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TOPCO崇越論文大賞

論文題目

The Deterrence Effect of Multimarket

Competition on MNCs Competitive

Aggressiveness- the Moderating Effect of

Resource Similarity and Culture

Distance

報名編號： AS0016

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The Deterrence Effect of Multimarket Competition on MNCs

Competitive Aggressiveness- the Moderating Effect of

Resource Similarity and Culture Distance

Abstract

Drawing on past researches of the drivers and consequences of competitive

aggressiveness, this present study explored how the internal and external factors affect

rivals’ competition in multimarket contact MMC). Based on the Red Queen effect, we

examined the contingency effects of resources similarity and culture distance to the

focal firms’ aggressive competition in MMC context.

The hypotheses tested a sample of the top 20 global shipping companies with 640

quarterly data from 2007 to 2014, by constructing a database of 3,625 news articles with

8,789 competitive actions. The empirical finding shows that the degree of MMC

positively affects the focal firm’s competitive aggressiveness. A higher degree of

resource similarity weakens the relationship between MMC and competitive

aggressiveness. However, a higher degree of culture distance between two parent

countries of MNCs and the parent-host countries strengthens the relations between

MMC and competitive aggressiveness, respectively.

The results suggested the concepts of rivalry deterrence and local response

pressure in highly overlapped global market of multinational corporations (MNCs),

contributing to the research of competitive dynamic and strategy management.

Keywords: competitive aggressiveness, multimarket contact, Red Queen effect,

resources similarity, culture distance, rivalry deterrence, local response pressure

Chapter 1 Introduction

Competitive interactions between rivals triggers an intense competition as the Red

Queen effect of accelerated competition (Barnett and Hansen, 1996; Carroll, 1970;

Derfus, Maggitti, Grimm, and Smith, 2008), whereas critical strategy interdependences

decrease competitive rivalry because of the mutual forbearance among rivals (Baum and

Korn, 1999; Chen, 1996; Edwards, 1955; Scott, 1982; Stephan et al., 2003; Upson et al.,

2012; Yu and Cannella, 2013; Yu, Subramaniam, and Cannella, 2009).

The reciprocal system of causality, known in evolutionary theory as the “Red Queen”

(Van, 1973), is a central, driving force behind the evolution of competitive success

and failure.

While in developing this extended concept of co-evolution, both of the attacker and

the defender constantly improve themselves to follow-up and surpass the advancer for

survival (Barnett and Hansen, 1996; Kapoor and Lee, 2013). Under a hyper-competitive

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environment, the Red Queen effect drives firms to learn continually, change innovatively,

and strengthen organizational capabilities incessantly (Barnett and Hansen, 1996;

D’Aveni, Dagnino, and Smith, 2010; Derfus et al., 2008). Such a self-reinforcing cycle

enhances the competitive capability of all the rivals; however firms may stay in the

same position unless they run forward at double speed (Carroll, 1970; Merry, 1999). For

example, the top five global smart phone vendors occupy more than 70% of 2011

market share and increase to 80% in 2012; however, they all stay in the same position

(e.g., Samsung, Apple, Nokia, HTC, and RIM).

Due to an increasing number of enterprises devote to multinational markets,

cross-border competition has become an important issue in the field of strategic

management (Ghoshal, 1987; Gimeno, 2004; Porter, 1993). More than 50% of strategic

alliances were shaped from competition (Harbison, Pekar, and Stasior, 1998), a figure

that has continually increased in recent years. In terms of the operation in foreign

markets, MNCs normally apply a higher commitment to resource allocation for saving

costs, and the successful ones typically consider their competitor as well as their

complementor to achieve economies of scale (Burt, 1980; Kogut, 1989; Porter, 1993).

Such as in a competition network, firms need to transform a competitive threat to a

complementary opportunity; in other words, they have to compete without a saint and

fight without killing the opposition (Gnyawili and Madhavan, 2001; Haveman and

Nonnemaker, 2000). Accordingly, how the Red Queen effect affects MNCs’ interactions

in a cross-border competition network is worth further exploration and discussion

(Barnett and Hansen, 1996).

Although a number of studies have made significant efforts in the context of MMC,

their work remains anchored to a single country, and seldom explores the infirm rivalry

of international business (except for Karnarni and Wernerfelt, 1985; Mitsuhashi and

Greve, 2009; Yu et al., 2009). Yu and her colleagues’ (2009) found that the competitive

aggressiveness of the subsidiary of multinational corporations (MNCs) is weaker when

global automobile manufacturers met rivals across a range of international market. In

the present work, we will examine the relationship between MMC and MNCs’

competitive aggressiveness at the level of focal firms’ actions, which was critical to

understanding the reality of interfirm rivalry and the strategic decision-making process

of competitive dynamics (Chen, Smith, and Grimm, 1992).

Referring to above-mentioned research background and motivation, this study aims

to explore how MNCs make the critical decision in multimarket competition owing to

Red Queen effect. Building on theories of competitive dynamics and multimarket

competition, this study intends to fill up the gap of past literatures on interfirm rivalry at

action level, specifically in a competition network. Moreover, we hope to provide

practical suggestions to MNCs engaging in cross-border multimarket competition,

particularly suffering in a contingency approach to aggressive competition.

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Chapter 2 Literature Review and Hypothesis Development

2.1. Competitive Dynamics

The success of the focal firm’s action leads to competitors’ response and attack,

thereby damages the focal firm's advantages (Chen and Miller, 2012; Nair and Selover,

2012; Smith, Grimm, Gannon, and Chen, 1991). Since the leader firm will continue to

suffer from other competitors’ incessant and relentless attacks, the competitive

advantage is temporary with uncertainty, leading to a short-term equilibrium (D'Aveni,

1994). In a rapidly changing hyper-competitive environment, firms have to take

aggressive actions and responses to strengthen their competitive advantage to maintain

their existing market position (Chen, 1996; Chen and Stucker, 1997; Ferrier, 2001;

Porter, 1980). In other words, interfirm competition is a bitter contest to defeat

competitors for a leading position or to achieve the advantage in the niche market

(Kirnzer, 1973; Chen et al., 2010).

The awareness of attack determines how firms take competitive action in interfirm

rivalry, and the defenders may not make a straightforward response unless having strong

motivations to take response for super profits (Yu and Cannella, 2007) with comparable

capability (Chen, 1996; Nelson and Winter, 1982; Yu et al., 2009). Therefore, a further

concept of the competitive repertoires is proposed to clarify interfirm competition at

firm-level, i.e. the simplicity of competitive repertories, competitive inertia, and

nonconformity in competitive repertories (Miller and Chen, 1994). In addition,

researchers integrate the variables of firm-level and market-level to explain the three

constructs, also the implication to firm’s performance.

In regard to corporate-level competition, Chen (1996) proposes two

complementary constructs of firm-specific, market commonality and resource similarity,

which are originated from multipoint contact and resource-based theory. From the

perspectives of firm’s market profile and strategic resource endowment, researchers can

analyze the focal firm and the competitor in dyad, reveal the competitive tension

between two parties, and predict how the focal firm competes with each competitor

(Sirmon, Gove, and Hitt, 2008). Moreover, competitive asymmetry clarifies a clearer

competitive mapping, that is, the rivalry deterrence for mutual parties is not in the state

of equilibrium.

