industries include the specific industries with these SIC codes: Building and repairing of ships and boats 351; Rubber and plastics products 25; Coke, refined petroleum products and nuclear fuel 23; other non-metallic mineral products 26; Basic metals and fabricated metal products 27-28. They are coded into 2;

(d) Low Technology Industries;

Low Technology Industries include the specific industries with these SIC codes: Recycling 36-37; Wood, pulp, paper, paper products, printing and publishing 20-22; Food products, beverages and tobacco 15-16; Textiles, textile products, leather and footwear 17-19. They are coded into 1.

Then we use dummies t1, t2 and t3 to represent the group of low technology industries, the group of medium low technology industries and the group of medium high industries. If they belong to a certain group, they are coded into value 1, or coded into value 0 otherwise.

3.2.3 Control Variable

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it is named as sector 5. If it is doing business related to Hotels & restaurants, it is labelled as sector 6. If it is in the industry of Insurance companies, Bank or other financial services, it is coded into sector 7. If it is doing Machinery, equipment, furniture or recycling, it is coded as sector 8. As for Metals & metal products, it is labelled as sector 9. If it is in other services, it is labelled as sector 10. If it is regarding to the business of post and telecommunications, it is put into the sector 11. If it is Primary Sector (agriculture, mining, etc.), it is coded into sector 12. If it is doing business regarding to publishing or printing, it is coded into sector 13. If it is in the industry of textiles, wearing apparel or leather, it is in the sector 14. As for transport, it is labelled as sector 15. And if it is regarding to business of wholesale & retail trade, it is coded into sector 16. Eventually, the industry of wood, cork and paper is put into sector 17.

Then we use dummies s1 to s16 to represent the different groups of sectors. If they belong to a certain group, they are coded into value 1, or coded into value 0 otherwise.

3.2.4. Operationalization of the Variables

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Variable Explanations

Deal Number Deal Number

Type "acquisition"=1, "joint venture"=0 Home Country Acquirer’s country

Country Acquirer’s country code

Culture

"c1"=Hong Kong, Macao, Taiwan; "c2"=Asian Neighbouring Countries, Japan, South Korea, Singapore, Philippines, Malaysia, Thailand; "c3"=Other Foreign

Countries

OECD If OECD membership, 1; Otherwise, 0

Value Deal value in th EUR

Date Deal Completed date

City Target city name

SEZ If in special economic zone, 1; otherwise, 0 Region "East China"=r1, "Central China"=r2, "West China"=r3

Sector

Target major sector categorization according to database: "Chemicals, rubber, plastics, non-metallic products"=1, "Construction"=2, "Education, Health"=3, "Food, beverages, tobacco"=4, "Gas, Water, Electricity"=5, "Hotels & restaurants"=6, " Insurance companies, Bank and other financial services "=7, "Machinery, equipment, furniture, recycling"=8, "Metals & metal products"=9, "Other services"=10, "Post and telecommunications"=11, "Primary Sector (agriculture, mining, etc.)"=12, "Publishing, printing"=13, "Textiles, wearing apparel, leather"=14, "Transport"=15, "Wholesale & retail trade"=16, "Wood, cork, paper"=17

Province The province of the target city SIC Target primary US Standard Industrial Code

Technology

High-technology industries (Aircraft and spacecraft 353; Pharmaceuticals 2423; Office, accounting and computing machinery 30; Radio, TV and communications equipment 32; Medical, precision and optical instruments 33) =4;

Medium-high-technology industries (Electrical machinery and apparatus, . 31; Motor vehicles, trailers and semi-trailers 34; Chemicals excluding pharmaceuticals 24 excl. 2423; Railroad equipment and transport equipment, 352 + 359;

Machinery and equipment, 29) =3;

Medium-low-technology industries (Building and repairing of ships and boats 351; Rubber and plastics products 25; Coke, refined petroleum products and nuclear fuel 23; Other non-metallic mineral products 26; Basic metals and fabricated metal products 27-28) =2;

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The entire data panel overviews are as the graphs below present.

