INTRODUCTION
The phenomenon that firms in the same industry tend to locate in the same geographical area has been a significant issue since Alfred Marshall (Reference Marshall1920). This interest was further strengthened by the increasingly important role played by clusters in the global economy. Although knowledge about the causes of clusters has been significantly advanced, researchers have yet to agree about the impact of industrial clusters on individual firms. While many theorists insist that these impacts are largely positive (e.g., Porter, Reference Porter1990, Reference Porter, Clark, Feldman and Gertler2000), many empirical studies find a more complicated picture (Bell, Tracey, & Heide, Reference Bell, Tracey and Heide2009; Kukalis, Reference Kukalis2010; Sorenson & Audia, Reference Sorenson and Audia2000). How to account for this issue posts an important challenge to studies of industrial clusters.
The aim of this study is to fill this research gap in two ways. First, at the theoretical level, we introduce the concept of ‘coopetition’, namely the coexistence of cooperation and competition among organizations (Bengtsson & Kock, Reference Bengtsson and Kock2000, Reference Bengtsson and Kock2014; Czakon, Fernandez, & Minà, Reference Czakon, Fernandez and Minà2014), to account for the complicated and sometimes paradoxical relationship between a cluster and individual firms. Coopetition involves value creation and value appropriation (Brandenburger & Nalebuff, Reference Brandenburger and Nalebuff1996). The tension between cooperation and competition mainly comes from when and in what stage firms cooperate on value creation or firms compete on value appropriation (Gnyawali, He, & Madhavan, Reference Gnyawali, He, Madhavan and Wankel2008; Tidström, Reference Tidström2014). In the case of clusters, networks and spillovers among firms in the same cluster facilitate cooperation and knowledge sharing (e.g., Arikan, Reference Arikan2009; Krugman, Reference Krugman1991; Maskell, Reference Maskell2001). However, the geographical concentration may also bring stronger competition among firms due to the reduction of search cost for customers and the difficulty of monopolizing important information and technology (Hendry & Brown, Reference Hendry and Brown2006; Kukalis, Reference Kukalis2010; Shaver & Flyer, Reference Shaver and Flyer2000). How firms compete or cooperate with each other in a cluster may demonstrate an evolutionary scenario (Kukalis, Reference Kukalis2010; Pouder & St. John, Reference Pouder and St. John1996), and thus the locus of coopetition among firms may present dynamic nature (Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008) and accordingly impacts firm performance (Czakon et al., Reference Czakon, Fernandez and Minà2014).
Second, at the empirical level, we follow the research program of organizational ecology and focus on the long-term evolution caused by the emergence and dissolution of organizations. In addressing the coopetition issues in clusters, scholars need to deal with how the firm's coopetition strategy may evolve over time accompanied by the cluster development process (Czakon et al., Reference Czakon, Fernandez and Minà2014; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008). The typical case studies provide detailed evolution of coopetition strategy inside a firm but hardly provide the overall picture in an industry (Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008). In this study, we employ the viewpoint of population ecology (Carroll & Hannan, Reference Carroll and Hannan2000; Hannan & Freeman, Reference Hannan and Freeman1989) to examine the dynamics of yacht manufacturing firms in Taiwan from 1957–2010. We argue that the population ecology perspective provides a good lens to investigate how and why industry clusters are performance enhancing for firms by differentiating the mechanisms of the birth and dissolution of firms in industrial development. Following this line of logic, employing the population ecology perspective is helpful to untangle the value creation and value appropriation created from coopetition among firms in a cluster. The yacht manufacturing industry data in Taiwan, which is characterized by geographical agglomeration and the evolution cycle of an organizational population, namely legitimation, competition, and revival (Hannan, Carroll, Dundon, & Torres, Reference Hannan, Carroll, Dundon and Torres1995; Hannan & Freeman, Reference Hannan and Freeman1989), affords a good example to advance the understanding of coopetition among firms in a cluster.