Competitive dynamics adopts action-response dyad, a fine analysis unit, to

understand and predict interfirm competition in detailed. Moreover, during the process

of interaction between the attacker and the defenders, firms have another choice to be

alliance partners in an embeddedness network, for example, the U.S. Airline

competition studies (Smith et al., 1991; Miller and Chen, 1994) and the global

automobile manufacturer research (Yu et al., 2009).

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2.2. Multimarket Contact and Competitive Aggressiveness

Multimarket competition is the focal firm competes with the same rival in many

overlapped markets (e.g. McDonald and Burger King; Coca Cola and Pepsi). The

competitive interaction in dyads, action and response, clarifies the interfirm rivalry.

From the perspective of the industry as a whole, the first battle is to grab a market share.

The competitive response from the defender must be taken in consideration (Chen and

MacMillan, 1992; Smith et al., 1991). In multimarket contact context, there is a high

interdependence among competitors, so a destructive response might happen rapidly.

For that reason, before initiating a competitive action, the focal firm has to predict how

the competitors will respond and when they will take the response (D’Aveni, 1994).

Previous studies stated that a firm taking more actions on behalf of its higher

competitive motivation (Ferrier, Smith, and Grimm, 1999; Young, Smith, and Grimm,

1996). Aggressive competition is likely to develop new and profitable market

opportunities and can obtain a favorable competitive position (Smith et al., 2001). A

higher competitive aggressiveness implies more competitive actions within a given

period (Ferrier et al., 1999; Lumpkin and Dess, 1996; Stambaugh, Yu, and Dubinsky,

2011; Young, Smith, and Grimm, 1996). Competitive aggressiveness implies various

characteristics of attack, such as the number of actions, duration, complexity, and

unpredictability (Ferrier, 2001).

Several streams of research have addressed the definition of competitive

aggressiveness. First, corporate entrepreneurship view captures an aspect that

competitive action is overt, demonstrable, and aggressive towards competitors. It is to

improve a firm’s competitive position and outperform competitors in the marketplace

(Covin and Slevin, 1991; Lumpkin and Dess, 1996). Second, from the viewpoint of

hyper-competition environment, the idea of aggressiveness is especially the speed of

competitive attacks consisting of multiple competitive strategies and tactics (D’Aveni,

1994). Third, researchers in the field of competitive dynamics developed a fine-grained

conceptualization of competitive action, e.g. the number of actions, the time of

action/response, and the speed of action/response (Smith et al., 1992).

Managers of MNCs are likely aware of rivals’ actions, and they are motivated to

strengthen their capability to prevent being overtaken by competitors, triggering a Red

Queen effect among rivals and extending interfirm competition (Barnett and Hansen,

1996; Barnett and McKendrick, 2004). Upon being aware of declined competitive

capability, firms are going to take some organizational innovation to improve

performance, leading to a series of searching activities to catch new opportunities

(Derfus et al., 2008; Schumpeter, 1962; Smith et al., 2001).

2.3. Resource Similarity

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Theorizing on resource-based theory, when firms possess resources with the

characteristics of value, rareness, imitability, and substitutability, they can create

sustained competitive advantage which is based on firms’ internal resource and capacity

(Barney, 1991). In terms of competitive response, when firms have similar resource

endowment with the attacker, they are not easy to attack but tend to payoff rapidly once

being attacked (Chen, 1996; Nelson and Winter, 1982; Yu et al., 2009). That is, the focal

firm has to be aware of the degree of resource similarity between itself and the

competitors, in addition, the response capability of competitors. To avoid competitors’

imitation, firms need to take the competitive action of resource heterogeneity, in order

to enhance the complicatedness to be copied (Rumelt, 1984, Collis, 1991).

Under a hyper-competition circumstance, resources heterogeneity and imperfect

mobility lead to organizational success. To achieve economies of scale, many MNCs

build a network based on trust and commitment (Gnyawali and Madhavan, 2001;

Nalebuff and Brandenburger, 1997). For all the players, how to identify and create a

bigger market for benefits is a vital mindset in the market. Applied to the game theory,

the win-win thinking implies the compatibility of the Red Queen effect (Brandenburger

and Nalebuff, 1996).

MNCs are generally good at utilizing national resource deployment (e.g. capital,

raw materials, techniques, markets, information, and human resources) as chips in

negotiating for exchange resources in the host country (Sirmon et al., 2008), leading to

enter the local market rapidly and obtain controlling power. Tacit collusion occurs

where firms agree upon a certain strategy in coordination of their actions without

putting it in writing out explicitly. In addition, a clearly defined distribution of benefits

leads to mutual profit equilibrium. The empirical results of Mitsuhashi and Greve (2009)

showed that alliance partners of shipping companies with higher resource similarity

provide better service to fit customer requirements, reduce conflicts among partners,

and create economies of scale. Notably, some researchers start to address this issue and

indicate that the relationship between MMC and competition is contingent on a variety

of factors (Bernheim and whinstone, 1990).

2.4. Culture Distance

Culture is an important component for MNCs operating in its unique task

environment, which as a significant influence on its competitive actions (Ma, 1998).

Culture distance is generally considered to distinguish between different institutional

environments in both countries, leading to unique customer preferences, different

organizational and administrative practices and employee expectations (Kogut and

Singh, 1988; Kostova, 1999). A foundational concept for such research has been known

as Hofstede dimensions of national culture (1980, 1993), i.e. power distance (PDI),

individualism versus collectivism (IDV), masculinity versus femininity (MAS) and

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uncertainty avoidance (UAI).

In multinational competition, MNCs are confronting many culture diversities and

have to make different strategy decisions in different countries (Morosine, Shane, and

Singh, 1998). Especially, MNCs have to adopt more complex and various actions and

responses among rivals’ interaction. Culture distance has a significant impact on the

foreign investment decision and affects MNCs’ decision making (Kogut and Singh,

1988; Schneider, 1989). Moreover, researchers have devoted substantial efforts on

MNC’s competitive strategy thinking under different cultural backgrounds in the host

countries (Schneider and DeMeyer, 1991; Song, Calantone, and Di Benedetto, 2002).

For example, Chinese culture is more collectivist tendency; so Chinese employees may

not force or dominate each other’s wishes but try to match mutual parties’ wellness. On

the contrary, American employees tend to solve problem on the base of truth in

negotiation (Ting-Toomey et al., 1991).

Culture distance may reduce the level of comfort and trust between the MNC and

its subsidiary, leading to a more difficult integrated relationship (Agarwal and

Ramaswami, 1992; Barkema et al., 1997; Earley, 1994; Kogut and Singh, 1988;

Newman and Nollen, 1996). If the subsidiary applies different strategic policy from the

headquarters, it may results in uncertain and unexpected result (Doyle et al., 1992;

Schneider and DeMeyer, 1991); moreover, it might reduce the benefits of multinational

trade will occur (Lee, Shenkar, and Li, 2008; Li, Lam, and Qian, 2001; Tadesse and

White, 2009).

