An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong

Transportation Research Part A xxx (2017) xxx–xxx

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An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong Wei Zhang, Jasmine Siu Lee Lam ⇑ School of Civil and Environmental Engineering, Nanyang Technological University, Singapore

a r t i c l e

i n f o

Article history: Available online xxxx Keywords: Maritime cluster evolution Port development Maritime service Symbiosis theory Lotka-Volterra model

a b s t r a c t The maritime industry has adopted the concept of clustering to promote the growth of related maritime sectors. Based on the theoretical development of maritime cluster evolution in the current research literature, components and functions of maritime clusters are observed to have changed over time. However, very few empirical studies have been conducted on maritime cluster evolution that reflect the diverse components and their interactions within a cluster. Particularly, there is insufficient literature that systematically studies the relationship between ports and other maritime sectors, though the port is deemed to play an important role among sectors in maritime cluster development. This paper aims to fill these research gaps by analysing two cases – London and Hong Kong. London is considered as an international maritime service centre, while Hong Kong is en route to be an international maritime service centre, with the latter cluster possesses a supportive port while the former does not. Grounded on the symbiosis theory, this paper examines the evolution of maritime clusters empirically through investigating the interactions between a port and other sectors within a maritime cluster with the Lotka-Volterra model. Empirical results show that advanced maritime services, namely marine insurance and shipbroking, benefit from port development in London. However, these maritime services sectors are in pure competition with the port sector in Hong Kong. The research provides reference for policy makers on the dynamic development path of maritime clusters in practice. Ó 2017 Elsevier Ltd. All rights reserved.

1. Introduction The concept of maritime cluster encompasses an array of linked maritime sectors in the maritime industry, including governmental and other marine institutions that provide a competitive and innovative edge. These sectors include but are not restricted to ports, ship finance, maritime law, marine insurance, ship registry, ship chartering and ship brokering. Recent research shows that maritime clusters can maximize competitive advantages in maritime and regional development (Doloreux and Shearmur, 2009; Shinohara, 2010). Thus clustering in the maritime industry has been used as a policy tool by governments to promote the growth of related maritime sectors. (Stavroulakis and Papadimitriou, 2016). Of all the maritime sectors within a maritime cluster, ports are regarded as an important maritime sector as they are identified as playing a core role in facilitating trade, as well as taking up a more active role in supply chains (Lam, 2015). Today, growing international trade is transforming the world economy into a single system and integrating world transport activities. Ports ⇑ Corresponding author. E-mail addresses: [email protected] (W. Zhang), [email protected] (J.S.L. Lam). http://dx.doi.org/10.1016/j.tra.2017.05.015 0965-8564/Ó 2017 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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are naturally being incorporated into this huge, changing and competitive system. This results in the change in ports’ functions to adapt to this dynamic system (Wang and Cheng, 2010). At the same time, the functions of maritime clusters are changing to provide better and more efficient maritime services (Chang, 2011). As such, based on the developing process of maritime clusters, the definition of maritime cluster is not a fixed concept but a changing and evolutional one. In practice, real cases of maritime cluster evolution are observed. Besides traditional port activities, a number of maritime clusters are on their way to providing more specialised and professional maritime services, with different characteristics for different maritime clusters. For example, London tries to ‘‘maintain and enhance the UK’s position as the world’s premier maritime centre” (Maritime London, 2015). Singapore focuses its mission not only on the development of a ‘‘premier global hub port” but also an ‘‘international maritime centre (IMC)” (MPA, 2015). In order to ‘‘consolidate Hong Kong’s position as a major international maritime centre”, Hong Kong Maritime Industry Council was formed to promote the development of maritime services (Hong Kong Maritime Industry Council, 2013). With these aims having been articulated, questions arise as to what types of maritime clusters should be adopted or achieved by different cities or regions, since different maritime clusters have different formations and functions. Especially, although the development process of a maritime cluster seems to have some relationship to that of a port, an important question is: what role and functions should a port perform within the maritime cluster in order to achieve a coordinated development between the port and other maritime service sectors? In addition, maritime clusters have various kinds of forms, which depend on the compound of maritime sectors that compose the cluster and their relative weights inside the cluster. Thus, when considering the evolution of a maritime cluster, it is a good starting point to analyze the relationship of the maritime sectors within the cluster. This research aims to fill the gap which remains largely untapped in the current literature. The study is grounded on the symbiosis theory (Morin, 1999) to analyze a maritime cluster and sectors in the cluster. This research aims to examine the evolution of maritime clusters empirically through investigating the interactions between a port and other sectors within a maritime cluster with symbiosis theory and the Lotka-Volterra model (L-V model) in the London and Hong Kong cases, then draw policy implications and recommendations accordingly. The paper draws insights for maritime clusters, especially those on their way to being maritime service centres.