This study contributes to the literature in three ways. First, it addresses the dynamic dimension of cluster formation and evolution (Carroll & Hannan, Reference Carroll and Hannan2000; Pouder & St. John, Reference Pouder and St. John1996). By focusing on the emergence and survival of firms rather than static correlation of profitability and firms’ attribute, this study argues that the impact of coopetition strategy is not only a game model for a firm (Brandenburger, & Nalebuff, Reference Brandenburger and Nalebuff1996; Padula & Dagnino, Reference Padula and Dagnino2007) or illustrates the firm's linkages or positions in a network (e.g., Gnyawali, He, & Madhavan, Reference Gnyawali, He and Madhavan2006; Gnyawali & Madhavan, Reference Gnyawali and Madhavan2001; Tsai, Reference Tsai2002); instead, it is possibly an outcome of a process that co-evolves with the stage of industrial life cycle. Focusing on the emergence, survival, and dissolution of firms can demonstrate the co-evolution of industrial cycles and the impact of cluster on the firm. Second, this study contributes to the debate on coopetition (Brandenburger, & Nalebuff, Reference Brandenburger and Nalebuff1996; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008). While the literature of coopetition is concentrated on the static tradeoff between value creation and value appropriation in value chains (Bengtsson & Kock, Reference Bengtsson and Kock1999, Reference Bengtsson and Kock2000; Brandenburger & Nalebuff, Reference Brandenburger and Nalebuff1996; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008), this study introduces a dynamic model focusing on evolutionary logic (Czakon et al., Reference Czakon, Fernandez and Minà2014). Third, by examining the evolution of a cluster in the yacht manufacturing industry in Taiwan, this study provides important information of the cluster evolution in emerging economies that allows further comparison with Western economies, which is crucial for understanding the dynamics of the contemporary global economy (Hoskisson, Eden, Lau, & Wright, Reference Hoskisson, Eden, Lau and Wright2000; Hoskisson, Wright, Filatotchev, & Peng, Reference Hoskisson, Wright, Filatotchev and Peng2013; Sonobe & Otsuka, Reference Sonobe and Otsuka2006). Firms from emerging and the mid-ranged economies play increasingly salient roles in global markets over the last several decades (Hoskisson et al., Reference Hoskisson, Eden, Lau and Wright2000, Reference Hoskisson, Wright, Filatotchev and Peng2013; Ramamurti & Singh, Reference Ramamurti and Singh2009) and their competitive advantages usually come from either participating in the global value chain (Mathews, Reference Mathews2002, Reference Mathews2006) or good market positions in domestic markets (Hoskisson et al., Reference Hoskisson, Eden, Lau and Wright2000, Reference Hoskisson, Wright, Filatotchev and Peng2013). The cluster is a crucial phenomenon in in both occasions (Sonobe & Otsuka, Reference Sonobe and Otsuka2006). Therefore, the studies on clusters can provide a better understanding on global economy.
THEORETICAL DEVELOPMENT AND HYPOTHESES
Coopetition and Cluster
The first theory addressing the causes of industrial clusters can be traced to Alfred Marshall (Reference Marshall1920). He observed the phenomenon of industrial clusters and indicated three major causes – lower transportation cost among buyers and suppliers, bigger pools of labor, and intellectual spillover. Since the mid-1970s, the rise of several important clusters inspired another wave of studies on clusters. While the inquiry about clusters never ceased, not until the 1980s when several successful clusters played salient roles in the global economy did the theory of clusters made substantial progress. Sable and Piore (Reference Piore and Sable1984) argued that the textile industry in northern Italy shows that the movement of flexible specialization embedded with clusters of small and medium enterprises has replaced the paradigm of mass production carried out by large firms. The most influential theory about clusters may be Michael Porter's (Reference Porter1990, Reference Porter, Clark, Feldman and Gertler2000) argument that attributes competitive advantages of firms and nations to clusters. He identifies three mechanisms through which a cluster may enhance a firm's competitiveness. First, a cluster can increase the productivity of a firm; second, it can encourage firms’ innovation; and third, it can stimulate new companies.
Kuah (Reference Kuah2002) summarizes later studies and shows that many of the theories on clusters, including externalities (Romer Reference Romer1990), positive feedback (Swann, Prevezer, & Stout, Reference Swann, Prevezer and Stout1998) and so on, are built on Marshall's and Porter's theories about the benefits brought by clusters to individual firms. Despite the substantial theoretical progress, empirical studies have yet shown consistent results. While much of the literature assumes that the impact of a cluster on individual firms is all positive (e.g., Arikan, Reference Arikan2009; Figueiredo, Jr., Meyer-Doyle, & Rawley, Reference Figueiredo, Meyer-Doyle and Rawley2013; Porter Reference Porter1990; Tallman, Jenkins, Henry, & Pinch, Reference Tallman, Jenkins, Henry and Pinch2004), many studies show some negative or at least inconclusive results (Bell et al., Reference Bell, Tracey and Heide2009; Sorenson & Audia, Reference Sorenson and Audia2000). For example, Kukalis (Reference Kukalis2010) shows that firms locating in a cluster perform worse than those outside the cluster in the late stage of the industrial life cycle. Saxenien's (Reference Saxenian1994) classical analysis also shows that while the innovative culture characterizing Silicon Valley creates entrepreneurship and prosperity, the resulting fierce competition also leads to higher failure rates for extant firms. In other words, unlike the assumptions shared by many studies suggest, growth of a cluster may not necessarily result in higher survival rates for firms. How to account for these contradictory impacts remains a challenge for studies of industrial clusters.