Culture distance between the MNC and its subsidiary may also increase the

difficulty of interpretation of messages (Heil and Roberston, 1991), complicate

interactions, hinder the development of competences, and increase transaction costs.

Practically, MNC’s subsidiaries have their own individual objectives and cannot always

satisfy internal coordination, leading to conflicting interests (Jayachandran, Gimeno,

and Varadarajan, 1999). The subsidiaries face increasing pressures and challenges of

local responsiveness in the host country; accordingly, their strategic initiatives are active

and dynamic in order to gain a competitive advantage (Blazejewski and

Becker-Ritterspach, 2011; Malnight, 1996; Prahalad and Doz, 1999; Tian and Slocum,

2013). Therefore, we consider a different awareness between MNC headquarters and its

subsidiary owing to culture distance.

2.5. Hypothesis Development

2.5.1. MMC and competitive aggressiveness

The intensity of global competition is constant, and both the competitor and the

defender must constantly increase their speed and enhance their power as the Red

Queen competition (Derfus et al., 2008). Ironically, the relative positions of competitors

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do not change, but they have to join the battle to avoid falling behind. For example,

Mahoney and Pandian (1992) found that enterprises normally follow competitors that

enter a new market in order to maintain competitive equilibrium. According to the

multipoint competition theory (Karnani and Wernerfelt, 1985), firms are likely to find

opportunities to cooperate with competitors instead of engaging in fierce competition.

Due to dreading of a rival’s comprehensive fight back, firms diminish their competitive

tension in a competition network (Ma, 1998).

On the contrary, the Red Queen effect implies a different argument. The

competitive interactions between two firms motivate them to enhance the performance

in order to succeed in bilateral competition (Carroll, 1970; Merry, 1999; Van, 1973;

Watson and Pollack, 2001). In the field of biology, the Red Queen effect is defined as a

co-evolutionary race between two populations, and a stronger competitive relationship

between mutual parties increases the aggressiveness of competition. In a higher degree

of MMC as market commonality, the Red Queen effect accelerates the learning

capability of firms, leading to a stronger competitive tension (Derfus et al., 2008).

However, Barnett and McKendrick (2004) stated that accelerated competition can only

bring a short-term competitive advantage. To sustain their current position, firms will be

motivated to compete aggressively even though they fear retaliation from their rivals.

A vast amount of literature addressed the phenomenon of rivalry deterrence. The

high overlapping of firms in terms of target, competitive advantage, product distribution,

or market profile may lead to more drastic competition in transaction interactions (Luo,

2005). In other words, increased competition corresponds to the commonality of mutual

markets (Chen, 1996; Luo, 2007). As the Red Queen says to Alice, she runs to stay in

the same place and must run forward at double speed if she wants to go to other places

(Carroll, 1970). This analogy well describes the Red Queen effect. With double effort,

firms can acquire a sustainable competitive advantage (Sirmon et al., 2010). Collis

(1991) also suggested that MMC may increase competition. For example, when two

firms compete in markets A and B, one firm becomes stronger in market A and the other

is expected to compete aggressively in market A in order to diminish the damage to its

related business in market B. Accordingly, the present study proposes the first

hypothesis below.

Hypothesis 1. The higher degree of MMC between an MNC and its rivals’ market,

the more Red Queen effect will be, leading to a higher competitive aggressiveness of the

focal firm.

2.5.2. Moderating effect of resource similarity

Global competition triggers a series of organizational learning and natural

elimination. Resource similarity implies the comparability of tangible and intangible

resources of mutual firms, and the internal resource and capacity determines a firm’s

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competitive advantage (Barney, 1991; Collis, 1991). Once being aware of the attacker’s

aggressive action, the defender can take revenge immediately in other overlapped

markets, as long as the cost of retaliation is less than the attacker’s (Chen et al., 2007;

Sirmon et al., 2008; Young et al., 2000). Extending to multinational competition, the

payoff of defenders in more than one market will inevitably lead to greater damages

than in a single market (Porter, 1980).

The potential threat to competitors is an important indicator of interfirm

competitive intensity (Chen, Su, and Tsai, 2007), and the dependence of market and

resource will changes interfirm rivalry (Pfeffer and Salancik, 2003). Accordingly, the

rivalry deterrence diminishes the Red Queen effect in multimarket competition (Chen,

1996; Chen, 2008; Porter, 1980; Upson et al., 2012). In sum, the present study tries to

explore if resource similarity will affect MNCs’ strategy decision and weaken the effect

of Red Queen in multinational competition. Accordingly, we propose the second

hypothesis below.

Hypothesis 2. The higher degree of resource similarity of an MNC with its rivals,

the lesser Red Queen effect of MMC will be, weakening the relationship between MMC

and competitive aggressiveness.

2.5.3. Moderating effect of culture distance

In multinational competition, if the culture distance is very large between two

MNCs, the perceived search and transfer costs will be sufficiently high to offset the

perceived benefits (Hansen and Lovas, 2004). Thus, MNCs not easily engage in

competitive actions under a great national culture distance with the competitors

(Hargadon and Sutton, 1997). However, they still have to devote to the battle to avoid of

falling behind, which implies the effect of Red Queen. Accordingly, MNCs have to

adopt more flexible and complex actions of a wide range to hinder rivals’ imitation.

In terms of MNCs and the subsidiary, MNC headquarters could not

comprehensively realize each foreign markets, and the subsidiary plays an important

role (Barlett and Ghoshal, 1999). Due to the local pressure, the subsidiary has to

improve the business position and take more diversity strategy to develop in the local

market (Birkinshaw and Fry, 1998; Pfeffer and Salancik, 2003). The subsidiary’s

hierarchical dependency on the headquarters might be undermined when they build up

environmental connections and access specific strategic resources in the host country

(Bouquet and Birkinshaw, 2008). For example, in response to the growing market of the

Asia–Mediterranean shipping route, the subsidiary of MOL in Europe directly

established a new subsidiary in Italy to facilitate the arrangement of vessel schedules

(CSG news, 2007.5.30,). Notably, Italy is the domain market and the home country of

Mediterranean Shipping, the leading shipping company with a second-place ranking.

However, MOL Europe B.V. (based on Germany) did not take this factor into

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consideration nor aligned with the integrated strategy of mutual forbearance by the

headquarters in Tokyo (Mitsui O.S.K. Lines). The UAI (uncertainty avoidance index) in

Germany is 66.43, as same as in Italy; however, it is much different from the parent

country, Japan of 92. Thus, culture distance strengthens the decision-making power of

the subsidiaries.

When the culture distance between the MNC and its subsidiary is high, the

subsidiary will take more competitive actions to deal with local pressures. Accordingly,

hypothesis 3 is proposed below.

Hypothesis 3a. The higher degree of culture distance between two parent countries

of MNCs, the more Red Queen effect of MMC will be, strengthening the relationship

between MMC and competitive aggressiveness.

Hypothesis 3b. The higher degree of culture distance between an MNC’s parent

country and a given host country, the more Red Queen effect of MMC will be,

strengthening the relationship between MMC and competitive aggressiveness.