Graph 5 Data Panel View One

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Graph 7 Data Panel View Three

3.3 Goodness of Fit

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4. Findings

Following the methodology in chapter 3, this chapter firstly has an overview of all determinants under examining and then estimate models to predict propensity of pursuing full control. Eventually, empirical tests related to hypotheses in chapter 2 have been conducted.

4.1 Descriptive statistics

Among all 854 deals, 631 are full control modes and 223 are shared control modes. 73.89% of the deals we selected are conducted via cross-border acquisitions. This is quite different from Sun (1999)’s study, where the majority of the modes of entry were joint ventures during 1989 to 1997. The modes of entry during 2000 to 2014 in this research are viewed by trend over time, cultural groups, OECD groups, economic areas, special economic zones and technology level of the economic activity as follows.

4.1.1 The Trend of the Modes of Entry

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Judging by the graph above, there has been a trend of increasing full control modes of entry over time since 2003. And for the last decade, full control modes have been the major way of MNCs entering into Chinese market.

4.1.2 Modes of Entry by Cultural Groups

Cultural Group Composition Full-Control Shared-Control Total Propensity

c1 Hong Kong, Macao,

Taiwan 212 18 230 92.17%

c2 Asian Neighbouring

Countries 85 123 208 40.87%

c3 Other Foreign

Countries 334 82 416 80.29%

Table 4 Modes of Entry by Cultural Groups

Firms from Hong Kong, Macao and Taiwan continue to have the highest propensity of pursuing full control modes. However, this group is not the major source any more. For the last decade, China has been welcoming firms from foreign countries apart from neighbouring countries.

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More specifically, the propensity of pursuing full control by group 1 has been increasing rapidly and has been staying at high level.

Graph 10 Modes of Entry by Firms from Asian Neighbouring Countries (2000-2014)

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Graph 11 Modes of Entry by Firms from Other Foreign Countries (2000-2014)

MNCs from other foreign countries have showed increasing motivation in pursuing full control modes of entry and have been gradually abandoning the traditional modes of joint venture in the past. And also the amount of market entry is enormous, nearly twice the size of the entries made by group 1 firms.

4.1.3 Modes of Entry by Economic Distance

Economic

Distance Composition Full-Control Shared-Control Total Propensity

OECD Acquirers form OECD

Membership Countries 179 18 335 53.43% Non OECD Other Countries 452 123 519 87.09%

Table 5 Modes of Entry by Economic Distance

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Graph 12 Modes of Entry by Firms from OECD Countries (2000-2014)

The propensity of firms from OECD countries pursuing full control has been increasing since 2001. However it collapsed quickly after the 2008 crisis.

Graph 13 Modes of Entry by Firms from Non OECD Countries (2000-2014)

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4.1.4 Modes of Entry by Different Economic Zones

Region Composition Full-Control Shared-Control Total Propensity

r1 Eastern Costal Area of China 567 188 755 75.10% r2 Middle Area of China 27 15 42 64.29% r3 Western Area of China 37 20 57 64.91%

Table 6 Modes of Entry into Different Economic Areas of China

The majority of the deals happened in the more developed economic area of China, the eastern coastal region. And this region shows higher propensity of attracting full control modes of entry as well.

Graph 14 Modes of Entry into the Area of Eastern China (2000-2014)

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Graph 15 Modes of Entry into the Area of Middle China (2000-2014)

In total, the middle area of China has been the least attractive market for MNCs during the last decade.

Graph 16 Modes of Entry into the Area of Western China (2000-2014)

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4.1.5 Modes of Entry by Government Policy (Special Economic Zones)

Region Composition Full-Control Shared-Control Total Propensity Special

Economic zones

Target Cities Located within Special Economic

Zones

577 206 783 73.69%

Non Special Economic

Zones

Target Cities Located Outside Special Economic Zones

54 17 71 76.06%

Table 7 Modes of Entry into Special Economic Zones and Non Special Economic Zones The vast majority of entries have been chosen in special economic zones of China. But the propensity of choosing full control or shared control did not differ between inside special economic zones and outside.