In this study we argue that the recent literature of ‘coopetition’, namely the coexistence of competition and cooperation, may provide new insights that can be helpful for accounting for the contradictory effects of a cluster on individual firms (Bengtsson & Kock, Reference Bengtsson and Kock2000, Reference Bengtsson and Kock2014; Czakon et al., Reference Czakon, Fernandez and Minà2014). As Oliver (Reference Oliver2004) shows, inter-firm relationship in knowledge intensive industries such as the biotech industry are often composed of collaboration and competition. Gnyawali et al. (Reference Gnyawali, He and Madhavan2006) also show the deep impact of simultaneous cooperation and competition on a firm's competitive behavior. Padula and Dagnino (Reference Padula and Dagnino2007) put competition and cooperation into the context of networks and see cooperation as positive interdependence, and competition as negative interdependence.
Surprisingly, despite the fruitful studies on coopetition, few try to bring it into the studies on industrial clusters. We argue that integrating the concept of coopetition can highlight the contradictory effects of an industrial cluster on individual firms. On the one hand, the network externality and spillover effects among firms in the same cluster facilitate cooperation and knowledge sharing (e.g., Arikan, Reference Arikan2009; Krugman, Reference Krugman1991; Maskell, Reference Maskell2001). On the other hand, the geographical concentration may also bring stronger competition among firms due to the reduction of search costs for customers and the difficulty of monopolizing important information and resources (Hendry & Brown, Reference Hendry and Brown2006; Kukalis, Reference Kukalis2010; Shaver & Flyer, Reference Shaver and Flyer2000). The concept of coopetition, especially the value creation and value appropriation concept caused by coopetition (Brandenburger, & Nalebuff, Reference Brandenburger and Nalebuff1996; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008) will bring new insights to the studies of clusters.
For individual firms, the tension between cooperation and competition is highly contingent on the tradeoff between collective value creation and struggles on value appropriation (Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008; Tidström, Reference Tidström2014). While the current literature mainly addresses the motives, processes, or consequences of coopetition strategy at different levels (e.g., Bengtsson & Kock, Reference Bengtsson and Kock2014; Czakon et al., Reference Czakon, Fernandez and Minà2014; Dagnino, Di Guardo, & Padula, Reference Dagnino, Di Guardo, Padula and Dagnino2012; Park, Srivastava, & Gnyawali, Reference Park, Srivastava and Gnyawali2014) or highlight the inherent paradoxical nature caused from the coopetition strategy (e.g., Chen, Reference Chen2008; Raza-Ullah, Bengtsson, & Kock, Reference Raza-Ullah, Bengtsson and Kock2014; Smith & Lewis, Reference Smith and Lewis2011), evolution of coopetition strategies is rarely addressed (for an exception, see Ritala & Tidström, Reference Ritala and Tidström2014). We argue that putting this tension into the evolution of clusters and industries can bring new insights to both the coopetition and cluster literatures (Czakon et al., Reference Czakon, Fernandez and Minà2014; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008).
In order to untangle the effects of value creation and value appropriation on firms in a cluster, we employ the viewpoint of population ecology to examine the creation, survival, and dissolution of firms in an industry (Carroll & Hannan, Reference Carroll and Hannan2000; Hannan & Freeman, Reference Hannan and Freeman1989). Organizational ecology is summarized as follows. First, the evolution of an organizational population is driven by selection, not collective adaptation to the environment. In other words, the most important mechanisms shaping a population is the vital events, namely the birth, death, and survival of organizations. Second, organizational density, which is measured by the number of existing firms, is a crucial factor shaping the birth and death of organizations. In terms of density, there are at least two stages of organizational evolution: legitimation and competition (Carroll & Hannan, Reference Carroll and Hannan2000; Hannan & Freeman, Reference Hannan and Freeman1989). In the stage of legitimation, the newly formed population begins to gain ‘cognitive legitimacy’ by which the specific form of organizations is accepted by more organizations and decision-makers in the industry. In this stage, the birth rate of organizations is higher than their death rate. In the stage of competition, the space for new organizations is statured and the density decreases. However, the overall size of the population may not decrease as well (Barron, Reference Barron1999). In addition to these two basic stages, Ruef (Reference Ruef2000) suggested that many organizational populations experience the third stage – resurgent. In this stage, firms that pass a threshold can gain the capability on innovation as well as on getting competitive advantage. In addition to the two basic propositions, organizational ecology also indicates that age and size of an organization may have significant impact on its chance of survival. However, these propositions are much less conclusive (for a more comprehensive review on organizational ecology, please see Baum, Reference Baum, Clegg, Hardy and Nord1996; Carroll & Hannan, Reference Carroll and Hannan2000; Hannan & Freeman, Reference Hannan and Freeman1989).