Chapter 3 Research Method

3.1. Data and Sample

The present study focused on the global liner shipping industry, which is a highly

oligopolistic and internationalized industry. The top 20 firms occupy almost 90% of the

total capacity of twenty-foot equivalent unit (TEU) in the world, a standard unit for

describing a ship’s cargo-carrying capacity (Alphaliner, http://www.alphaliner.com).

After checking the constantly updated ranking of the 100 largest container liner

operators in the past years in Alphaliner, we found a stable ranking of the top 20

shipping firms for more than 10 years: APM-Maersk, Mediterranean Shg Co., CMA

CGM Group, Hapag-Lloyd, Evergreen Line, COSCO Container L. CSCL, Hanjin

Shipping, MOL, APL, Hamburg Süd Group, OOCL, NYK Line, Yang Ming Marine

Trans., Hyundai M.M., PIL (Pacific Int. Line), K Line, UASC, Zim, and Wan Hai Lines.

The most important reason for choosing this industry is the intense interfirm

rivalry among shipping firms in an embedded network of strategic competition. Firms in

this competition network are easily aware of rivals’ competitive actions and have

capability to respond rapidly. In addition, in such a highly internationalized industry, the

competitors erode the focal firm’s profits because of a higher degree of overlapped

markets. Therefore, firms have stronger motivations in a competitive rivalry. For

example, on November 22, 2013, COSCON announced a rate restoration for all

shipments from the Far East to the Red Sea trade since December 1, 2013. In the same

day, Evergreen Line immediately announced the similar strategy, a rate restoration

program for the Far East/ Indian Sub-Continent and Europe/ Mediterranean trade for all

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cargoes and commodities, including temperature-controlled and special equipment.

The phenomenon of interdependence is also prevalent in the global shipping

industry, such as slot swaps, slot purchases, joint route operations, and trade association.

All the practical and valuable information can be accessed in professional institutions,

for example, Alphaliner, Containerization International, and Shipping Digest. Moreover,

most shipping firms concentrate only on the shipping market domain, which releases the

potential interference typically occurring in the composite business (Rumelt, 1974).

Thus, higher accuracy and reliability can be achieved by examining the results of

organization behavior and performance.

The data sources of the present study are from the Cyber Shipping Guide (CSG,

http://www.ocean-commere.co.jp) and the Alphaliner. The CSG is operated by Ocean

Commerce Company in Japan, which has published shipping news articles and

magazines for more than 40 years. The CSG website offers electronic data of shipping

companies in 18 arenas of global market since 2003, including industry news, operating

routes, ports, and vessels. Another data source is the Alphaliner website in France,

which offers professional information of ranking, market share, operating TEUs, and the

number of ships.

3.2. The Process of Database Construction

The process of database construction was divided into three stages. First, we

collected all the news articles related to the top 20 firms from 2007 to 2014 and sorted

the data in time sequence. Second, referring to previous literature (Chen and Hambrick,

1995; Smith et al., 1991), we identified the news of competitive actions and classify

them into 24 categories of actions. The competitive actions include rate decrease, rate

increase, service improvement, new service, route adjustment, resume service, new

route, exit route, tariff alliance, exit tariff alliance, strategic alliance, exit strategic

alliance, inter-industry cooperation, intra-industry cooperation, mergers, capacity

expansion, capacity reduction, new vessel, vessel charter, vessel refund, port

construction, refining technology, and speed deceleration.

In the third stage, we have all the 24 categories of competitive actions checked and

confirmed by professional managers of a shipping company and the professor

specialized dynamic competition of shipping company. Four well-trained researchers

followed the same procedures to sort the data, which increased the validity of the

database. By referring to the recommendations of professionals in the container liner

shipping industry, the database was finally constructed, totally 8,789 competitive

actions from 3,625 news articles.

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3.3. Measurements

3.3.1. Competitive aggressiveness

Competitive aggressiveness was measured by the indicators of competitive

extensiveness and complexity. To measure the competitive extensiveness, the number of

actions was multiplied with the proportion of the category. In terms of competitive

complexity, we multiplied each action and its weighted score, which is based on the

questionnaire of 38 technologists of liner shipping company from 8 facets. Each kind of

action from the 24 categories receives a weighted score in accordance with the

necessary resources. The greater the resources needed to initiate actions, the higher the

weighted score. The measurement was similar with past research on competitive

dynamics (Ferrier et al., 2002; Gnyawali and He, 2006). The formula is given as follows:

competitive aggressiveness = the proportion of category × the number of actions i × the

weighted score of each action i.

3.3.2. Multimarket contact

The measurement of MMC has been developed in previous literature (e.g., Baum

and Korn, 1996; Evans and Kessides, 1994; Fuentelsaz and Gomez, 2001). Similar to

the study by Gimeno and Woo (1996), the present study identified whether the focal

firm i overlaps with competitor j in market m. Here, “Yes” was coded as “1” and “0”

otherwise. Summing up the number of overlapped ports between mutual firms resulted

in dyad-overlapped ports between firms i and j. The dyad-data between firm i and all

other competitors were then shown in accordance with the number of competitors. The

formula is given as follow MMCi,j,m,t = ΣMMCij,mn,t/ 19, where MMCij,mn,t represents

all the ports firms i and j contact in season t.

3.3.3. Resource similarity

In the shipping industry, the vessel is the most significant tangible capital of

resources. Referring to Mitsuhashi and Greve’s (2009) research, the characteristics of

vessel were attributed to shape collaborative alliance and to maintain a sustained

relationship. The present study collected the information of owned vessels in all routes

of 18 arenas in global market, and used vessel age, speed and size as the indicators of

resource similarity.

A large difference in vessel age reduces the steadiness of joint operation, increases

the cost of route maintenance, and reduces the customer’s trust (Mitsuhashi and Greve,

2009). On the contrary, the greater similarity in vessel ages for shipping firms, the more

similar competitive capability will be, weakening competitive intent. Vessel speed

decides the voyage days and the costs of oil energy. The greater similarity in vessel

speed for shipping firms indicates the more similar capability for firms to operate a

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specific route for customers. Therefore, it causes the deterrence effect to grab the

market aggressively. Vessel size implies the loading capacity of ships. Shipping firms

have to arrange specific vessel sizes for different shipping lines to save cost and meet

customer requirements (Ryoo and Thanopoulou, 1999). The similarity of vessel size

importantly determines shipping firms’ operating effectiveness in global market. The

similarity of vessel age, speed and size are measured by the difference between the focal

firm and the average of all competitors. AgeSpeedSizeit represents the capacity of the

alliance partner i in season t, AgeSpeedSizekt represents the capacity of the focal firm k

in season t, and N represents the number of alliance firms in a given season. We used

the absolute value of the difference. The formula is as follow:

RS=

20

1

20

1

20

1

20//120//120//1i

itkt

i

itkt

i

itkt SizeSizeSpeedSpeedAgeAge

3.3.4. Culture distance.

The present study adopted Hofstede’s (1980) four dimensions to measure the

culture distance, including power distance, individualism and collectivism, masculinity

and femininity, and uncertainty avoidance. Referring to the formula of Kougt and Singh

(1988), firstly, we measured the culture distance of the parent country of the 20 top

shipping companies in dyad (P-R CD). Pij represents the parent country culture of

Hofstede index i of the focal firm j, and Rik represents the country culture of index i of

rival k. We further measured the culture distance between the parent country and its host

countries (P-H CD) of each port the vessels stop. Pij represents the parent country

culture of Hofstede index i of the focal firm j, and Hik represents the host country

culture of index i of a given port p. The formulas are as follow:

P-R CD= ; P-H CD=

3.4. Control Variables.

To avoid the effect of related variables to the focal firm aggressiveness, this study

include several variables at firm-level (resource and market), action-level (focal and

competitors), and corporate-level (global index) in the analyses.