2. Literature review on the concept of maritime cluster In recent years, there has been more research that focuses on maritime cluster development. A maritime cluster encompasses a wide range of linked units, such as firms, institutes, authorities and organisations. As such, it is necessary to illustrate the maritime cluster concept through existing literature by analysing and summarising from three aspects. They are (1) the definition of maritime cluster; (2) the formation of maritime clusters of different countries; (3) the linkages and relationships of sectors within a maritime cluster, as summarised in Table 1. After reviewing these prior studies, this section links port development with the concept of maritime cluster. These elements are reviewed to further address the evolution of the definition and concept of maritime cluster, especially the evolution that depends largely on the changing port functions and their development and maritime services. 2.1. The definition of maritime cluster The idea of maritime cluster can be traced back to industry cluster, also known as business cluster or competitive cluster (Porter, 1990). However, so far there has not been a standard definition for the maritime sector. Commonly, the definition begins with a general industry cluster before focusing on maritime as one of the many sections. For example, Chang (2011) proposed the definition of maritime cluster as a network of firms, research, development and innovation units and training organizations. In this case, some traditional areas of the maritime sectors are identified, such as inland navigation, marine aggregates, marine equipment, maritime services, navy and coastguard, offshore supply, recreational boating, seaports, ship building and shipping. Given the very wide scope, the definition not only includes the marine sectors, such as emerging knowledge-intensive businesses and services in marine science and technology, but also the coastal and sea-related recreation, tourism, and fisheries (Kwak et al., 2005). However, the premise of defining a maritime cluster lies in finding the driving force and yardsticks for identification. With this consideration, public support mechanisms involving governments and regional stakeholders are viewed as crucial and indispensable. As such, a cluster can be taken as being different from merely the agglomeration or geographic concentration of interacting firms (Doloreux and Shearmur, 2009; Brett and Roe, 2010).

Table 1 Maritime cluster concept. Source: Compiled by authors based on sources referred in the table. Criteria and contents

References

d The definition of maritime cluster d The formation of maritime cluster

d Kwak et al. (2005), Doloreux and Shearmur (2009), Brett and Roe (2010), Chang (2011) d Porter (1998), De Langen (2002), Peeters and Webers (2006), Doloreux and Melançon (2008), Shinohara (2010), Othman (2011), Zhang and Lam (2013) d The linkages and relationships of sectors d Knarvik and Steen (1999), Benito et al. (2003) in a maritime cluster

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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Such a difference paves the way for further discussion in this paper on drawing recommendations of the development priority and path for policy makers of maritime clusters.

2.2. Formation of maritime cluster A maritime cluster is regarded as encompassing various linked sectors. Thus, the formation of a maritime cluster is one of the main research thrusts in establishing the cluster concept. This is also the starting point of empirical studies on maritime clusters with various sectors in this research. As characteristics and functions vary for different maritime clusters, the detailed discussion on the formation was conducted in the previous study (Zhang and Lam, 2013). The review in this sub-section will focus on local case studies. For example, Porter (1998) studied the Norwegian maritime cluster, taking the shipping industry as a core, with maritime services, fisheries and fishing equipment, maritime equipment suppliers, offshore exploration and oil production, maritime authorities, and education surrounding the core sector. Based on Porter (1998)’s study and maritime cluster development under dynamic backgrounds and contexts, researchers analyzed, modified and formed their own opinions on the formation of maritime clusters. Overall, three main groups constitute a maritime cluster, namely, shipping, maritime services, and the ship industry, and the cluster is surrounded by facilitating associations, educational and research institutions and political bodies, such as the complete maritime cluster in Norway (Benito et al., 2003). In the case of the Netherlands, three main parts consisting of 11 maritime sectors are identified (Peeters and Webers, 2006), in which ship building and maritime services are the same as those of Norway, but with an additional sector of exploitation (De Langen, 2002). In Quebec’s coastal region, Doloreux and Melancon (2008) specified six maritime sectors which are quite different from other studies. They are marine biotechnology, marine technologies, aquaculture, commercial fisheries, shipbuilding and industrial maritime activities and fish and seafood product preparation. In Asia, the economic size of the maritime cluster in Japan was discussed, measured by the GDP of 12 maritime sectors (Shinohara, 2010). Othman (2011) provided a conceptual model of Malaysia’s maritime cluster which can be divided into three parts, namely shipping services, ship industry, and ports and terminals.

2.3. Linkages among maritime sectors Further to the review as above, the linkages and relationships among maritime sectors are often taken for granted and set as default in the current literature, with few studies attempting to identify and investigate the relationships among the maritime sectors. The point of such studies is to figure out the plausibly significant role of clustering, in the overall development of a maritime cluster, from a sustainability perspective. Knarvik and Steen (1999) firstly observed the potential linkages between two sub-clusters, i.e. the service-oriented shipping and the manufacturing-oriented ship industries. On the basis of an econometric analysis on the Norwegian maritime industry with data ranging from 1978 to 1992, their research discovered that significant scale economy existed in the maritime industry. While they did not observe any significant economies of scale between sub-clusters, they were found within each sub-cluster instead. This weak connection between the ship industry and the shipping industry was agreed and adopted by Benito et al. (2003), based on perceptual data from the Norwegian maritime industry. In addition, they identified shipping companies generally as a core player in a maritime cluster, possessing stronger ties with companies in sub-clusters of the shipping industry rather than the ship industry in itself.