While the ecology literature largely overlooks the impact of spatial concentration, some studies find that geographic location is crucial for firms’ founding, survival, and death. Wenting and Frenken (Reference Wenting and Frenken2011) find that geographic concentration in the global ready-to-wear fashion design industry is caused by higher entry rates in these areas. Folta, Cooper, and Baik (Reference Folta, Cooper and Baik2006) also find that although the spillover effect may benefit firms in the whole region, it also brings fiercer competition that raises the death rates of firms. In other words, evidences from the ecology literature provide important clues about the tension between cooperation and competition brought by a cluster (Kukalis, Reference Kukalis2010; Pouder & St. John, Reference Pouder and St. John1996). In what follows, we demonstrate our strategy by the data of the yacht manufacturing industry data in Taiwan.
Rationale on Hypotheses
In this study, we focus on three paths through which a cluster evolves and impacts firms: founding of new firms, survival of existing firms, and firm size in the resurgence stage. One of the most important insights of organizational ecology is the need for long-term data for determining the causal mechanisms in the study. Because cross-sectional data can only show existing firms at the time of survey, they inevitably have the problem of selection bias and cannot help to solve the problem raised in this study. For example, if a cluster can reduce the death rates of firms located inside it, utilizing panel data can show the different survival rate between firms located inside and outside the cluster and thus untangle the coopetition impact over time.
Firms’ founding rate and their locations in the early stage of cluster
Based on the above discussion, we establish the following hypotheses. The first hypothesis is about firms’ founding rate and their locations in the early stage of cluster. Following this argument, this study argues that firms located inside a cluster can easily find the resources and cognitive legitimation in the early stage of cluster (Stuart & Sorenson, Reference Stuart and Sorenson2003). New firms can easily find partners or cooperators on value chain activities in agglomerated areas even though they also will confront the possible challenges from other firms (Folta et al., Reference Folta, Cooper and Baik2006; Galaskiewicz, Bielefeld, & Dowell, Reference Galaskiewicz, Bielefeld and Dowell2006). For example, the successful cluster of biotechnological industries results from the networks among large, extant firms and small, new firms (Whittington, Owen-Smith, & Powell, Reference Whittington, Owen-Smith and Powell2009). Galaskiewicz et al. (Reference Galaskiewicz, Bielefeld and Dowell2006) also find that firms’ inter-organizational ties within a cluster enhance organizational growth. When a new firm is established in a cluster, it can gain the cognitive legitimation as well as the financial or technological resources from other firms (Ruan & Zhang, Reference Ruan and Zhang2009). In other words, industrial clusters may not directly benefit individual firms but rather create the coevolution process for firms and their embedded environment at the aggregate level (Audia, Freeman, & Reynolds, Reference Audia, Freeman and Reynolds2006; Galaskiewicz et al., Reference Galaskiewicz, Bielefeld and Dowell2006; McCann & Folta, Reference McCann and Folta2008). In other words, locating in a cluster can also create value among firms during the cooperation and legitimacy creation stage (Ritala & Tidström, Reference Ritala and Tidström2014), and has positive effects on the founding rates of firms located inside the cluster. Therefore, we posit the following hypothesis:
Hypothesis 1:
The founding rate of new firms will more likely be higher inside the cluster. This effect will be positively associated with the size of a cluster.
Survival rate of firms in a cluster during the competition stage
The second hypothesis is about the survival rate of firms in a cluster during the competition stage. When firms that choose to locate in a nearby industrial area increase, they inevitably have overlapping products and have to compete for customers with each other (Baum & Mezias, Reference Baum and Mezias1992; Wenting & Frenken, Reference Wenting and Frenken2011). We argue that in this stage a cluster has dual effects on firms: they share common resources but also face more fierce competition in the stage of competition (Bigelow, Carroll, Seidel, & Tsai, Reference Bigelow, Carroll, Seidel and Tsai1997). In this situation, cooperation and competition happen at the same time at the industrial level (Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008; Raza-Ullah et al., Reference Raza-Ullah, Bengtsson and Kock2014). Even though each firm in the cluster may have a fiercer struggle for resources and competition (Shaver & Flyer, Reference Shaver and Flyer2000), and search for the value appropriation for itself (Bengtsson & Kock, Reference Bengtsson and Kock1999), this focal firm still cooperates with others during the competition stage and obtains resources and information on innovation (Park et al., Reference Park, Srivastava and Gnyawali2014; Tallman et al., Reference Tallman, Jenkins, Henry and Pinch2004; Whittington et al., Reference Whittington, Owen-Smith and Powell2009). In the case of yacht manufacturers in the cluster, they usually outsource the wood making activity in the yacht manufacturing chain to those independent wood workers and those wood workers will share the knowledge and skill among each other and implement it among different yacht manufacturers (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012). Thereby, even though the yacht manufacturers compete on customer orders, they share the knowledge and resources with each other in the manufacturing process. At the ecology level, for those survived firms, it is hardly to justify the value creation and value appropriation effect accordingly. As a result, we suggest that in the competition stage, locating in a cluster have no overall effect on firm survival because a cluster may bring two opposite impacts on firm survival rate (Kukalis, Reference Kukalis2010; St. John & Pouder, Reference St. John and Pouder2006). Based on the fact that cluster advantages and disadvantages coexist, we argue that the coexistence of these two effects will cause the cluster impact to be irrelevant on firm surviving rate in the competition stage (Lomi, Reference Lomi1995; Wenting & Frenken, Reference Wenting and Frenken2011).