3.4.1. Firm size

In regards to firm-level aspect, competitors with different sizes show different

competitive propensities (Chen and Hambrick, 1995). Large firms create economies of

scale and have more slack resources as buffer space in competition (March, 1981).

However, small firms have to continually create opportunities and employ different

4

1

2

iip

Hij

P

4

1

2

i ikR

ijP

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strategies to compete with large firms (Chen and Hambrick, 1995). Vessel is the main

resource for liner shipping company, and we measure firm size by the number of total

ships (owned and chartered) quarterly from 2007 to 2014. We took a natural log to bring

the coefficient close to the normal distribution required for an Ordinary Least Squares

(OLS) regression analysis.

3.4.2. Routes

From the aspect of market at firm-level, the more shipping lines the focal firm has,

the more economics of scale it may have access to. We figured out the number of liner

routes operated by the top 20 firms in 18 arenas of global market, including Australia,

Caribbean Sea, China, East and South Africa, East Coast of South America, Europe,

Korea, Mediterranean and Black Sea, Mexico and Central America, Middle East and

South Asia, New Guinea and South Pacific Islands, New Zealand, North America, Red

Sea, Southeast Asia, Vostochny Nakhodka, West Africa, and West Coast of South

America quarterly from 2007 to 2014. We also took a natural log for this variable.

3.4.3. Ports

Port is another market factor at firm-level. Shipping firms that operate in

multinational markets have more experience in competitive rivalries. Thus, the present

study controlled the number of ports of each route in 18 arenas of global markets

quarterly from 2007 to 2014.

3.4.4. Competitors’ previous action

It signifies the competitive action launched by all competitors within the industry

except the focal firm. In previous studies on competitive dynamics, the action and

response among competitors are usually investigated in a dyad background to understand

the active back-and-forth rivalry between firms (Chen, 1996; Yu et al., 2009). Given that

the present research focuses on a highly concentrated and oligopolistic liner shipping

industry (the top 20 firms occupy nearly 90% market share) with a high degree of market

overlap, we reckon any action launched by a firm will certainly influence the other 19

firms. Further, competitors’ previous competitive action might trigger the focal firm’s

aggressiveness of response in this season. So we measured this variable by calculating all

the numbers of competitors’ action in previous season.

3.4.5. Focal firm’s previous action

A firm’s competitive action is likely to trigger a retaliatory response from its

competitors (Chen et al., 2007). We also controlled the focal firm’s action in previous

season for the related effect to its aggressive action in this season. The above two

variables are both at action-level.

3.4.6. The World Economic Outlook

14

The shipping market is closely linked with world economic. For example, the

global financial crisis in 2009 led to world economic depression, and the top 20 liner

shipping firms all have experienced a negative growth of cargo-carrying capacity. The

World Economic Outlook (WEO) is the growth forecast for the world economy by the

International Monetary Fund (IMF) annually, which is an organization of 188 countries,

working to foster global growth and economic stability. The IMF provides policy advice

and financing to members in economic difficulties and also works with developing

nations to help them achieve macroeconomic stability and reduce poverty around the

world, and the global growth projection for 2015 is lowered to 3.8 percent (IMF,

http://www.imf.org). We include this available at corporate-level, the index of WEO,

from 2007 to 2014 in this analysis (WEO, http://www.imf.org).

3.4.7 The Baltic Dry Index

The Baltic Dry Index (BDI) is a bulk shipping freight index of raw materials, for

example steel, pulp, grain, coal, ore, phosphate rock, bauxite and other livelihood-based

materials and industrial raw materials. Thus, the bulk shipping industry is closely

related to global economic ups and downs, which can be regarded as a leading

economic indicator. The BDI consists of four components: the Capesize Index (BCI),

Panamax Index (BPI), Supramax Index (BSI) and Handysize Index (BHSI), and is

managed by the Baltic Exchange in London. We include this variable at corporate-level

variable from 2007 to 2014 in this analysis (The Baltic Exchange,

http://www.balticexchange.com/market-information/indices/BDI/). We also took a

natural log for this variable. The formula is as below.

BDI=((Capesize5TCavg+PanamaxTCavg+SupramaxTCavg+HandysizeTCavg)/4)*

0.110345333; TCavg = Time charter average

3.5. Methodology

Referring to Miller and Friesen (1977), the present study adopted a structured

content analysis method (Jauch, Osborn, and Martin, 1980). Data were collected

through a massive review of published information in time sequence. Following the

steps of developing a content analysis, the present research first established the research

concept, decided on the unit of analysis in season, and then developed the approaches of

analysis. We first use OLS regression in SPSS 18.0 to analyze the relationship between

the independent and dependent variables. We also run the robustness test and panel data

analysis in Stata 11 and the results are reported in the next section of data analysis.

Chapter 4 Results and Discussion

The present study tested a sample of the top 20 liner shipping companies with 640

quarterly data from 2007 to 2014, by constructing a database of 3,625 news articles with

8,789 competitive actions in 18 global arenas. The data of competitive actions is

15

extracted from CSG, which is highly recognized by academicians and practitioners as

the main publication of container shipping industry. According to the data of ranking of

the top 20 container liner shipping companies from 2007 to 2014, Maserk, MSC, and

CMA CGM are stable top 3 every year. Specifically, Hapag-Lloyd and CSAV completed

the merger on December 2, 2014, and become the 4th

container liner shipping company

in the world. Notably, Hamburg has a great ranking up from 15th

to 11th

from 2007 to

2014. Unfortunately, NYK, “K” Line, and Zim all fell at least 4 in ranking.

4.1. Result

Table 1 reports the descriptive statistics, including mean, standard deviations, and

Pearson correlation coefficient of all variables used in the analysis. All items show

substantial variation and correlation. Except P-R culture distance and P-H culture

distance show a significant correlation (0.90), other coefficient values are less than the

possibility of multicollinearity (correlation coefficient value> |0.6|) (Kennedy, 2003). To

test for multicollinearity, variance inflation factors (VIFs) were calculated for our

variables. All VIF values were within the acceptable range (from 1.183 to 7.78).

---------------------------------------------------

Insert Table 1 around here

---------------------------------------------------

The present study used a hierarchical regression method to test the hypotheses.