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Graph 18 Modes of Entry into the Non Special Economic Zones of China (2000-2014) As the two graphs show above, deals in special economic zones and outside have shared similar propensity of full control entry.

4.1.6 Modes of Entry by Research and Development Intensity

Technology

Level Composition Full-Control Shared-Control Total Propensity t1 Low Technology Industry 138 55 193 71.50%

t2 Industry of Medium low

Technology 69 16 85 81.18%

t3 Industry of Medium High

Technology 24 6 30 80.00%

t4 High Technology Industry 8 4 12 66.67% Table 8 Modes of Entry for Manufacturing Industries

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4.2 Model Estimates and Empirical Tests

As the descriptive statistics summarized in Chapter 4.1, 73.89% of the deals we collected are conducted via cross-border acquisitions. This means that in total, only 26.11% of modes of entry are made in shared-control ways. The percentages of fully-control modes of entry and shared-control modes of entry have large gap, which shows in reality the modes of entry are unbalanced. Logit model using cumulative distribution would be more reliable in estimating than probit model where the transformation is in standard normal distribution (Brooks, 2008). Hence, in this case, only the basic multiple regression model and logit model of non-linear regression would be estimated.

Firstly, the multiple regression model for probability is as the equation below.

i 1 i 2 i 3 i 4 i 5 i 6 i j ij i

j 1:16

type =c+( c1 + c2 )+ oecd +(

r1 + r2 )+ sez +(

m s )







 

Equation 4 Simple Multiple Regression Model of Modes of Entry

Where the coefficient for every variable explains how much percent or to what extent it contributes to the propensity of pursuing fully-control modes of entry by the MNCs.

The dummies are as Chapter 3.2.4 operates.

C1=1, if the acquirer is in cultural group 1 (Hong Kong, Macao, Taiwan) =0, otherwise.

C2=1, if the acquirer is in cultural group 2 (Asian Neighbouring Countries) =0, otherwise.

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R1=1, if the acquirer’s target city is located in the eastern coastal area of China, =0, otherwise.

R2=1, if the acquirer’s target city is located in the middle area of China, =0, otherwise.

SEZ=1, if the acquirer’s target city is located in the special economic zone of China, =0, otherwise.

S1 to S16, =1, if the acquirer is categorised into this sector, =0, otherwise.

Secondly, the non-linear model for estimating the propensity would in the form as the equation shows below. Here, different from the basic multiple regression model, the coefficients of the variables does not explain the marginal contribution to the propensity. In this case, we need to calculate the mean of each variable and get F (z). Then as Anderson & Newell (2003) summarized, we could calculate the marginal effect of each variable to the propensity which is βi [F (z)]. And also the dummies are as the same as in the basic model above.

i i i z i z z i i 1 i 2 i 3 i 4 i 5 i 6 i j ij i j 1:16

e

1 F(z )

1 e

z =type =c+( c1 + c2 )+ oecd +(

r1 + r2 )+ sez +(

m s )











 

Equation 5 Logistic Model of Modes of Entry

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Variable Mean Marginal Effects of Basic Model Sig.

Estimates of Logit Model Sig.