Hypothesis 2:
After a population enters the stage of competition in which the overall death rate will be higher than the birth rate of organizations, whether locating in a cluster has no impact on survival rate.
Firm's upgrading strategy after survival
After the competition stage, some firms survive while others fail and exit the market. Population ecology researches argue that organizational size is positively associated with survival rate (Baum, Reference Baum, Clegg, Hardy and Nord1996; Baum & Mezias, Reference Baum and Mezias1992; Bigelow et al., Reference Bigelow, Carroll, Seidel and Tsai1997). Organizational size is closely related to firms’ slack resources as well as on the base to compete (Bigelow et al., Reference Bigelow, Carroll, Seidel and Tsai1997). Larger firms usually have a better chance to find a cooperator as well as to compete. They have a stronger ability of innovation than the smaller ones in a cluster do (Carroll & Hannan, Reference Carroll and Hannan2000; Cooper & Folta, Reference Cooper, Folta, Sexton and Landstrom2000). Thus, if a firm can survive through the stage of competition, it can gain strong legitimacy and attract more resources to grow (Audia et al., Reference Audia, Freeman and Reynolds2006; Galaskiewicz et al., Reference Galaskiewicz, Bielefeld and Dowell2006). We argue that in the yacht industry, if the manufacturer's size grows over a threshold, it is an important indicator that this firm has the capability of making a mega-yacht (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012). Since making a mega-yacht will take more time than a typical smaller yacht, a firm's size that is over a threshold is a critical indicator for the customers that this firm has the ability and resources to make the mega-yacht (Taiwan Yacht Industry Association, 2007). Therefore, for those firms that their size is over the size threshold in a cluster, those firms can gain more opportunities on upgrading, and get bigger and more competitive. Thus, we get hypothesis 3:
Hypothesis 3:
For those surviving firms, locating in a cluster will help them to expand their size.
METHODS
Data and History
In this study we use panel data of the yacht industry in Taiwan. Taiwan is one of the world's 25 largest economies despite having a population of less than 25 million (IMD, 2006). The island also has well-established legal traditions that help to ensure that the public data reported by business groups is reliable (IMD, 2006). Taiwan is representative of a number of other newly industrialized economies with a history of newly international firms such as South Korea, Hong Kong, and Singapore (Lasserre & Schütte, Reference Lasserre and Schütte2006), and Taiwan is also recognized as a kind of mid-ranged emerging economy (Hoskission et al., Reference Hoskisson, Wright, Filatotchev and Peng2013).
Although the value of the yacht manufacturing industry in Taiwan is relatively small in terms of market value (between 150 to 300 million USD), its characteristics make it a strategic site to answer the research question. First, it has already experienced all of the three stages of evolution of an organizational population, namely legitimation, competition, and resurgence. In other words, the data allow us to fully examine the organizational dynamics at different stages of population development (Cheng, Reference Cheng2011). Second, we are fortunately able to collect the complete data of the basic information of every firm in this industry since the beginning of this industry. The completeness of data allows us to overcome the major challenge for empirical studies of organizational ecology. Third, the yacht industry in Taiwan has experienced the process of shifting geographic location and obviously forms a cluster over time. Although yacht manufacturers originated from Taipei in the 1960s, after the 1990s yacht manufacturers were overwhelmingly concentrated in Kaohsiung, which is the second largest city in Taiwan and is a cluster of the yacht industry (Hsu, Reference Hsu2001; Taiwan Yacht Industry Association, 2007). This process of location shifting provides an important opportunity to examine the interaction between geographic location and organizational demography (Carroll & Hannan, Reference Carroll and Hannan2000; Kukalis, Reference Kukalis2010). Finally, Taiwan has almost no domestic yacht market and Taiwanese yacht manufacturers are overwhelmingly export oriented until now (Cheng & Chung, Reference Cheng and Chung2012; Taiwan Yacht Industry Association, 2007). The impact of the domestic market can be fully controlled and the disparate performance among firms can be fully attributed to the factor of production sites.