2.4. Port development within maritime cluster As noted in the introduction, maritime cluster is an evolving concept. The dynamic characteristic of maritime clusters depends largely on the change and development of port functions, which reflect different stages of economic and social development. As such, port positions in different maritime clusters are varied (UNCTAD, 1992 and 1999; Woo et al., 2011). For example, a port acts as the changing point of a transport node (Brett and Roe, 2010, Othman (2011)), transport, industrial and commercial centre (De Langen, 2002; Fisher Associates, 2004), the integrated transport centre and logistic platform for international trade (Wijnolst, 2006; Panayides et al., 2015; Wiegmans et al., 2015) and occupies various roles in some maritime service oriented maritime clusters (Fisher Associates, 2004; Lam et al., 2011). In addition, the development of port cluster has drawn attention and its associated research has emerged, such as the collective action regimes as a key governance action (de Langen and Visser, 2005), changes to port authority functions (Verhoeven, 2010) and coordination among key port cluster actors (Bai and Lam, 2015). In sum, we devise that the role of port changes as a maritime cluster evolves. This dynamic research topic would enhance the understanding of port development, maritime cluster development as well as their interplay from a new perspective. In fact, the above literature did not explicitly relate a port with maritime cluster evolution. Also, there is a major gap in the existing knowledge concerning the quantitative and empirical study of maritime cluster evolution from a port development perspective. This research is intended to fill these gaps by providing a useful reference for maritime authorities on the most beneficial and effective development coordination between ports and maritime clusters, both theoretically and practically. Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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3. Theoretical development and methodology 3.1. Symbiosis theory Considering maritime cluster evolution from the port development perspective, a determining factor is the relationship and interactions between a port and another maritime sector. However, the forms of interactions, such as competition and symbiosis, are uncertain and changeable. As such, considering the rationale of studying the relationships between the port and other maritime sectors within the same maritime cluster, a multi-mode framework is proposed to assess the interaction between two or more sectors by possessing a rich setting. Though such a framework is new to the maritime domain, it has been applied for measuring the uncertain interactions in other domains, such as economies and technologies (Lee et al., 2005; Sandén and Hillman, 2011). In contrast to the limited scope with only one mode, the multi-mode framework provides comprehensive interactional modes related to restricting or promoting one another’s growth in the dynamic circumstances. It also considers the transitionary effects (Pistorius and Utterback, 1997). As claimed by Zhang and Lam (2013), the linkage among maritime sectors has transitionary effects, which means that the interactions among sectors may transgress from one mode to another with the evolution of the whole maritime cluster. Under the multi-mode interaction framework, the relationships in ecology can be introduced in the maritime cluster domain for reference. In this case, symbiosis theory is considered suitable for the study of maritime cluster evolution. The symbiosis theory, which originates firstly from the biological domain (Campbell, 1996), draws an analogy with maritime studies. The symbiosis theory explains the mechanism of evolution of a biotic community encompassing two or more populations of different species (Morin, 1999). As discussed in Section 2, there are various sectors under a maritime cluster and their functions would change over time. The evolutionary nature of maritime cluster is analogical to that of a biotic community (Zhang and Lam, 2013). For instance, both evolutionary processes go through the path from simple to complex; from a basic form to an improving structure (Campbell, 1996; Doloreux and Melancon, 2008). Also, ecological science describes adaptability as the capability of dealing with unanticipated disturbances in the environment (Conrad, 1983). Similarly, stakeholders and governments in a maritime cluster devise mechanisms and innovations to adapt to unexpected shocks (Doloreux and Shearmur, 2009). Regarding symbiosis theory, researchers in biology and ecology have developed mathematical formulations for ecosystems to identify suitable variables to explain the relationships among various species. Researchers in mathematical ecology have worked out many solutions to the studies of interacting species, and many of these researchers are from other scientific fields (Modis, 1999). Since the analogy exists between a biological community in ecology and a maritime cluster in the maritime domain, it will be interesting to investigate whether there is an empirical base to support such an analogy. As such, solutions in ecology, such as the Lotka-Volterra model, can be applied to solve maritime problems including maritime cluster formation and evolution. 3.2. Lotka-Volterra model After introducing the theory, the discussion moves on to the methodology to quantify the linkage between maritime sectors. This study proposes the use of the Lotka-Volterra model derived from the multi-mode interaction framework as stated above (Morris and Pratt, 2003). The interaction between two sectors in a cluster can be given in two differential equations with the essential parameters affecting the growth rate of two sectors (Tsai and Li, 2009). The interpretation and description for symbols in the model are indicated in Table 2.

Table 2 Notations for symbols. Symbol

Notation

X1, X2

Populations of two maritime sectors and they are represented by a few ways in the maritime domain, such as revenue (Shinohara, 2010) and number of people employed (Tovar and Wall, 2015) Growth rate of X1 and X2 at time t

dX1 dX2 , dt dt X21, X22 X1X2, X2X1 a1, a2 b1, b2 c1, c2 X1ðtþ1Þ , X2ðtþ1Þ X1ðtÞ , X2ðtÞ a1(2), b1(2) c1, c2 i

The same maritime sector interacting internally with itself Different maritime sectors interacting with one another The logistic parameters of geometric growth for the maritime sectors 1 and 2, when they are living alone The growth effects of internal interaction within each maritime sector Coupling coefficients, i.e. the interaction parameters with the other sector The populations of two maritime sectors at time (t + 1) The populations of two maritime sectors at time t The logistic parameters for the single sector X1 ðX2 Þ, when it is living alone The magnitude of the effects that revenue from X1 has on the growth rate of revenue from X2 and revenue from X2 has on the growth rate of revenue from X1 Maritime sector X1 or X2

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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W. Zhang, J.S.L. Lam / Transportation Research Part A xxx (2017) xxx–xxx

dX1 ¼ ða1  b1 X1  c1 X2 ÞX1 ¼ a1 X1  b1 X21  c1 X2 X1 ; dt

ð1Þ

dX2 ¼ ða2  b2 X2  c2 X1 ÞX2 ¼ a2 X2  b2 X22  c2 X1 X2 ; dt

ð2Þ

As the quantification of maritime cluster sectors involves discrete time data, the discrete time version is needed by converting from the continuous Lotka-Volterra model. Difference equations can be transformed from Eqs. (1) and (2) (Leslie, 1958):

a1 X1ðtÞ

X1ðtþ1Þ ¼

1 þ b1 X1ðtÞ þ c1 X2 ðtÞ

X2ðtþ1Þ ¼

1 þ b2 X2ðtÞ þ c2 X1ðtÞ

a2 X2ðtÞ

;

ð3Þ

;