Marginal Effects of Logit Model C n. a 0.9014 *** 0.901365 *** n. a C1 0.9217 -0.0106 -- -0.010646 -- -0.0066 C2 0.4087 -0.3618 *** -0.361784 *** -0.2230 OECD 0.5343 -0.2737 *** -0.273723 *** -0.1687 R1 0.7510 0.1024 * 0.102368 * 0.0631 R2 0.6429 -0.0203 -- -0.020326 -- -0.0125 SEZ 0.7369 -0.0424 -- -0.042361 -- -0.0261 S1 0.7835 0.0138 -- 0.013846 -- 0.0085 S2 0.7963 -0.0560 -- -0.055997 -- -0.0345 S3 0.9286 0.0946 -- 0.094583 -- 0.0583 S4 0.7843 0.0835 -- 0.08352 -- 0.0515 S5 0.6800 -0.1554 -- -0.1554 -- -0.0958 S6 0.7692 0.0508 -- 0.050791 -- 0.0313 S7 0.1538 -0.5174 *** -0.517431 *** -0.3189 S8 0.6995 -0.0348 -- -0.034762 -- -0.0214 S9 0.7358 0.0077 -- 0.007666 -- 0.0047 S10 0.7902 0.0152 -- 0.015152 -- 0.0093 S11 0.0000 -0.3259 -- -0.325864 -- -0.2009 S12 0.7500 -0.0203 -- -0.020264 -- -0.0125 S13 0.7273 -0.0908 -- -0.090765 -- -0.0559 S14 0.8261 -0.0053 -- -0.005296 -- -0.0033 S15 0.6286 -0.0903 -- -0.090265 -- -0.0556 S16 0.7273 0.0275 -- 0.02749 -- 0.0169 *** Significant at 0.01; ** Significant at 0.05; * Significant at 0.1; -- Not Significant

Table 9 Estimates of Basic Model and Logit Model

The R Squared value of the basic multiple regression is 0.3017 and the Adjusted R Squared value is 0.2832 which are relatively not high. However, the probability of F statistics is 0.0000 which shows the model has satisfying goodness of fit. So the determinants all together could capture the propensity of pursuing full-control modes that we intend to measure.

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4.2.1 Culture Distance between Home Country and Host Country (H1)

From the estimates table of basic regression, we could see that if the acquirer is from cultural group 1, then its propensity of pursuing full-control modes of entry would reduce by 1.06%, but it is not significant. And if it is from cultural group 2, the propensity of pursuing full-control modes of entry would significantly deduct by 36.18%.

From the estimates table of logit model, it could be predicted that if the acquirer is from cultural group 1, then its propensity of pursuing full-control modes of entry would reduce by 0.66%, but it is not significant. And if it is from cultural group 2, the propensity of pursuing full-control modes of entry would significantly deduct by 22.3%.

The cultural group 2 dummies in both models are very statistically significant. This shows that if the acquirer is an Asian Neighbouring country, it embraces higher motivation for setting up joint ventures as modes of entry. The negative signs prove that the larger the culture distance between home Country and host Country is, the less willing the MNC would be to choose full-control modes to enter into a bottom of pyramid market.

4.2.2 Economic Distance between Home Country and Host Country (H2)

From the estimates table of basic regression, we could see that if the acquirer is OECD country, then its propensity of pursuing full-control modes of entry would significantly reduce by 27.37%.

From the estimates table of logit model, it could be predicted that if the acquirer is membership country of OECD, then its propensity of pursuing full-control modes of entry would significantly reduce by 16.87%.

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that if the acquirer is a membership country of OECD, it embraces higher motivation for setting up joint ventures as modes of entry. The negative signs prove that the larger the economic distance between home country and host country is, the less motivated the MNC would be to use full-control modes entering into a bottom of pyramid market.

4.2.3 Economic Condition of the Host Country (H3)

From the estimates table of basic regression, we could see that if the acquirer chooses target city in eastern China, then its propensity of pursuing full-control modes of entry would significantly increase 10.24%. And if it is located in middle China, the propensity reduces 2.03% but it is not statistically supported.

From the estimates table of logit model, it could be predicted that if the deal is in eastern China, then the propensity of pursuing full-control modes of entry would significantly increase 6.31%. And if the deal is targeting at middle China, the propensity reduces 1.25% but it is not statistically supported

The eastern coastal area dummies in both models are very statistically significant. This shows that if the target city is in more economic developed area of China, MNC embraces higher motivation for full control modes of entry. The positive signs prove that the higher the local economic development of the market is, the more motivated the MNC would be to use full-control modes entry into a bottom of pyramid market.