The first Taiwanese yacht maker was the Tachiao corporation, established in 1957 in Taipei. Originally, it provided small boats for US military officers for their entertainment and later exported to the US market. In the early period, yacht makers were overwhelmingly surrounding the Tamsui River, which is the major river of northern Taiwan. In the 1970s, the family who owned Tachiao Corporation and their business partners in Southern Taiwan built several new firms, including Tayana corporation and Tashin corporation (Taiwan Yacht Industry Association, 2007). The founding of these two firms opened the yacht manufacturing industry in Kaohsiung, which later became the place where yacht manufacturers concentrated. Since 1957, both the number of manufacturers and production value kept rising until 1988 when the overall production value reached 200 million USD. However, as NTD rapidly appreciated since the late 1980s, Taiwanese yacht manufacturers soon lost competitiveness and the total product value declined to 50 million USD. After 1995, yacht manufacturers in Kaohsiung gradually developed the new business model of customized production and shifted the products from small yachts to luxurious mega-yachts. These efforts of upgradation successfully raised the added value of the whole industry and generated a new period of growth until 2008 when the production value reached 340 million USD. Our early work has provided a detailed account and value-added on the characteristic of customized production in the yacht industry in Taiwan (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012).
Data Source
Based on the methodology of organizational ecology (Carroll & Hannan, Reference Carroll and Hannan2000; Hannan et al., Reference Hannan, Carroll, Dundon and Torres1995), in this study we treat yacht makers in Taiwan as a population and analyze their founding, dissolution, and growth. Our data is from the following sources. First, we use membership records the Taiwan Shipbuilding Industry Association and Taiwan Yacht Industry Association to record all yacht manufacturers since 1957, when the establishment of the first yacht manufacturer is recorded (Lu, Chung, & Tsai, Reference Lu, Chung and Tsai2010; Taiwan Yacht Industry Association, 2007). We further checked the registration data from the Ministry of Economic Affairs within the Taiwanese government. Because the export of yachts is highly regulated, we are confident that our data contains all yacht manufacturers that once existed in Taiwan. We use the registration date as the time point of the birth of a firm, and dissolution day declared to the government as the date of organizational death. We compare the data from the government and the two associations and also conducted some interviews among firms. Thus, we found 107 yacht manufacturers that ever existed in Taiwan.
In addition to birth and death of firms, we also use the data of ‘registered capital’ from the Ministry of Economic Affairs in the Taiwanese government as the indicator of organizational size. Although in the literature there are better indicators, such as sales or number of employees; however, we face difficulty when obtaining this data, especially for those already disappeared. On the other hand, since firms have motives to expand registered capital when their revenue grows, we believe that it is still a proximate indicator for organizational size. The number of yacht manufacturers and their total registered capital is shown in Figures 1 and 2.
Figure 1. The survival number of yacht manufacturers inside and outside the cluster.
Figure 2. The asset (registered capital) change of those survival yacht manufacturers inside the cluster and the whole country over time (indicated in 10 thousand NT dollars).
Figure 1 and Figure 2 above clearly show the trend and geographic distribution of yacht manufacturers. The number of existing firms in every year can clearly show the two stage of population evolution – legitimation based on cooperation in the early stage and the competition stage. Between 1957 and 1988 the birth rate of yacht makers is higher than the death rate and the total number continuously rose. After 1988 the number of firms began to decline, and this trend has not stopped yet. On the other hand, the total registered capitals of the whole industry also declined after 1988, which reflected the shock brought by the appreciation of NTD. However, it soon rebounded after 1996 and exceeded the previous peak in 2005. Additionally, from Figure 3, we can observe the shift of firm location from Northern to Southern Taiwan. Our data show clusters in Northern and Southern Taiwan began to have different dynamics after 1988; after 1988 the number of firms in Kaohsiung slowly rose but those in Taipei kept declining. On the other hand, the total registered capital in Kaohsiung exceeded that in Taipei since 1970, and we can find that the capital gap between manufacturers in Kaohsiung cluster and their counterpart outside this cluster was never narrowed. This process provides an important cue to analyze the relationship between the industrial cluster and a firm's survival rate.
Figure 3. The founding time and number of yacht manufacturers.
Variables and Analysis
We follow the analytical model of population ecology, thus there will be specific dependent and independent variables based on the different hypotheses.
For the first hypothesis, we use locating outside Taipei and Kaohsiung as the baseline. Thus, the dependent variable (Y) in hypothesis 1 is the ‘location of the yacht manufacturers’. In this study, the yacht manufacturers agglomerate on the Kaohsiung location compared with the other location (Taipei). Thus, the Kaohsiung location is a cluster compared with the Taipei location. The independent variable (X) in hypothesis 1 is the ‘number of yacht manufacturers in Taipei and Kaohsiung in the previous year’. In hypothesis 1, we control the ‘total registered capital of yacht manufacturers in Taipei and Kaohsiung’ and the ‘period effect’ – this study divides the history of yacht industry into two periods: the legitimation period between 1957 and 1988, and the competition period between 1988 and 2012.