ð4Þ

The relations between coefficients of Eqs. (1) and (2) and Eqs. (3) and (4) (Tsai and Li, 2009) are:

ai ¼ ln ai : bi ¼

bi ai

ai  1

ci ¼ ci

ð5Þ ¼

bi ln ai ai  1

ð6Þ

bi ci bi ln ai ci ln ai ¼ ¼ : bi bi ai  1 ai  1

ð7Þ

The multi-mode form between two sectors is indicated by the coefficients c1 and c2 as shown in Table 3. The different combinations of the signs of c1 and c2 reveal the two sectors’ relationship (Modis, 1999). For example, if both signs of c1 and c2 are positive, the sectors compete with each other entirely. If one is positive while the other is negative, the relationship is called ‘predator-prey’ meaning that the second sector feeds the first sector. The sign of ci must be the same as the sign of ci since

ln ai ai 1

is always positive if ai > 0 and ai –1 in Eq. (7). Hence, the relationship can be determined by the sign of ci .

3.3. Equilibrium analysis An interesting topic and outcome when analysing the relationships is the equilibrium point. Equilibrium point relates to the equilibrium state. For example, what the state is? How does the trajectory change over time and stability of the equilibrium (Kim et al., 2006)? The equilibrium state means there is no compelling simultaneous change over time for each maritime sector. On the premise of the equilibrium, Eqs. (1) and (2) are zero at the same time. By solving the equations mentioned above, Eqs. (8) and (9) can be obtained as below.

X1 ¼

a1  c1 X2 : b1

ð8Þ

X2 ¼

a2  c2 X1 : b2

ð9Þ

1 X2 1 In Eqs. (8) and (9), if X 1 < a1 c , then dX > 0. In this case, the population of maritime sector X 1 increases in size over time. b1 dt 1 X2 1 Conversely, if X 1 > a1 c , then dX < 0, which means the population of maritime sector X 1 decreases in size over time. Similar b1 dt 2 X1 2 2 X1 , then dX > 0. As such, the population of maritime sector X 2 increases in size over time. If X 2 > a2 c , then to X2, if X 2 < a2 c b2 dt b2

dX2 dt

< 0. This denotes the population of maritime sector X 2 decreases in size over time. The above two lines (Eqs. (8) and (9)) intersect each other eventually. If the two lines intersect in the second or fourth quadrant, the equilibrium point indicates that one of the maritime sectors will survive in the future and the other will withdraw from the maritime market (as shown in Figs. 1 and 2). Only if the two lines of viii and iv intersect each other

Table 3 Interpretation of interaction parameters. Source: Tsai and Li (2009). c1

c2

Type of relationship

Interpretation

+ + – + – 0

+ – – 0 0 0

Pure competition Predator-prey Mutualism Amensalism Commensalism Neutralism

Both species suffer from each other’s existence One of them serves as direct food to the other It is the case of symbiosis or a win-win situation One suffers from the existence of the other, who is impervious to what is happening One benefits from the existence of the other, who nevertheless remains unaffected There is no interaction

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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in the first quadrant can two competing maritime sectors have an equilibrium point. It means that the paired maritime sectors are expected to coexist without dynamic changes. Otherwise, only one sector can survive finally in the competing system. The value of parameters in the Lotka-Volterra model determines the stability of equilibrium state. Figs. 1–4 demonstrate four possible equilibrium states. 1 X2 In Figs. 1–4, for line X 1 ¼ a1 c , when the point falls into the region of the vertical hatching, i.e. X 1 < ba11 , the population of b1 X1 will increase in size below the line. Conversely, it decreases in size when above this region, i.e. X 1 > ba11 . Similarly, for line 2 X1 , when the point drops in the horizontal area with X 2 < ba22 , the population of X2 will increase below the line. Or X 2 ¼ a2 c b2

else, it decreases above the line. 1 X2 2 X1 Fig. 1 shows that X 1 ¼ a1 c is above the line X 2 ¼ a2 c wholly in the first quadrant, i.e. ac11 > ba22 and ba11 > ac22 . As a result, the b1 b2 population of maritime sector X1 will increase and X2 decreases. X2 will be replaced by X1 and dies out eventually. The reverse situation is indicated in Fig. 2. In Figure 2, ba22 > ac11 and ac22 > ba11 , the population X2 wins and X1 dies out finally. 1 X2 2 X1 and X 2 ¼ a2 c intersect each other in the first quadrant. They meet at Observing Figs. 3 and 4, the two lines X 1 ¼ a1 c b1 b2 2 c1 the point of (X 1 ⁄, X 2 ⁄) = (ba11bb22a ; a2 b1 a1 c2 ), with stable or unstable equilibrium state. The stability of equilibrium point deterc1 c2 b1 b2 c1 c2

mines the moving trajectory of two populations in size. For a stable equilibrium point, no matter what population sizes of two initial maritime sectors, they approach to the equilibrium point finally or deviation from the equilibrium point will go back to the equilibrium. Conversely, the two maritime sectors will deviate away from the equilibrium point as for an unstable equilibrium point. When ac11 > ba22 and ac22 > ba11 , it implies the stable equilibrium as in Fig. 3. It indicates that the populations of two maritime sectors will move and reach to the equilibrium point (X⁄1, X⁄2) without dynamic changes. When

a1 b1

>

a2 , c2

a2 b2

> ac11 and

the equilibrium state is not stable. It follows that the two maritime sectors will not be replaced entirely by each other

as time passes. As such, it can be concluded that if two populations from the equilibrium point are in the same increasing/ decreasing direction, they will return to equilibrium. In the condition of moving in opposite ways of growth, the two maritime populations will arrive at the unstable state. This paper verifies the reciprocal influences of maritime cluster evolutions two-by-two in pairs between a port and another maritime sector within a maritime cluster. While the revenues are in turn grouped into some comparative pairs, these pairs are examined separately by Eqs. (3) and (4). This determines the mutual impacts between sectors within the maritime cluster. In addition, this investigation further advances to forecast the trend of the London maritime cluster. This is achieved by studying the existence of an equilibrium point. It is also realised by analysing the stability of the equilibrium point with the estimated functions.