Table 2 summarizes the OLS regression results of hypotheses 1 to 3. In Table 2, all the

eight models for competitive aggressiveness reached a level of significance (Model 1

F=30.553, p<0.001; Model 2 F=25.537, p< 0.001; Model 3 F=24.936, p< 0.001;

Model 4 F=22.989, p< 0.001; Model 5 F=25.118, p< 0.001; Model 6 F=24.387, p<

0.001; Model 7 F=24.551, p< 0.001; Model 8 F=23.406, p< 0.001). In addition, after

including the independence variables, moderating variables, and interaction terms, all the

models significantly enhanced the explanatory power (R-Squared) (Model 2 ΔR2=0.006,

p<0.05; Model 3 ΔR2=0.004, p<0.1; Model 4 ΔR

2=0.005; p<0.05; Model 5 ΔR

2=0.005;

p<0.05; Model 6 ΔR2=0.015, p<0.001; Model 7 ΔR

2=0.001; p>0.01; Model 8

ΔR2=0.012, p<0.01). This result indicated that the model for exploring competitive

aggressiveness fits with the mentioned variables.

---------------------------------------------------

Insert Table 2 around here

---------------------------------------------------

Model 1 reports the influence of the four control variables (firm size, routes, ports,

competitors’ previous action, focal firm’s previous action, WEO, and BDI) on the focal

16

firm’s competitive aggressiveness. Model 2 tests the rivalry deterrence effect of Red

Queen effect (Hypothesis 1). The significant and positive coefficient for MMC

(β=0.135, p<0.05) indicates that a higher degree of MMC of the focal firm increases its

aggressiveness to initiate an attack in the market. Thus, Hypothesis 1 is supported.

In models 3, 5, and 7 we added the moderating variables resource similarity (RS)

and culture distance (P-R CD and P-H CD). Models 4, 6, and 8 examined hypotheses 2,

3a, and 3b respectively. In terms of the interaction terms, we computed by multiplying

variables after standardization to reduce the multicollinearity (Jaccard, Wan, and Turrisi,

1990). As shown in Model 4, the interaction between MMC and resource similarity is

negative and significant (β=-0.189, p<0.05), thus supporting Hypothesis 2. That is, the

rivalry deterrence of resource similarity weakens the effect of MMC on competitive

aggressiveness.

To avoid of the problem of autocorrelation for a longitudinal data, we have done

Durbin Watson test (Durbin and Watson, 1951). The values of Model 1 to Model 4 are

2.065, 2.047, 2.034, and 2.028 respectively, which means a relatively low probability of

autocorrelation when the value is closed to 2.

Figure 1 illustrates this interaction effect, which demonstrated a moderating effect

of rivalry deterrence, an indication of further support for Hypothesis 2. It implicates that

the focal firm will reduce the motivation of contact to avoid of retaliation from

competitors with similar capability.

---------------------------------------------------

Insert Figure 1 around here

---------------------------------------------------

As shown in model 6, the interaction between MMC and P-R culture distance

(CD1) is positive and significant (β=0.133, p<0.001), thus supporting Hypothesis 3a.

That is, the greater culture distance between the focal firm’s parent country and

competitors’ parent country, the effect of MMC on competitive aggressiveness is

stronger. Figure 2 illustrates this interaction effect. The slope at a higher level of cultural

distance demonstrated the increase of positive association between MMC and

competitive aggressiveness. P-R cultural distance has a moderating effect, an indication

of further support for Hypothesis 3a.

---------------------------------------------------

Insert Figure 2 around here

---------------------------------------------------

17

To avoid of the problem of autocorrelation for a longitudinal data, we have done

Durbin Watson test (Durbin and Watson, 1951). The values of Model 5 and 6 are the

same of 2.050, which means a relatively low probability of autocorrelation when the

value is closed to 2.

In model 8, the interaction between MMC and P-H culture distance (CD2) is

positive and significant (β=0.114, p<0.001), thus supporting Hypothesis 3b. That is, the

greater culture distance between the parent country and the host country of port of call,

the effect of MMC on competitive aggressiveness is stronger. Figure 3 illustrates this

interaction effect. The slope at a higher level of cultural distance demonstrated the

increase of positive association between MMC and competitive aggressiveness. P-H

cultural distance has a moderating effect, an indication of further support for Hypothesis

3b.

---------------------------------------------------

Insert Figure 3 around here

---------------------------------------------------

To avoid of the problem of autocorrelation for a longitudinal data, we have done

Durbin Watson test (Durbin and Watson, 1951). The values of Model 7 and 8 are 2.047

and 2.049 respectively, which means a relatively low probability of autocorrelation

when the value is closed to 2.

4.2 Discussion

Most of previous empirical studies discuss rivals competition in multimarket based

on mutual forbearance effect (Baum and Korn, 1996; Chen, 1996; Yu and Cannella,

2013; Yu et al., 2009). However, in the present study, we examined how the Red Queen

effect triggers more aggressive actions in global markets (Barnett and McKendrick,

2004; Derfus et al., 2008; Stambaugh et al., 2011). In addition, only few of studies

explored at level of competitive actions (except Gnyawali and Madhavan, 2001;

Gnyawali et al., 2006). The present paper, based on theories of multimarket competition

and competitive dynamics, exquisitely examined the dyad relationship of focal firm’s

action and competitors’ responses, also competitors’ contacted ports in dyad (Chen,

2009; Chen and Miller, 2012; Gimeno, 1999).

In keen competition of multinational market, MNCs must continue to learn new

technology and share information to ensure the sustainable competitive advantage. For

subsidiary manager of MNCs, taking quick response is typical means when they

confront a forceful competition in the host country (Cui, Griffith, and Cavusgil, 2005).

Therefore, how to take complex, effective and aggressive strategies is indeed a critical

issue for MNCs to sail in global market and keep a good competitive position. The

18

empirical results of this study supported Hypothesis 1, indicating that MMC has a

significantly positive impact on competitive aggressiveness.

The present study further examined the moderating effects of resource similarity

and culture distance on the relationship between focal firm’s MMC and its performance.

Resource similarity was defined as the comparability of resource endowment between

rivals. A high degree of resource similarity implies that MNCs possessing similar

resources might be familiar with mutual actions and strategic intent; moreover, they

might have similar capabilities to take border retaliation in multinational market. From

the perspectives of resource-based view, resource endowment is a basic advantage to

deter interfirm rivalry. The empirical result supported that resource similarity causes

rivalry deterrence and weakens the positive relationship between MMC and competitive

aggressiveness. The moderating effect is existed, thus, Hypothesis 2 is supported.

Culture distance is generally regarded as the factor determining the institutional

environment between two countries (Kostova, 1999). In the context of multinational

competition, MNCs face competitors in different parent countries with different national

cultures. National culture has great influence on MNCs strategy management in

different countries, and a high degree of culture distance between two countries implies

different type of business model, cognition, practices and rules. Schneider (1989)

explored the influence of national culture to MNCs strategy decision, and Kogut and

Singh (1988) claimed culture distance has significant impact to foreign investment

decision of United States enterprises.