For the second and third hypothesis (H2 & H3), we are interested in examining the impact from the cluster evolution on the firm's survival rate. Thus, we choose the basic exponential model as the parameter. In hypothesis 2, the dependent variable (Y) is the ‘dissolution rate of yacht manufacturers’. We use the registration date as the time point of the birth of a firm, and dissolution day declared to the government as the date of firm's death.
Furthermore, in hypothesis 3, the dependent variable (Y) is the ‘yacht manufacturer's size over a threshold’ as the indicator that firm has the capability. In the yacht industry, the firm size over a threshold is an indicator that whether this firm has the capability to make mega-yacht (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012). Thus, for those firms to achieve this size threshold is an important indicator that this firm is survival and has the competitive advantage. In this study, the data of ‘registered capital over 26 Million N. T. dollars’ from the Ministry of Economic Affairs as the threshold indicator of organizational size (Taiwan Yacht Industry Association, 2007) and the proxy of firm size over a threshold. The X is the dummy code of whether the firm locates inside a cluster (Kaohsiung) or outside the cluster (firm location (dummy variables of Taipei, Kaohsiung, outside these two locations as the baseline). The following variables are controlled in testing hypothesis 2 and hypothesis 3, including: 1) Firm age; 2) Firm size: measured by log of registered capital; 3) Period (between 1957 and 1988; between 1989 and 2012); 4) Interaction term of period and size; 5) Organizational density: measured by number of existing yacht manufacturers; 6) Square of organizational density/1000; and 7) log of total registered capital.
RESULTS
Table 1 shows a clear decline of founding rate of the yacht manufacturers since 1988. The results show that the overall size of manufacturers in a region is positively related to the location of new firms, and number of manufacturers has no impact or even negative impact. In other words, when total industry size in a location or a cluster is crucial for new firm's choice of location. The firm's founding rate is positively related with the cluster size and thus hypothesis 1 (H1) is supported.
Table 1. Multi-nominal logistic regression on location of yacht makers (Baseline: Locating in area outside Taipei or Kaohsiung)
Notes: Observations: 107. p < 0.10; *p < 0.05; **p < 0.01.
In terms of the second hypothesis (H2), we follow the standard procedure to use event history model to examine the factors influencing the survival rate of yacht manufacturers. According to Figure 4, in terms of the distribution of birth and death of firms, an important pattern is the near separation of time between founding and dissolution. Although the first yacht maker was founded in 1957, not until 1983 did the first manufacturer dissolve.
Figure 4. The founding and dearth of yacht manufacturers over time.
Furthermore, according to Table 2, the above result confirms the traditional wisdoms of organizational ecology about the impact of organizational age, density, and size on organizational survival. On the other hand, considering the transformation of the industrial environment, locating in clusters brings a higher mortality rate for yacht manufacturers. This pattern may result from the fiercer competition for resources for firms in the same cluster. It means that the disadvantages of competition may outweigh the advantages of cooperation among firms located inside the cluster in this stage. Thus, hypothesis 2 (After a population enters the stage of competition, whether locating in a cluster has no impact on survival rate) is not supported.
Table 2. Event history on the dissolution rate of yacht makers
Notes: N = 104; Number of obs = 1733; No. of failures = 65; Time at risk = 207780; LR chi2(9) = 408.88; Log likelihood = 108.75908; Prob > chi2 = 0.0000.
For the third hypothesis (H3), because firms’ registered capital only changes after a certain period, we use the historical average 26 million N.T. dollars as a threshold and adopt event history analysis to test what kind of firms and when they will pass this threshold. The results are as follows in Table 3. In this model we find that organizational age and locating in Kaohsiung (the cluster) have a significant effect on the chance of exceeding the threshold. In other words, not those firms located inside the cluster (Kaohsiung area in this case) can always get the bigger size. Those older firms that are located in the cluster can get bigger. It indirectly proves the cluster effect on organizational size. Thus, hypothesis 3 (For those surviving firms locating in a cluster help them expand their sizes) is partially supported.
Table 3. Event history on registered capital exceeding 26 million
Notes: N = 103; Number of obs = 1240; No. of failures = 39; Time at risk = 205310; LR chi2(9) = 134.11; Log likelihood = −9.898251; Prob > chi2 = 0.0000.
DISCUSSION
In this study, we integrate the literature of cluster and coopetition and employ the perspective of organizational ecology (Carroll & Hannan, Reference Carroll and Hannan2000; Hannan & Freeman, Reference Hannan and Freeman1989) to analyze the impact of clusters on individual firms. The ecological perspective allows us to decompose the impact of clusters on firms into three possible paths: facilitating the founding of new firms, decreasing the death rate of existing firms in the competition stage, and enhancing the growth of surviving firms in the resurgence stage. By analyzing the dynamic dimension of cluster formation and evolution (Carroll & Hannan, Reference Carroll and Hannan2000; Pouder & St. John, Reference Pouder and St. John1996), we argue this ecological perspective will provide insightful implications to address the coopetition issues in a cluster.