4. Empirical analysis and policy implications The empirical analysis based on the Lotka-Volterra model is conducted on two major evolving maritime clusters with higher service orientation over the years and their ports: London (Type 4 maritime cluster) and Hong Kong (evolving to Type 4 maritime cluster). A Type 4 maritime cluster appears with its main function as a maritime service centre, which can provide services to users who are very far away from the location where the cluster is centred. The most distinguished characteristics for a Type 4 maritime cluster are knowhow and the workforce’s expertise, and it is upon this knowledge that the international maritime services depend. Maritime services in this category are provided in a wide range, such as ship finance, marine insurance, maritime law and shipbroking, to meet the comprehensive requirements of modern maritime business (Zhang and Lam, 2013). The UK is the leading centre worldwide in the supply of a broad range of professional and business services to the international maritime community, that are largely concentrated in London. According to TheCityUK (2013), London is a leading source of capital and expertise for ship finance, shipbroking, marine insurance, legal services and many other services. The growth of overseas earnings from maritime service sectors is tremendous, which is more than twice from 1999 to 2010.

X2 a1/c1 a2/b2

0

a2/c2

a1/b1

X1

Source: Drawn by authors. Fig. 1. Maritime sector X1 survives, as X1 increases and X2 decreases.

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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X2 a2/b2 a1/c1

0

a1/b1

a2/c2

X1

Source: Drawn by authors. Fig. 2. Maritime sector X2 survives, as X2 increases and X1 decreases.

However, we see stagnation or even a slight downswing of freight volume handled by Port of London (DfT, 2014). For Hong Kong, it also experienced strong development in its maritime service cluster while the port’s throughput had slower growth rate over the past years, contrasting with the background of expansion in international trade and port throughput worldwide (Marine Department, 2000–2014; Economic Development and Labour Bureau, 2004a, 2006; Transport and Housing Bureau, 2007–2012). Hence, given the port and maritime service developments of London and Hong Kong, they are among the most suitable targets for study out of all the major ports and maritime clusters in the world. The following sub-sections firstly explain the chosen paired services, and then the calculation and results analysis are presented accordingly. Finally, the research devises maritime policy implications and recommendations based on the empirical results. 4.1. Choice of paired services As discussed in the literature review section, there are many types of maritime clusters in the world, possessing dynamic characteristics with various cluster formations and functions. As such, the composition of maritime sectors in future concerns the strategic direction of every cluster. This research applies the Lotka-Volterra model to measure the relationships between ports and other maritime sectors in a paired analysis, with the port sector being half of the pair, and the other component sectors as variants for comparison. This section discusses the reasons for choosing the paired services. Nowadays, various maritime clusters perform a multitude of different functions, with each cluster embodying unique features. For example, London concentrates on various service sectors, such as shipbroking which is the biggest contributor to the UK maritime services’ overseas earnings, and marine insurance which also generates significant overseas earnings (TheCityUK, 2013). There is an approximately three-time increase in earnings from marine insurance and about twice from brokering from 1999 to 2010. London plays an important part in the international maritime services market with a large proportion of international market share. For example, London makes up 62% in marine insurance (P&I Clubs), 50% in the tanker chartering market, and 30–40% in the dry bulk chartering of the world’s market share. Many large shipbrokers have their headquarters in London, such as Clarksons, Braemar Seascope, EA Gibson, Galbraith’s, Howe Robinson, and Simpson Spence and Young, which are internationally established (TheCityUK, 2013). As for Hong Kong, maritime services are put in a strategic position and promoted by the Hong Kong government. So far, Hong Kong has the good reputation for the high-quality maritime services. They are famous for the professionalism, efficiency and competitiveness (Hong Kong Maritime Industry Council, 2013). Among the maritime services, marine insurance continues to develop. For example, the major P&I Clubs set up their representative offices in Hong Kong, aiming to conduct business relating to underwriting and claims administration. In addition, a hull insurance market targeting in the Asian area was established to serve ship owners in Asia. As such, Hong Kong is building up its ability to provide comprehensive marine

X2 a1/c1 a2/b2

0

a1/b1

a2/c2

X1

Source: Drawn by authors. Fig. 3. Maritime sectors X1 and X2 coexist with stable equilibrium.

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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X2 a2/b2 a1/c1

0

a2/c2

a1/b1

X1

Source: Drawn by authors. Fig. 4. Unstable equilibrium between maritime sectors X1 and X2.

insurance services. In the meanwhile, Hong Kong sees a vibrant shipbroking industry. Hong Kong’s ship brokers have the ability to develop a full range of business outside of Hong Kong. In addition, Hong Kong remains its role as a major crosstrading centre for business. A large amount of international bodies, such as the Baltic Exchange and Institute of Chartered Shipbrokers, contribute to the shipbroking industry of Hong Kong (Maunsell Consultants, 2003; Hong Kong Maritime Industry Council, 2013). As such, marine insurance and shipbroking are the key sectors for both London’s and Hong Kong’s maritime clusters. For policy makers, key questions include: is the growth of maritime services beneficial to the port sector which focuses on physical ship and cargo handling? Do these sectors complement each other in a maritime cluster? Or do they actually compete with each other in terms of resource allocation when the sectors develop? This paper studies two pairs of sectors, namely (1) port and marine insurance, and (2) port and shipbroking, for each cluster of London and Hong Kong, thereby identifying the interactions between the two sectors within a pair. The available data for analysis are gross premium of marine insurance and net overseas earnings of shipbroking in the UK. Similar to London, the service sectors’ revenue data in Hong Kong are used for analysis. The data are gross premium of marine insurance and business receipt of shipbroking. The port sector for both cases utilizes data of cargo handling income which is a common port performance indicator. These data, all in monetary terms, represent the sectors’ revenue which is a suitable indicator of growth performance.