Due to increased costs of searching and analyzing information, and different

strategy thinking on competitive action and response, MNCs have to adopt more

complex and diverse competitive actions to keep the existed position, moreover, to take

over superior advantage among competitors. In addition, each dimension of national

culture might indirectly affect MNCs’ strategic decision. For example, people in

Western countries with a higher score of individualism may more emphasis on personal

freedom and benefit. Thus, they are tending to take aggressive competition instead of

partner harmony in Eastern countries. A high degree of culture distance increases the

response pressure that urges MNCs’ competitive action and response. Accordingly,

culture distance between two parent countries of MNCs might strengthen the positive

relationship between MMC and competitive aggressiveness, which supported

Hypothesis 3a.

Culture distance is also a very important issue between the headquarters and

subsidiary for MNCs. Due to not familiar with the host country, MNCs might spend

more costs on alignment management (e.g., information research and technology

transfer), and subsidiary might confront more risks and potential costs due to local

response pressure. Accordingly, the headquarters of MNCs operating in multinational

19

market will be more constructive in management strategy, and subsidiary manager shall

be more enthusiastic in operating business.

Moreover, information asymmetry and uncertainty usually hinder the integration of

the headquarters and subsidiary. A higher degree of culture distance results in different

practices of organization and administration, and employee expectations, thus, the

subsidiary and headquarter are forced to run at double speed to keep in the same

position. Consequently, the culture distance between the parent country and a given host

country might strengthen the positive relationship between MMC and competitive

aggressiveness, which supported Hypothesis 3b.

Chapter 5 Conclusions and Suggestions

5.1. Conclusion

According to the research questions and the research objectives in Introduction,

this research uses the top 20 global container liner shipping companies as the sample to

examine the mediating effect of competitive aggressiveness between multimarket

contact and operating performance, also the moderating effect of resource similarity and

culture distance.

This study counts all the ports of each route of the top 20 shipping companies in 18

operating areas around the world from 2007 to 2014. Through constructing 20 dyad

matrixes of contacted ports for each two firms (110-140 ports/firm/season in average),

we figure out the degree of multimarket contact (i.e. multimarket competition). Further,

we calculate more than 180,000 competitive actions to get the index of competitive

aggressiveness. The empirical results answer 1st research question and 1

st research

objective- the Red Queen effect will trigger MNCs aggressive motivation in

hyper-competitive multinational market.

In addition, we collect 2,568 owned ships information of age, speed, and size

(capacity) to calculate the index of resource similarity. The empirical result answer 2nd

research question and 2nd research objective- resource similarity will weaken MNCs’

competitive intension due to rivalry deterrence of retaliation from the competitors. To

MNCs, market overlap is the most important factor determining the competitive

strategy; however, resource capability is another contingency factor in consideration.

In regard to culture distance, we calculate the four dimensions of power distance,

Individualism and collectivism, masculinity and femininity, and uncertainty avoidance,

the empirical result answer 3rd research question and 3rd research objective. The

culture distance, including the differences between the parent country of the 20 MNCs

in dyad (P-R CD) and the differences of MNC’s parent-host country (P-H CD), will

stimulate MNCs’ rivalry intension due to local response pressure and avoiding of falling

20

behind. This reflects a higher Red Queen effect among rivalry competition in highly

overlapped global market.

5.2. Implications

5.2.1. Theoretical implications

Existing research gives many discussions of competition among MNCs, however,

its pre-factors, the importance of competitive aggressiveness, is rarely to be noted.

Meanwhile, the effects of aggressive actions on the performance in the embedded

competitive networks are also worth to explore. In addition, the present study finds out

that MNCs have higher level of market commonality (MMC) and resource similarity

with competitors would not easily initiate aggressive actions, which is consistent with

past researches (Chen, 1996). Although resource similarity causes rivalry deterrence and

reduces the focal MNC’s motivation to initiate attacks, once the competitors take

actions, MNCs have the capability to take rapid retaliation aggressively. Specifically,

this paper further examines the aggressive competition brings better operating

performance, which empirical results provide a practical implication and suggestion to

MNCs suffering in different national cultures of the host countries.

Based on the theories of resource-based views, resource dependence, organization

change and learning, and competition network, the present study explores how the

characteristics of firms and actions (Chen and MacMillan, 1992; Chen, Smith, and

Grimm, 1992; Ferrier, 2001; Smith et al., 1991) affect competitive rivalry. The current

paper also discusses how the cooperative relationship among competitors influences

firms’ behavior in the global container liner shipping industry. Combining the theories

of competitive dynamics and hyper-competition, the core value of competition is to

initiate attacks rapidly and aggressively to diminish the capability and response speed of

the defenders (D’Aveni, 1994). More cooperative connections reduce the motivation to

act, whereas strong attacks trigger the competitive aggressiveness of the focal firm.

In terms of theoretical contribution, the present study fills the gap in competitive

dynamics, especially in competitor behavior within a competition network. With the

global container liner shipping firms as the research target, the present study collected

longitudinal data, built a detailed dyad competitive database, tested research hypotheses,

and conducted statistical analysis. Moreover, our empirical results support the four

hypotheses as interpreted above. Globalization is an irresistible trend based on the rapid

development of information technology. At present, the global market has integrated

into a single liberalization market under the Internet. In this rapidly changing era,

competition among MNCs has become increasingly intense, with more cooperation

elements rather than purely competitive business models. As Harvard scholars Nalebuff

and Brandenburger (1997) indicated, cooperation is required to increase the benefits to

all players (focus on market growth) and competition is needed to divide the existing

21

benefits among these players (focus on market share). The statement clearly explains

the interesting relationship between competition and cooperation. In other words,

MNCs access resources through collaboration while competing in the market.

5.2.2. Empirical implications

The operating scale of the global container liner shipping industry covers the three

largest economies (Asia, Europe, and America) of the world in 18 regional domains.

Shipping firms have to cooperate alternatively with competitors in common routes (e.g.,

pooling vessels, slot change, slot charter) because of limited resources. Based on their

mutual commitment to cooperate, these alliances significantly reduce operating costs,

create advantages of scale, and provide better service quality for customers. This

situation may be completely different from the traditional competition, but it still

facilitates the development of an industrial environment. Mr. Wei, the chairperson of

COSCO, said that the shipping firms should avoid an “irrational expansion of the fleet”

in a single arena, which may result in an oversupply of transport capacity, bargained

competition, and tragic losses. Hence, the current study recommends that shipping firms

might cooperate actively with existing partners, strengthen mutual ties to confront other

competitors, and avoid of a head-to-head fight

Empirical results of the current study show that MNCs should first recognize the

problem of market commonality and avoid the overlapping of operating regions and

ports of call. A further consideration is the utilization of resource similarity to increase

benefits to all players and ease competitive tension among inter-alliance partners. These

actions allow firms to acquire the most competitive profits with the least resources. If

the competition is frequent in a highly overlapped market, shipping firms should reduce

the frequency to avoid blind competition and wastage of organizational resources.

Shipping firms are very familiar with competitive strategies and can easily retaliate

because of the rich history of confrontations. The launching of actions at the right time

can be beneficial in stabilizing the market supply and demand and improving operating

performance.

5.3 Limitations and Future Suggestions

The action data of the present study were subtracted from CSG, and the database

construction was a complex processor involving the cautious sorting of news articles.

Moreover, all the published news articles and online information were downloaded on

time; otherwise, missing data or information bias may result. This is the first research

limitation of the current research. Further researcher may purchase the membership of

CSG and Alphaliner to ensure stable and correct data resource.