4.2.4 Government Policy of the Host Country (H4)

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From the estimates table of logit model, it could be predicted that if the deal is in special economic zone, then the propensity of pursuing full-control modes of entry would deduct 2.61% but it is not statistically supported as well.

The special economic zone dummies in both models are not statistically significant. And the positive signs did not accommodate to our hypothesis. This shows that the effects of government policy do not have proof here.

4.2.5 Research and Development Intensity (H5)

Next, we narrow down the sample to manufacturing industries only to see whether the technology intensity of the firm’s activity would have statistically significant impacts on the propensity of pursuing fully-control modes by the MNCs.

We add technology dummies into the original ones. T1=1, if it is categorised as low technology industry, =0, otherwise.

T2=1, if it is categorised as medium low technology industry, =0, otherwise.

T3=1, if it is categorised as medium high technology industry, =0, otherwise.

Also since now all deals are in one sector, manufacturing, we take the s dummies for sectors out to avoid singular matrix problem. Hence the basic regression and logit model are as follows.

i 1 i 2 i 3 i 4 i 5 i 6 i j ij i

j 1:3

type =c+( c1 + c2 )+ oecd +( r1 + r2 )+ sez

(

q t )









 

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i i i z i z z i i 1 i 2 i 3 i 4 i 5 i 6 i j ij i j 1:3 e 1 F(z ) 1 e 1 e

z =type =c+( c1 + c2 )+ oecd +( r1 + r2 )+ sez +( q t )





 

 

     



 

Equation 7 Logistic Model of Modes of Entry

The model estimates are summarized into the table below and the raw estimations are available in Appendix 9.4. The F(z) calculated from this sample is.0.6566.

Variable Mean Marginal Effects of Basic Model Sig.

Estimates of

Logit Model Sig.

Marginal Effects of logit Model C n. a 0.780483 *** 0.827701 -- n. a C1 0.9412 -0.006089 -- 0.167555 -- 0.1100 C2 0.4085 -0.347328 *** -1.042707 *** -0.6846 OECD 0.5507 -0.265831 *** -0.918027 *** -0.6028 R1 0.7692 0.048873 -- 0.145156 -- 0.0953 R2 0.4286 -0.185517 -- -0.702008 -- -0.4609 SEZ 0.7534 0.05217 -- 0.26614 -- 0.1747 T1 0.715 0.072336 -- 0.247265 -- 0.1624 T2 0.8118 0.09581 -- 0.290198 -- 0.1905 T3 0.8 0.079637 -- 0.213135 -- 0.1399 *** Significant at 0.01; ** Significant at 0.05; * Significant at 0.1; -- Not Significant

Table 10 Estimates of Basic Model and Logit Model for Manufacturing Industry

The R Squared value of the basic multiple regression is 0.2792 and the Adjusted R Squared value is 0.2583 which are relatively not high. However, the probability of F statistics is 0.0000 which shows the model has not bad goodness of fit. So the determinants all together could capture the propensity of pursuing full-control modes that we intend to measure for manufacturing industry.

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5. Discussion

5.1 Results

As Chapter 4.2 summarized, H1, H2 and H3 have been supported while we did not find sound proof for H4 or H5. The evidences for cultural distance, economic distance and economic conditions of host country have once again explained how transactional costs influence MNCs to choose modes of entry into bottom of pyramid markets. The disadvantages in languages, cultural understandings, ways of doing business, business ethics, different market dynamisms and other perspectives that embody high uncertainty and large amount of risks show high transactional costs of entering bottom of pyramid markets. In line with the transactional cost (TC) theories, higher risks and uncertainties make MNCs have higher motivations to cooperate with local firms.

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technology and medium low technology, which limited our test for the relation between technology level and propensity of pursuing full control. However, this cannot be ignored that generally, MNCs who decide to serve the bottom of pyramid markets, are those do not involve high technology, because of their pursuits for cheaper labour or natural resources instead of higher intelligence.