4.2. Case of London Based on the Lotka-Volterra model using available data from the year 2002 to the year 2010, as in Appendix, the result shows one zero and one negative sign for gamma values for the relationship between the port of London and the marine insurance sector. The estimated coefficients and accompanying statistics by the Lotka-Volterra model are shown in Table 4. In the ecological domain, the two sectors have a commensalism relationship. One of them benefits from the existence of the other, while the other remains unaffected. The negative one behaves as the one benefiting from the other (Tsai and Li, 2009). In this case, the result reflects that the marine insurance sector benefits from port development. It also indicates that port development does not rely on the marine insurance business, which takes up 62% of the market share in P&I Club business all over the world (TheCityUK, 2013). It is interesting to find that even when the port of London seems to play a relatively small part in the whole London maritime cluster, marine insurance still benefits from port. This may result from two main reasons. Firstly, this could be the influence of port heritage. Although maritime services make a great contribution to the UK economy, they are derived from port activities and shipping traffic. The historical factor of London port has a tremendous position in London’s maritime service development (Port of London Authority, 2013). Another reason is the expansion and innovation of port activities and functions. Nowadays, ports attempt to reform and provide more value-added services (Lee and Lam, 2016). Such changes benefit port development and promote and stimulate maritime services development as well. As a result, even maritime services play a dominant role in a maritime cluster, the services sectors benefit from port development (Lam and Cullinane, 2003; The UNCTAD Secretariat, 2010, 2011). Judging from the interaction between the port and shipbroking business in London, it can be identified that the relationship between these two sectors is commensalism. This is identical to the relationship between the port and marine insurance, that is, shipbroking benefits from port development while the port remains unaffected by shipbroking development. Such a relationship attributes as a positive-neutral relationship. This set of result demonstrates that again port development benefits a maritime service sector, in this case, the advanced shipbroking sector in London which contributes the largest portion of UK maritime services’ overseas earnings (TheCityUK, 2013). Empirical results show that the relationship between the port of London and the marine insurance sector is consistent with the interaction between the port and the shipbroking sector. Both advanced maritime services, namely marine insurPlease cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

London

a (Std. Error) 95% CI b (Std. Error) 95% CI

c (Std. Error) 95% CI R2

Hong Kong

Port and Marine insurance

Port and Shipbroking

Port and Marine insurance

2.264 0.502 (0.974, 3.554) 0.025 0.011 (0.004, 0.054) 0.000 0.000 (0.000, 7.751E05) 0.927

1.578 0.564 (0.127, 3.029) 0.006 0.011 (0.023, 0.034) 0.000 0.000 (0.000, 0.001) 0.865

2100220.1 1.163E+12 (2.989E+12, 2.989E+12) 203.665 1.128E+08 (2.989E+08, 2.989E+08) 625.592 3.464E+08 (8.903E+08, 8.903E+8) 0.903

1.130 0.767 (0.841, 3.102) 9.138E05 0.000 (0.000, 0.000) 0.006 0.014 (0.014, 0.030) 0.581

1.091 0.938 (1.320, 3.503) 0.001 0.000 (0.000, 0.002) 0.014 0.010 (0.040, 0.012) 0.686

Port and Shipbroking 8.478E+10 3.912E+17 (1.006E+18, 1.006E+18) 23808674 1.098E+14 (2.824E+14, 2.824E+14) 6950149 3.207E+13 (8.243E+13, 8.243E+13) 0.803

34.602 271.362 (662.956, 732.160) 0.004 0.032 (0.079, 0.087) 0.010 0.079 (0.194, 0.214) 0.916

12.084 198.475 (498.112, 522.280) 0.009 0.157 (0.393, 0.412) 0.001 0.010 (0.026, 0.027) 0.699

Note: 95% CI denotes 95% Confidence Interval meaning the interval estimate of population parameter at the 95% confidence level and indicating the reliability of an estimate, with a Lower Bound and a Upper Bound shown as (Lower Bound, Upper Bound).

W. Zhang, J.S.L. Lam / Transportation Research Part A xxx (2017) xxx–xxx 9

Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

Table 4 Estimation result for each pair of sectors in London and Hong Kong cases (based on original data of Year 2002-Year 2010).

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Fig. 5. Equilibrium point between port revenue and gross premium of marine insurance in London.

ance and shipbroking, benefit from port development. However, the port sector does not benefit from these maritime services sectors, showing that maritime services are highly mobile and can have little connection with the local shipping market. But according to the result these maritime services sectors, though demonstrating a much faster growth than the port sector, do not pose any competition to the port. That is, the port can keep on growing even London’s maritime cluster becomes more service dominate. Results draw practical policy implications. London cannot neglect the port’s contribution to the whole maritime cluster. Practically, although maritime services contribute significantly to the UK economy, there are concerns about the UK’s future prospects as a maritime services centre. London faces the challenge of attracting maritime business from other maritime centres, such as Hong Kong and Singapore in Asia and Dubai in the Middle East (TheCityUK, 2011). These three maritime clusters are well-known for their world-class port and value-added activities. Although nowadays the port does not have a leading role in maritime cluster development, it would be advantageous to further develop the port of London since it substantially facilitates London being a world-major maritime service provider. Looking into the strategic planning for the port, London is ambitious in enhancing its port’s competitiveness, even the maritime cluster is service oriented as a whole. London Gateway with the annual capacity of 3.5 million-TEU is UK’s largest and deepest container facility. In addition to the new port, London aims to combine with Europe’s largest logistics park, which offers a port-centric solution that today’s port users require in their supply chains (IHS Fairplay, 2011; London Gateway, 2015). This strategic plan and decision confirms the findings above from empirical demonstration.