Secondly, we only explored the global container liner shipping industry, which has

specific industrial characteristics. Thus, our results may only be generalized with

22

caution, which comprises another limitation. For example, we calculated the age, speed,

and size of ships for the variable of resource similarity in this study, not only because

ship is the most important resource of liner shipping company but a limited observations

of secondary date we could access to in CSG website.

Environmental change is another limitation of this eight-year study. For example,

the previous three years included the global financial crisis from 2007 to 2009.

Therefore, some observed values of variables may have special meanings and affect the

results. Especially in 2009, the number of competitive action had largely increased;

unfortunately, the performance was still declined a lot.

In addition, the present study only included one international business variable (i.e.,

culture distance). Future research may add related variables of international business,

such as the importance of the different markets across 18 regions of competition.

Finally, most current studies on competitive dynamics focus on the relationship

between the focal firm and its competitors or partners; studies on inter-alliance

competition are quite few. Therefore, future research can further explore and analyze the

relationship between alliance networks, such as the three strategic alliances in the

shipping industry (CKYH, Grand Alliance, and New World Alliance), which involve

complicated and dynamic elements.

23

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Table 1 The Descriptive statistics and Pearson correlation

Variables Mean S.D. 2 3 4 5 6 7 8 9 10 11 12

1 Firm size 4.84 .64 .39***

.56***

-.06 .16***

-.36***

-.04 .40***

-.07* .47

*** .41

*** .15

***

2. Routes 4.00 .57 .36***

.08* .37

*** -.22

*** .03 .57

*** -.13

*** .13

*** .04 .37

***

3 Ports 125.57 46.93 .02 .35***

-.34***

.18***

.72***

-.15***

.35***

.26***

.30***

4 Competitors’

pre- action 276.37 87.20 .43

*** -.02 .38

*** -.01 .02 .00 -.11

** -.02

5 Firm’s pre-

action 13.80 9.22 -.13

** .23

*** .43

*** -.23

*** .16

*** .07

† .35

***

6 WEO 4.02 4.12 .13***

-.29***

.19***

-.34***

-.45***

-.16***

7 BDI 7.64 .79 .05 .02 .00 -.17***

.15***

8 MMC 57.53 12.47 -.31***

.28***

.22***

.40***

9. RS 2.04 4.72 -.20***

-.28***

-.20***

10 CD1 59.78 9.43 .90***

.17***

11. CD2 60.31 10.21 .09*

12 Aggressiveness 11.03 10.24 a n=640;

†p<.10,

*p<.05,

**p<.01,

***p<.001

b MMC=Multimarket contact; RS=Resource similarity; CD1=P-R Culture distance; CD2=P-H Culture distance

c Firm size and Routes are natural log value.

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Table 2 Results of Hierarchical Regression Analyses of Competitive Aggressiveness Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Variables β t β t β t Β t β t Β t Β t Β t Firm size -0.100 -2.250* -0.083 -1.849† -0.081 -1.819† -0.065 -1.438 -0.100 -2.250* -0.136 -2.869** -0.095 -2.024* -0.100 -2.134*

(1.662) (1.710) (1.711) (1.764) (1.662) (1.962) (1.885) (1.887)

Routes 0.258 6.463*** 0.212 4.745*** 0.221 4.917*** 0.213 4.748*** 0.258 6.463*** 0.241 5.385*** 0.221 4.815*** 0.224 4.902***

(1.347) (1.701) (1.719) (1.731) (1.347) (1.752) (1.799) (1.800)

Ports 0.121 2.615** 0.038 .637 0.051 .865 0.085 1.387 0.121 2.615** 0.025 0.423 0.040 0.682 0.023 0.393

(1.797) (2.957) (3.006) (3.235) (1.797) (2.966) (2.965) (2.991)

Rivals’

pre-action

-0.226 -5.475***

(1.444)

-0.211 -5.055***

(1.483)

-0.205 -4.903***

(1.492)

-0.201 -4.821***

(1.495)

-0.226 -5.475***

(1.444)

-0.203 -4.908***

(1.487)

-0.209 -4.987***

(1.489)

-0.206 -4.965***

(1.490)

Firm’s

pre-action

0.276 6.431***

(1.561)

0.252 5.723***

(1.656)

0.239 5.370***

(1.699)

0.230 5.132***

(1.719)

0.276 6.431***

(1.561)

0.220 4.973***

(1.708)

0.250 5.652***

(1.663)

0.233 5.275***

(1.687)

WEO -0.085 -2.212* -0.081 -2.125* -0.071 -1.834† -0.062 -1.603 -0.085 -2.212* -0.060 -1.561 -0.069 -1.684† -0.075 -1.855†

(1.243) (1.245) (1.273) (1.289) (1.243) (1.293) (1.422) (1.425)

BDI 0.154 3.924*** 0.162 4.140*** 0.162 4.142*** 0.164 4.205*** 0.153 3.924*** 0.155 4.008*** 0.166 4.203*** 0.156 3.982***

(1.295) (1.307) (1.307) (1.308) (1.295) (1.310) (1.320) (1.327)

MMC 0.135 2.249* 0.107 1.733† 0.072 1.128 0.126 2.097* 0.170 2.802** 0.129 2.140* 0.170 2.775**

(3.058) (3.257) (3.502) (3.074) (3.200) (3.096) (3.241)

RS -0.068 -1.822† -0.249 -2.620**

(1.183) (7.777)

CD1 0.086 2.128* 0.062 1.541

(1.387) (1.423)

CD2 0.036 0.863 0.010 0.228

(1.490) (1.550)

MMC*RS -0.189 -2.072*

(7.164)

MMC*CD1 0.133 3.657***

(1.156)

MMC*CD2 0.114 3.157**

(1.128)

F Value 30.553*** 27.537*** 24.936*** 22.989*** 25.118*** 24.387*** 24.551*** 23.406***

Adj. R2 0.253 0.259 0.263 0.268 0.264 0.279 0.260 0.271

△Adj. R2 0.006* 0.004† 0. 005* 0.005* 0.015*** 0.001 0.012** a n=640; †p<.10, *p<.05, **p<.01, ***p<.001；( )=VIF b MMC=Multimarket contact, RS=Resource similarity, CD1=P-R Culture distance, CD2=P-H Culture distance

30

0

5

10

15

20

25

30

30 40 50 60 70 80

Com

pet

itors

' A

ctio

ns

Multimarket Contact

P-R CD -1s.d.

P-R CD +1s.d.

Figure 1 The Interaction of Multimarket Contact and Resource Similarity

Figure 2 The Interaction of Multimarket Contact and P-R Culture Distance

Figure 3 The Interaction of Multimarket Contact and P-H Culture Distance

0

5

10

15

20

20 30 40 50 60 70 80

Com

pet

itors

' A

ctio

ns

Multimarket Contact

Low RES

High RES

0

5

10

15

20

25

30

30 40 50 60 70 80

Com

pet

itors

' A

ctio

ns

Multimarket Contact

P-H CD -1s.d.

P-H CD +1s.d.