5.2 Contributions of the Research

Based on the existing entry mode of MNCs models, this research has taken the local/ regional level factors into considerations, expanding the categories of national level and firm level.

Instead of controlling for home country effects as other research prevailed, here host country effects have been controlled by examining the modes of entry by MNCs into the markets of different cities. This shows more detailed analysis of regional markets than the national market only.

In addition, the estimated models clearly show which determinant has the most import influence in modes of entry strategy of MNCs, suggest accurate marginal effect of each determinant. And prove that transaction costs should be issues to be concerned with when entering bottom of pyramid market.

5.3 Limitations of the Research

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Here we only focus on comparing two types of entry, cross-border acquisition as full-control and joint venture as shared control. If detailed information about the other mode of entry, cooperated ventures, could be collected, it would provide a more comprehensive image of testing government’s policy. Since this one is also the possible modes of entry listed in National Foreign Investment Report. But there is no source collecting the deals so far.

Furthermore, more detailed information could be explored about what the economic activity of the MNC is and how it helps to serve this market, improve people’s living conditions and increase its income level. More information would be suggested in chapter 7.

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6. Conclusions

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7. Suggestions for Further Work

7.1 More Options of Modes of Entry

We could collect more options of modes of entry to compare, as the summary graph shows below, not limiting to inorganic modes.

Graph 19 Modes of Entry (Gubbi, 2014b)

7.2 More Determinants to Improve Model’s Goodness of Fit

More determinants of modes of entry could be captured not only from the public database but also could be from using questionnaires and doing in depth interviews with the managers of MNCs. For example the indicators representing institutional factors, such as the institutional thickness by the layers of governance, the number of government organisations, the number of local communities, etc. could be explored.

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7.3 Local Economic Development

As for the research on why it is important to serve the bottom of pyramid markets, it is also interesting to continue this study and carry on with whether the modes of entry decision could influence the local economic development of the bottom of pyramid markets. This requires more details about what kinds of economic activities the MNCs would be involved after entering the market.

This important issue is the significant focus on the local economic development of the bottom of the pyramid by the local government, which addresses reducing poverty of the people who live at the bottom of the pyramid and incorporates many local government and private sector functions including environmental planning, transportation development, infrastructure provision, real estate development and finance (World Bank, 2014). The comprehensive measurement of how the local economic development has been improved is the improvement of the income level (Rodrik, 2005). Although the progress of the local economic development is driven by improvements in multiple levels, including whether the customers’ needs are met (low price, good product quality, multiple choices in product ranges), whether people’s living conditions are increased (sanitary conditions, basic facilities), whether infrastructures are improved (communications, transportation, other public goods) and whether the barriers of doing business in the markets are reduced (formal and informal institutions) (Farag Nagi, 2012), the composite measurement of income level (GDP per capita, adjusted from Purchasing Power Parity) is still the most simple and comprehensive one to give one a quick assessment of the local economic development level. With the improvements of all multiple levels, the poverty problem of the people who live at the bottom of the pyramid could be gradually released and reflected on the local income level (GDP per capita, adjusted from Purchasing Power Parity).

Graduation Thesis

Dual Masters Award in Advanced International Business

Management

Academic Intake 2013/15

Graduation Thesis

MNCs’ Modes of Entry into the Bottom of Pyramid Markets:

Fully-Control or Shared-Control?

Abstract

Acknowledgement

Contents

1. Introduction

2. Literature Review

3. Methodology

4. Findings

type =c+( c1 + c2 )+ oecd +(

r1 + r2 )+ sez +(

m s )















 

e

1

F(z )

1 e

1 e

z =type =c+( c1 + c2 )+ oecd +(

r1 + r2 )+ sez +(

m s )























 

type =c+( c1 + c2 )+ oecd +( r1 + r2 )+ sez

(

q t )

















 



5. Discussion

6. Conclusions

7. Suggestions for Further Work