4.3. Case of Hong Kong For the interactions between the port and the marine insurance sector in Hong Kong, we find that the two signs for gamma values are positive. It means these two sectors are in a relationship of pure competition. In this relationship, each sector has a negative influence on the other’s growth rate (Tsai and Li, 2009). From the perspective of innovative development within the maritime cluster, pure competition is a prevalent case and happens extensively (Doloreux and Melancon, 2008). In this background, the emerging sector, which is marine insurance in Hong Kong’s case, is regarded as the substitute of port development with consideration of generating the added value for port and gross premium for marine insurance. Although the functions of a port and marine insurance are different, the overall objective of each sector is the same—to generate revenue and profit from the maritime industry. In addition, the broad factor requirements of these sectors are similar considering professional human capital and investment. Substitutes are taken as a powerful force in a competition. This force is recognised as one of the five forces in Porter’s model of industrial competition (Porter, 1990). If a substitute has the same market niche as an existing maritime sector, generally speaking, it will exert an inhibiting effect on the existing sector and serve the same niche. If a port, as the matured sector, does not realise the importance of dynamic development and innovation, marine insurance, in this situation as a more profitable sector, can be regarded as a powerful substitute. The substitute will serve the same niche market as the existing port sector, resulting in these two sectors possessing an inhibiting effect on each other. Although the relationship between a port and marine insurance probably used to coexist symbiotically at the initial stage of maritime cluster development, such a relationship may transgress to the competition mode, as the transitionary effects exist. As such, each of the two Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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sectors has exerted a negative effect on the other’s growth rate in recent years and even maintains such a relationship into the near future. The parameters and related statistics of Lotka-Volterra model are shown in Table 4. In Hong Kong’s case, the relationship between the port and marine insurance represents competition for maritime resources, such as human capital and investment. Marine insurance is categorised as an advanced maritime service, which requires higher-lever maritime professionals and experts in this specific insurance domain. Meanwhile, expansion and innovation of port activities and functions require more maritime experts and professionals than ever before. The same requirements for maritime professionals may constrain further expansion and development of both the port and marine insurance business in Hong Kong. Beside a shortage of professionals in the maritime industry, the same situation in terms of limited investment is another concern. Considering the fight between the port and marine insurance for financial investment and professional human capital, both sectors need to take the initiative to adopt innovative strategies to promote further development and find their own niche markets to achieve complementary development and to avoid the fierce and vicious competition (Pistorius and Utterback, 1997). Based on the empirical result, the situation between the port and shipbroking is the same as the relationship between the port and marine insurance in Hong Kong’s case. The results are in line with the policy direction in practice. In contrast with the ambitious port expansion in London, the port of Hong Kong decided not to build new seaport terminals in the near future after extensive debate amongst the government, port operators and port users in its master plan for 2020 (Economic Development and Labour Bureau, 2004b). The findings show that this is the right direction since the port is seen having slower growth in recent years. More economic benefits could be generated with the rise in investment in physical port construction in earlier years. In view of fierce competition from the neighbouring ports of Shenzhen and Guangzhou (Lam and Yap, 2011; Wang et al., 2012), port expansion in Hong Kong would reduce its efficiency unless port output can grow significantly, driven by external favourable circumstances. Such external factors are usually uncontrollable, therefore policy makers may not want to risk a huge capital investment. Meanwhile, the result implies that the matured port sector needs to consider diversifying to the emerging advanced maritime service sectors, such as insurance and shipbroking, to evolve the maritime cluster to a knowledge-based and highvalue added stage. Due to scarce land resource, it is recommended that developing service oriented sectors would be the priority in view of space utilisation. In 2016, the Hong Kong Maritime & Port Board was established officially. It is responsible for ‘‘formulating strategies and policies to drive the growth of high value-added and professional maritime services in Hong Kong, foster talent development, and promote Hong Kong as an international maritime hub” (HKTDC Research, 2016). This strategic plan confirms and strengthens our empirical results. 4.4. Equilibrium analysis: an example Based on formulas v, vi and vii, coefficients estimated from two empirical cases and concept of equilibrium analysis in Section 3.3, the equilibrium points can be obtained. Based on the data ranging from year 2002 to year 2010, the two lines intersect at (50.56, 4742.394) in the first quadrant for the port and the marine insurance sector in London’s case. For the port and the shipbroking business, they intersect at point (77.39581, 1174.541). Another two intersection points are (6060.38, 5330.161) for the port and marine insurance in Hong Kong, as well as (6317.492, 847.3207) for the port and shipbroking. Taking the port and marine insurance in London’s case for example in Fig. 5, real data for the port and marine insurance in year 2012 is (79.309, 7434.000), which has not reached the stable equilibrium point yet. The region with vertical hatchings   1 represents the area where port revenue increases dX < 0 . The region with horizontal hatchings indicates the area where dt   2 < 0 . As such, the blank area, which the real data for the year 2012 (79.309, gross premium of marine insurance increase dX dt 7434.000) falls, means the growth for two sectors decreases. As a result, the two maritime sectors will move to the left in a downward direction to the equilibrium point. In this case, the growth of port development will decrease and marine insurance will decrease in the same direction to reach the equilibrium point. When the two sectors reach it, they may deviate again. Then the two sectors will recur in the equilibrium, since their equilibrium point is identified stable judging from   the coefficients ac11 > ba22 and ac22 > ba11 . 5. Conclusion This research advances maritime cluster study to a new and significant area from a theoretical perspective, i.e. the classification and evolution of maritime cluster from the changing port function perspective. Based on this relationship between maritime clusters and ports, the study categorizes major world maritime clusters into two parts — with and without strong port throughput as the support of the maritime cluster. One typical case of a maritime cluster from each of these two groups — London and Hong Kong respectively — is selected and analysed. This research is the first attempt in the literature to analyse maritime cluster evolution through the study of various sectors’ linkages. From the port research’s perspective, the paper is also a pioneer study of the interactions between a port and other maritime sectors. Symbiosis theory, which is originated from the biological domain, is applied to the study of maritime cluster. The Lotka-Volterra model, which combines the required features and functions, is adopted to measure multi-mode relationships between the investigated sectors. This reveals the development path and priority of maritime sectors within a maritime cluster. This study takes insight of maritime cluster development by combining the most relevant aspects and Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