The results based in the analysis of over 30-years of data of the yacht industry in an emerging economy indicate that the impact on individual firms of locating in an industrial cluster is mainly enhancing organizational founding rather than reducing the death rate. While firms in an industrial cluster are more likely to fail due to fiercer competition, they also gain more resources and legitimacy once they can survive (Audia et al., Reference Audia, Freeman and Reynolds2006; Galaskiewicz et al., Reference Galaskiewicz, Bielefeld and Dowell2006). In the case of the yacht industry from this study, the shift of geographic location of yacht manufacturers from Taipei to Kaohsiung (the cluster) demonstrates this process. Although yacht manufacturers in Kaohsiung suffered from a higher chance of failure, more new firms were attracted to this cluster. The higher total size of yacht manufacturers since the 1970s kept attracting the entrance of new firms. Thus, and thereby, the yacht manufacturers who survive can obtain more resources (McCann & Folta, Reference McCann and Folta2008). However, when more and more yacht manufacturers agglomerate together in cluster (the Kaohsiung area in this case), they also face fiercer competition if they cannot follow the new trend to upgrade (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012). The non-supported hypothesis of H2 indicates the rigorous environment faced by firms in a cluster during the stage of competition (Folta et al., Reference Folta, Cooper and Baik2006). It also indicates during the competition stage, firms will search more on individual value appropriation rather than creating the common value among the firms located inside the cluster (Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008; Ritala & Tidström, Reference Ritala and Tidström2014).
Additionally, firms that have a longer history and locate in the cluster have a higher chance of upgrading themselves and maintaining growth (Audia et al., Reference Audia, Freeman and Reynolds2006; Galaskiewicz et al., Reference Galaskiewicz, Bielefeld and Dowell2006). The partial support of hypothesis 3 reveals the innovation consequence is not equal for all the firms located inside the cluster (Park et al., Reference Park, Srivastava and Gnyawali2014). Older firms may have more experience to balance the cooperation and competition among firms located inside the cluster and can seize the chance to make bigger yachts and accordingly, can be bigger and therefore competitive (Baum, Reference Baum, Clegg, Hardy and Nord1996; Carroll & Hannan, Reference Carroll and Hannan2000). By introducing a dynamic model focusing on the evolutionary logic (Kukalis, Reference Kukalis2010; Pouder & St. John, Reference Pouder and St. John1996), this study contributes to the debate on coopetition: whether and when coopetition is advantaged for firm outcomes (Brandenburger & Nalebuff, Reference Brandenburger and Nalebuff1996; Czakon et al., Reference Czakon, Fernandez and Minà2014; Gnyawali et al., Reference Gnyawali, He, Madhavan and Wankel2008).
This study also shows the pathway of development of firms in emerging economies. Yacht manufacturers in Taiwan who do not have a domestic market accumulate capabilities and find the markets globally (Cheng, Reference Cheng2011; Cheng & Chung, Reference Cheng and Chung2012). Examining whether those firms inside the cluster in the yacht industry can survive and accumulate assets and capabilities is critical to the firms from the emerging economics aiming towards global expansion (Hoskission, Reference Hoskisson, Eden, Lau and Wright2000, Reference Hoskisson, Wright, Filatotchev and Peng2013; Ramamurti & Singh, Reference Ramamurti and Singh2009). Additionally, this study illustrates the importance of stages of population evolution in addressing the cluster impact issues (Kukalis, Reference Kukalis2010). Studies overlooking the long-term evolution of organizational population may reach an incorrect conclusion if they fail to take different stages into account. Thus, it will be helpful to answer what kind of firms can survive during the temporal evolution of the cluster (McCann & Folta, Reference McCann and Folta2008; Pouder & St. John, Reference Pouder and St. John1996).
As we emphasize in the data and history section in this study, the analysis is highly constrained by the relatively small population and only over 30 years of history in the yacht industry in Taiwan. However, under this limitation, we still can trace the dynamic pattern of the coopetition strategy among firms in a cluster. We believe the organizational ecology employed in this study provides a more novel framework than traditional firm centered studies based on cross sectional data addressing the cooperation issues in a cluster. Additionally, the unsupported hypothesis 2 on the coopetition impact on the firm survival in the competition stage reveals the limitation of this study: that we cannot observe and code exactly in what kind of activities during the value chain of the yacht manufacturing process that firms will cooperate or compete with each other (Bengtsson & Kock, Reference Bengtsson and Kock1999, Reference Bengtsson and Kock2000). This is absolutely a limitation on the ecological level. We hope more work can be done in the future to further investigate the imbalance from coopetition among firms in different industrial stages.