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Data in year London ($m)

2002

2003

2004

2005

2006

2007

2008

2009

2010

Port Turnover 48.670 56.078 64.615 69.677 70.405 70.514 78.027 74.519 75.767 Marine Insurance -Underwriting Gross premiums 2045 3376 3276 3549 4342 4716 4558 4824 6662 Ship brokering Net overseas earnings 550.425 649.570 941.877 1256.405 1206.833 1314.525 1620.506 1220.508 1275.209

Hong Kong Port (HKD million) Marine Insurance Ship brokering

Value added

8009.919 7874.064 8079.040 7626.557 7875.798 7420.626 7129.329 5979.429 6436.721

Gross premiums Business receipt

716 131

728 158

868 287

910 383

1063 393

1087 678

1439 1059

1272 696

1574 802

Source: Compiled by authors, based on Port of London Authority (2004-2011), IFSL (2000, 2003, 2005, 2007, 2009), TheCityUK (2011, 2013), Lloyd’s (2012), International Union of Marine Insurance (IUMI) (2013), Office for national statistics (ONS) (2013), Economic Development and Labour Bureau (2004b, 2006), Transport and Housing Bureau (2007–2010), Census and Statistics Department (2000–2009), Census and Statistics Department (2010, 2011) and X-rate (2013).

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Please cite this article in press as: Zhang, W., Lam, J.S.L. An empirical analysis of maritime cluster evolution from the port development perspective – Cases of London and Hong Kong. Transport. Res. Part A (2017), http://dx.doi.org/10.1016/j.tra.2017.05.015

Appendix A. Original data in the cases of London and Hong Kong

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associated resources to investigate a complex interaction system. With the empirical analyses based on London and Hong Kong, the paper explains the originally uncertain and complex maritime cluster system. It provides references for clusters’ policy makers to answer questions associated with clusters’ further development, such as is the growth of maritime services beneficial to the port sector which focuses on physical ship and cargo handling? Do these sectors complement each other in a maritime cluster? Or do they actually compete with each other in terms of resource allocation when the sectors develop? A key suggestion from the study is that the essence of a maritime cluster is the strong link among a comprehensive array of sectors in order for the cluster to be truly competitive and sustainable. For maritime clusters with good maritime service performances, such as the well-established marine insurance and shipbroking industries in the case of London, port development should not be neglected. Even if the port would not take a dominant role in a service-oriented cluster, the port’s development is better to take advantage of maritime services development and be coordinated with the services. Both the port and maritime services still benefit from each other. As for clusters with established port performances like Hong Kong, they cannot rely solely on port development in the long run. As major maritime clusters are expected to be onestop-service centres, clusters with established ports are expected to take notice of the great potential and revenue from providing higher-value-added services such as marine insurance and shipbroking. However, ports and other maritime service sectors share and compete for some similar resource inputs, such as capital investment, advanced and professional human resources, and land resource, though the functions of and operation markets on which various maritime sectors differ. Take professional human resources for example, professionals’ qualification and capability required in the port sector are different from those in the marine insurance sector. However, maritime degree holders have various choices to specialise their expertise among various maritime sectors, which leads to the competition for professional human resources within a broader maritime cluster. As such, with limited resources in capital investment, professional human resources and land, maritime clusters should better coordinate the future development among various players. The recommended path is that both ports and maritime services grow healthily to support each other, being promoted and guided by proper governmental planning and policies. The double-edged sword will make maritime clusters robust and resilient in the diverse and rapidly evolving global economic system. This research contributes by empirically analysing the relationships between maritime sectors to guide policies such as sector prioritisation and pairing of sectors for complementary development. In particular, this research presents a useful reference for policy suggestions on the formation of maritime cluster in future for maritime cities and regions en route to higher value generating international maritime centres. As for future research work, one of the significant focuses is to identify the influential maritime players and explore more interactions between these maritime sectors and the port with the Lotka-Volterra model. Such major sectors are pertinent in a maritime cluster or intended to be highly recommended and promoted by decision makers when mapping the future plan for the whole cluster. Future research can be carried out for other clusters as well, especially for those aiming to be serviceoriented maritime clusters, to coordinate the development between a port and maritime services. Acknowledgement The research was supported by the funding from Nanyang Technological University, Singapore during the PhD study of the first author.

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